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""" Open Nodes web server Copyright (c) 2018 Opennodes / Blake Bjorn Anderson Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import gzip import json import os import sys from io import BytesIO from flask import Flask, render_template, request, redirect, flash, Response from flask_sqlalchemy import SQLAlchemy from geoip2.errors import AddressNotFoundError from sqlalchemy import and_ from config import load_config, DefaultFlaskConfig from crawler import init_geoip, connect from models import * import pandas as pd from autodoc import Autodoc app = Flask(__name__) auto = Autodoc(app) app.config.from_object(DefaultFlaskConfig()) app.config.from_object('flask_config') db = SQLAlchemy(app) CONF = load_config() COUNTRY, CITY, ASN = init_geoip() @app.route('/') @app.route('/networks/<network_name>', methods=['GET']) def network_dashboard(network_name=None): if not network_name in ("okcash", "testnet", None): flash("Invalid network") return redirect("/") with open("static/network_summaries.json", 'r') as f: summaries = json.load(f) if network_name: age_min = summaries[network_name]['age_min'] age_max = summaries[network_name]['age_max'] else: age_min = min((summaries[network]['age_min'] for network in CONF['networks'])) age_max = max((summaries[network]['age_max'] for network in CONF['networks'])) return render_template("network_dashboard.html", network=network_name, include_client=False if network_name is not None else False, include_user_agent=True if network_name is not None else False, include_network=True if network_name is None else False, include_version=True if network_name is not None else False, include_active=True if CONF['export_inactive_nodes'] else False, age_min=age_min * 1000.0, age_max=age_max * 1000.0) def gzip_response(input_str, pre_compressed): response = Response() if not pre_compressed: buffer = BytesIO() gzip_file = gzip.GzipFile(mode='wb', fileobj=buffer) gzip_file.write(input_str if isinstance(input_str, bytes) else input_str.encode()) gzip_file.close() response.data = buffer.getvalue() else: response.data = input_str response.headers['Content-Encoding'] = 'gzip' response.headers['Vary'] = 'Accept-Encoding' response.headers['Content-Length'] = len(response.data) return response @app.route('/api/get_networks', methods=['POST']) @auto.doc() def get_networks(): """ Returns a list of all available network names :return: JSON string, ex. "['okcash','testnet']" """ return json.dumps([x[0] for x in db.session.query(Node.network).distinct().all()]) @app.route('/api/gzip_file/<filename>', methods=['GET']) @auto.doc() def gzip_static_file(filename): """ Returns a crawl result as a gzipped response :param filename: file_network.ext - file is 'data' or 'history', ext is either .json, .csv, .txt (data.ext returns data for all crawled networks) :return: gzip encoded html response """ valid_files = ["custom.geo.json"] for coin in ("", "_groestlcoin", "_testnet"): for suff in ("", "_unique"): for ext in (".csv", ".json", ".txt"): valid_files.append("data" + coin + suff + ext) valid_files.append("history" + coin + '.json') if filename not in valid_files: return redirect("/", code=404) with open(os.path.join("static", filename), "r") as f: return gzip_response(f.read(), False) def deconstruct_address_string(inp): assert isinstance(inp, str) resp = {} aliases = {'ok': 'okcash', 'tok': 'testnet'} inp = inp.lower() network = inp.split(":")[0] if network: inp = ":".join(inp.split(":")[1:]) network = aliases[network] if network in aliases else network network = network if network in CONF['networks'] else None if not network: network = "okcash" resp['warning'] = "Network not recognized, using OK" if ":" in inp: port = inp.split(":")[-1] try: port = int(port) inp = ":".join(inp.split(":")[:-1]) except ValueError: resp['warning'] = "port not recognized, using default" port = int(CONF['networks'][network]['port']) else: port = int(CONF['networks'][network]['port']) return network, inp, port, resp @app.route('/api/check_node', methods=['POST']) @auto.doc() def check_node(): """ Checks the current status of a node. This is a live result, so response times will be longer - to view a saved result see /api/check_historic_node. :param node: connection string, e.g. ok:127.0.0.1:6970 - port is optional if it is the network default :param to_services (integer, optional): outgoing services to broadcast, default=0 :param from_services (integer, optional): outgoing services to broadcast, default=0 :param version (integer, optional): version code to broadcast, default varies by network :param user_agent (string, optional): user agent to broadcast, default="/oknodes:0.1/" :param height (integer, optional): block height to broadcast during handshake. default=network median :param p2p_nodes (bool, optional): issues a getaddr call and list of connected nodes, default=False :return: json dict {"result":{"user_agent":"/oktoshi:5.0.0.2/", "version":" .... }, "nodes":[["127.0.0.1:6970, 157532132191], ...]} """ dat = request.form node = dat.get("node") network, address, port, resp = deconstruct_address_string(node) network_data = CONF['networks'][network] if dat.get("height"): network_data['height'] = dat.get("height") else: with open("static/network_summaries.json", 'r') as f: network_data['height'] = int(json.load(f)[network]['med']) network_data['protocol_version'] = dat.get("version") or network_data['protocol_version'] result = connect(network, address, port, to_services=dat.get("to_services") or network_data['services'], network_data=network_data, user_agent=dat.get("user_agent") or None, p2p_nodes=False, explicit_p2p=dat.get("p2p_nodes") or False, from_services=dat.get('from_services') or None, keepalive=False) resp['result'] = result[0] resp['nodes'] = result[1] resp['result'] = geocode(resp['result']) return to_json(resp) @app.route('/api/check_historic_node', methods=['POST', 'GET']) @auto.doc() def check_historic_node(): """ Checks the status of a node based on the last crawl result see /api/check_historical_node :param node: connection string, e.g. ok:127.0.0.1:6970 - port is optional if it is the network default :return: json dict {"result":{"user_agent":"/oktoshi:5.0.0.2/", "version":" .... }} """ if request.method == "POST": dat = request.form else: dat = request.args node = dat.get("node") network, address, port, resp = deconstruct_address_string(node) if network not in CONF['networks']: return json.dumps({'error': "network not recognized"}) result = db.session.query(Node).get((network, address, port)) resp['result'] = "None" if result is None else result.to_dict() return to_json(resp) @app.route("/about") def about(): return render_template("about.html") @app.route("/api_docs") def api_docs(): return auto.html() @app.route('/api/get_nodes', methods=['POST']) @auto.doc() def get_node_list(): """ Gets a list of all nodes visible during the past 30 days :param network (optional): Filters the result set based on the given network :return: json array [{"address":"127.0.0.1" ... }, {"address":"0.0.0.0", "port:6970}] """ q = db.session.query(Node.network, Node.address, Node.port, Node.user_agent, Node.version, Node.first_seen, Node.last_seen, Node.last_checked, Node.country, Node.city, Node.asn, Node.aso).filter( Node.seen) if request.args.get("network") is not None: network = request.args.get("network") if network not in CONF['networks']: return {"error": "network must be one of " + ", ".join(CONF['networks'])} q = q.filter(Node.network == network) return pd.read_sql(q.statement, q.session.bind).to_json(orient='records') @app.route('/api/node_history', methods=['POST']) @auto.doc() def get_node_history(): """ Returns the data associated with a node, and all crawler visitations on record :param node: connection string, e.g. ok:127.0.0.1:6970 - port is optional if it is the network default. :return: json dict {"node":{"user_agent":"/oktoshi/", "last_seen": ... }, "history":{"timestamp":157032190321,"height":56000, "success":1 ...}} """ node = request.form.get("node") network, address, port, resp = deconstruct_address_string(node) if network not in CONF['networks']: return json.dumps({'error': "network not recognized"}) default_port = int(CONF['networks'][network]['port']) resp = {} try: port = int(port) if port is not None else default_port except ValueError: resp['warning'] = "port not recognized, using default" port = default_port n = db.session.query(Node.network, Node.address, Node.port, Node.user_agent, Node.version, Node.first_seen, Node.last_seen, Node.last_checked, Node.country, Node.city, Node.asn, Node.aso) \ .filter(and_(Node.network == network, Node.address == address, Node.port == port)).one() q = db.session.query(NodeVisitation.timestamp, NodeVisitation.height, NodeVisitation.success) \ .join(Node, and_(Node.network == NodeVisitation.network, Node.address == NodeVisitation.address, Node.port == NodeVisitation.port)) \ .filter(and_(Node.network == network, Node.address == address, Node.port == port)) \ .order_by(NodeVisitation.timestamp.desc()) df = pd.read_sql(q.statement, q.session.bind) df['timestamp'] = df['timestamp'].astype(pd.np.int64) // 10 ** 9 resp.update({"node": {"network": n.network, 'address': n.address, "port": n.port, "user_agent": n.user_agent, "version": n.version, "first_seen": n.first_seen, "last_seen": n.last_seen, "last_checked": n.last_checked, "country": n.country, "city": n.city, "asn": n.asn, "aso": n.aso}, "history": df.to_dict(orient='records')}) return to_json(resp) def geocode(result): if result and result['address'].endswith('.onion'): aso, asn, country, city = "Anonymous", "Anonymous", "Anonymous", "Anonymous" elif result: try: aso = ASN.asn(result['address']).autonomous_system_organization asn = ASN.asn(result['address']).autonomous_system_number except AddressNotFoundError: aso = None asn = None try: country = COUNTRY.country(result['address']).country.name except AddressNotFoundError: country = None try: city = CITY.city(result['address']).city.name except AddressNotFoundError: city = None else: return result result['aso'] = aso result['asn'] = asn result['country'] = country result['city'] = city return result def clean_dates(d): for i in d: if isinstance(d[i], datetime.datetime): d[i] = d[i].timestamp() if isinstance(d[i], dict): d[i] = clean_dates(d[i]) return d def to_json(d): """ Sanitizes a dictionary - converts datetime.datetime instances to timestamps :param d: dictionary :return: json string """ d = clean_dates(d) return json.dumps(d) def main(): app.run("0.0.0.0", debug=False if "--prod" in sys.argv else True, port=8888 if "--prod" in sys.argv else 5000) # app.run("0.0.0.0", debug=False if "--prod" in sys.argv else True, port=443 if "--prod" in sys.argv else 5000, ssl_context=('/etc/letsencrypt/live/nodes.okcash.org/fullchain.pem', '/etc/letsencrypt/live/nodes.okcash.org/privkey.pem')) if __name__ == '__main__': main()
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#!/usr/bin/python import hashlib, re, sys, os, base64, time, random, hmac # stripped down from https://github.com/vbuterin/pybitcointools/blob/master/bitcoin/main.py ### Elliptic curve parameters P = 2**256-2**32-2**9-2**8-2**7-2**6-2**4-1 N = 115792089237316195423570985008687907852837564279074904382605163141518161494337 A = 0 B = 7 H = 1 Gx = 55066263022277343669578718895168534326250603453777594175500187360389116729240 Gy = 32670510020758816978083085130507043184471273380659243275938904335757337482424 G = (Gx,Gy) ### Extended Euclidean Algorithm def inv(a,n): lm, hm = 1,0 low, high = a%n,n while low > 1: r = high/low nm, new = hm-lm*r, high-low*r lm, low, hm, high = nm, new, lm, low return lm % n ### Base switching def get_code_string(base): if base == 2: return '01' elif base == 10: return '0123456789' elif base == 16: return "0123456789abcdef" elif base == 58: return "123456789ABCDEFGHJKLMNPQRSTUVWXYZabcdefghijkmnopqrstuvwxyz" elif base == 256: return ''.join([chr(x) for x in range(256)]) else: raise ValueError("Invalid base!") def encode(val,base,minlen=0): base, minlen = int(base), int(minlen) code_string = get_code_string(base) result = "" while val > 0: result = code_string[val % base] + result val /= base if len(result) < minlen: result = code_string[0]*(minlen-len(result))+result return result def decode(string,base): base = int(base) code_string = get_code_string(base) result = 0 if base == 16: string = string.lower() while len(string) > 0: result *= base result += code_string.find(string[0]) string = string[1:] return result def changebase(string,frm,to,minlen=0): return encode(decode(string,frm),to,minlen) ### Elliptic Curve functions def isinf(p): return p[0] == 0 and p[1] == 0 def base10_add(a,b): if isinf(a): return b[0],b[1] if isinf(b): return a[0],a[1] if a[0] == b[0]: if a[1] == b[1]: return base10_double((a[0],a[1])) else: return (0,0) m = ((b[1]-a[1]) * inv(b[0]-a[0],P)) % P x = (m*m-a[0]-b[0]) % P y = (m*(a[0]-x)-a[1]) % P return (x,y) def base10_double(a): if isinf(a): return (0,0) m = ((3*a[0]*a[0]+A)*inv(2*a[1],P)) % P x = (m*m-2*a[0]) % P y = (m*(a[0]-x)-a[1]) % P return (x,y) def base10_multiply(a,n): if isinf(a) or n == 0: return (0,0) if n == 1: return a if n < 0 or n >= N: return base10_multiply(a,n%N) if (n%2) == 0: return base10_double(base10_multiply(a,n/2)) if (n%2) == 1: return base10_add(base10_double(base10_multiply(a,n/2)),a) # Functions for handling pubkey and privkey formats def get_pubkey_format(pub): if isinstance(pub,(tuple,list)): return 'decimal' elif len(pub) == 65 and pub[0] == '\x04': return 'bin' elif len(pub) == 130 and pub[0:2] == '04': return 'hex' elif len(pub) == 33 and pub[0] in ['\x02','\x03']: return 'bin_compressed' elif len(pub) == 66 and pub[0:2] in ['02','03']: return 'hex_compressed' elif len(pub) == 64: return 'bin_electrum' elif len(pub) == 128: return 'hex_electrum' else: raise Exception("Pubkey not in recognized format") def encode_pubkey(pub,formt): if not isinstance(pub,(tuple,list)): pub = decode_pubkey(pub) if formt == 'decimal': return pub elif formt == 'bin': return '\x04' + encode(pub[0],256,32) + encode(pub[1],256,32) elif formt == 'bin_compressed': return chr(2+(pub[1]%2)) + encode(pub[0],256,32) elif formt == 'hex': return '04' + encode(pub[0],16,64) + encode(pub[1],16,64) elif formt == 'hex_compressed': return '0'+str(2+(pub[1]%2)) + encode(pub[0],16,64) elif formt == 'bin_electrum': return encode(pub[0],256,32) + encode(pub[1],256,32) elif formt == 'hex_electrum': return encode(pub[0],16,64) + encode(pub[1],16,64) else: raise Exception("Invalid format!") def decode_pubkey(pub,formt=None): if not formt: formt = get_pubkey_format(pub) if formt == 'decimal': return pub elif formt == 'bin': return (decode(pub[1:33],256),decode(pub[33:65],256)) elif formt == 'bin_compressed': x = decode(pub[1:33],256) beta = pow(x*x*x+7,(P+1)/4,P) y = (P-beta) if ((beta + ord(pub[0])) % 2) else beta return (x,y) elif formt == 'hex': return (decode(pub[2:66],16),decode(pub[66:130],16)) elif formt == 'hex_compressed': return decode_pubkey(pub.decode('hex'),'bin_compressed') elif formt == 'bin_electrum': return (decode(pub[:32],256),decode(pub[32:64],256)) elif formt == 'hex_electrum': return (decode(pub[:64],16),decode(pub[64:128],16)) else: raise Exception("Invalid format!") def get_privkey_format(priv): if isinstance(priv,(int,long)): return 'decimal' elif len(priv) == 32: return 'bin' elif len(priv) == 33: return 'bin_compressed' elif len(priv) == 64: return 'hex' elif len(priv) == 66: return 'hex_compressed' else: bin_p = b58check_to_bin(priv) if len(bin_p) == 32: return 'wif' elif len(bin_p) == 33: return 'wif_compressed' else: raise Exception("WIF does not represent privkey") def encode_privkey(priv,formt): if not isinstance(priv,(int,long)): return encode_privkey(decode_privkey(priv),formt) if formt == 'decimal': return priv elif formt == 'bin': return encode(priv,256,32) elif formt == 'bin_compressed': return encode(priv,256,32)+'\x01' elif formt == 'hex': return encode(priv,16,64) elif formt == 'hex_compressed': return encode(priv,16,64)+'01' else: raise Exception("Invalid format!") def decode_privkey(priv,formt=None): if not formt: formt = get_privkey_format(priv) if formt == 'decimal': return priv elif formt == 'bin': return decode(priv,256) elif formt == 'bin_compressed': return decode(priv[:32],256) elif formt == 'hex': return decode(priv,16) elif formt == 'hex_compressed': return decode(priv[:64],16) else: raise Exception("Invalid format!") def add_pubkeys(p1,p2): f1,f2 = get_pubkey_format(p1), get_pubkey_format(p2) return encode_pubkey(base10_add(decode_pubkey(p1,f1),decode_pubkey(p2,f2)),f1) def add_privkeys(p1,p2): f1,f2 = get_privkey_format(p1), get_privkey_format(p2) return encode_privkey((decode_privkey(p1,f1) + decode_privkey(p2,f2)) % N,f1) def multiply(pubkey,privkey): f1,f2 = get_pubkey_format(pubkey), get_privkey_format(privkey) pubkey, privkey = decode_pubkey(pubkey,f1), decode_privkey(privkey,f2) # http://safecurves.cr.yp.to/twist.html if not isinf(pubkey) and (pubkey[0]**3+7-pubkey[1]*pubkey[1]) % P != 0: raise Exception("Point not on curve") return encode_pubkey(base10_multiply(pubkey,privkey),f1) def divide(pubkey,privkey): factor = inv(decode_privkey(privkey),N) return multiply(pubkey,factor) def compress(pubkey): f = get_pubkey_format(pubkey) if 'compressed' in f: return pubkey elif f == 'bin': return encode_pubkey(decode_pubkey(pubkey,f),'bin_compressed') elif f == 'hex' or f == 'decimal': return encode_pubkey(decode_pubkey(pubkey,f),'hex_compressed') def decompress(pubkey): f = get_pubkey_format(pubkey) if 'compressed' not in f: return pubkey elif f == 'bin_compressed': return encode_pubkey(decode_pubkey(pubkey,f),'bin') elif f == 'hex_compressed' or f == 'decimal': return encode_pubkey(decode_pubkey(pubkey,f),'hex') def privkey_to_pubkey(privkey): f = get_privkey_format(privkey) privkey = decode_privkey(privkey,f) if privkey == 0 or privkey >= N: raise Exception("Invalid privkey") if f in ['bin','bin_compressed','hex','hex_compressed','decimal']: return encode_pubkey(base10_multiply(G,privkey),f) else: return encode_pubkey(base10_multiply(G,privkey),f.replace('wif','hex')) privtopub = privkey_to_pubkey def privkey_to_address(priv,magicbyte=0): return pubkey_to_address(privkey_to_pubkey(priv),magicbyte) privtoaddr = privkey_to_address def neg_pubkey(pubkey): f = get_pubkey_format(pubkey) pubkey = decode_pubkey(pubkey,f) return encode_pubkey((pubkey[0],(P-pubkey[1]) % P),f) def neg_privkey(privkey): f = get_privkey_format(privkey) privkey = decode_privkey(privkey,f) return encode_privkey((N - privkey) % N,f) def subtract_pubkeys(p1, p2): f1,f2 = get_pubkey_format(p1), get_pubkey_format(p2) k2 = decode_pubkey(p2,f2) return encode_pubkey(base10_add(decode_pubkey(p1,f1),(k2[0],(P - k2[1]) % P)),f1) def subtract_privkeys(p1, p2): f1,f2 = get_privkey_format(p1), get_privkey_format(p2) k2 = decode_privkey(p2,f2) return encode_privkey((decode_privkey(p1,f1) - k2) % N,f1) ### Hashes def bin_sha256(string): return hashlib.sha256(string).digest() def sha256(string): return bin_sha256(string).encode('hex') def hash_to_int(x): if len(x) in [40,64]: return decode(x,16) else: return decode(x,256) def num_to_var_int(x): x = int(x) if x < 253: return chr(x) elif x < 65536: return chr(253) + encode(x,256,2)[::-1] elif x < 4294967296: return chr(254) + encode(x,256,4)[::-1] else: return chr(255) + encode(x,256,8)[::-1] ### Encodings ### EDCSA def encode_sig(v,r,s): vb, rb, sb = chr(v), encode(r,256), encode(s,256) return base64.b64encode(vb+'\x00'*(32-len(rb))+rb+'\x00'*(32-len(sb))+sb) def decode_sig(sig): bytez = base64.b64decode(sig) return ord(bytez[0]), decode(bytez[1:33],256), decode(bytez[33:],256) # https://tools.ietf.org/html/rfc6979#section-3.2 def deterministic_generate_k(msghash,priv): v = '\x01' * 32 k = '\x00' * 32 priv = encode_privkey(priv,'bin') msghash = encode(hash_to_int(msghash),256,32) k = hmac.new(k, v+'\x00'+priv+msghash, hashlib.sha256).digest() v = hmac.new(k, v, hashlib.sha256).digest() k = hmac.new(k, v+'\x01'+priv+msghash, hashlib.sha256).digest() v = hmac.new(k, v, hashlib.sha256).digest() return decode(hmac.new(k, v, hashlib.sha256).digest(),256) def ecdsa_raw_sign(msghash,priv): z = hash_to_int(msghash) k = deterministic_generate_k(msghash,priv) r,y = base10_multiply(G,k) s = inv(k,N) * (z + r*decode_privkey(priv)) % N return 27+(y%2),r,s def ecdsa_sign(msg,priv): return encode_sig(*ecdsa_raw_sign(electrum_sig_hash(msg),priv)) def ecdsa_raw_verify(msghash,vrs,pub): v,r,s = vrs w = inv(s,N) z = hash_to_int(msghash) u1, u2 = z*w % N, r*w % N x,y = base10_add(base10_multiply(G,u1), base10_multiply(decode_pubkey(pub),u2)) return r == x def ecdsa_verify(msg,sig,pub): return ecdsa_raw_verify(electrum_sig_hash(msg),decode_sig(sig),pub) def ecdsa_raw_recover(msghash,vrs): v,r,s = vrs x = r beta = pow(x*x*x+7,(P+1)/4,P) y = beta if v%2 ^ beta%2 else (P - beta) z = hash_to_int(msghash) Qr = base10_add(neg_pubkey(base10_multiply(G,z)),base10_multiply((x,y),s)) Q = base10_multiply(Qr,inv(r,N)) if ecdsa_raw_verify(msghash,vrs,Q): return encode_pubkey(Q,'hex') return False def ecdsa_recover(msg,sig): return ecdsa_raw_recover(electrum_sig_hash(msg),decode_sig(sig))
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# # ovirt-engine-setup -- ovirt engine setup # # Copyright oVirt Authors # SPDX-License-Identifier: Apache-2.0 # # """ovirt-host-setup vmconsole_proxy plugin.""" from otopi import util from . import config from . import pki from . import system @util.export def createPlugins(context): config.Plugin(context=context) pki.Plugin(context=context) system.Plugin(context=context) # vim: expandtab tabstop=4 shiftwidth=4
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# Licensed to the StackStorm, Inc ('StackStorm') under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import logging from st2client.models import core LOG = logging.getLogger(__name__) class PolicyType(core.Resource): _alias = 'Policy-Type' _display_name = 'Policy type' _plural = 'PolicyTypes' _plural_display_name = 'Policy types' _repr_attributes = ['ref', 'enabled', 'description'] class Policy(core.Resource): _plural = 'Policies' _repr_attributes = ['name', 'pack', 'enabled', 'policy_type', 'resource_ref']
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#!/usr/bin/python # -*- coding: utf-8 -*- ########################################################### # KivyCalendar (X11/MIT License) # Calendar & Date picker widgets for Kivy (http://kivy.org) # https://bitbucket.org/xxblx/kivycalendar # # Oleg Kozlov (xxblx), 2015 # https://xxblx.bitbucket.org/ ########################################################### from kivy.lang import Builder from kivy.uix.screenmanager import ScreenManager, Screen from kivy.uix.popup import Popup from kivy.uix.relativelayout import RelativeLayout from kivy.uix.gridlayout import GridLayout from kivy.uix.button import Button from kivy.uix.togglebutton import ToggleButton from kivy.uix.textinput import TextInput from kivy.uix.label import Label from kivy.core.window import Window from kivy.factory import Factory from kivy.properties import NumericProperty, ReferenceListProperty from kivyblocks.i18n import I18n from . import calendar_data as cal_data ########################################################### Builder.load_string(""" <ArrowButton>: background_normal: "" background_down: "" background_color: 1, 1, 1, 0 size_hint: .1, .1 <MonthYearLabel>: pos_hint: {"top": 1, "center_x": .5} size_hint: None, 0.1 halign: "center" <MonthsManager>: pos_hint: {"top": .9} size_hint: 1, .9 <ButtonsGrid>: cols: 7 rows: 7 size_hint: 1, 1 pos_hint: {"top": 1} <DayAbbrLabel>: text_size: self.size[0], None halign: "center" <DayAbbrWeekendLabel>: color: 1, 0, 0, 1 <DayButton>: group: "day_num" <DayNumWeekendButton>: background_color: 1, 0, 0, 1 """) ########################################################### class DatePicker(TextInput): """ Date picker is a textinput, if it focused shows popup with calendar which allows you to define the popup dimensions using pHint_x, pHint_y, and the pHint lists, for example in kv: DatePicker: pHint: 0.7,0.4 would result in a size_hint of 0.7,0.4 being used to create the popup """ def __init__(self, touch_switch=False, value=None, *args, **kwargs): super(DatePicker, self).__init__(*args, **kwargs) self.touch_switch = touch_switch self.init_ui(value) def getValue(self): return self.text def setValue(self, sdate): self.text = sdate d = [int(i) for i in sdate.split('-')] d.reverse() self.cal.active_date = d def init_ui(self, value): if not value: value = cal_data.today_date() d = [int(i) for i in value.split('.')] value = '%04d-%02d-%02d' % (d[2],d[1],d[0]) # Calendar self.cal = CalendarWidget(as_popup=True, touch_switch=self.touch_switch) self.setValue(value) # Popup self.popup = Popup(content=self.cal, on_dismiss=self.update_value, size_hint=(0.7,0.7), title="") self.cal.parent_popup = self.popup self.bind(focus=self.show_popup) def show_popup(self, isnt, val): """ Open popup if textinput focused, and regardless update the popup size_hint """ if val: # Automatically dismiss the keyboard # that results from the textInput Window.release_all_keyboards() self.popup.open() def update_value(self, inst): """ Update textinput value on popup close """ d = self.cal.active_date self.text = "%04d-%02d-%02d" % (d[2],d[1],d[0]) self.focus = False class CalendarWidget(RelativeLayout): """ Basic calendar widget """ def __init__(self, as_popup=False, touch_switch=False, *args, **kwargs): super(CalendarWidget, self).__init__(*args, **kwargs) self.i18n = I18n() self.as_popup = as_popup self.touch_switch = touch_switch self.prepare_data() self.init_ui() def init_ui(self): self.left_arrow = ArrowButton(text="<", on_press=self.go_prev, pos_hint={"top": 1, "left": 0}) self.right_arrow = ArrowButton(text=">", on_press=self.go_next, pos_hint={"top": 1, "right": 1}) self.add_widget(self.left_arrow) self.add_widget(self.right_arrow) # Title self.title_label = MonthYearLabel(text=self.title) self.add_widget(self.title_label) # ScreenManager self.sm = MonthsManager() self.add_widget(self.sm) self.create_month_scr(self.quarter[1], toogle_today=True) def create_month_scr(self, month, toogle_today=False): """ Screen with calendar for one month """ scr = Screen() m = self.month_names_eng[self.active_date[1] - 1] scr.name = "%s-%s" % (m, self.active_date[2]) # like march-2015 # Grid for days grid_layout = ButtonsGrid() scr.add_widget(grid_layout) # Days abbrs for i in range(7): if i >= 5: # weekends #l = DayAbbrWeekendLabel(text=self.days_abrs[i]) l = Factory.Text(text=self.days_abrs[i], i18n=True) else: # work days #l = DayAbbrLabel(text=self.days_abrs[i]) l = Factory.Text(text=self.days_abrs[i], i18n=True) grid_layout.add_widget(l) # Buttons with days numbers for week in month: for day in week: if day[1] >= 5: # weekends tbtn = DayNumWeekendButton(text=str(day[0])) else: # work days tbtn = DayNumButton(text=str(day[0])) tbtn.bind(on_press=self.get_btn_value) if toogle_today: # Down today button if day[0] == self.active_date[0] and day[2] == 1: tbtn.state = "down" # Disable buttons with days from other months if day[2] == 0: tbtn.disabled = True grid_layout.add_widget(tbtn) self.sm.add_widget(scr) def prepare_data(self): """ Prepare data for showing on widget loading """ # Get days abbrs and month names lists self.month_names = cal_data.get_month_names() self.month_names_eng = cal_data.get_month_names_eng() self.days_abrs = cal_data.get_days_abbrs() # Today date self.active_date = cal_data.today_date_list() # Set title self.title = "%s - %s" % (self.i18n(self.month_names[self.active_date[1] - 1]), self.active_date[2]) # Quarter where current month in the self.quarter[1] self.get_quarter() def get_quarter(self): """ Get caledar and months/years nums for quarter """ self.quarter_nums = cal_data.calc_quarter(self.active_date[2], self.active_date[1]) self.quarter = cal_data.get_quarter(self.active_date[2], self.active_date[1]) def get_btn_value(self, inst): """ Get day value from pressed button """ self.active_date[0] = int(inst.text) if self.as_popup: self.parent_popup.dismiss() def go_prev(self, inst): """ Go to screen with previous month """ # Change active date self.active_date = [self.active_date[0], self.quarter_nums[0][1], self.quarter_nums[0][0]] # Name of prev screen n = self.quarter_nums[0][1] - 1 prev_scr_name = "%s-%s" % (self.month_names_eng[n], self.quarter_nums[0][0]) # If it's doen't exitst, create it if not self.sm.has_screen(prev_scr_name): self.create_month_scr(self.quarter[0]) self.sm.current = prev_scr_name self.sm.transition.direction = "right" self.get_quarter() self.title = "%s - %s" % (self.i18n(self.month_names[self.active_date[1] - 1]), self.active_date[2]) self.title_label.text = self.title def go_next(self, inst): """ Go to screen with next month """ # Change active date self.active_date = [self.active_date[0], self.quarter_nums[2][1], self.quarter_nums[2][0]] # Name of prev screen n = self.quarter_nums[2][1] - 1 next_scr_name = "%s-%s" % (self.month_names_eng[n], self.quarter_nums[2][0]) # If it's doen't exitst, create it if not self.sm.has_screen(next_scr_name): self.create_month_scr(self.quarter[2]) self.sm.current = next_scr_name self.sm.transition.direction = "left" self.get_quarter() self.title = "%s - %s" % (self.i18n(self.month_names[self.active_date[1] - 1]), self.active_date[2]) self.title_label.text = self.title def on_touch_move(self, touch): """ Switch months pages by touch move """ if self.touch_switch: # Left - prev if touch.dpos[0] < -30: self.go_prev(None) # Right - next elif touch.dpos[0] > 30: self.go_next(None) class ArrowButton(Button): pass class MonthYearLabel(Label): pass class MonthsManager(ScreenManager): pass class ButtonsGrid(GridLayout): pass class DayAbbrLabel(Label): pass class DayAbbrWeekendLabel(DayAbbrLabel): pass class DayButton(ToggleButton): pass class DayNumButton(DayButton): pass class DayNumWeekendButton(DayButton): pass
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""" Utilities for API Gateway response formatting """ import json def format_response(data, status=200): return { 'body': json.dumps(data), 'headers': { 'Content-Type': 'application/json' }, 'statusCode': int(status) } def format_error(msg, code='BadRequest', status=400): data = { 'success': False, 'error': { 'code': code, 'message': msg } } return format_response(data, status)
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# Copyright (c) 2013 Hewlett-Packard Development Company, L.P. # Copyright (c) 2012 VMware, Inc. # Copyright (c) 2011 Citrix Systems, Inc. # Copyright 2011 OpenStack Foundation # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. """ Class for VM tasks like spawn, snapshot, suspend, resume etc. """ import collections import copy import os import time import decorator from oslo.config import cfg from oslo.vmware import exceptions as vexc from nova.api.metadata import base as instance_metadata from nova import compute from nova.compute import power_state from nova.compute import task_states from nova.compute import vm_states from nova.console import type as ctype from nova import context as nova_context from nova import exception from nova.i18n import _, _LE, _LW from nova import objects from nova.openstack.common import excutils from nova.openstack.common import lockutils from nova.openstack.common import log as logging from nova.openstack.common import units from nova.openstack.common import uuidutils from nova import utils from nova.virt import configdrive from nova.virt import diagnostics from nova.virt import driver from nova.virt.vmwareapi import constants from nova.virt.vmwareapi import ds_util from nova.virt.vmwareapi import error_util from nova.virt.vmwareapi import imagecache from nova.virt.vmwareapi import vif as vmwarevif from nova.virt.vmwareapi import vim_util from nova.virt.vmwareapi import vm_util from nova.virt.vmwareapi import vmware_images CONF = cfg.CONF CONF.import_opt('image_cache_subdirectory_name', 'nova.virt.imagecache') CONF.import_opt('remove_unused_base_images', 'nova.virt.imagecache') CONF.import_opt('vnc_enabled', 'nova.vnc') CONF.import_opt('my_ip', 'nova.netconf') LOG = logging.getLogger(__name__) VMWARE_POWER_STATES = { 'poweredOff': power_state.SHUTDOWN, 'poweredOn': power_state.RUNNING, 'suspended': power_state.SUSPENDED} RESIZE_TOTAL_STEPS = 4 DcInfo = collections.namedtuple('DcInfo', ['ref', 'name', 'vmFolder']) class VirtualMachineInstanceConfigInfo(object): """Parameters needed to create and configure a new instance.""" def __init__(self, instance, instance_name, image_info, datastore, dc_info, image_cache): # Some methods called during spawn take the instance parameter purely # for logging purposes. # TODO(vui) Clean them up, so we no longer need to keep this variable self.instance = instance # Get the instance name. In some cases this may differ from the 'uuid', # for example when the spawn of a rescue instance takes place. self.instance_name = instance_name or instance.uuid self.ii = image_info self.root_gb = instance.root_gb self.datastore = datastore self.dc_info = dc_info self._image_cache = image_cache @property def cache_image_folder(self): if self.ii.image_id is None: return return self._image_cache.get_image_cache_folder( self.datastore, self.ii.image_id) @property def cache_image_path(self): if self.ii.image_id is None: return cached_image_file_name = "%s.%s" % (self.ii.image_id, self.ii.file_type) return self.cache_image_folder.join(cached_image_file_name) # Note(vui): See https://bugs.launchpad.net/nova/+bug/1363349 # for cases where mocking time.sleep() can have unintended effects on code # not under test. For now, unblock the affected test cases by providing # a wrapper function to work around needing to mock time.sleep() def _time_sleep_wrapper(delay): time.sleep(delay) @decorator.decorator def retry_if_task_in_progress(f, *args, **kwargs): retries = max(CONF.vmware.api_retry_count, 1) delay = 1 for attempt in range(1, retries + 1): if attempt != 1: _time_sleep_wrapper(delay) delay = min(2 * delay, 60) try: f(*args, **kwargs) return except error_util.TaskInProgress: pass class VMwareVMOps(object): """Management class for VM-related tasks.""" def __init__(self, session, virtapi, volumeops, cluster=None, datastore_regex=None): """Initializer.""" self.compute_api = compute.API() self._session = session self._virtapi = virtapi self._volumeops = volumeops self._cluster = cluster self._datastore_regex = datastore_regex # Ensure that the base folder is unique per compute node if CONF.remove_unused_base_images: self._base_folder = '%s%s' % (CONF.my_ip, CONF.image_cache_subdirectory_name) else: # Aging disable ensures backward compatibility self._base_folder = CONF.image_cache_subdirectory_name self._tmp_folder = 'vmware_temp' self._default_root_device = 'vda' self._rescue_suffix = '-rescue' self._migrate_suffix = '-orig' self._datastore_dc_mapping = {} self._datastore_browser_mapping = {} self._imagecache = imagecache.ImageCacheManager(self._session, self._base_folder) def _extend_virtual_disk(self, instance, requested_size, name, dc_ref): service_content = self._session._get_vim().service_content LOG.debug("Extending root virtual disk to %s", requested_size) vmdk_extend_task = self._session._call_method( self._session._get_vim(), "ExtendVirtualDisk_Task", service_content.virtualDiskManager, name=name, datacenter=dc_ref, newCapacityKb=requested_size, eagerZero=False) try: self._session._wait_for_task(vmdk_extend_task) except Exception as e: with excutils.save_and_reraise_exception(): LOG.error(_('Extending virtual disk failed with error: %s'), e, instance=instance) # Clean up files created during the extend operation files = [name.replace(".vmdk", "-flat.vmdk"), name] for file in files: ds_path = ds_util.DatastorePath.parse(file) self._delete_datastore_file(instance, ds_path, dc_ref) LOG.debug("Extended root virtual disk") def _delete_datastore_file(self, instance, datastore_path, dc_ref): try: ds_util.file_delete(self._session, datastore_path, dc_ref) except (vexc.CannotDeleteFileException, vexc.FileFaultException, vexc.FileLockedException, vexc.FileNotFoundException): LOG.debug("Unable to delete %(ds)s. There may be more than " "one process or thread trying to delete the file", {'ds': datastore_path}, exc_info=True) def _extend_if_required(self, dc_info, image_info, instance, root_vmdk_path): """Increase the size of the root vmdk if necessary.""" if instance.root_gb > image_info.file_size_in_gb: size_in_kb = instance.root_gb * units.Mi self._extend_virtual_disk(instance, size_in_kb, root_vmdk_path, dc_info.ref) def _configure_config_drive(self, instance, vm_ref, dc_info, datastore, injected_files, admin_password): session_vim = self._session._get_vim() cookies = session_vim.client.options.transport.cookiejar uploaded_iso_path = self._create_config_drive(instance, injected_files, admin_password, datastore.name, dc_info.name, instance['uuid'], cookies) uploaded_iso_path = datastore.build_path(uploaded_iso_path) self._attach_cdrom_to_vm( vm_ref, instance, datastore.ref, str(uploaded_iso_path)) def build_virtual_machine(self, instance, instance_name, image_info, dc_info, datastore, network_info): node_mo_id = vm_util.get_mo_id_from_instance(instance) res_pool_ref = vm_util.get_res_pool_ref(self._session, self._cluster, node_mo_id) vif_infos = vmwarevif.get_vif_info(self._session, self._cluster, utils.is_neutron(), image_info.vif_model, network_info) allocations = self._get_cpu_allocations(instance.instance_type_id) # Get the create vm config spec client_factory = self._session._get_vim().client.factory config_spec = vm_util.get_vm_create_spec(client_factory, instance, instance_name, datastore.name, vif_infos, image_info.os_type, allocations=allocations) # Create the VM vm_ref = vm_util.create_vm(self._session, instance, dc_info.vmFolder, config_spec, res_pool_ref) return vm_ref def _get_cpu_allocations(self, instance_type_id): # Read flavors for allocations flavor = objects.Flavor.get_by_id( nova_context.get_admin_context(read_deleted='yes'), instance_type_id) allocations = {} for (key, type) in (('cpu_limit', int), ('cpu_reservation', int), ('cpu_shares_level', str), ('cpu_shares_share', int)): value = flavor.extra_specs.get('quota:' + key) if value: allocations[key] = type(value) return allocations def _fetch_image_as_file(self, context, vi, image_ds_loc): """Download image as an individual file to host via HTTP PUT.""" session = self._session session_vim = session._get_vim() cookies = session_vim.client.options.transport.cookiejar LOG.debug("Downloading image file data %(image_id)s to " "%(file_path)s on the data store " "%(datastore_name)s", {'image_id': vi.ii.image_id, 'file_path': image_ds_loc, 'datastore_name': vi.datastore.name}, instance=vi.instance) vmware_images.fetch_image( context, vi.instance, session._host, vi.dc_info.name, vi.datastore.name, image_ds_loc.rel_path, cookies=cookies) def _prepare_sparse_image(self, vi): tmp_dir_loc = vi.datastore.build_path( self._tmp_folder, uuidutils.generate_uuid()) tmp_image_ds_loc = tmp_dir_loc.join( vi.ii.image_id, "tmp-sparse.vmdk") return tmp_dir_loc, tmp_image_ds_loc def _prepare_flat_image(self, vi): tmp_dir_loc = vi.datastore.build_path( self._tmp_folder, uuidutils.generate_uuid()) tmp_image_ds_loc = tmp_dir_loc.join( vi.ii.image_id, vi.cache_image_path.basename) ds_util.mkdir(self._session, tmp_image_ds_loc.parent, vi.dc_info.ref) vm_util.create_virtual_disk( self._session, vi.dc_info.ref, vi.ii.adapter_type, vi.ii.disk_type, str(tmp_image_ds_loc), vi.ii.file_size_in_kb) flat_vmdk_name = vi.cache_image_path.basename.replace('.vmdk', '-flat.vmdk') flat_vmdk_ds_loc = tmp_dir_loc.join(vi.ii.image_id, flat_vmdk_name) self._delete_datastore_file(vi.instance, str(flat_vmdk_ds_loc), vi.dc_info.ref) return tmp_dir_loc, flat_vmdk_ds_loc def _prepare_iso_image(self, vi): tmp_dir_loc = vi.datastore.build_path( self._tmp_folder, uuidutils.generate_uuid()) tmp_image_ds_loc = tmp_dir_loc.join( vi.ii.image_id, vi.cache_image_path.basename) return tmp_dir_loc, tmp_image_ds_loc def _move_to_cache(self, dc_ref, src_folder_ds_path, dst_folder_ds_path): try: ds_util.file_move(self._session, dc_ref, src_folder_ds_path, dst_folder_ds_path) except vexc.FileAlreadyExistsException: # Folder move has failed. This may be due to the fact that a # process or thread has already completed the operation. # Since image caching is synchronized, this can only happen # due to action external to the process. # In the event of a FileAlreadyExists we continue, # all other exceptions will be raised. LOG.warning(_LW("Destination %s already exists! Concurrent moves " "can lead to unexpected results."), dst_folder_ds_path) def _cache_sparse_image(self, vi, tmp_image_ds_loc): tmp_dir_loc = tmp_image_ds_loc.parent.parent converted_image_ds_loc = tmp_dir_loc.join( vi.ii.image_id, vi.cache_image_path.basename) # converts fetched image to preallocated disk vm_util.copy_virtual_disk( self._session, vi.dc_info.ref, str(tmp_image_ds_loc), str(converted_image_ds_loc)) self._delete_datastore_file(vi.instance, str(tmp_image_ds_loc), vi.dc_info.ref) self._move_to_cache(vi.dc_info.ref, tmp_image_ds_loc.parent, vi.cache_image_folder) def _cache_flat_image(self, vi, tmp_image_ds_loc): self._move_to_cache(vi.dc_info.ref, tmp_image_ds_loc.parent, vi.cache_image_folder) def _cache_iso_image(self, vi, tmp_image_ds_loc): self._move_to_cache(vi.dc_info.ref, tmp_image_ds_loc.parent, vi.cache_image_folder) def _get_vm_config_info(self, instance, image_info, instance_name=None): """Captures all relevant information from the spawn parameters.""" if (instance.root_gb != 0 and image_info.file_size_in_gb > instance.root_gb): reason = _("Image disk size greater than requested disk size") raise exception.InstanceUnacceptable(instance_id=instance.uuid, reason=reason) datastore = ds_util.get_datastore( self._session, self._cluster, self._datastore_regex) dc_info = self.get_datacenter_ref_and_name(datastore.ref) return VirtualMachineInstanceConfigInfo(instance, instance_name, image_info, datastore, dc_info, self._imagecache) def _get_image_callbacks(self, vi): disk_type = vi.ii.disk_type image_fetch = self._fetch_image_as_file if vi.ii.is_iso: image_prepare = self._prepare_iso_image image_cache = self._cache_iso_image elif disk_type == constants.DISK_TYPE_SPARSE: image_prepare = self._prepare_sparse_image image_cache = self._cache_sparse_image elif disk_type in constants.SUPPORTED_FLAT_VARIANTS: image_prepare = self._prepare_flat_image image_cache = self._cache_flat_image else: reason = _("disk type '%s' not supported") % disk_type raise exception.InvalidDiskInfo(reason=reason) return image_prepare, image_fetch, image_cache def _fetch_image_if_missing(self, context, vi): image_prepare, image_fetch, image_cache = self._get_image_callbacks(vi) LOG.debug("Processing image %s", vi.ii.image_id) with lockutils.lock(str(vi.cache_image_path), lock_file_prefix='nova-vmware-fetch_image'): self.check_cache_folder(vi.datastore.name, vi.datastore.ref) ds_browser = self._get_ds_browser(vi.datastore.ref) if not ds_util.file_exists(self._session, ds_browser, vi.cache_image_folder, vi.cache_image_path.basename): LOG.debug("Preparing fetch location") tmp_dir_loc, tmp_image_ds_loc = image_prepare(vi) LOG.debug("Fetch image to %s", tmp_image_ds_loc) image_fetch(context, vi, tmp_image_ds_loc) LOG.debug("Caching image") image_cache(vi, tmp_image_ds_loc) LOG.debug("Cleaning up location %s", str(tmp_dir_loc)) self._delete_datastore_file(vi.instance, str(tmp_dir_loc), vi.dc_info.ref) def spawn(self, context, instance, image_meta, injected_files, admin_password, network_info, block_device_info=None, instance_name=None, power_on=True): client_factory = self._session._get_vim().client.factory image_info = vmware_images.VMwareImage.from_image(instance.image_ref, image_meta) vi = self._get_vm_config_info(instance, image_info, instance_name) # Creates the virtual machine. The virtual machine reference returned # is unique within Virtual Center. vm_ref = self.build_virtual_machine(instance, vi.instance_name, image_info, vi.dc_info, vi.datastore, network_info) # Cache the vm_ref. This saves a remote call to the VC. This uses the # instance_name. This covers all use cases including rescue and resize. vm_util.vm_ref_cache_update(vi.instance_name, vm_ref) # Set the machine.id parameter of the instance to inject # the NIC configuration inside the VM if CONF.flat_injected: self._set_machine_id(client_factory, instance, network_info) # Set the vnc configuration of the instance, vnc port starts from 5900 if CONF.vnc_enabled: self._get_and_set_vnc_config(client_factory, instance) block_device_mapping = [] if block_device_info is not None: block_device_mapping = driver.block_device_info_get_mapping( block_device_info) # NOTE(mdbooth): the logic here is that we ignore the image if there # are block device mappings. This behaviour is incorrect, and a bug in # the driver. We should be able to accept an image and block device # mappings. if len(block_device_mapping) > 0: msg = "Block device information present: %s" % block_device_info # NOTE(mriedem): block_device_info can contain an auth_password # so we have to scrub the message before logging it. LOG.debug(logging.mask_password(msg), instance=instance) for root_disk in block_device_mapping: connection_info = root_disk['connection_info'] # TODO(hartsocks): instance is unnecessary, remove it # we still use instance in many locations for no other purpose # than logging, can we simplify this? self._volumeops.attach_root_volume(connection_info, instance, self._default_root_device, vi.datastore.ref) else: self._imagecache.enlist_image( image_info.image_id, vi.datastore, vi.dc_info.ref) self._fetch_image_if_missing(context, vi) if image_info.is_iso: self._use_iso_image(vm_ref, vi) elif image_info.linked_clone: self._use_disk_image_as_linked_clone(vm_ref, vi) else: self._use_disk_image_as_full_clone(vm_ref, vi) if configdrive.required_by(instance): self._configure_config_drive( instance, vm_ref, vi.dc_info, vi.datastore, injected_files, admin_password) if power_on: vm_util.power_on_instance(self._session, instance, vm_ref=vm_ref) def _create_config_drive(self, instance, injected_files, admin_password, data_store_name, dc_name, upload_folder, cookies): if CONF.config_drive_format != 'iso9660': reason = (_('Invalid config_drive_format "%s"') % CONF.config_drive_format) raise exception.InstancePowerOnFailure(reason=reason) LOG.info(_('Using config drive for instance'), instance=instance) extra_md = {} if admin_password: extra_md['admin_pass'] = admin_password inst_md = instance_metadata.InstanceMetadata(instance, content=injected_files, extra_md=extra_md) try: with configdrive.ConfigDriveBuilder(instance_md=inst_md) as cdb: with utils.tempdir() as tmp_path: tmp_file = os.path.join(tmp_path, 'configdrive.iso') cdb.make_drive(tmp_file) upload_iso_path = "%s/configdrive.iso" % ( upload_folder) vmware_images.upload_iso_to_datastore( tmp_file, instance, host=self._session._host, data_center_name=dc_name, datastore_name=data_store_name, cookies=cookies, file_path=upload_iso_path) return upload_iso_path except Exception as e: with excutils.save_and_reraise_exception(): LOG.error(_('Creating config drive failed with error: %s'), e, instance=instance) def _attach_cdrom_to_vm(self, vm_ref, instance, datastore, file_path): """Attach cdrom to VM by reconfiguration.""" client_factory = self._session._get_vim().client.factory devices = self._session._call_method(vim_util, "get_dynamic_property", vm_ref, "VirtualMachine", "config.hardware.device") (controller_key, unit_number, controller_spec) = vm_util.allocate_controller_key_and_unit_number( client_factory, devices, 'ide') cdrom_attach_config_spec = vm_util.get_cdrom_attach_config_spec( client_factory, datastore, file_path, controller_key, unit_number) if controller_spec: cdrom_attach_config_spec.deviceChange.append(controller_spec) LOG.debug("Reconfiguring VM instance to attach cdrom %s", file_path, instance=instance) vm_util.reconfigure_vm(self._session, vm_ref, cdrom_attach_config_spec) LOG.debug("Reconfigured VM instance to attach cdrom %s", file_path, instance=instance) def _create_vm_snapshot(self, instance, vm_ref): LOG.debug("Creating Snapshot of the VM instance", instance=instance) snapshot_task = self._session._call_method( self._session._get_vim(), "CreateSnapshot_Task", vm_ref, name="%s-snapshot" % instance.uuid, description="Taking Snapshot of the VM", memory=False, quiesce=True) self._session._wait_for_task(snapshot_task) LOG.debug("Created Snapshot of the VM instance", instance=instance) task_info = self._session._call_method(vim_util, "get_dynamic_property", snapshot_task, "Task", "info") snapshot = task_info.result return snapshot @retry_if_task_in_progress def _delete_vm_snapshot(self, instance, vm_ref, snapshot): LOG.debug("Deleting Snapshot of the VM instance", instance=instance) delete_snapshot_task = self._session._call_method( self._session._get_vim(), "RemoveSnapshot_Task", snapshot, removeChildren=False, consolidate=True) self._session._wait_for_task(delete_snapshot_task) LOG.debug("Deleted Snapshot of the VM instance", instance=instance) def snapshot(self, context, instance, image_id, update_task_state): """Create snapshot from a running VM instance. Steps followed are: 1. Get the name of the vmdk file which the VM points to right now. Can be a chain of snapshots, so we need to know the last in the chain. 2. Create the snapshot. A new vmdk is created which the VM points to now. The earlier vmdk becomes read-only. 3. Call CopyVirtualDisk which coalesces the disk chain to form a single vmdk, rather a .vmdk metadata file and a -flat.vmdk disk data file. 4. Now upload the -flat.vmdk file to the image store. 5. Delete the coalesced .vmdk and -flat.vmdk created. """ vm_ref = vm_util.get_vm_ref(self._session, instance) service_content = self._session._get_vim().service_content def _get_vm_and_vmdk_attribs(): # Get the vmdk file name that the VM is pointing to hw_devices = self._session._call_method(vim_util, "get_dynamic_property", vm_ref, "VirtualMachine", "config.hardware.device") (vmdk_file_path_before_snapshot, adapter_type, disk_type) = vm_util.get_vmdk_path_and_adapter_type( hw_devices, uuid=instance.uuid) if not vmdk_file_path_before_snapshot: LOG.debug("No root disk defined. Unable to snapshot.") raise error_util.NoRootDiskDefined() datastore_name = ds_util.DatastorePath.parse( vmdk_file_path_before_snapshot).datastore os_type = self._session._call_method(vim_util, "get_dynamic_property", vm_ref, "VirtualMachine", "summary.config.guestId") return (vmdk_file_path_before_snapshot, adapter_type, disk_type, datastore_name, os_type) (vmdk_file_path_before_snapshot, adapter_type, disk_type, datastore_name, os_type) = _get_vm_and_vmdk_attribs() snapshot = self._create_vm_snapshot(instance, vm_ref) update_task_state(task_state=task_states.IMAGE_PENDING_UPLOAD) def _check_if_tmp_folder_exists(): # Copy the contents of the VM that were there just before the # snapshot was taken ds_ref_ret = self._session._call_method( vim_util, "get_dynamic_property", vm_ref, "VirtualMachine", "datastore") if ds_ref_ret is None: raise exception.DatastoreNotFound() ds_ref = ds_ref_ret.ManagedObjectReference[0] self.check_temp_folder(datastore_name, ds_ref) return ds_ref ds_ref = _check_if_tmp_folder_exists() # Generate a random vmdk file name to which the coalesced vmdk content # will be copied to. A random name is chosen so that we don't have # name clashes. random_name = uuidutils.generate_uuid() dest_vmdk_file_path = ds_util.DatastorePath( datastore_name, self._tmp_folder, "%s.vmdk" % random_name) dest_vmdk_data_file_path = ds_util.DatastorePath( datastore_name, self._tmp_folder, "%s-flat.vmdk" % random_name) dc_info = self.get_datacenter_ref_and_name(ds_ref) def _copy_vmdk_content(): # Consolidate the snapshotted disk to a temporary vmdk. LOG.debug('Copying snapshotted disk %s.', vmdk_file_path_before_snapshot, instance=instance) copy_disk_task = self._session._call_method( self._session._get_vim(), "CopyVirtualDisk_Task", service_content.virtualDiskManager, sourceName=vmdk_file_path_before_snapshot, sourceDatacenter=dc_info.ref, destName=str(dest_vmdk_file_path), destDatacenter=dc_info.ref, force=False) self._session._wait_for_task(copy_disk_task) LOG.debug('Copied snapshotted disk %s.', vmdk_file_path_before_snapshot, instance=instance) _copy_vmdk_content() self._delete_vm_snapshot(instance, vm_ref, snapshot) cookies = self._session._get_vim().client.options.transport.cookiejar def _upload_vmdk_to_image_repository(): # Upload the contents of -flat.vmdk file which has the disk data. LOG.debug("Uploading image %s", image_id, instance=instance) vmware_images.upload_image( context, image_id, instance, os_type=os_type, disk_type=constants.DEFAULT_DISK_TYPE, adapter_type=adapter_type, image_version=1, host=self._session._host, data_center_name=dc_info.name, datastore_name=datastore_name, cookies=cookies, file_path="%s/%s-flat.vmdk" % (self._tmp_folder, random_name)) LOG.debug("Uploaded image %s", image_id, instance=instance) update_task_state(task_state=task_states.IMAGE_UPLOADING, expected_state=task_states.IMAGE_PENDING_UPLOAD) _upload_vmdk_to_image_repository() def _clean_temp_data(): """Delete temporary vmdk files generated in image handling operations. """ # The data file is the one occupying space, and likelier to see # deletion problems, so prioritize its deletion first. In the # unlikely event that its deletion fails, the small descriptor file # is retained too by design since it makes little sense to remove # it when the data disk it refers to still lingers. for f in dest_vmdk_data_file_path, dest_vmdk_file_path: self._delete_datastore_file(instance, f, dc_info.ref) _clean_temp_data() def reboot(self, instance, network_info): """Reboot a VM instance.""" vm_ref = vm_util.get_vm_ref(self._session, instance) lst_properties = ["summary.guest.toolsStatus", "runtime.powerState", "summary.guest.toolsRunningStatus"] props = self._session._call_method(vim_util, "get_object_properties", None, vm_ref, "VirtualMachine", lst_properties) query = vm_util.get_values_from_object_properties(self._session, props) pwr_state = query['runtime.powerState'] tools_status = query['summary.guest.toolsStatus'] tools_running_status = query['summary.guest.toolsRunningStatus'] # Raise an exception if the VM is not powered On. if pwr_state not in ["poweredOn"]: reason = _("instance is not powered on") raise exception.InstanceRebootFailure(reason=reason) # If latest vmware tools are installed in the VM, and that the tools # are running, then only do a guest reboot. Otherwise do a hard reset. if (tools_status == "toolsOk" and tools_running_status == "guestToolsRunning"): LOG.debug("Rebooting guest OS of VM", instance=instance) self._session._call_method(self._session._get_vim(), "RebootGuest", vm_ref) LOG.debug("Rebooted guest OS of VM", instance=instance) else: LOG.debug("Doing hard reboot of VM", instance=instance) reset_task = self._session._call_method(self._session._get_vim(), "ResetVM_Task", vm_ref) self._session._wait_for_task(reset_task) LOG.debug("Did hard reboot of VM", instance=instance) def _destroy_instance(self, instance, destroy_disks=True, instance_name=None): # Destroy a VM instance # Get the instance name. In some cases this may differ from the 'uuid', # for example when the spawn of a rescue instance takes place. if instance_name is None: instance_name = instance['uuid'] try: vm_ref = vm_util.get_vm_ref_from_name(self._session, instance_name) if vm_ref is None: LOG.warning(_('Instance does not exist on backend'), instance=instance) return lst_properties = ["config.files.vmPathName", "runtime.powerState", "datastore"] props = self._session._call_method(vim_util, "get_object_properties", None, vm_ref, "VirtualMachine", lst_properties) query = vm_util.get_values_from_object_properties( self._session, props) pwr_state = query['runtime.powerState'] vm_config_pathname = query['config.files.vmPathName'] vm_ds_path = None if vm_config_pathname: vm_ds_path = ds_util.DatastorePath.parse(vm_config_pathname) # Power off the VM if it is in PoweredOn state. if pwr_state == "poweredOn": vm_util.power_off_instance(self._session, instance, vm_ref) # Un-register the VM try: LOG.debug("Unregistering the VM", instance=instance) self._session._call_method(self._session._get_vim(), "UnregisterVM", vm_ref) LOG.debug("Unregistered the VM", instance=instance) except Exception as excep: LOG.warn(_("In vmwareapi:vmops:_destroy_instance, got this " "exception while un-registering the VM: %s"), excep) # Delete the folder holding the VM related content on # the datastore. if destroy_disks and vm_ds_path: try: dir_ds_compliant_path = vm_ds_path.parent LOG.debug("Deleting contents of the VM from " "datastore %(datastore_name)s", {'datastore_name': vm_ds_path.datastore}, instance=instance) ds_ref_ret = query['datastore'] ds_ref = ds_ref_ret.ManagedObjectReference[0] dc_info = self.get_datacenter_ref_and_name(ds_ref) ds_util.file_delete(self._session, dir_ds_compliant_path, dc_info.ref) LOG.debug("Deleted contents of the VM from " "datastore %(datastore_name)s", {'datastore_name': vm_ds_path.datastore}, instance=instance) except Exception: LOG.warn(_("In vmwareapi:vmops:_destroy_instance, " "exception while deleting the VM contents from " "the disk"), exc_info=True) except Exception as exc: LOG.exception(exc, instance=instance) finally: vm_util.vm_ref_cache_delete(instance_name) def destroy(self, instance, destroy_disks=True): """Destroy a VM instance. Steps followed for each VM are: 1. Power off, if it is in poweredOn state. 2. Un-register. 3. Delete the contents of the folder holding the VM related data. """ # If there is a rescue VM then we need to destroy that one too. LOG.debug("Destroying instance", instance=instance) if instance['vm_state'] == vm_states.RESCUED: LOG.debug("Rescue VM configured", instance=instance) try: self.unrescue(instance, power_on=False) LOG.debug("Rescue VM destroyed", instance=instance) except Exception: rescue_name = instance['uuid'] + self._rescue_suffix self._destroy_instance(instance, destroy_disks=destroy_disks, instance_name=rescue_name) # NOTE(arnaud): Destroy uuid-orig and uuid VMs iff it is not # triggered by the revert resize api call. This prevents # the uuid-orig VM to be deleted to be able to associate it later. if instance.task_state != task_states.RESIZE_REVERTING: # When VM deletion is triggered in middle of VM resize before VM # arrive RESIZED state, uuid-orig VM need to deleted to avoid # VM leak. Within method _destroy_instance it will check vmref # exist or not before attempt deletion. resize_orig_vmname = instance['uuid'] + self._migrate_suffix vm_orig_ref = vm_util.get_vm_ref_from_name(self._session, resize_orig_vmname) if vm_orig_ref: self._destroy_instance(instance, destroy_disks=destroy_disks, instance_name=resize_orig_vmname) self._destroy_instance(instance, destroy_disks=destroy_disks) LOG.debug("Instance destroyed", instance=instance) def pause(self, instance): msg = _("pause not supported for vmwareapi") raise NotImplementedError(msg) def unpause(self, instance): msg = _("unpause not supported for vmwareapi") raise NotImplementedError(msg) def suspend(self, instance): """Suspend the specified instance.""" vm_ref = vm_util.get_vm_ref(self._session, instance) pwr_state = self._session._call_method(vim_util, "get_dynamic_property", vm_ref, "VirtualMachine", "runtime.powerState") # Only PoweredOn VMs can be suspended. if pwr_state == "poweredOn": LOG.debug("Suspending the VM", instance=instance) suspend_task = self._session._call_method(self._session._get_vim(), "SuspendVM_Task", vm_ref) self._session._wait_for_task(suspend_task) LOG.debug("Suspended the VM", instance=instance) # Raise Exception if VM is poweredOff elif pwr_state == "poweredOff": reason = _("instance is powered off and cannot be suspended.") raise exception.InstanceSuspendFailure(reason=reason) else: LOG.debug("VM was already in suspended state. So returning " "without doing anything", instance=instance) def resume(self, instance): """Resume the specified instance.""" vm_ref = vm_util.get_vm_ref(self._session, instance) pwr_state = self._session._call_method(vim_util, "get_dynamic_property", vm_ref, "VirtualMachine", "runtime.powerState") if pwr_state.lower() == "suspended": LOG.debug("Resuming the VM", instance=instance) suspend_task = self._session._call_method( self._session._get_vim(), "PowerOnVM_Task", vm_ref) self._session._wait_for_task(suspend_task) LOG.debug("Resumed the VM", instance=instance) else: reason = _("instance is not in a suspended state") raise exception.InstanceResumeFailure(reason=reason) def rescue(self, context, instance, network_info, image_meta): """Rescue the specified instance. - shutdown the instance VM. - spawn a rescue VM (the vm name-label will be instance-N-rescue). """ vm_ref = vm_util.get_vm_ref(self._session, instance) self.power_off(instance) r_instance = copy.deepcopy(instance) instance_name = r_instance.uuid + self._rescue_suffix self.spawn(context, r_instance, image_meta, None, None, network_info, instance_name=instance_name, power_on=False) # Attach vmdk to the rescue VM hardware_devices = self._session._call_method(vim_util, "get_dynamic_property", vm_ref, "VirtualMachine", "config.hardware.device") (vmdk_path, adapter_type, disk_type) = vm_util.get_vmdk_path_and_adapter_type( hardware_devices, uuid=instance.uuid) rescue_vm_ref = vm_util.get_vm_ref_from_name(self._session, instance_name) self._volumeops.attach_disk_to_vm( rescue_vm_ref, r_instance, adapter_type, disk_type, vmdk_path) vm_util.power_on_instance(self._session, r_instance, vm_ref=rescue_vm_ref) def unrescue(self, instance, power_on=True): """Unrescue the specified instance.""" # Get the original vmdk_path vm_ref = vm_util.get_vm_ref(self._session, instance) hardware_devices = self._session._call_method(vim_util, "get_dynamic_property", vm_ref, "VirtualMachine", "config.hardware.device") (vmdk_path, adapter_type, disk_type) = vm_util.get_vmdk_path_and_adapter_type( hardware_devices, uuid=instance.uuid) r_instance = copy.deepcopy(instance) instance_name = r_instance.uuid + self._rescue_suffix # detach the original instance disk from the rescue disk vm_rescue_ref = vm_util.get_vm_ref_from_name(self._session, instance_name) hardware_devices = self._session._call_method(vim_util, "get_dynamic_property", vm_rescue_ref, "VirtualMachine", "config.hardware.device") device = vm_util.get_vmdk_volume_disk(hardware_devices, path=vmdk_path) vm_util.power_off_instance(self._session, r_instance, vm_rescue_ref) self._volumeops.detach_disk_from_vm(vm_rescue_ref, r_instance, device) self._destroy_instance(r_instance, instance_name=instance_name) if power_on: vm_util.power_on_instance(self._session, instance, vm_ref=vm_ref) def power_off(self, instance): """Power off the specified instance. :param instance: nova.objects.instance.Instance """ vm_util.power_off_instance(self._session, instance) def power_on(self, instance): vm_util.power_on_instance(self._session, instance) def _get_orig_vm_name_label(self, instance): return instance.uuid + '-orig' def _update_instance_progress(self, context, instance, step, total_steps): """Update instance progress percent to reflect current step number """ # Divide the action's workflow into discrete steps and "bump" the # instance's progress field as each step is completed. # # For a first cut this should be fine, however, for large VM images, # the clone disk step begins to dominate the equation. A # better approximation would use the percentage of the VM image that # has been streamed to the destination host. progress = round(float(step) / total_steps * 100) instance_uuid = instance.uuid LOG.debug("Updating instance '%(instance_uuid)s' progress to" " %(progress)d", {'instance_uuid': instance_uuid, 'progress': progress}, instance=instance) instance.progress = progress instance.save() def migrate_disk_and_power_off(self, context, instance, dest, flavor): """Transfers the disk of a running instance in multiple phases, turning off the instance before the end. """ # Checks if the migration needs a disk resize down. if flavor['root_gb'] < instance['root_gb']: reason = _("Unable to shrink disk.") raise exception.InstanceFaultRollback( exception.ResizeError(reason=reason)) # 0. Zero out the progress to begin self._update_instance_progress(context, instance, step=0, total_steps=RESIZE_TOTAL_STEPS) vm_ref = vm_util.get_vm_ref(self._session, instance) # Read the host_ref for the destination. If this is None then the # VC will decide on placement host_ref = self._get_host_ref_from_name(dest) # 1. Power off the instance self.power_off(instance) self._update_instance_progress(context, instance, step=1, total_steps=RESIZE_TOTAL_STEPS) # 2. Disassociate the linked vsphere VM from the instance vm_util.disassociate_vmref_from_instance(self._session, instance, vm_ref, suffix=self._migrate_suffix) self._update_instance_progress(context, instance, step=2, total_steps=RESIZE_TOTAL_STEPS) ds_ref = ds_util.get_datastore( self._session, self._cluster, datastore_regex=self._datastore_regex).ref dc_info = self.get_datacenter_ref_and_name(ds_ref) # 3. Clone the VM for instance vm_util.clone_vmref_for_instance(self._session, instance, vm_ref, host_ref, ds_ref, dc_info.vmFolder) self._update_instance_progress(context, instance, step=3, total_steps=RESIZE_TOTAL_STEPS) def confirm_migration(self, migration, instance, network_info): """Confirms a resize, destroying the source VM.""" # Destroy the original VM. The vm_ref needs to be searched using the # instance.uuid + self._migrate_suffix as the identifier. We will # not get the vm when searched using the instanceUuid but rather will # be found using the uuid buried in the extraConfig vm_ref = vm_util.search_vm_ref_by_identifier(self._session, instance.uuid + self._migrate_suffix) if vm_ref is None: LOG.debug("instance not present", instance=instance) return try: LOG.debug("Destroying the VM", instance=instance) destroy_task = self._session._call_method( self._session._get_vim(), "Destroy_Task", vm_ref) self._session._wait_for_task(destroy_task) LOG.debug("Destroyed the VM", instance=instance) except Exception as excep: LOG.warn(_("In vmwareapi:vmops:confirm_migration, got this " "exception while destroying the VM: %s"), excep) def finish_revert_migration(self, context, instance, network_info, block_device_info, power_on=True): """Finish reverting a resize.""" vm_util.associate_vmref_for_instance(self._session, instance, suffix=self._migrate_suffix) if power_on: vm_util.power_on_instance(self._session, instance) def finish_migration(self, context, migration, instance, disk_info, network_info, image_meta, resize_instance=False, block_device_info=None, power_on=True): """Completes a resize, turning on the migrated instance.""" vm_ref = vm_util.get_vm_ref(self._session, instance) if resize_instance: client_factory = self._session._get_vim().client.factory vm_resize_spec = vm_util.get_vm_resize_spec(client_factory, instance) vm_util.reconfigure_vm(self._session, vm_ref, vm_resize_spec) # Resize the disk (if larger) old_root_gb = instance.system_metadata['old_instance_type_root_gb'] if instance['root_gb'] > int(old_root_gb): root_disk_in_kb = instance['root_gb'] * units.Mi vmdk_path = vm_util.get_vmdk_path(self._session, vm_ref, instance) data_store_ref = ds_util.get_datastore(self._session, self._cluster, datastore_regex=self._datastore_regex).ref dc_info = self.get_datacenter_ref_and_name(data_store_ref) self._extend_virtual_disk(instance, root_disk_in_kb, vmdk_path, dc_info.ref) # TODO(ericwb): add extend for ephemeral disk # 4. Start VM if power_on: vm_util.power_on_instance(self._session, instance, vm_ref=vm_ref) self._update_instance_progress(context, instance, step=4, total_steps=RESIZE_TOTAL_STEPS) def live_migration(self, context, instance_ref, dest, post_method, recover_method, block_migration=False): """Spawning live_migration operation for distributing high-load.""" vm_ref = vm_util.get_vm_ref(self._session, instance_ref) host_ref = self._get_host_ref_from_name(dest) if host_ref is None: raise exception.HostNotFound(host=dest) LOG.debug("Migrating VM to host %s", dest, instance=instance_ref) try: vm_migrate_task = self._session._call_method( self._session._get_vim(), "MigrateVM_Task", vm_ref, host=host_ref, priority="defaultPriority") self._session._wait_for_task(vm_migrate_task) except Exception: with excutils.save_and_reraise_exception(): recover_method(context, instance_ref, dest, block_migration) post_method(context, instance_ref, dest, block_migration) LOG.debug("Migrated VM to host %s", dest, instance=instance_ref) def poll_rebooting_instances(self, timeout, instances): """Poll for rebooting instances.""" ctxt = nova_context.get_admin_context() instances_info = dict(instance_count=len(instances), timeout=timeout) if instances_info["instance_count"] > 0: LOG.info(_("Found %(instance_count)d hung reboots " "older than %(timeout)d seconds") % instances_info) for instance in instances: LOG.info(_("Automatically hard rebooting"), instance=instance) self.compute_api.reboot(ctxt, instance, "HARD") def get_info(self, instance): """Return data about the VM instance.""" vm_ref = vm_util.get_vm_ref(self._session, instance) lst_properties = ["summary.config.numCpu", "summary.config.memorySizeMB", "runtime.powerState"] vm_props = self._session._call_method(vim_util, "get_object_properties", None, vm_ref, "VirtualMachine", lst_properties) query = vm_util.get_values_from_object_properties( self._session, vm_props) max_mem = int(query['summary.config.memorySizeMB']) * 1024 return {'state': VMWARE_POWER_STATES[query['runtime.powerState']], 'max_mem': max_mem, 'mem': max_mem, 'num_cpu': int(query['summary.config.numCpu']), 'cpu_time': 0} def _get_diagnostics(self, instance): """Return data about VM diagnostics.""" vm_ref = vm_util.get_vm_ref(self._session, instance) lst_properties = ["summary.config", "summary.quickStats", "summary.runtime"] vm_props = self._session._call_method(vim_util, "get_object_properties", None, vm_ref, "VirtualMachine", lst_properties) query = vm_util.get_values_from_object_properties(self._session, vm_props) data = {} # All of values received are objects. Convert them to dictionaries for value in query.values(): prop_dict = vim_util.object_to_dict(value, list_depth=1) data.update(prop_dict) return data def get_diagnostics(self, instance): """Return data about VM diagnostics.""" data = self._get_diagnostics(instance) # Add a namespace to all of the diagnostsics return dict([('vmware:' + k, v) for k, v in data.items()]) def get_instance_diagnostics(self, instance): """Return data about VM diagnostics.""" data = self._get_diagnostics(instance) state = data.get('powerState') if state: state = power_state.STATE_MAP[VMWARE_POWER_STATES[state]] uptime = data.get('uptimeSeconds', 0) config_drive = configdrive.required_by(instance) diags = diagnostics.Diagnostics(state=state, driver='vmwareapi', config_drive=config_drive, hypervisor_os='esxi', uptime=uptime) diags.memory_details.maximum = data.get('memorySizeMB', 0) diags.memory_details.used = data.get('guestMemoryUsage', 0) # TODO(garyk): add in cpu, nic and disk stats return diags def _get_vnc_console_connection(self, instance): """Return connection info for a vnc console.""" vm_ref = vm_util.get_vm_ref(self._session, instance) opt_value = self._session._call_method(vim_util, 'get_dynamic_property', vm_ref, 'VirtualMachine', vm_util.VNC_CONFIG_KEY) if opt_value: port = int(opt_value.value) else: raise exception.ConsoleTypeUnavailable(console_type='vnc') return {'port': port, 'internal_access_path': None} @staticmethod def _get_machine_id_str(network_info): machine_id_str = '' for vif in network_info: # TODO(vish): add support for dns2 # TODO(sateesh): add support for injection of ipv6 configuration network = vif['network'] ip_v4 = netmask_v4 = gateway_v4 = broadcast_v4 = dns = None subnets_v4 = [s for s in network['subnets'] if s['version'] == 4] if len(subnets_v4) > 0: if len(subnets_v4[0]['ips']) > 0: ip_v4 = subnets_v4[0]['ips'][0] if len(subnets_v4[0]['dns']) > 0: dns = subnets_v4[0]['dns'][0]['address'] netmask_v4 = str(subnets_v4[0].as_netaddr().netmask) gateway_v4 = subnets_v4[0]['gateway']['address'] broadcast_v4 = str(subnets_v4[0].as_netaddr().broadcast) interface_str = ";".join([vif['address'], ip_v4 and ip_v4['address'] or '', netmask_v4 or '', gateway_v4 or '', broadcast_v4 or '', dns or '']) machine_id_str = machine_id_str + interface_str + '#' return machine_id_str def _set_machine_id(self, client_factory, instance, network_info): """Set the machine id of the VM for guest tools to pick up and reconfigure the network interfaces. """ vm_ref = vm_util.get_vm_ref(self._session, instance) machine_id_change_spec = vm_util.get_machine_id_change_spec( client_factory, self._get_machine_id_str(network_info)) LOG.debug("Reconfiguring VM instance to set the machine id", instance=instance) vm_util.reconfigure_vm(self._session, vm_ref, machine_id_change_spec) LOG.debug("Reconfigured VM instance to set the machine id", instance=instance) @utils.synchronized('vmware.get_and_set_vnc_port') def _get_and_set_vnc_config(self, client_factory, instance): """Set the vnc configuration of the VM.""" port = vm_util.get_vnc_port(self._session) vm_ref = vm_util.get_vm_ref(self._session, instance) vnc_config_spec = vm_util.get_vnc_config_spec( client_factory, port) LOG.debug("Reconfiguring VM instance to enable vnc on " "port - %(port)s", {'port': port}, instance=instance) vm_util.reconfigure_vm(self._session, vm_ref, vnc_config_spec) LOG.debug("Reconfigured VM instance to enable vnc on " "port - %(port)s", {'port': port}, instance=instance) def _get_ds_browser(self, ds_ref): ds_browser = self._datastore_browser_mapping.get(ds_ref.value) if not ds_browser: ds_browser = self._session._call_method( vim_util, "get_dynamic_property", ds_ref, "Datastore", "browser") self._datastore_browser_mapping[ds_ref.value] = ds_browser return ds_browser def _get_host_ref_from_name(self, host_name): """Get reference to the host with the name specified.""" host_objs = self._session._call_method(vim_util, "get_objects", "HostSystem", ["name"]) vm_util._cancel_retrieve_if_necessary(self._session, host_objs) for host in host_objs: if hasattr(host, 'propSet'): if host.propSet[0].val == host_name: return host.obj return None def _get_vmfolder_ref(self): """Get the Vm folder ref from the datacenter.""" dc_objs = self._session._call_method(vim_util, "get_objects", "Datacenter", ["vmFolder"]) vm_util._cancel_retrieve_if_necessary(self._session, dc_objs) # There is only one default datacenter in a standalone ESX host vm_folder_ref = dc_objs.objects[0].propSet[0].val return vm_folder_ref def _create_folder_if_missing(self, ds_name, ds_ref, folder): """Create a folder if it does not exist. Currently there are two folder that are required on the datastore - base folder - the folder to store cached images - temp folder - the folder used for snapshot management and image uploading This method is aimed to be used for the management of those folders to ensure that they are created if they are missing. The ds_util method mkdir will be used to check if the folder exists. If this throws and exception 'FileAlreadyExistsException' then the folder already exists on the datastore. """ path = ds_util.DatastorePath(ds_name, folder) dc_info = self.get_datacenter_ref_and_name(ds_ref) try: ds_util.mkdir(self._session, path, dc_info.ref) LOG.debug("Folder %s created.", path) except vexc.FileAlreadyExistsException: # NOTE(hartsocks): if the folder already exists, that # just means the folder was prepped by another process. pass def check_cache_folder(self, ds_name, ds_ref): """Check that the cache folder exists.""" self._create_folder_if_missing(ds_name, ds_ref, self._base_folder) def check_temp_folder(self, ds_name, ds_ref): """Check that the temp folder exists.""" self._create_folder_if_missing(ds_name, ds_ref, self._tmp_folder) def _check_if_folder_file_exists(self, ds_browser, ds_ref, ds_name, folder_name, file_name): # Ensure that the cache folder exists self.check_cache_folder(ds_name, ds_ref) # Check if the file exists or not. folder_ds_path = ds_util.DatastorePath(ds_name, folder_name) return ds_util.file_exists( self._session, ds_browser, folder_ds_path, file_name) def inject_network_info(self, instance, network_info): """inject network info for specified instance.""" # Set the machine.id parameter of the instance to inject # the NIC configuration inside the VM client_factory = self._session._get_vim().client.factory self._set_machine_id(client_factory, instance, network_info) def manage_image_cache(self, context, instances): if not CONF.remove_unused_base_images: LOG.debug("Image aging disabled. Aging will not be done.") return datastores = ds_util.get_available_datastores(self._session, self._cluster, self._datastore_regex) datastores_info = [] for ds in datastores: dc_info = self.get_datacenter_ref_and_name(ds.ref) datastores_info.append((ds, dc_info)) self._imagecache.update(context, instances, datastores_info) def _get_valid_vms_from_retrieve_result(self, retrieve_result): """Returns list of valid vms from RetrieveResult object.""" lst_vm_names = [] while retrieve_result: token = vm_util._get_token(retrieve_result) for vm in retrieve_result.objects: vm_name = None conn_state = None for prop in vm.propSet: if prop.name == "name": vm_name = prop.val elif prop.name == "runtime.connectionState": conn_state = prop.val # Ignoring the orphaned or inaccessible VMs if conn_state not in ["orphaned", "inaccessible"]: lst_vm_names.append(vm_name) if token: retrieve_result = self._session._call_method(vim_util, "continue_to_get_objects", token) else: break return lst_vm_names def instance_exists(self, instance): try: vm_util.get_vm_ref(self._session, instance) return True except exception.InstanceNotFound: return False def attach_interface(self, instance, image_meta, vif): """Attach an interface to the instance.""" vif_model = image_meta.get("hw_vif_model", constants.DEFAULT_VIF_MODEL) vif_model = vm_util.convert_vif_model(vif_model) vif_info = vmwarevif.get_vif_dict(self._session, self._cluster, vif_model, utils.is_neutron(), vif) vm_ref = vm_util.get_vm_ref(self._session, instance) # Ensure that there is not a race with the port index management with lockutils.lock(instance.uuid, lock_file_prefix='nova-vmware-hot-plug'): port_index = vm_util.get_attach_port_index(self._session, vm_ref) client_factory = self._session._get_vim().client.factory attach_config_spec = vm_util.get_network_attach_config_spec( client_factory, vif_info, port_index) LOG.debug("Reconfiguring VM to attach interface", instance=instance) try: vm_util.reconfigure_vm(self._session, vm_ref, attach_config_spec) except Exception as e: LOG.error(_LE('Attaching network adapter failed. Exception: ' ' %s'), e, instance=instance) raise exception.InterfaceAttachFailed( instance_uuid=instance['uuid']) LOG.debug("Reconfigured VM to attach interface", instance=instance) def detach_interface(self, instance, vif): """Detach an interface from the instance.""" vm_ref = vm_util.get_vm_ref(self._session, instance) # Ensure that there is not a race with the port index management with lockutils.lock(instance.uuid, lock_file_prefix='nova-vmware-hot-plug'): port_index = vm_util.get_vm_detach_port_index(self._session, vm_ref, vif['id']) if port_index is None: msg = _("No device with interface-id %s exists on " "VM") % vif['id'] raise exception.NotFound(msg) hardware_devices = self._session._call_method(vim_util, "get_dynamic_property", vm_ref, "VirtualMachine", "config.hardware.device") device = vmwarevif.get_network_device(hardware_devices, vif['address']) if device is None: msg = _("No device with MAC address %s exists on the " "VM") % vif['address'] raise exception.NotFound(msg) client_factory = self._session._get_vim().client.factory detach_config_spec = vm_util.get_network_detach_config_spec( client_factory, device, port_index) LOG.debug("Reconfiguring VM to detach interface", instance=instance) try: vm_util.reconfigure_vm(self._session, vm_ref, detach_config_spec) except Exception as e: LOG.error(_LE('Detaching network adapter failed. Exception: ' '%s'), e, instance=instance) raise exception.InterfaceDetachFailed( instance_uuid=instance['uuid']) LOG.debug("Reconfigured VM to detach interface", instance=instance) def _use_disk_image_as_full_clone(self, vm_ref, vi): """Uses cached image disk by copying it into the VM directory.""" instance_folder = vi.instance_name root_disk_name = "%s.vmdk" % vi.instance_name root_disk_ds_loc = vi.datastore.build_path(instance_folder, root_disk_name) vm_util.copy_virtual_disk( self._session, vi.dc_info.ref, str(vi.cache_image_path), str(root_disk_ds_loc)) self._extend_if_required( vi.dc_info, vi.ii, vi.instance, str(root_disk_ds_loc)) self._volumeops.attach_disk_to_vm( vm_ref, vi.instance, vi.ii.adapter_type, vi.ii.disk_type, str(root_disk_ds_loc), vi.root_gb * units.Mi, False) def _sized_image_exists(self, sized_disk_ds_loc, ds_ref): ds_browser = self._get_ds_browser(ds_ref) return ds_util.file_exists( self._session, ds_browser, sized_disk_ds_loc.parent, sized_disk_ds_loc.basename) def _use_disk_image_as_linked_clone(self, vm_ref, vi): """Uses cached image as parent of a COW child in the VM directory.""" sized_image_disk_name = "%s.vmdk" % vi.ii.image_id if vi.root_gb > 0: sized_image_disk_name = "%s.%s.vmdk" % (vi.ii.image_id, vi.root_gb) sized_disk_ds_loc = vi.cache_image_folder.join(sized_image_disk_name) # Ensure only a single thread extends the image at once. # We do this by taking a lock on the name of the extended # image. This allows multiple threads to create resized # copies simultaneously, as long as they are different # sizes. Threads attempting to create the same resized copy # will be serialized, with only the first actually creating # the copy. # # Note that the object is in a per-nova cache directory, # so inter-nova locking is not a concern. Consequently we # can safely use simple thread locks. with lockutils.lock(str(sized_disk_ds_loc), lock_file_prefix='nova-vmware-image'): if not self._sized_image_exists(sized_disk_ds_loc, vi.datastore.ref): LOG.debug("Copying root disk of size %sGb", vi.root_gb) try: vm_util.copy_virtual_disk( self._session, vi.dc_info.ref, str(vi.cache_image_path), str(sized_disk_ds_loc)) except Exception as e: LOG.warning(_("Root disk file creation " "failed - %s"), e) with excutils.save_and_reraise_exception(): LOG.error(_LE('Failed to copy cached ' 'image %(source)s to ' '%(dest)s for resize: ' '%(error)s'), {'source': vi.cache_image_path, 'dest': sized_disk_ds_loc, 'error': e.message}) try: ds_util.file_delete(self._session, sized_disk_ds_loc, vi.dc_info.ref) except vexc.FileNotFoundException: # File was never created: cleanup not # required pass # Resize the copy to the appropriate size. No need # for cleanup up here, as _extend_virtual_disk # already does it self._extend_if_required( vi.dc_info, vi.ii, vi.instance, str(sized_disk_ds_loc)) # Associate the sized image disk to the VM by attaching to the VM a # COW child of said disk. self._volumeops.attach_disk_to_vm( vm_ref, vi.instance, vi.ii.adapter_type, vi.ii.disk_type, str(sized_disk_ds_loc), vi.root_gb * units.Mi, vi.ii.linked_clone) def _use_iso_image(self, vm_ref, vi): """Uses cached image as a bootable virtual cdrom.""" self._attach_cdrom_to_vm( vm_ref, vi.instance, vi.datastore.ref, str(vi.cache_image_path)) # Optionally create and attach blank disk if vi.root_gb > 0: instance_folder = vi.instance_name root_disk_name = "%s.vmdk" % vi.instance_name root_disk_ds_loc = vi.datastore.build_path(instance_folder, root_disk_name) # It is pointless to COW a blank disk linked_clone = False vm_util.create_virtual_disk( self._session, vi.dc_info.ref, vi.ii.adapter_type, vi.ii.disk_type, str(root_disk_ds_loc), vi.root_gb * units.Mi) self._volumeops.attach_disk_to_vm( vm_ref, vi.instance, vi.ii.adapter_type, vi.ii.disk_type, str(root_disk_ds_loc), vi.root_gb * units.Mi, linked_clone) def _update_datacenter_cache_from_objects(self, dcs): """Updates the datastore/datacenter cache.""" while dcs: token = vm_util._get_token(dcs) for dco in dcs.objects: dc_ref = dco.obj ds_refs = [] prop_dict = vm_util.propset_dict(dco.propSet) name = prop_dict.get('name') vmFolder = prop_dict.get('vmFolder') datastore_refs = prop_dict.get('datastore') if datastore_refs: datastore_refs = datastore_refs.ManagedObjectReference for ds in datastore_refs: ds_refs.append(ds.value) else: LOG.debug("Datacenter %s doesn't have any datastore " "associated with it, ignoring it", name) for ds_ref in ds_refs: self._datastore_dc_mapping[ds_ref] = DcInfo(ref=dc_ref, name=name, vmFolder=vmFolder) if token: dcs = self._session._call_method(vim_util, "continue_to_get_objects", token) else: break def get_datacenter_ref_and_name(self, ds_ref): """Get the datacenter name and the reference.""" dc_info = self._datastore_dc_mapping.get(ds_ref.value) if not dc_info: dcs = self._session._call_method(vim_util, "get_objects", "Datacenter", ["name", "datastore", "vmFolder"]) self._update_datacenter_cache_from_objects(dcs) dc_info = self._datastore_dc_mapping.get(ds_ref.value) return dc_info def list_instances(self): """Lists the VM instances that are registered with vCenter cluster.""" properties = ['name', 'runtime.connectionState'] LOG.debug("Getting list of instances from cluster %s", self._cluster) vms = [] root_res_pool = self._session._call_method( vim_util, "get_dynamic_property", self._cluster, 'ClusterComputeResource', 'resourcePool') if root_res_pool: vms = self._session._call_method( vim_util, 'get_inner_objects', root_res_pool, 'vm', 'VirtualMachine', properties) lst_vm_names = self._get_valid_vms_from_retrieve_result(vms) LOG.debug("Got total of %s instances", str(len(lst_vm_names))) return lst_vm_names def get_vnc_console(self, instance): """Return connection info for a vnc console using vCenter logic.""" # vCenter does not run virtual machines and does not run # a VNC proxy. Instead, you need to tell OpenStack to talk # directly to the ESX host running the VM you are attempting # to connect to via VNC. vnc_console = self._get_vnc_console_connection(instance) host_name = vm_util.get_host_name_for_vm( self._session, instance) vnc_console['host'] = host_name # NOTE: VM can move hosts in some situations. Debug for admins. LOG.debug("VM %(uuid)s is currently on host %(host_name)s", {'uuid': instance.name, 'host_name': host_name}, instance=instance) return ctype.ConsoleVNC(**vnc_console)
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from pathlib import Path import json # Directory dir = Path().resolve() # Configuration with open(dir/'config.json') as config_file: CONFIG = json.load(config_file) def output_dir(config = CONFIG): """ Return string for default output directory path. """ return(config['output_dir']['path'])
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# -*- coding: utf-8 -*- from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np from scipy.ndimage import map_coordinates from scipy.ndimage.interpolation import shift from scipy.optimize import curve_fit, minimize def reproject_image_into_polar(data, origin=None, Jacobian=False, dr=1, dt=None): """ Reprojects a 2D numpy array (``data``) into a polar coordinate system. "origin" is a tuple of (x0, y0) relative to the bottom-left image corner, and defaults to the center of the image. Parameters ---------- data : 2D np.array origin : tuple The coordinate of the image center, relative to bottom-left Jacobian : boolean Include ``r`` intensity scaling in the coordinate transform. This should be included to account for the changing pixel size that occurs during the transform. dr : float Radial coordinate spacing for the grid interpolation tests show that there is not much point in going below 0.5 dt : float Angular coordinate spacing (in radians) if ``dt=None``, dt will be set such that the number of theta values is equal to the maximum value between the height or the width of the image. Returns ------- output : 2D np.array The polar image (r, theta) r_grid : 2D np.array meshgrid of radial coordinates theta_grid : 2D np.array meshgrid of theta coordinates Notes ----- Adapted from: http://stackoverflow.com/questions/3798333/image-information-along-a-polar-coordinate-system """ # bottom-left coordinate system requires numpy image to be np.flipud data = np.flipud(data) ny, nx = data.shape[:2] if origin is None: origin = (nx//2, ny//2) # Determine that the min and max r and theta coords will be... x, y = index_coords(data, origin=origin) # (x,y) coordinates of each pixel r, theta = cart2polar(x, y) # convert (x,y) -> (r,θ), note θ=0 is vertical nr = np.int(np.ceil((r.max()-r.min())/dr)) if dt is None: nt = max(nx, ny) else: # dt in radians nt = np.int(np.ceil((theta.max()-theta.min())/dt)) # Make a regular (in polar space) grid based on the min and max r & theta r_i = np.linspace(r.min(), r.max(), nr, endpoint=False) theta_i = np.linspace(theta.min(), theta.max(), nt, endpoint=False) theta_grid, r_grid = np.meshgrid(theta_i, r_i) # Project the r and theta grid back into pixel coordinates X, Y = polar2cart(r_grid, theta_grid) X += origin[0] # We need to shift the origin Y += origin[1] # back to the bottom-left corner... xi, yi = X.flatten(), Y.flatten() coords = np.vstack((yi, xi)) # (map_coordinates requires a 2xn array) zi = map_coordinates(data, coords) output = zi.reshape((nr, nt)) if Jacobian: output = output*r_i[:, np.newaxis] return output, r_grid, theta_grid def index_coords(data, origin=None): """ Creates x & y coords for the indicies in a numpy array Parameters ---------- data : numpy array 2D data origin : (x,y) tuple defaults to the center of the image. Specify origin=(0,0) to set the origin to the *bottom-left* corner of the image. Returns ------- x, y : arrays """ ny, nx = data.shape[:2] if origin is None: origin_x, origin_y = nx//2, ny//2 else: origin_x, origin_y = origin x, y = np.meshgrid(np.arange(float(nx)), np.arange(float(ny))) x -= origin_x y -= origin_y return x, y def cart2polar(x, y): """ Transform Cartesian coordinates to polar Parameters ---------- x, y : floats or arrays Cartesian coordinates Returns ------- r, theta : floats or arrays Polar coordinates """ r = np.sqrt(x**2 + y**2) theta = np.arctan2(x, y) # θ referenced to vertical return r, theta def polar2cart(r, theta): """ Transform polar coordinates to Cartesian Parameters ------- r, theta : floats or arrays Polar coordinates Returns ---------- x, y : floats or arrays Cartesian coordinates """ y = r * np.cos(theta) # θ referenced to vertical x = r * np.sin(theta) return x, y
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# -*- coding: utf-8 -*- # PLEASE DO NOT EDIT THIS FILE, IT IS GENERATED AND WILL BE OVERWRITTEN: # https://github.com/ccxt/ccxt/blob/master/CONTRIBUTING.md#how-to-contribute-code from ccxt.async_support.base.exchange import Exchange import math from ccxt.base.errors import ExchangeError from ccxt.base.errors import AuthenticationError from ccxt.base.errors import ArgumentsRequired from ccxt.base.errors import InsufficientFunds from ccxt.base.errors import InvalidOrder from ccxt.base.errors import OrderNotFound from ccxt.base.errors import DDoSProtection class okcoinusd (Exchange): def describe(self): return self.deep_extend(super(okcoinusd, self).describe(), { 'id': 'okcoinusd', 'name': 'OKCoin USD', 'countries': ['CN', 'US'], 'version': 'v1', 'rateLimit': 1000, # up to 3000 requests per 5 minutes ≈ 600 requests per minute ≈ 10 requests per second ≈ 100 ms 'has': { 'CORS': False, 'fetchOHLCV': True, 'fetchOrder': True, 'fetchOrders': False, 'fetchOpenOrders': True, 'fetchClosedOrders': True, 'withdraw': True, 'futures': False, }, 'extension': '.do', # appended to endpoint URL 'timeframes': { '1m': '1min', '3m': '3min', '5m': '5min', '15m': '15min', '30m': '30min', '1h': '1hour', '2h': '2hour', '4h': '4hour', '6h': '6hour', '12h': '12hour', '1d': '1day', '3d': '3day', '1w': '1week', }, 'api': { 'web': { 'get': [ 'futures/pc/market/marketOverview', # todo: merge in fetchMarkets 'spot/markets/index-tickers', # todo: add fetchTickers 'spot/markets/currencies', 'spot/markets/products', 'spot/markets/tickers', 'spot/user-level', ], }, 'public': { 'get': [ 'depth', 'exchange_rate', 'future_depth', 'future_estimated_price', 'future_hold_amount', 'future_index', 'future_kline', 'future_price_limit', 'future_ticker', 'future_trades', 'kline', 'otcs', 'ticker', 'tickers', # todo: add fetchTickers 'trades', ], }, 'private': { 'post': [ 'account_records', 'batch_trade', 'borrow_money', 'borrow_order_info', 'borrows_info', 'cancel_borrow', 'cancel_order', 'cancel_otc_order', 'cancel_withdraw', 'funds_transfer', 'future_batch_trade', 'future_cancel', 'future_devolve', 'future_explosive', 'future_order_info', 'future_orders_info', 'future_position', 'future_position_4fix', 'future_trade', 'future_trades_history', 'future_userinfo', 'future_userinfo_4fix', 'lend_depth', 'order_fee', 'order_history', 'order_info', 'orders_info', 'otc_order_history', 'otc_order_info', 'repayment', 'submit_otc_order', 'trade', 'trade_history', 'trade_otc_order', 'wallet_info', 'withdraw', 'withdraw_info', 'unrepayments_info', 'userinfo', ], }, }, 'urls': { 'logo': 'https://user-images.githubusercontent.com/1294454/27766791-89ffb502-5ee5-11e7-8a5b-c5950b68ac65.jpg', 'api': { 'web': 'https://www.okcoin.com/v2', 'public': 'https://www.okcoin.com/api', 'private': 'https://www.okcoin.com', }, 'www': 'https://www.okcoin.com', 'doc': [ 'https://www.okcoin.com/docs/en/', 'https://www.npmjs.com/package/okcoin.com', ], }, 'fees': { 'trading': { 'taker': 0.002, 'maker': 0.002, }, }, 'exceptions': { # see https://github.com/okcoin-okex/API-docs-OKEx.com/blob/master/API-For-Spot-EN/Error%20Code%20For%20Spot.md '10000': ExchangeError, # "Required field, can not be null" '10001': DDoSProtection, # "Request frequency too high to exceed the limit allowed" '10005': AuthenticationError, # "'SecretKey' does not exist" '10006': AuthenticationError, # "'Api_key' does not exist" '10007': AuthenticationError, # "Signature does not match" '1002': InsufficientFunds, # "The transaction amount exceed the balance" '1003': InvalidOrder, # "The transaction amount is less than the minimum requirement" '1004': InvalidOrder, # "The transaction amount is less than 0" '1013': InvalidOrder, # no contract type(PR-1101) '1027': InvalidOrder, # createLimitBuyOrder(symbol, 0, 0): Incorrect parameter may exceeded limits '1050': InvalidOrder, # returned when trying to cancel an order that was filled or canceled previously '1217': InvalidOrder, # "Order was sent at ±5% of the current market price. Please resend" '10014': InvalidOrder, # "Order price must be between 0 and 1,000,000" '1009': OrderNotFound, # for spot markets, cancelling closed order '1019': OrderNotFound, # order closed?("Undo order failed") '1051': OrderNotFound, # for spot markets, cancelling "just closed" order '10009': OrderNotFound, # for spot markets, "Order does not exist" '20015': OrderNotFound, # for future markets '10008': ExchangeError, # Illegal URL parameter # todo: sort out below # 10000 Required parameter is empty # 10001 Request frequency too high to exceed the limit allowed # 10002 Authentication failure # 10002 System error # 10003 This connection has requested other user data # 10004 Request failed # 10005 api_key or sign is invalid, 'SecretKey' does not exist # 10006 'Api_key' does not exist # 10007 Signature does not match # 10008 Illegal parameter, Parameter erorr # 10009 Order does not exist # 10010 Insufficient funds # 10011 Amount too low # 10012 Only btc_usd ltc_usd supported # 10013 Only support https request # 10014 Order price must be between 0 and 1,000,000 # 10015 Order price differs from current market price too much / Channel subscription temporally not available # 10016 Insufficient coins balance # 10017 API authorization error / WebSocket authorization error # 10018 borrow amount less than lower limit [usd:100,btc:0.1,ltc:1] # 10019 loan agreement not checked # 1002 The transaction amount exceed the balance # 10020 rate cannot exceed 1% # 10021 rate cannot less than 0.01% # 10023 fail to get latest ticker # 10024 balance not sufficient # 10025 quota is full, cannot borrow temporarily # 10026 Loan(including reserved loan) and margin cannot be withdrawn # 10027 Cannot withdraw within 24 hrs of authentication information modification # 10028 Withdrawal amount exceeds daily limit # 10029 Account has unpaid loan, please cancel/pay off the loan before withdraw # 1003 The transaction amount is less than the minimum requirement # 10031 Deposits can only be withdrawn after 6 confirmations # 10032 Please enabled phone/google authenticator # 10033 Fee higher than maximum network transaction fee # 10034 Fee lower than minimum network transaction fee # 10035 Insufficient BTC/LTC # 10036 Withdrawal amount too low # 10037 Trade password not set # 1004 The transaction amount is less than 0 # 10040 Withdrawal cancellation fails # 10041 Withdrawal address not exsit or approved # 10042 Admin password error # 10043 Account equity error, withdrawal failure # 10044 fail to cancel borrowing order # 10047 self function is disabled for sub-account # 10048 withdrawal information does not exist # 10049 User can not have more than 50 unfilled small orders(amount<0.15BTC) # 10050 can't cancel more than once # 10051 order completed transaction # 10052 not allowed to withdraw # 10064 after a USD deposit, that portion of assets will not be withdrawable for the next 48 hours # 1007 No trading market information # 1008 No latest market information # 1009 No order # 1010 Different user of the cancelled order and the original order # 10100 User account frozen # 10101 order type is wrong # 10102 incorrect ID # 10103 the private otc order's key incorrect # 10106 API key domain not matched # 1011 No documented user # 1013 No order type # 1014 No login # 1015 No market depth information # 1017 Date error # 1018 Order failed # 1019 Undo order failed # 10216 Non-available API / non-public API # 1024 Currency does not exist # 1025 No chart type # 1026 No base currency quantity # 1027 Incorrect parameter may exceeded limits # 1028 Reserved decimal failed # 1029 Preparing # 1030 Account has margin and futures, transactions can not be processed # 1031 Insufficient Transferring Balance # 1032 Transferring Not Allowed # 1035 Password incorrect # 1036 Google Verification code Invalid # 1037 Google Verification code incorrect # 1038 Google Verification replicated # 1039 Message Verification Input exceed the limit # 1040 Message Verification invalid # 1041 Message Verification incorrect # 1042 Wrong Google Verification Input exceed the limit # 1043 Login password cannot be same as the trading password # 1044 Old password incorrect # 1045 2nd Verification Needed # 1046 Please input old password # 1048 Account Blocked # 1050 Orders have been withdrawn or withdrawn # 1051 Order completed # 1201 Account Deleted at 00: 00 # 1202 Account Not Exist # 1203 Insufficient Balance # 1204 Invalid currency # 1205 Invalid Account # 1206 Cash Withdrawal Blocked # 1207 Transfer Not Support # 1208 No designated account # 1209 Invalid api # 1216 Market order temporarily suspended. Please send limit order # 1217 Order was sent at ±5% of the current market price. Please resend # 1218 Place order failed. Please try again later # 20001 User does not exist # 20002 Account frozen # 20003 Account frozen due to forced liquidation # 20004 Contract account frozen # 20005 User contract account does not exist # 20006 Required field missing # 20007 Illegal parameter # 20008 Contract account balance is too low # 20009 Contract status error # 20010 Risk rate ratio does not exist # 20011 Risk rate lower than 90%/80% before opening BTC position with 10x/20x leverage. or risk rate lower than 80%/60% before opening LTC position with 10x/20x leverage # 20012 Risk rate lower than 90%/80% after opening BTC position with 10x/20x leverage. or risk rate lower than 80%/60% after opening LTC position with 10x/20x leverage # 20013 Temporally no counter party price # 20014 System error # 20015 Order does not exist # 20016 Close amount bigger than your open positions, liquidation quantity bigger than holding # 20017 Not authorized/illegal operation/illegal order ID # 20018 Order price cannot be more than 103-105% or less than 95-97% of the previous minute price # 20019 IP restricted from accessing the resource # 20020 Secret key does not exist # 20021 Index information does not exist # 20022 Wrong API interface(Cross margin mode shall call cross margin API, fixed margin mode shall call fixed margin API) # 20023 Account in fixed-margin mode # 20024 Signature does not match # 20025 Leverage rate error # 20026 API Permission Error # 20027 no transaction record # 20028 no such contract # 20029 Amount is large than available funds # 20030 Account still has debts # 20038 Due to regulation, self function is not availavle in the country/region your currently reside in. # 20049 Request frequency too high # 20100 request time out # 20101 the format of data is error # 20102 invalid login # 20103 event type error # 20104 subscription type error # 20107 JSON format error # 20115 The quote is not match # 20116 Param not match # 21020 Contracts are being delivered, orders cannot be placed # 21021 Contracts are being settled, contracts cannot be placed }, 'options': { 'marketBuyPrice': False, 'defaultContractType': 'this_week', # next_week, quarter 'warnOnFetchOHLCVLimitArgument': True, 'fiats': ['USD', 'CNY'], 'futures': { 'BCH': True, 'BTC': True, 'BTG': True, 'EOS': True, 'ETC': True, 'ETH': True, 'LTC': True, 'NEO': True, 'QTUM': True, 'USDT': True, 'XRP': True, }, }, }) async def fetch_markets(self, params={}): response = await self.webGetSpotMarketsProducts() markets = response['data'] result = [] for i in range(0, len(markets)): id = markets[i]['symbol'] baseId, quoteId = id.split('_') baseIdUppercase = baseId.upper() quoteIdUppercase = quoteId.upper() base = self.common_currency_code(baseIdUppercase) quote = self.common_currency_code(quoteIdUppercase) symbol = base + '/' + quote precision = { 'amount': markets[i]['maxSizeDigit'], 'price': markets[i]['maxPriceDigit'], } minAmount = markets[i]['minTradeSize'] minPrice = math.pow(10, -precision['price']) active = (markets[i]['online'] != 0) baseNumericId = markets[i]['baseCurrency'] quoteNumericId = markets[i]['quoteCurrency'] market = self.extend(self.fees['trading'], { 'id': id, 'symbol': symbol, 'base': base, 'quote': quote, 'baseId': baseId, 'quoteId': quoteId, 'baseNumericId': baseNumericId, 'quoteNumericId': quoteNumericId, 'info': markets[i], 'type': 'spot', 'spot': True, 'future': False, 'active': active, 'precision': precision, 'limits': { 'amount': { 'min': minAmount, 'max': None, }, 'price': { 'min': minPrice, 'max': None, }, 'cost': { 'min': minAmount * minPrice, 'max': None, }, }, }) result.append(market) if (self.has['futures']) and(market['base'] in list(self.options['futures'].keys())): fiats = self.options['fiats'] for j in range(0, len(fiats)): fiat = fiats[j] lowercaseFiat = fiat.lower() result.append(self.extend(market, { 'quote': fiat, 'symbol': market['base'] + '/' + fiat, 'id': market['base'].lower() + '_' + lowercaseFiat, 'quoteId': lowercaseFiat, 'type': 'future', 'spot': False, 'future': True, })) return result async def fetch_order_book(self, symbol, limit=None, params={}): await self.load_markets() market = self.market(symbol) method = 'publicGet' request = { 'symbol': market['id'], } if limit is not None: request['size'] = limit if market['future']: method += 'Future' request['contract_type'] = self.options['defaultContractType'] # self_week, next_week, quarter method += 'Depth' orderbook = await getattr(self, method)(self.extend(request, params)) return self.parse_order_book(orderbook) def parse_ticker(self, ticker, market=None): # # { buy: "48.777300", # change: "-1.244500", # changePercentage: "-2.47%", # close: "49.064000", # createdDate: 1531704852254, # currencyId: 527, # dayHigh: "51.012500", # dayLow: "48.124200", # high: "51.012500", # inflows: "0", # last: "49.064000", # low: "48.124200", # marketFrom: 627, # name: {}, # open: "50.308500", # outflows: "0", # productId: 527, # sell: "49.064000", # symbol: "zec_okb", # volume: "1049.092535" } # timestamp = self.safe_integer_2(ticker, 'timestamp', 'createdDate') symbol = None if market is None: if 'symbol' in ticker: marketId = ticker['symbol'] if marketId in self.markets_by_id: market = self.markets_by_id[marketId] else: baseId, quoteId = ticker['symbol'].split('_') base = baseId.upper() quote = quoteId.upper() base = self.common_currency_code(base) quote = self.common_currency_code(quote) symbol = base + '/' + quote if market is not None: symbol = market['symbol'] last = self.safe_float(ticker, 'last') open = self.safe_float(ticker, 'open') change = self.safe_float(ticker, 'change') percentage = self.safe_float(ticker, 'changePercentage') return { 'symbol': symbol, 'timestamp': timestamp, 'datetime': self.iso8601(timestamp), 'high': self.safe_float(ticker, 'high'), 'low': self.safe_float(ticker, 'low'), 'bid': self.safe_float(ticker, 'buy'), 'bidVolume': None, 'ask': self.safe_float(ticker, 'sell'), 'askVolume': None, 'vwap': None, 'open': open, 'close': last, 'last': last, 'previousClose': None, 'change': change, 'percentage': percentage, 'average': None, 'baseVolume': self.safe_float_2(ticker, 'vol', 'volume'), 'quoteVolume': None, 'info': ticker, } async def fetch_ticker(self, symbol, params={}): await self.load_markets() market = self.market(symbol) method = 'publicGet' request = { 'symbol': market['id'], } if market['future']: method += 'Future' request['contract_type'] = self.options['defaultContractType'] # self_week, next_week, quarter method += 'Ticker' response = await getattr(self, method)(self.extend(request, params)) ticker = self.safe_value(response, 'ticker') if ticker is None: raise ExchangeError(self.id + ' fetchTicker returned an empty response: ' + self.json(response)) timestamp = self.safe_integer(response, 'date') if timestamp is not None: timestamp *= 1000 ticker = self.extend(ticker, {'timestamp': timestamp}) return self.parse_ticker(ticker, market) def parse_trade(self, trade, market=None): symbol = None if market: symbol = market['symbol'] return { 'info': trade, 'timestamp': trade['date_ms'], 'datetime': self.iso8601(trade['date_ms']), 'symbol': symbol, 'id': str(trade['tid']), 'order': None, 'type': None, 'side': trade['type'], 'price': self.safe_float(trade, 'price'), 'amount': self.safe_float(trade, 'amount'), } async def fetch_trades(self, symbol, since=None, limit=None, params={}): await self.load_markets() market = self.market(symbol) method = 'publicGet' request = { 'symbol': market['id'], } if market['future']: method += 'Future' request['contract_type'] = self.options['defaultContractType'] # self_week, next_week, quarter method += 'Trades' response = await getattr(self, method)(self.extend(request, params)) return self.parse_trades(response, market, since, limit) def parse_ohlcv(self, ohlcv, market=None, timeframe='1m', since=None, limit=None): numElements = len(ohlcv) volumeIndex = 6 if (numElements > 6) else 5 return [ ohlcv[0], # timestamp float(ohlcv[1]), # Open float(ohlcv[2]), # High float(ohlcv[3]), # Low float(ohlcv[4]), # Close # float(ohlcv[5]), # quote volume # float(ohlcv[6]), # base volume float(ohlcv[volumeIndex]), # okex will return base volume in the 7th element for future markets ] async def fetch_ohlcv(self, symbol, timeframe='1m', since=None, limit=None, params={}): await self.load_markets() market = self.market(symbol) method = 'publicGet' request = { 'symbol': market['id'], 'type': self.timeframes[timeframe], } if market['future']: method += 'Future' request['contract_type'] = self.options['defaultContractType'] # self_week, next_week, quarter method += 'Kline' if limit is not None: if self.options['warnOnFetchOHLCVLimitArgument']: raise ExchangeError(self.id + ' fetchOHLCV counts "limit" candles from current time backwards, therefore the "limit" argument for ' + self.id + ' is disabled. Set ' + self.id + '.options["warnOnFetchOHLCVLimitArgument"] = False to suppress self warning message.') request['size'] = int(limit) # max is 1440 candles if since is not None: request['since'] = since else: request['since'] = self.milliseconds() - 86400000 # last 24 hours response = await getattr(self, method)(self.extend(request, params)) return self.parse_ohlcvs(response, market, timeframe, since, limit) async def fetch_balance(self, params={}): await self.load_markets() response = await self.privatePostUserinfo(params) balances = response['info']['funds'] result = {'info': response} ids = list(balances['free'].keys()) usedField = 'freezed' # wtf, okex? # https://github.com/okcoin-okex/API-docs-OKEx.com/commit/01cf9dd57b1f984a8737ef76a037d4d3795d2ac7 if not(usedField in list(balances.keys())): usedField = 'holds' usedKeys = list(balances[usedField].keys()) ids = self.array_concat(ids, usedKeys) for i in range(0, len(ids)): id = ids[i] code = id.upper() if id in self.currencies_by_id: code = self.currencies_by_id[id]['code'] else: code = self.common_currency_code(code) account = self.account() account['free'] = self.safe_float(balances['free'], id, 0.0) account['used'] = self.safe_float(balances[usedField], id, 0.0) account['total'] = self.sum(account['free'], account['used']) result[code] = account return self.parse_balance(result) async def create_order(self, symbol, type, side, amount, price=None, params={}): await self.load_markets() market = self.market(symbol) method = 'privatePost' order = { 'symbol': market['id'], 'type': side, } if market['future']: method += 'Future' order = self.extend(order, { 'contract_type': self.options['defaultContractType'], # self_week, next_week, quarter 'match_price': 0, # match best counter party price? 0 or 1, ignores price if 1 'lever_rate': 10, # leverage rate value: 10 or 20(10 by default) 'price': price, 'amount': amount, }) else: if type == 'limit': order['price'] = price order['amount'] = amount else: order['type'] += '_market' if side == 'buy': if self.options['marketBuyPrice']: if price is None: # eslint-disable-next-line quotes raise ExchangeError(self.id + " market buy orders require a price argument(the amount you want to spend or the cost of the order) when self.options['marketBuyPrice'] is True.") order['price'] = price else: order['price'] = self.safe_float(params, 'cost') if not order['price']: # eslint-disable-next-line quotes raise ExchangeError(self.id + " market buy orders require an additional cost parameter, cost = price * amount. If you want to pass the cost of the market order(the amount you want to spend) in the price argument(the default " + self.id + " behaviour), set self.options['marketBuyPrice'] = True. It will effectively suppress self warning exception as well.") else: order['amount'] = amount params = self.omit(params, 'cost') method += 'Trade' response = await getattr(self, method)(self.extend(order, params)) timestamp = self.milliseconds() return { 'info': response, 'id': str(response['order_id']), 'timestamp': timestamp, 'datetime': self.iso8601(timestamp), 'lastTradeTimestamp': None, 'status': None, 'symbol': symbol, 'type': type, 'side': side, 'price': price, 'amount': amount, 'filled': None, 'remaining': None, 'cost': None, 'trades': None, 'fee': None, } async def cancel_order(self, id, symbol=None, params={}): if symbol is None: raise ArgumentsRequired(self.id + ' cancelOrder() requires a symbol argument') await self.load_markets() market = self.market(symbol) request = { 'symbol': market['id'], 'order_id': id, } method = 'privatePost' if market['future']: method += 'FutureCancel' request['contract_type'] = self.options['defaultContractType'] # self_week, next_week, quarter else: method += 'CancelOrder' response = await getattr(self, method)(self.extend(request, params)) return response def parse_order_status(self, status): statuses = { '-1': 'canceled', '0': 'open', '1': 'open', '2': 'closed', '3': 'open', '4': 'canceled', } return self.safe_value(statuses, status, status) def parse_order_side(self, side): if side == 1: return 'buy' # open long position if side == 2: return 'sell' # open short position if side == 3: return 'sell' # liquidate long position if side == 4: return 'buy' # liquidate short position return side def parse_order(self, order, market=None): side = None type = None if 'type' in order: if (order['type'] == 'buy') or (order['type'] == 'sell'): side = order['type'] type = 'limit' elif order['type'] == 'buy_market': side = 'buy' type = 'market' elif order['type'] == 'sell_market': side = 'sell' type = 'market' else: side = self.parse_order_side(order['type']) if ('contract_name' in list(order.keys())) or ('lever_rate' in list(order.keys())): type = 'margin' status = self.parse_order_status(self.safe_string(order, 'status')) symbol = None if market is None: marketId = self.safe_string(order, 'symbol') if marketId in self.markets_by_id: market = self.markets_by_id[marketId] if market: symbol = market['symbol'] timestamp = None createDateField = self.get_create_date_field() if createDateField in order: timestamp = order[createDateField] amount = self.safe_float(order, 'amount') filled = self.safe_float(order, 'deal_amount') amount = max(amount, filled) remaining = max(0, amount - filled) if type == 'market': remaining = 0 average = self.safe_float(order, 'avg_price') # https://github.com/ccxt/ccxt/issues/2452 average = self.safe_float(order, 'price_avg', average) cost = average * filled result = { 'info': order, 'id': str(order['order_id']), 'timestamp': timestamp, 'datetime': self.iso8601(timestamp), 'lastTradeTimestamp': None, 'symbol': symbol, 'type': type, 'side': side, 'price': order['price'], 'average': average, 'cost': cost, 'amount': amount, 'filled': filled, 'remaining': remaining, 'status': status, 'fee': None, } return result def get_create_date_field(self): # needed for derived exchanges # allcoin typo create_data instead of create_date return 'create_date' def get_orders_field(self): # needed for derived exchanges # allcoin typo order instead of orders(expected based on their API docs) return 'orders' async def fetch_order(self, id, symbol=None, params={}): if symbol is None: raise ExchangeError(self.id + ' fetchOrder requires a symbol parameter') await self.load_markets() market = self.market(symbol) method = 'privatePost' request = { 'order_id': id, 'symbol': market['id'], # 'status': 0, # 0 for unfilled orders, 1 for filled orders # 'current_page': 1, # current page number # 'page_length': 200, # number of orders returned per page, maximum 200 } if market['future']: method += 'Future' request['contract_type'] = self.options['defaultContractType'] # self_week, next_week, quarter method += 'OrderInfo' response = await getattr(self, method)(self.extend(request, params)) ordersField = self.get_orders_field() numOrders = len(response[ordersField]) if numOrders > 0: return self.parse_order(response[ordersField][0]) raise OrderNotFound(self.id + ' order ' + id + ' not found') async def fetch_orders(self, symbol=None, since=None, limit=None, params={}): if symbol is None: raise ExchangeError(self.id + ' fetchOrders requires a symbol parameter') await self.load_markets() market = self.market(symbol) method = 'privatePost' request = { 'symbol': market['id'], } order_id_in_params = ('order_id' in list(params.keys())) if market['future']: method += 'FutureOrdersInfo' request['contract_type'] = self.options['defaultContractType'] # self_week, next_week, quarter if not order_id_in_params: raise ExchangeError(self.id + ' fetchOrders() requires order_id param for futures market ' + symbol + '(a string of one or more order ids, comma-separated)') else: status = None if 'type' in params: status = params['type'] elif 'status' in params: status = params['status'] else: name = 'type' if order_id_in_params else 'status' raise ExchangeError(self.id + ' fetchOrders() requires ' + name + ' param for spot market ' + symbol + '(0 - for unfilled orders, 1 - for filled/canceled orders)') if order_id_in_params: method += 'OrdersInfo' request = self.extend(request, { 'type': status, 'order_id': params['order_id'], }) else: method += 'OrderHistory' request = self.extend(request, { 'status': status, 'current_page': 1, # current page number 'page_length': 200, # number of orders returned per page, maximum 200 }) params = self.omit(params, ['type', 'status']) response = await getattr(self, method)(self.extend(request, params)) ordersField = self.get_orders_field() return self.parse_orders(response[ordersField], market, since, limit) async def fetch_open_orders(self, symbol=None, since=None, limit=None, params={}): open = 0 # 0 for unfilled orders, 1 for filled orders return await self.fetch_orders(symbol, since, limit, self.extend({ 'status': open, }, params)) async def fetch_closed_orders(self, symbol=None, since=None, limit=None, params={}): closed = 1 # 0 for unfilled orders, 1 for filled orders orders = await self.fetch_orders(symbol, since, limit, self.extend({ 'status': closed, }, params)) return orders async def withdraw(self, code, amount, address, tag=None, params={}): self.check_address(address) await self.load_markets() currency = self.currency(code) # if amount < 0.01: # raise ExchangeError(self.id + ' withdraw() requires amount > 0.01') # for some reason they require to supply a pair of currencies for withdrawing one currency currencyId = currency['id'] + '_usd' if tag: address = address + ':' + tag request = { 'symbol': currencyId, 'withdraw_address': address, 'withdraw_amount': amount, 'target': 'address', # or 'okcn', 'okcom', 'okex' } query = params if 'chargefee' in query: request['chargefee'] = query['chargefee'] query = self.omit(query, 'chargefee') else: raise ExchangeError(self.id + ' withdraw() requires a `chargefee` parameter') if self.password: request['trade_pwd'] = self.password elif 'password' in query: request['trade_pwd'] = query['password'] query = self.omit(query, 'password') elif 'trade_pwd' in query: request['trade_pwd'] = query['trade_pwd'] query = self.omit(query, 'trade_pwd') passwordInRequest = ('trade_pwd' in list(request.keys())) if not passwordInRequest: raise ExchangeError(self.id + ' withdraw() requires self.password set on the exchange instance or a password / trade_pwd parameter') response = await self.privatePostWithdraw(self.extend(request, query)) return { 'info': response, 'id': self.safe_string(response, 'withdraw_id'), } def sign(self, path, api='public', method='GET', params={}, headers=None, body=None): url = '/' if api != 'web': url += self.version + '/' url += path if api != 'web': url += self.extension if api == 'private': self.check_required_credentials() query = self.keysort(self.extend({ 'api_key': self.apiKey, }, params)) # secret key must be at the end of query queryString = self.rawencode(query) + '&secret_key=' + self.secret query['sign'] = self.hash(self.encode(queryString)).upper() body = self.urlencode(query) headers = {'Content-Type': 'application/x-www-form-urlencoded'} else: if params: url += '?' + self.urlencode(params) url = self.urls['api'][api] + url return {'url': url, 'method': method, 'body': body, 'headers': headers} def handle_errors(self, code, reason, url, method, headers, body, response): if len(body) < 2: return # fallback to default error handler if body[0] == '{': if 'error_code' in response: error = self.safe_string(response, 'error_code') message = self.id + ' ' + self.json(response) if error in self.exceptions: ExceptionClass = self.exceptions[error] raise ExceptionClass(message) else: raise ExchangeError(message) if 'result' in response: if not response['result']: raise ExchangeError(self.id + ' ' + self.json(response))
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''' Description: Shuffle a set of numbers without duplicates. Example: // Init an array with set 1, 2, and 3. int[] nums = {1,2,3}; Solution solution = new Solution(nums); // Shuffle the array [1,2,3] and return its result. Any permutation of [1,2,3] must equally likely to be returned. solution.shuffle(); // Resets the array back to its original configuration [1,2,3]. solution.reset(); // Returns the random shuffling of array [1,2,3]. solution.shuffle(); Hint #1 The solution expects that we always use the original array to shuffle() else some of the test cases fail. (Credits; @snehasingh31) ''' from typing import List from random import shuffle class Solution: def __init__(self, nums: List[int]): # copy to class member: self.array self.array = [ *nums ] self.origin = nums def reset(self) -> List[int]: """ Resets the array to its original configuration and return it. """ self.array = [ *(self.origin) ] return self.array def shuffle(self) -> List[int]: """ Returns a random shuffling of the array. """ shuffle( self.array ) return self.array # n : the length of input array ## Time Complexity: O( n ) # # The overhead in time is the cost of shuffle and reset, which are of O( n ). ## Space Complexity: O( n ) # # The overhead in space is the storage for class member, self.array, which is of O( n ). from collections import namedtuple TestEntry = namedtuple('TestEntry', 'sequence') def test_bench(): t = TestEntry( sequence = [1,2,3] ) # reference output # this is a challenge about randomness, so any valid permutation of shuffling result is accpeted. ''' [1, 3, 2] [1, 2, 3] [3, 2, 1] ''' obj = Solution( t.sequence ) print( obj.shuffle() ) print( obj.reset() ) print( obj.shuffle() ) if __name__ == '__main__': test_bench()
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# Copyright (c) 2019-2021, NVIDIA CORPORATION. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # Please install UMAP before running the code # use 'conda install -c conda-forge umap-learn' command to install it import numpy as np import pytest import umap import copy import cupyx import scipy.sparse from cuml.manifold.umap import UMAP as cuUMAP from cuml.test.utils import array_equal, unit_param, \ quality_param, stress_param from sklearn.neighbors import NearestNeighbors import joblib from cuml.common import logger from sklearn import datasets from sklearn.cluster import KMeans from sklearn.datasets import make_blobs from sklearn.manifold import trustworthiness from sklearn.metrics import adjusted_rand_score dataset_names = ['iris', 'digits', 'wine', 'blobs'] @pytest.mark.parametrize('nrows', [unit_param(500), quality_param(5000), stress_param(500000)]) @pytest.mark.parametrize('n_feats', [unit_param(20), quality_param(100), stress_param(1000)]) def test_blobs_cluster(nrows, n_feats): data, labels = datasets.make_blobs( n_samples=nrows, n_features=n_feats, centers=5, random_state=0) embedding = cuUMAP().fit_transform(data, convert_dtype=True) if nrows < 500000: score = adjusted_rand_score(labels, KMeans(5).fit_predict(embedding)) assert score == 1.0 @pytest.mark.parametrize('nrows', [unit_param(500), quality_param(5000), stress_param(500000)]) @pytest.mark.parametrize('n_feats', [unit_param(10), quality_param(100), stress_param(1000)]) def test_umap_fit_transform_score(nrows, n_feats): n_samples = nrows n_features = n_feats data, labels = make_blobs(n_samples=n_samples, n_features=n_features, centers=10, random_state=42) model = umap.UMAP(n_neighbors=10, min_dist=0.1) cuml_model = cuUMAP(n_neighbors=10, min_dist=0.01) embedding = model.fit_transform(data) cuml_embedding = cuml_model.fit_transform(data, convert_dtype=True) assert not np.isnan(embedding).any() assert not np.isnan(cuml_embedding).any() if nrows < 500000: cuml_score = adjusted_rand_score(labels, KMeans(10).fit_predict( cuml_embedding)) score = adjusted_rand_score(labels, KMeans(10).fit_predict(embedding)) assert array_equal(score, cuml_score, 1e-2, with_sign=True) def test_supervised_umap_trustworthiness_on_iris(): iris = datasets.load_iris() data = iris.data embedding = cuUMAP(n_neighbors=10, random_state=0, min_dist=0.01).fit_transform( data, iris.target, convert_dtype=True) trust = trustworthiness(iris.data, embedding, n_neighbors=10) assert trust >= 0.97 def test_semisupervised_umap_trustworthiness_on_iris(): iris = datasets.load_iris() data = iris.data target = iris.target.copy() target[25:75] = -1 embedding = cuUMAP(n_neighbors=10, random_state=0, min_dist=0.01).fit_transform( data, target, convert_dtype=True) trust = trustworthiness(iris.data, embedding, n_neighbors=10) assert trust >= 0.97 def test_umap_trustworthiness_on_iris(): iris = datasets.load_iris() data = iris.data embedding = cuUMAP(n_neighbors=10, min_dist=0.01, random_state=0).fit_transform( data, convert_dtype=True) trust = trustworthiness(iris.data, embedding, n_neighbors=10) assert trust >= 0.97 @pytest.mark.parametrize('target_metric', ["categorical", "euclidean"]) def test_umap_transform_on_iris(target_metric): iris = datasets.load_iris() iris_selection = np.random.RandomState(42).choice( [True, False], 150, replace=True, p=[0.75, 0.25]) data = iris.data[iris_selection] fitter = cuUMAP(n_neighbors=10, init="random", n_epochs=800, min_dist=0.01, random_state=42, target_metric=target_metric) fitter.fit(data, convert_dtype=True) new_data = iris.data[~iris_selection] embedding = fitter.transform(new_data, convert_dtype=True) assert not np.isnan(embedding).any() trust = trustworthiness(new_data, embedding, n_neighbors=10) assert trust >= 0.85 @pytest.mark.parametrize('input_type', ['cupy', 'scipy']) @pytest.mark.parametrize('xform_method', ['fit', 'fit_transform']) @pytest.mark.parametrize('target_metric', ["categorical", "euclidean"]) def test_umap_transform_on_digits_sparse(target_metric, input_type, xform_method): digits = datasets.load_digits() digits_selection = np.random.RandomState(42).choice( [True, False], 1797, replace=True, p=[0.75, 0.25]) if input_type == 'cupy': sp_prefix = cupyx.scipy.sparse else: sp_prefix = scipy.sparse data = sp_prefix.csr_matrix( scipy.sparse.csr_matrix(digits.data[digits_selection])) fitter = cuUMAP(n_neighbors=15, verbose=logger.level_info, init="random", n_epochs=0, min_dist=0.01, random_state=42, target_metric=target_metric) new_data = sp_prefix.csr_matrix( scipy.sparse.csr_matrix(digits.data[~digits_selection])) if xform_method == 'fit': fitter.fit(data, convert_dtype=True) embedding = fitter.transform(new_data, convert_dtype=True) else: embedding = fitter.fit_transform(new_data, convert_dtype=True) if input_type == 'cupy': embedding = embedding.get() trust = trustworthiness(digits.data[~digits_selection], embedding, n_neighbors=15) assert trust >= 0.96 @pytest.mark.parametrize('target_metric', ["categorical", "euclidean"]) def test_umap_transform_on_digits(target_metric): digits = datasets.load_digits() digits_selection = np.random.RandomState(42).choice( [True, False], 1797, replace=True, p=[0.75, 0.25]) data = digits.data[digits_selection] fitter = cuUMAP(n_neighbors=15, verbose=logger.level_debug, init="random", n_epochs=0, min_dist=0.01, random_state=42, target_metric=target_metric) fitter.fit(data, convert_dtype=True) new_data = digits.data[~digits_selection] embedding = fitter.transform(new_data, convert_dtype=True) trust = trustworthiness(digits.data[~digits_selection], embedding, n_neighbors=15) assert trust >= 0.96 @pytest.mark.parametrize('target_metric', ["categorical", "euclidean"]) @pytest.mark.parametrize('name', dataset_names) def test_umap_fit_transform_trust(name, target_metric): if name == 'iris': iris = datasets.load_iris() data = iris.data labels = iris.target elif name == 'digits': digits = datasets.load_digits(n_class=5) data = digits.data labels = digits.target elif name == 'wine': wine = datasets.load_wine() data = wine.data labels = wine.target else: data, labels = make_blobs(n_samples=500, n_features=10, centers=10, random_state=42) model = umap.UMAP(n_neighbors=10, min_dist=0.01, target_metric=target_metric) cuml_model = cuUMAP(n_neighbors=10, min_dist=0.01, target_metric=target_metric) embedding = model.fit_transform(data) cuml_embedding = cuml_model.fit_transform(data, convert_dtype=True) trust = trustworthiness(data, embedding, n_neighbors=10) cuml_trust = trustworthiness(data, cuml_embedding, n_neighbors=10) assert array_equal(trust, cuml_trust, 1e-1, with_sign=True) @pytest.mark.parametrize('target_metric', ["categorical", "euclidean"]) @pytest.mark.parametrize('name', [unit_param('digits')]) @pytest.mark.parametrize('nrows', [quality_param(5000), stress_param(500000)]) @pytest.mark.parametrize('n_feats', [quality_param(100), stress_param(1000)]) @pytest.mark.parametrize('should_downcast', [True]) @pytest.mark.parametrize('input_type', ['dataframe', 'ndarray']) def test_umap_data_formats(input_type, should_downcast, nrows, n_feats, name, target_metric): dtype = np.float32 if not should_downcast else np.float64 n_samples = nrows n_feats = n_feats if name == 'digits': # use the digits dataset for unit test digits = datasets.load_digits(n_class=9) X = digits["data"].astype(dtype) else: X, y = datasets.make_blobs(n_samples=n_samples, n_features=n_feats, random_state=0) umap = cuUMAP(n_neighbors=3, n_components=2, target_metric=target_metric) embeds = umap.fit_transform(X) assert type(embeds) == np.ndarray @pytest.mark.parametrize('target_metric', ["categorical", "euclidean"]) @pytest.mark.filterwarnings("ignore:(.*)connected(.*):UserWarning:sklearn[.*]") def test_umap_fit_transform_score_default(target_metric): n_samples = 500 n_features = 20 data, labels = make_blobs(n_samples=n_samples, n_features=n_features, centers=10, random_state=42) model = umap.UMAP(target_metric=target_metric) cuml_model = cuUMAP(target_metric=target_metric) embedding = model.fit_transform(data) cuml_embedding = cuml_model.fit_transform(data, convert_dtype=True) cuml_score = adjusted_rand_score(labels, KMeans(10).fit_predict( cuml_embedding)) score = adjusted_rand_score(labels, KMeans(10).fit_predict(embedding)) assert array_equal(score, cuml_score, 1e-2, with_sign=True) def test_umap_fit_transform_against_fit_and_transform(): n_samples = 500 n_features = 20 data, labels = make_blobs(n_samples=n_samples, n_features=n_features, centers=10, random_state=42) """ First test the default option does not hash the input """ cuml_model = cuUMAP() ft_embedding = cuml_model.fit_transform(data, convert_dtype=True) fit_embedding_same_input = cuml_model.transform(data, convert_dtype=True) assert joblib.hash(ft_embedding) != joblib.hash(fit_embedding_same_input) """ Next, test explicitly enabling feature hashes the input """ cuml_model = cuUMAP(hash_input=True) ft_embedding = cuml_model.fit_transform(data, convert_dtype=True) fit_embedding_same_input = cuml_model.transform(data, convert_dtype=True) assert joblib.hash(ft_embedding) == joblib.hash(fit_embedding_same_input) fit_embedding_diff_input = cuml_model.transform(data[1:], convert_dtype=True) assert joblib.hash(ft_embedding) != joblib.hash(fit_embedding_diff_input) @pytest.mark.parametrize('n_components,random_state', [unit_param(2, None), unit_param(2, 8), unit_param(2, np.random.RandomState(42)), unit_param(21, None), unit_param(21, np.random.RandomState(42)), unit_param(25, 8), unit_param(50, None), stress_param(50, 8)]) def test_umap_fit_transform_reproducibility(n_components, random_state): n_samples = 8000 n_features = 200 if random_state is None: n_components *= 2 data, labels = make_blobs(n_samples=n_samples, n_features=n_features, centers=10, random_state=42) def get_embedding(n_components, random_state): reducer = cuUMAP(init="random", n_components=n_components, random_state=random_state) return reducer.fit_transform(data, convert_dtype=True) state = copy.copy(random_state) cuml_embedding1 = get_embedding(n_components, state) state = copy.copy(random_state) cuml_embedding2 = get_embedding(n_components, state) assert not np.isnan(cuml_embedding1).any() assert not np.isnan(cuml_embedding2).any() # Reproducibility threshold raised until intermittent failure is fixed # Ref: https://github.com/rapidsai/cuml/issues/1903 mean_diff = np.mean(np.abs(cuml_embedding1 - cuml_embedding2)) if random_state is not None: assert mean_diff == 0.0 else: assert mean_diff > 0.5 @pytest.mark.parametrize('n_components,random_state', [unit_param(2, None), unit_param(2, 8), unit_param(2, np.random.RandomState(42)), unit_param(21, None), unit_param(25, 8), unit_param(25, np.random.RandomState(42)), unit_param(50, None), stress_param(50, 8)]) def test_umap_transform_reproducibility(n_components, random_state): n_samples = 5000 n_features = 200 if random_state is None: n_components *= 2 data, labels = make_blobs(n_samples=n_samples, n_features=n_features, centers=10, random_state=42) selection = np.random.RandomState(42).choice( [True, False], n_samples, replace=True, p=[0.5, 0.5]) fit_data = data[selection] transform_data = data[~selection] def get_embedding(n_components, random_state): reducer = cuUMAP(init="random", n_components=n_components, random_state=random_state) reducer.fit(fit_data, convert_dtype=True) return reducer.transform(transform_data, convert_dtype=True) state = copy.copy(random_state) cuml_embedding1 = get_embedding(n_components, state) state = copy.copy(random_state) cuml_embedding2 = get_embedding(n_components, state) assert not np.isnan(cuml_embedding1).any() assert not np.isnan(cuml_embedding2).any() # Reproducibility threshold raised until intermittent failure is fixed # Ref: https://github.com/rapidsai/cuml/issues/1903 mean_diff = np.mean(np.abs(cuml_embedding1 - cuml_embedding2)) if random_state is not None: assert mean_diff == 0.0 else: assert mean_diff > 0.5 def test_umap_fit_transform_trustworthiness_with_consistency_enabled(): iris = datasets.load_iris() data = iris.data algo = cuUMAP(n_neighbors=10, min_dist=0.01, init="random", random_state=42) embedding = algo.fit_transform(data, convert_dtype=True) trust = trustworthiness(iris.data, embedding, n_neighbors=10) assert trust >= 0.97 def test_umap_transform_trustworthiness_with_consistency_enabled(): iris = datasets.load_iris() data = iris.data selection = np.random.RandomState(42).choice( [True, False], data.shape[0], replace=True, p=[0.5, 0.5]) fit_data = data[selection] transform_data = data[~selection] model = cuUMAP(n_neighbors=10, min_dist=0.01, init="random", random_state=42) model.fit(fit_data, convert_dtype=True) embedding = model.transform(transform_data, convert_dtype=True) trust = trustworthiness(transform_data, embedding, n_neighbors=10) assert trust >= 0.92 @pytest.mark.filterwarnings("ignore:(.*)zero(.*)::scipy[.*]|umap[.*]") def test_exp_decay_params(): def compare_exp_decay_params(a=None, b=None, min_dist=0.1, spread=1.0): cuml_model = cuUMAP(a=a, b=b, min_dist=min_dist, spread=spread) state = cuml_model.__getstate__() cuml_a, cuml_b = state['a'], state['b'] skl_model = umap.UMAP(a=a, b=b, min_dist=min_dist, spread=spread) skl_model.fit(np.zeros((1, 1))) sklearn_a, sklearn_b = skl_model._a, skl_model._b assert abs(cuml_a) - abs(sklearn_a) < 1e-6 assert abs(cuml_b) - abs(sklearn_b) < 1e-6 compare_exp_decay_params(min_dist=0.1, spread=1.0) compare_exp_decay_params(a=0.5, b=2.0) compare_exp_decay_params(a=0.5) compare_exp_decay_params(b=0.5) compare_exp_decay_params(min_dist=0.1, spread=10.0) @pytest.mark.parametrize('n_neighbors', [5, 15]) def test_umap_knn_parameters(n_neighbors): data, labels = datasets.make_blobs( n_samples=2000, n_features=10, centers=5, random_state=0) data = data.astype(np.float32) def fit_transform_embed(knn_graph=None): model = cuUMAP(random_state=42, init='random', n_neighbors=n_neighbors) return model.fit_transform(data, knn_graph=knn_graph, convert_dtype=True) def transform_embed(knn_graph=None): model = cuUMAP(random_state=42, init='random', n_neighbors=n_neighbors) model.fit(data, knn_graph=knn_graph, convert_dtype=True) return model.transform(data, knn_graph=knn_graph, convert_dtype=True) def test_trustworthiness(embedding): trust = trustworthiness(data, embedding, n_neighbors=n_neighbors) assert trust >= 0.92 def test_equality(e1, e2): mean_diff = np.mean(np.abs(e1 - e2)) print("mean diff: %s" % mean_diff) assert mean_diff < 1.0 neigh = NearestNeighbors(n_neighbors=n_neighbors) neigh.fit(data) knn_graph = neigh.kneighbors_graph(data, mode="distance") embedding1 = fit_transform_embed(None) embedding2 = fit_transform_embed(knn_graph.tocsr()) embedding3 = fit_transform_embed(knn_graph.tocoo()) embedding4 = fit_transform_embed(knn_graph.tocsc()) embedding5 = transform_embed(knn_graph.tocsr()) embedding6 = transform_embed(knn_graph.tocoo()) embedding7 = transform_embed(knn_graph.tocsc()) test_trustworthiness(embedding1) test_trustworthiness(embedding2) test_trustworthiness(embedding3) test_trustworthiness(embedding4) test_trustworthiness(embedding5) test_trustworthiness(embedding6) test_trustworthiness(embedding7) test_equality(embedding2, embedding3) test_equality(embedding3, embedding4) test_equality(embedding5, embedding6) test_equality(embedding6, embedding7)
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# Given a binary tree, find its maximum depth. # The maximum depth is the number of nodes along the longest path from the root node down to the farthest leaf node. # Definition for a binary tree node class TreeNode: def __init__(self, x): self.val = x self.left = None self.right = None class Solution: # @param root, a tree node # @return an integer def maxDepth(self, root): if root is None: return 0 L = 0; R = 0; if not (root.left is None): L = self.maxDepth(root.left) if not (root.right is None): R = self.maxDepth(root.right) return (L + 1) if L > R else (R + 1) # if __name__ == "__main__" : # root = TreeNode(1) # root.left = TreeNode(1) # root.right = TreeNode(1) # s = Solution() # print s.maxDepth(root) # print "hello"
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import os def shell(): inputuser = input("> ") if (inputuser == "exit"): exit() os.system(inputuser) return shell() print("Welcome to duckshell (python alpha)") print("System info: ") os.system("echo distro: $(uname -o)"); os.system("echo hostname: $(uname -n)"); os.system("echo architecture: $(uname -m)"); os.system("echo linux kernel: $(uname -r)"); os.system("echo python version: $(python --version)") shell()
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import logging import subprocess import click try: from instance import settings APP_ROOT = settings.APP_ROOT except ImportError: logging.error('Ensure __init__.py and settings.py both exist in instance/') exit(1) except AttributeError: from config import settings APP_ROOT = settings.APP_ROOT PACKAGE_PATH = '{0}/{1}'.format(APP_ROOT, '/catwatch') @click.command() @click.argument('path', default=PACKAGE_PATH) def cli(path): """ Run test coverage report. :return: Subprocess call result """ cmd = 'py.test --cov-report term-missing --cov {0} {0}'.format(path) return subprocess.call(cmd, shell=True)
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import os import time from multiprocessing import Process from typing import Tuple import flwr as fl import numpy as np import tensorflow as tf from flwr.server.strategy import FedAvg import dataset # generate random integer values from random import seed from random import randint # Make TensorFlow log less verbose os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3" # K: Prevent TF from using GPU (not enough memory) os.environ["CUDA_VISIBLE_DEVICES"] = "-1" DATASET = Tuple[Tuple[np.ndarray, np.ndarray], Tuple[np.ndarray, np.ndarray]] def start_server(num_rounds: int, num_clients: int, fraction_fit: float): """Start the server with a slightly adjusted FedAvg strategy.""" strategy = FedAvg(min_available_clients=num_clients, fraction_fit=fraction_fit) # Exposes the server by default on port 8080 fl.server.start_server(strategy=strategy, config={"num_rounds": num_rounds}) def start_client(dataset: DATASET) -> None: """Start a single client with the provided dataset.""" # Load and compile a Keras model for CIFAR-10 #model = tf.keras.applications.MobileNetV2((32, 32, 3), classes=10, weights=None) model = tf.keras.Sequential( [ tf.keras.Input(shape=(32, 32, 3)), tf.keras.layers.Conv2D(32, kernel_size=(3, 3), activation="relu"), tf.keras.layers.MaxPooling2D(pool_size=(2, 2)), tf.keras.layers.Conv2D(64, kernel_size=(3, 3), activation="relu"), tf.keras.layers.MaxPooling2D(pool_size=(2, 2)), tf.keras.layers.Flatten(), tf.keras.layers.Dropout(0.5), tf.keras.layers.Dense(10, activation="softmax"), ] ) model.compile("adam", "sparse_categorical_crossentropy", metrics=[tf.keras.metrics.CategoricalAccuracy(), tf.keras.metrics.MeanSquaredError()]) ### @TODO: check if "accuracy" and tf.keras.metrics.CategoricalAccuracy() return the same results # Unpack the CIFAR-10 dataset partition (x_train, y_train), (x_test, y_test) = dataset # Define a Flower client class CifarClient(fl.client.NumPyClient): def get_parameters(self): """Return current weights.""" return model.get_weights() def fit(self, parameters, config): """Fit model and return new weights as well as number of training examples.""" model.set_weights(parameters) # Remove steps_per_epoch if you want to train over the full dataset # https://keras.io/api/models/model_training_apis/#fit-method #nap_time = randint (0, 5) #time.sleep (nap_time) #print ("Slept for", nap_time, "seconds.") model.fit(x_train, y_train, epochs=10, batch_size=256, steps_per_epoch=10) return model.get_weights(), len(x_train), {} def evaluate(self, parameters, config): """Evaluate using provided parameters.""" model.set_weights(parameters) loss, accuracy, mse = model.evaluate(x_test, y_test) print ('"Loss:', loss, ". Accuracy:", accuracy, ". MSE:", mse, ".") return loss, len(x_test), {"accuracy": accuracy} # Start Flower client fl.client.start_numpy_client("0.0.0.0:8080", client=CifarClient()) def run_simulation(num_rounds: int, num_clients: int, fraction_fit: float): """Start a FL simulation.""" # This will hold all the processes which we are going to create processes = [] # Start the server server_process = Process( target=start_server, args=(num_rounds, num_clients, fraction_fit) ) server_process.start() processes.append(server_process) # Optionally block the script here for a second or two so the server has time to start time.sleep(2) # Load the dataset partitions partitions = dataset.load(num_partitions=num_clients) # Start all the clients for partition in partitions: client_process = Process(target=start_client, args=(partition,)) client_process.start() processes.append(client_process) # Block until all processes are finished for p in processes: p.join() if __name__ == "__main__": run_simulation(num_rounds=100, num_clients=5, fraction_fit=0.5)
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#!/usr/bin/env python3 elements = (1, 2, 4) bitset = 0 # 1. Initialize bitset # Add elements to bitset for i in elements: bitset = bitset | 1<<i # 2. Add element to bitset # Print contents of bitset print(bitset) # Test for elements in bitset for i in range(6): if bitset & 1<<i: # 3. Test if element is in bitset print(i) # Remove elements from bitset for i in elements: bitset = bitset & ~(1<<i) # 4. Remove element from bitset # Print contents of bitset print(bitset)
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''' The management of salt command line utilities are stored in here ''' # Import python libs import os import sys # Import salt components import salt.cli.caller import salt.cli.cp import salt.cli.key import salt.cli.batch import salt.client import salt.output import salt.runner import optparse from salt.utils import parsers from salt.utils.verify import verify_env from salt.version import __version__ as VERSION from salt.exceptions import SaltInvocationError, SaltClientError, SaltException class SaltCMD(parsers.SaltCMDOptionParser): ''' The execution of a salt command happens here ''' def run(self): ''' Execute the salt command line ''' self.parse_args() try: local = salt.client.LocalClient(self.get_config_file_path('master')) except SaltClientError as exc: self.exit(2, '{0}\n'.format(exc)) return if self.options.query: ret = local.find_cmd(self.config['cmd']) for jid in ret: if isinstance(ret, list) or isinstance(ret, dict): print('Return data for job {0}:'.format(jid)) salt.output.display_output(ret[jid], None, self.config) print('') elif self.options.batch: batch = salt.cli.batch.Batch(self.config) batch.run() else: if self.options.timeout <= 0: self.options.timeout = local.opts['timeout'] args = [ self.config['tgt'], self.config['fun'], self.config['arg'], self.options.timeout, ] if self.selected_target_option: args.append(self.selected_target_option) else: args.append('glob') if getattr(self.options, 'return'): args.append(getattr(self.options, 'return')) else: args.append('') try: # local will be None when there was an error if local: if self.options.static: if self.options.verbose: args.append(True) full_ret = local.cmd_full_return(*args) ret, out = self._format_ret(full_ret) self._output_ret(ret, out) elif self.config['fun'] == 'sys.doc': ret = {} out = '' for full_ret in local.cmd_cli(*args): ret_, out = self._format_ret(full_ret) ret.update(ret_) self._output_ret(ret, out) else: if self.options.verbose: args.append(True) for full_ret in local.cmd_cli(*args): ret, out = self._format_ret(full_ret) self._output_ret(ret, out) except SaltInvocationError as exc: ret = exc out = '' def _output_ret(self, ret, out): ''' Print the output from a single return to the terminal ''' # Handle special case commands if self.config['fun'] == 'sys.doc': self._print_docs(ret) else: # Determine the proper output method and run it salt.output.display_output(ret, out, self.config) def _format_ret(self, full_ret): ''' Take the full return data and format it to simple output ''' ret = {} out = '' for key, data in full_ret.items(): ret[key] = data['ret'] if 'out' in data: out = data['out'] return ret, out def _print_docs(self, ret): ''' Print out the docstrings for all of the functions on the minions ''' docs = {} if not ret: self.exit(2, 'No minions found to gather docs from\n') for host in ret: for fun in ret[host]: if fun not in docs: if ret[host][fun]: docs[fun] = ret[host][fun] for fun in sorted(docs): print(fun + ':') print(docs[fun]) print('') class SaltCP(parsers.SaltCPOptionParser): ''' Run the salt-cp command line client ''' def run(self): ''' Execute salt-cp ''' self.parse_args() cp_ = salt.cli.cp.SaltCP(self.config) cp_.run() class SaltKey(parsers.SaltKeyOptionParser): ''' Initialize the Salt key manager ''' def run(self): ''' Execute salt-key ''' self.parse_args() if self.config['verify_env']: verify_env([ os.path.join(self.config['pki_dir'], 'minions'), os.path.join(self.config['pki_dir'], 'minions_pre'), os.path.join(self.config['pki_dir'], 'minions_rejected'), os.path.dirname(self.config['key_logfile']), ], self.config['user'], permissive=self.config['permissive_pki_access'], pki_dir=self.config['pki_dir'], ) self.setup_logfile_logger() key = salt.cli.key.Key(self.config) key.run() class SaltCall(parsers.SaltCallOptionParser): ''' Used to locally execute a salt command ''' def run(self): ''' Execute the salt call! ''' self.parse_args() if self.config['verify_env']: verify_env([ self.config['pki_dir'], self.config['cachedir'], os.path.dirname(self.config['log_file']) ], self.config['user'], permissive=self.config['permissive_pki_access'], pki_dir=self.config['pki_dir'], ) caller = salt.cli.caller.Caller(self.config) if self.options.doc: caller.print_docs() self.exit(0) if self.options.grains_run: caller.print_grains() self.exit(0) caller.run() class SaltRun(parsers.SaltRunOptionParser): def run(self): ''' Execute salt-run ''' self.parse_args() runner = salt.runner.Runner(self.config) if self.options.doc: runner._print_docs() else: # Run this here so SystemExit isn't raised anywhere else when # someone tries to use the runners via the python api try: runner.run() except SaltClientError as exc: raise SystemExit(str(exc))
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# # ⚠ Warning # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT # LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN # NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, # WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE # SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # # [🥭 Mango Markets](https://mango.markets/) support is available at: # [Docs](https://docs.mango.markets/) # [Discord](https://discord.gg/67jySBhxrg) # [Twitter](https://twitter.com/mangomarkets) # [Github](https://github.com/blockworks-foundation) # [Email](mailto:hello@blockworks.foundation) import typing from decimal import Decimal from solana.publickey import PublicKey from .accountinfo import AccountInfo from .addressableaccount import AddressableAccount from .cache import Cache, PerpMarketCache, MarketCache from .constants import SYSTEM_PROGRAM_ADDRESS from .context import Context from .instrumentlookup import InstrumentLookup from .instrumentvalue import InstrumentValue from .layouts import layouts from .lotsizeconverter import LotSizeConverter, RaisingLotSizeConverter from .marketlookup import MarketLookup from .metadata import Metadata from .token import Instrument, Token from .tokenbank import TokenBank from .version import Version # # 🥭 GroupSlotSpotMarket class # class GroupSlotSpotMarket: def __init__(self, address: PublicKey, maint_asset_weight: Decimal, init_asset_weight: Decimal, maint_liab_weight: Decimal, init_liab_weight: Decimal) -> None: self.address: PublicKey = address self.maint_asset_weight: Decimal = maint_asset_weight self.init_asset_weight: Decimal = init_asset_weight self.maint_liab_weight: Decimal = maint_liab_weight self.init_liab_weight: Decimal = init_liab_weight @staticmethod def from_layout(layout: typing.Any) -> "GroupSlotSpotMarket": spot_market: PublicKey = layout.spot_market maint_asset_weight: Decimal = round(layout.maint_asset_weight, 8) init_asset_weight: Decimal = round(layout.init_asset_weight, 8) maint_liab_weight: Decimal = round(layout.maint_liab_weight, 8) init_liab_weight: Decimal = round(layout.init_liab_weight, 8) return GroupSlotSpotMarket(spot_market, maint_asset_weight, init_asset_weight, maint_liab_weight, init_liab_weight) @staticmethod def from_layout_or_none(layout: typing.Any) -> typing.Optional["GroupSlotSpotMarket"]: if (layout.spot_market is None) or (layout.spot_market == SYSTEM_PROGRAM_ADDRESS): return None return GroupSlotSpotMarket.from_layout(layout) def __str__(self) -> str: return f"""« 𝙶𝚛𝚘𝚞𝚙𝚂𝚕𝚘𝚝𝚂𝚙𝚘𝚝𝙼𝚊𝚛𝚔𝚎𝚝 [{self.address}] Asset Weights: Initial: {self.init_asset_weight} Maintenance: {self.maint_asset_weight} Liability Weights: Initial: {self.init_liab_weight} Maintenance: {self.maint_liab_weight} »""" def __repr__(self) -> str: return f"{self}" # # 🥭 GroupSlotPerpMarket class # class GroupSlotPerpMarket: def __init__(self, address: PublicKey, maint_asset_weight: Decimal, init_asset_weight: Decimal, maint_liab_weight: Decimal, init_liab_weight: Decimal, liquidation_fee: Decimal, base_lot_size: Decimal, quote_lot_size: Decimal) -> None: self.address: PublicKey = address self.maint_asset_weight: Decimal = maint_asset_weight self.init_asset_weight: Decimal = init_asset_weight self.maint_liab_weight: Decimal = maint_liab_weight self.init_liab_weight: Decimal = init_liab_weight self.liquidation_fee: Decimal = liquidation_fee self.base_lot_size: Decimal = base_lot_size self.quote_lot_size: Decimal = quote_lot_size @staticmethod def from_layout(layout: typing.Any) -> "GroupSlotPerpMarket": perp_market: PublicKey = layout.perp_market maint_asset_weight: Decimal = round(layout.maint_asset_weight, 8) init_asset_weight: Decimal = round(layout.init_asset_weight, 8) maint_liab_weight: Decimal = round(layout.maint_liab_weight, 8) init_liab_weight: Decimal = round(layout.init_liab_weight, 8) liquidation_fee: Decimal = round(layout.liquidation_fee, 8) base_lot_size: Decimal = layout.base_lot_size quote_lot_size: Decimal = layout.quote_lot_size return GroupSlotPerpMarket(perp_market, maint_asset_weight, init_asset_weight, maint_liab_weight, init_liab_weight, liquidation_fee, base_lot_size, quote_lot_size) @staticmethod def from_layout_or_none(layout: typing.Any) -> typing.Optional["GroupSlotPerpMarket"]: if (layout.perp_market is None) or (layout.perp_market == SYSTEM_PROGRAM_ADDRESS): return None return GroupSlotPerpMarket.from_layout(layout) def __str__(self) -> str: return f"""« 𝙶𝚛𝚘𝚞𝚙𝚂𝚕𝚘𝚝𝙿𝚎𝚛𝚙𝙼𝚊𝚛𝚔𝚎𝚝 [{self.address}] Asset Weights: Initial: {self.init_asset_weight} Maintenance: {self.maint_asset_weight} Liability Weights: Initial: {self.init_liab_weight} Maintenance: {self.maint_liab_weight} Liquidation Fee: {self.liquidation_fee} Base Lot Size: {self.base_lot_size} Quote Lot Size: {self.quote_lot_size} »""" def __repr__(self) -> str: return f"{self}" # # 🥭 GroupSlot class # # `GroupSlot` gathers indexed slot items together instead of separate arrays. # class GroupSlot: def __init__(self, index: int, base_instrument: Instrument, base_token_bank: typing.Optional[TokenBank], quote_token_bank: TokenBank, spot_market_info: typing.Optional[GroupSlotSpotMarket], perp_market_info: typing.Optional[GroupSlotPerpMarket], perp_lot_size_converter: LotSizeConverter, oracle: PublicKey) -> None: self.index: int = index self.base_instrument: Instrument = base_instrument self.base_token_bank: typing.Optional[TokenBank] = base_token_bank self.quote_token_bank: TokenBank = quote_token_bank self.spot_market: typing.Optional[GroupSlotSpotMarket] = spot_market_info self.perp_market: typing.Optional[GroupSlotPerpMarket] = perp_market_info self.perp_lot_size_converter: LotSizeConverter = perp_lot_size_converter self.oracle: PublicKey = oracle def __str__(self) -> str: base_token_bank = f"{self.base_token_bank}".replace("\n", "\n ") quote_token_bank = f"{self.quote_token_bank}".replace("\n", "\n ") spot_market_info = f"{self.spot_market}".replace("\n", "\n ") perp_market_info = f"{self.perp_market}".replace("\n", "\n ") return f"""« 𝙶𝚛𝚘𝚞𝚙𝚂𝚕𝚘𝚝[{self.index}] {self.base_instrument} Base Token Info: {base_token_bank} Quote Token Info: {quote_token_bank} Oracle: {self.oracle} Spot Market: {spot_market_info} Perp Market: {perp_market_info} »""" def __repr__(self) -> str: return f"{self}" # # 🥭 Group class # # `Group` defines root functionality for Mango Markets. # class Group(AddressableAccount): def __init__(self, account_info: AccountInfo, version: Version, name: str, meta_data: Metadata, shared_quote: TokenBank, slot_indices: typing.Sequence[bool], slots: typing.Sequence[GroupSlot], signer_nonce: Decimal, signer_key: PublicKey, admin: PublicKey, serum_program_address: PublicKey, cache: PublicKey, valid_interval: Decimal, insurance_vault: PublicKey, srm_vault: PublicKey, msrm_vault: PublicKey, fees_vault: PublicKey) -> None: super().__init__(account_info) self.version: Version = version self.name: str = name self.meta_data: Metadata = meta_data self.shared_quote: TokenBank = shared_quote self.slot_indices: typing.Sequence[bool] = slot_indices self.slots: typing.Sequence[GroupSlot] = slots self.signer_nonce: Decimal = signer_nonce self.signer_key: PublicKey = signer_key self.admin: PublicKey = admin self.serum_program_address: PublicKey = serum_program_address self.cache: PublicKey = cache self.valid_interval: Decimal = valid_interval self.insurance_vault: PublicKey = insurance_vault self.srm_vault: PublicKey = srm_vault self.msrm_vault: PublicKey = msrm_vault self.fees_vault: PublicKey = fees_vault @property def shared_quote_token(self) -> Token: return Token.ensure(self.shared_quote.token) @property def liquidity_incentive_token_bank(self) -> TokenBank: for token_bank in self.tokens: if token_bank.token.symbol_matches("MNGO"): return token_bank raise Exception(f"Could not find token info for symbol 'MNGO' in group {self.address}") @property def liquidity_incentive_token(self) -> Token: return Token.ensure(self.liquidity_incentive_token_bank.token) @property def tokens(self) -> typing.Sequence[TokenBank]: return [*self.base_tokens, self.shared_quote] @property def tokens_by_index(self) -> typing.Sequence[typing.Optional[TokenBank]]: return [*self.base_tokens_by_index, self.shared_quote] @property def slots_by_index(self) -> typing.Sequence[typing.Optional[GroupSlot]]: mapped_items: typing.List[typing.Optional[GroupSlot]] = [] slot_counter = 0 for available in self.slot_indices: if available: mapped_items += [self.slots[slot_counter]] slot_counter += 1 else: mapped_items += [None] return mapped_items @property def base_tokens(self) -> typing.Sequence[TokenBank]: return [slot.base_token_bank for slot in self.slots if slot.base_token_bank is not None] @property def base_tokens_by_index(self) -> typing.Sequence[typing.Optional[TokenBank]]: return [slot.base_token_bank if slot is not None else None for slot in self.slots_by_index] @property def oracles(self) -> typing.Sequence[PublicKey]: return [slot.oracle for slot in self.slots if slot.oracle is not None] @property def oracles_by_index(self) -> typing.Sequence[typing.Optional[PublicKey]]: return [slot.oracle if slot is not None else None for slot in self.slots_by_index] @property def spot_markets(self) -> typing.Sequence[GroupSlotSpotMarket]: return [slot.spot_market for slot in self.slots if slot.spot_market is not None] @property def spot_markets_by_index(self) -> typing.Sequence[typing.Optional[GroupSlotSpotMarket]]: return [slot.spot_market if slot is not None else None for slot in self.slots_by_index] @property def perp_markets(self) -> typing.Sequence[GroupSlotPerpMarket]: return [slot.perp_market for slot in self.slots if slot.perp_market is not None] @property def perp_markets_by_index(self) -> typing.Sequence[typing.Optional[GroupSlotPerpMarket]]: return [slot.perp_market if slot is not None else None for slot in self.slots_by_index] @staticmethod def from_layout(layout: typing.Any, name: str, account_info: AccountInfo, version: Version, instrument_lookup: InstrumentLookup, market_lookup: MarketLookup) -> "Group": meta_data: Metadata = Metadata.from_layout(layout.meta_data) tokens: typing.List[typing.Optional[TokenBank]] = [ TokenBank.from_layout_or_none(t, instrument_lookup) for t in layout.tokens] # By convention, the shared quote token is always at the end. quote_token_bank: typing.Optional[TokenBank] = tokens[-1] if quote_token_bank is None: raise Exception("Could not find quote token info at end of group tokens.") slots: typing.List[GroupSlot] = [] in_slots: typing.List[bool] = [] for index in range(len(tokens) - 1): spot_market_info: typing.Optional[GroupSlotSpotMarket] = GroupSlotSpotMarket.from_layout_or_none( layout.spot_markets[index]) perp_market_info: typing.Optional[GroupSlotPerpMarket] = GroupSlotPerpMarket.from_layout_or_none( layout.perp_markets[index]) if (spot_market_info is None) and (perp_market_info is None): in_slots += [False] else: perp_lot_size_converter: LotSizeConverter = RaisingLotSizeConverter() base_token_bank: typing.Optional[TokenBank] = tokens[index] base_instrument: Instrument if base_token_bank is not None: base_instrument = base_token_bank.token else: # It's possible there's no underlying SPL token and we have a pure PERP market. if perp_market_info is None: raise Exception(f"Cannot find base token or perp market info for index {index}") perp_market = market_lookup.find_by_address(perp_market_info.address) if perp_market is None: raise Exception(f"Cannot find base token or perp market for index {index}") base_instrument = perp_market.base if perp_market_info is not None: perp_lot_size_converter = LotSizeConverter( base_instrument, perp_market_info.base_lot_size, quote_token_bank.token, perp_market_info.quote_lot_size) oracle: PublicKey = layout.oracles[index] slot: GroupSlot = GroupSlot(index, base_instrument, base_token_bank, quote_token_bank, spot_market_info, perp_market_info, perp_lot_size_converter, oracle) slots += [slot] in_slots += [True] signer_nonce: Decimal = layout.signer_nonce signer_key: PublicKey = layout.signer_key admin: PublicKey = layout.admin serum_program_address: PublicKey = layout.serum_program_address cache_address: PublicKey = layout.cache valid_interval: Decimal = layout.valid_interval insurance_vault: PublicKey = layout.insurance_vault srm_vault: PublicKey = layout.srm_vault msrm_vault: PublicKey = layout.msrm_vault fees_vault: PublicKey = layout.fees_vault return Group(account_info, version, name, meta_data, quote_token_bank, in_slots, slots, signer_nonce, signer_key, admin, serum_program_address, cache_address, valid_interval, insurance_vault, srm_vault, msrm_vault, fees_vault) @staticmethod def parse(account_info: AccountInfo, name: str, instrument_lookup: InstrumentLookup, market_lookup: MarketLookup) -> "Group": data = account_info.data if len(data) != layouts.GROUP.sizeof(): raise Exception( f"Group data length ({len(data)}) does not match expected size ({layouts.GROUP.sizeof()})") layout = layouts.GROUP.parse(data) return Group.from_layout(layout, name, account_info, Version.V3, instrument_lookup, market_lookup) @staticmethod def parse_with_context(context: Context, account_info: AccountInfo) -> "Group": name = context.lookup_group_name(account_info.address) return Group.parse(account_info, name, context.instrument_lookup, context.market_lookup) @staticmethod def load(context: Context, address: typing.Optional[PublicKey] = None) -> "Group": group_address: PublicKey = address or context.group_address account_info = AccountInfo.load(context, group_address) if account_info is None: raise Exception(f"Group account not found at address '{group_address}'") name = context.lookup_group_name(account_info.address) return Group.parse(account_info, name, context.instrument_lookup, context.market_lookup) def slot_by_spot_market_address(self, spot_market_address: PublicKey) -> GroupSlot: for slot in self.slots: if slot.spot_market is not None and slot.spot_market.address == spot_market_address: return slot raise Exception(f"Could not find spot market {spot_market_address} in group {self.address}") def slot_by_perp_market_address(self, perp_market_address: PublicKey) -> GroupSlot: for slot in self.slots: if slot.perp_market is not None and slot.perp_market.address == perp_market_address: return slot raise Exception(f"Could not find perp market {perp_market_address} in group {self.address}") def slot_by_instrument_or_none(self, instrument: Instrument) -> typing.Optional[GroupSlot]: for slot in self.slots: if slot.base_instrument == instrument: return slot return None def slot_by_instrument(self, instrument: Instrument) -> GroupSlot: slot: typing.Optional[GroupSlot] = self.slot_by_instrument_or_none(instrument) if slot is not None: return slot raise Exception(f"Could not find slot for {instrument} in group {self.address}") def token_bank_by_instrument(self, instrument: Instrument) -> TokenBank: for token_bank in self.tokens: if token_bank.token == instrument: return token_bank raise Exception(f"Could not find token {instrument} in group {self.address}") def token_price_from_cache(self, cache: Cache, token: Instrument) -> InstrumentValue: market_cache: MarketCache = self.market_cache_from_cache(cache, token) return market_cache.adjusted_price(token, self.shared_quote_token) def perp_market_cache_from_cache(self, cache: Cache, token: Instrument) -> typing.Optional[PerpMarketCache]: market_cache: MarketCache = self.market_cache_from_cache(cache, token) return market_cache.perp_market def market_cache_from_cache(self, cache: Cache, instrument: Instrument) -> MarketCache: slot: GroupSlot = self.slot_by_instrument(instrument) instrument_index: int = slot.index return cache.market_cache_for_index(instrument_index) def fetch_cache(self, context: Context) -> Cache: return Cache.load(context, self.cache) def __str__(self) -> str: slot_count = len(self.slots) slots = "\n ".join([f"{item}".replace("\n", "\n ") for item in self.slots]) return f"""« 𝙶𝚛𝚘𝚞𝚙 {self.version} [{self.address}] {self.meta_data} Name: {self.name} Signer [Nonce: {self.signer_nonce}]: {self.signer_key} Admin: {self.admin} DEX Program ID: {self.serum_program_address} Cache: {self.cache} Insurance Vault: {self.insurance_vault} SRM Vault: {self.srm_vault} MSRM Vault: {self.msrm_vault} Fees Vault: {self.fees_vault} Valid Interval: {self.valid_interval} Basket [{slot_count} markets]: {slots} »"""
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ 排序算法: O(n^2) 冒泡排序 插入排序 选择排序 Q(n log n) 分而治之 快速排序 归并排序 """
[]
from logging import getLogger from typing import ( List, Optional, Set, ) from pydantic import ( BaseModel, Extra, Field, ) from galaxy import exceptions from galaxy.datatypes.registry import Registry from galaxy.managers.collections import DatasetCollectionManager from galaxy.managers.collections_util import ( api_payload_to_create_params, dictify_dataset_collection_instance, dictify_element_reference, ) from galaxy.managers.context import ProvidesHistoryContext from galaxy.managers.hdcas import HDCAManager from galaxy.managers.histories import HistoryManager from galaxy.schema.fields import ( EncodedDatabaseIdField, ModelClassField, ) from galaxy.schema.schema import ( AnyHDCA, CreateNewCollectionPayload, DatasetCollectionInstanceType, DCESummary, DCEType, HDCADetailed, TagCollection, ) from galaxy.security.idencoding import IdEncodingHelper from galaxy.webapps.base.controller import UsesLibraryMixinItems from galaxy.webapps.galaxy.services.base import ServiceBase log = getLogger(__name__) class UpdateCollectionAttributePayload(BaseModel): """Contains attributes that can be updated for all elements in a dataset collection.""" dbkey: str = Field(..., description="TODO") class Config: extra = Extra.forbid # will cause validation to fail if extra attributes are included, class DatasetCollectionAttributesResult(BaseModel): dbkey: str = Field(..., description="TODO") # Are the following fields really used/needed? extension: str = Field(..., description="The dataset file extension.", example="txt") model_class: str = ModelClassField("HistoryDatasetCollectionAssociation") dbkeys: Optional[Set[str]] extensions: Optional[Set[str]] tags: TagCollection class SuitableConverter(BaseModel): tool_id: str = Field(..., description="The ID of the tool that can perform the type conversion.") name: str = Field(..., description="The name of the converter.") target_type: str = Field(..., description="The type to convert to.") original_type: str = Field(..., description="The type to convert from.") class SuitableConverters(BaseModel): """Collection of converters that can be used on a particular dataset collection.""" __root__: List[SuitableConverter] class DatasetCollectionContentElements(BaseModel): """Represents a collection of elements contained in the dataset collection.""" __root__: List[DCESummary] class DatasetCollectionsService(ServiceBase, UsesLibraryMixinItems): def __init__( self, security: IdEncodingHelper, history_manager: HistoryManager, hdca_manager: HDCAManager, collection_manager: DatasetCollectionManager, datatypes_registry: Registry, ): super().__init__(security) self.history_manager = history_manager self.hdca_manager = hdca_manager self.collection_manager = collection_manager self.datatypes_registry = datatypes_registry def create(self, trans: ProvidesHistoryContext, payload: CreateNewCollectionPayload) -> HDCADetailed: """ Create a new dataset collection instance. :type payload: dict :param payload: (optional) dictionary structure containing: * collection_type: dataset collection type to create. * instance_type: Instance type - 'history' or 'library'. * name: the new dataset collections's name * datasets: object describing datasets for collection :rtype: dict :returns: element view of new dataset collection """ # TODO: Error handling... create_params = api_payload_to_create_params(payload.dict(exclude_unset=True)) if payload.instance_type == DatasetCollectionInstanceType.history: if payload.history_id is None: raise exceptions.RequestParameterInvalidException("Parameter history_id is required.") history_id = self.decode_id(payload.history_id) history = self.history_manager.get_owned(history_id, trans.user, current_history=trans.history) create_params["parent"] = history create_params["history"] = history elif payload.instance_type == DatasetCollectionInstanceType.library: library_folder = self.get_library_folder(trans, payload.folder_id, check_accessible=True) self.check_user_can_add_to_library_item(trans, library_folder, check_accessible=False) create_params["parent"] = library_folder else: raise exceptions.RequestParameterInvalidException() dataset_collection_instance = self.collection_manager.create(trans=trans, **create_params) rval = dictify_dataset_collection_instance( dataset_collection_instance, security=trans.security, url_builder=trans.url_builder, parent=create_params["parent"], ) return rval def copy( self, trans: ProvidesHistoryContext, id: EncodedDatabaseIdField, payload: UpdateCollectionAttributePayload ): """ Iterate over all datasets of a collection and copy datasets with new attributes to a new collection. e.g attributes = {'dbkey': 'dm3'} """ self.collection_manager.copy( trans, trans.history, "hdca", id, copy_elements=True, dataset_instance_attributes=payload.dict() ) def attributes( self, trans: ProvidesHistoryContext, id: EncodedDatabaseIdField, instance_type: DatasetCollectionInstanceType = DatasetCollectionInstanceType.history, ) -> DatasetCollectionAttributesResult: """ Returns dbkey/extension for collection elements """ dataset_collection_instance = self.collection_manager.get_dataset_collection_instance( trans, id=id, instance_type=instance_type, check_ownership=True ) rval = dataset_collection_instance.to_dict(view="dbkeysandextensions") return rval def suitable_converters( self, trans: ProvidesHistoryContext, id: EncodedDatabaseIdField, instance_type: DatasetCollectionInstanceType = DatasetCollectionInstanceType.history, ) -> SuitableConverters: """ Returns suitable converters for all datatypes in collection """ rval = self.collection_manager.get_converters_for_collection(trans, id, self.datatypes_registry, instance_type) return rval def show( self, trans: ProvidesHistoryContext, id: EncodedDatabaseIdField, instance_type: DatasetCollectionInstanceType = DatasetCollectionInstanceType.history, ) -> AnyHDCA: """ Returns information about a particular dataset collection. """ dataset_collection_instance = self.collection_manager.get_dataset_collection_instance( trans, id=id, instance_type=instance_type, ) if instance_type == DatasetCollectionInstanceType.history: parent = dataset_collection_instance.history elif instance_type == DatasetCollectionInstanceType.library: parent = dataset_collection_instance.folder else: raise exceptions.RequestParameterInvalidException() rval = dictify_dataset_collection_instance( dataset_collection_instance, security=trans.security, url_builder=trans.url_builder, parent=parent, view="element", ) return rval def contents( self, trans: ProvidesHistoryContext, hdca_id: EncodedDatabaseIdField, parent_id: EncodedDatabaseIdField, instance_type: DatasetCollectionInstanceType = DatasetCollectionInstanceType.history, limit: Optional[int] = None, offset: Optional[int] = None, ) -> DatasetCollectionContentElements: """ Shows direct child contents of indicated dataset collection parent id :type string: encoded string id :param id: HDCA.id :type string: encoded string id :param parent_id: parent dataset_collection.id for the dataset contents to be viewed :type integer: int :param limit: pagination limit for returned dataset collection elements :type integer: int :param offset: pagination offset for returned dataset collection elements :rtype: list :returns: list of dataset collection elements and contents """ # validate HDCA for current user, will throw error if not permitted # TODO: refactor get_dataset_collection_instance hdca = self.collection_manager.get_dataset_collection_instance( trans, id=hdca_id, check_ownership=True, instance_type=instance_type ) # check to make sure the dsc is part of the validated hdca decoded_parent_id = self.decode_id(parent_id) if parent_id != hdca_id and not hdca.contains_collection(decoded_parent_id): raise exceptions.ObjectNotFound( "Requested dataset collection is not contained within indicated history content" ) # retrieve contents contents = self.collection_manager.get_collection_contents(trans, decoded_parent_id, limit=limit, offset=offset) # dictify and tack on a collection_url for drilling down into nested collections def serialize_element(dsc_element) -> DCESummary: result = dictify_element_reference(dsc_element, recursive=False, security=trans.security) if result["element_type"] == DCEType.dataset_collection: assert trans.url_builder result["object"]["contents_url"] = trans.url_builder( "contents_dataset_collection", hdca_id=self.encode_id(hdca.id), parent_id=self.encode_id(result["object"]["id"]), ) trans.security.encode_all_ids(result, recursive=True) return result rval = [serialize_element(el) for el in contents] return DatasetCollectionContentElements.parse_obj(rval)
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# Generated by Django 2.2.10 on 2020-03-04 23:25 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('dcim', '0101_auto_20200304_1403'), ] operations = [ migrations.CreateModel( name='ApplicationType', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False)), ('created', models.DateField(auto_now_add=True, null=True)), ('last_updated', models.DateTimeField(auto_now=True, null=True)), ('name', models.CharField(max_length=100, unique=True)), ('slug', models.SlugField(max_length=100, unique=True)), ('language', models.CharField(blank=True, max_length=50, null=True)), ('actual_version', models.CharField(blank=True, max_length=50)), ('recommended_version', models.CharField(max_length=100)), ], options={ 'ordering': ['name', 'slug', 'language', 'actual_version', 'recommended_version'], }, ), ]
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# -*- coding:utf-8 -*- """Test function for vega.run""" import unittest def lazy(func): """lazy function wrapper :param func: function name """ attr_name = "_lazy_" + func.__name__ def lazy_func(*args, **kwargs): """Wrapper of lazy func :param args: any object :param kwargs: any kwargs :return: """ if not hasattr(func, attr_name): setattr(func, attr_name, func(*args, **kwargs)) return getattr(func, attr_name) return lazy_func @lazy def env_args(args): """A lazy function will be execute when call :param args: any object :return: """ return args class TestPipeline(unittest.TestCase): """Test lazy function worked in pipeline""" def test_env_args(self): """Test function 'env_args' is a lazy function""" args = {'env': 'test'} env_args(args) self.assertEqual(env_args(), {'env': 'test'})
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#!/usr/bin/env python # Copyright (c) Facebook, Inc. and its affiliates. """ Almost every FBCodeBuilder string is ultimately passed to a shell. Escaping too little or too much tends to be the most common error. The utilities in this file give a systematic way of avoiding such bugs: - When you write literal strings destined for the shell, use `ShellQuoted`. - When these literal strings are parameterized, use `ShellQuoted.format`. - Any parameters that are raw strings get `shell_quote`d automatically, while any ShellQuoted parameters will be left intact. - Use `path_join` to join path components. - Use `shell_join` to join already-quoted command arguments or shell lines. """ import os from collections import namedtuple # pyre-fixme[13] This is too magical for Pyre. class ShellQuoted(namedtuple("ShellQuoted", ("do_not_use_raw_str",))): """ Wrap a string with this to make it transparent to shell_quote(). It will almost always suffice to use ShellQuoted.format(), path_join(), or shell_join(). If you really must, use raw_shell() to access the raw string. """ def __new__(cls, s): "No need to nest ShellQuoted." return super(ShellQuoted, cls).__new__( cls, s.do_not_use_raw_str if isinstance(s, ShellQuoted) else s ) def __str__(self): raise RuntimeError( "One does not simply convert {0} to a string -- use path_join() " "or ShellQuoted.format() instead".format(repr(self)) ) def __repr__(self) -> str: return "{0}({1})".format(self.__class__.__name__, repr(self.do_not_use_raw_str)) def format(self, **kwargs) -> "ShellQuoted": """ Use instead of str.format() when the arguments are either `ShellQuoted()` or raw strings needing to be `shell_quote()`d. Positional args are deliberately not supported since they are more error-prone. """ return ShellQuoted( self.do_not_use_raw_str.format( **dict( (k, shell_quote(v).do_not_use_raw_str) for k, v in kwargs.items() ) ) ) def shell_quote(s) -> ShellQuoted: "Quotes a string if it is not already quoted" return ( s if isinstance(s, ShellQuoted) else ShellQuoted("'" + str(s).replace("'", "'\\''") + "'") ) def raw_shell(s: ShellQuoted): "Not a member of ShellQuoted so we get a useful error for raw strings" if isinstance(s, ShellQuoted): return s.do_not_use_raw_str raise RuntimeError("{0} should have been ShellQuoted".format(s)) def shell_join(delim, it) -> ShellQuoted: "Joins an iterable of ShellQuoted with a delimiter between each two" return ShellQuoted(delim.join(raw_shell(s) for s in it)) def path_join(*args) -> ShellQuoted: "Joins ShellQuoted and raw pieces of paths to make a shell-quoted path" return ShellQuoted(os.path.join(*[raw_shell(shell_quote(s)) for s in args])) def shell_comment(c: ShellQuoted) -> ShellQuoted: "Do not shell-escape raw strings in comments, but do handle line breaks." return ShellQuoted("# {c}").format( c=ShellQuoted( (raw_shell(c) if isinstance(c, ShellQuoted) else c).replace("\n", "\n# ") ) )
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"""Assortment of utilities. """ from datetime import datetime from hashlib import sha256, md5 import random import re import string import unicodedata epoch = datetime.utcfromtimestamp(0) def unix_time(dt=None): """Returns the UNIX time representation for a given date or current UTC.""" dt = dt or datetime.utcnow() return int((dt - epoch).total_seconds()) def unix_time_millis(dt=None): """Returns the UNIX time representation for a given date or current UTC.""" dt = dt or datetime.utcnow() return int((dt - epoch).total_seconds() * 1000) def from_iso_to_unix(iso_dt): """Converts from ISO format (e.g., "1984-06-02T19:05:00.000Z") to UNIX. """ if isinstance(iso_dt, int): return iso_dt # Already UNIX. try: dt = datetime.strptime(iso_dt, '%Y-%m-%dT%H:%M:%S.%fZ') except ValueError: dt = datetime.strptime(iso_dt, '%Y-%m-%dT%H:%M:%SZ') return unix_time(dt) def from_unix_to_iso(dt=None): """Returns the ISO representation for a given date or current UTC.""" dt = int(dt) if dt is not None else unix_time() return datetime.utcfromtimestamp(dt).strftime('%Y-%m-%dT%H:%M:%SZ') def datetime_from_unix_time(unix_dt): """Returns a datetime object.""" return datetime.utcfromtimestamp(unix_dt) def datetime_from_iso(iso_dt): """Returns a datetime object.""" return datetime.strptime(iso_dt, '%Y-%m-%dT%H:%M:%SZ') def password_hash(password, salt): if salt: return sha256(password + salt).hexdigest() else: return md5(password).hexdigest()[::-1] def random_string(size): return ''.join(random.SystemRandom().choice( string.ascii_letters + string.digits) for _ in range(size)) def remove_accents(input_str): """Replaces accented chars by their ascii equivalents.""" nfkd_form = unicodedata.normalize('NFKD', input_str) return u"".join([c for c in nfkd_form if not unicodedata.combining(c)]) def make_url_friendly(input_str): """Returns a URL-friedly version of input_str. Removes non-word chars, replaces accented ones and makes it lowercase. """ if input_str is None: return None return re.sub(r'[\W\\/_]+', '-', remove_accents(input_str)).lower()
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"""Copyright (c) 2021, Deep Net. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ EPSILON = 1e-20
[ [ [ 582, 589 ] ] ]
# exported from PySB model 'model' from pysb import Model, Monomer, Parameter, Expression, Compartment, Rule, Observable, Initial, MatchOnce, Annotation, ANY, WILD Model() Monomer('Ligand', ['Receptor']) Monomer('ParpU', ['C3A']) Monomer('C8A', ['BidU', 'C3pro']) Monomer('SmacM', ['BaxA']) Monomer('BaxM', ['BidM', 'BaxA']) Monomer('Apop', ['C3pro', 'Xiap']) Monomer('Fadd', ['Receptor', 'C8pro']) Monomer('SmacC', ['Xiap']) Monomer('ParpC') Monomer('Xiap', ['SmacC', 'Apop', 'C3A']) Monomer('C9') Monomer('C3ub') Monomer('C8pro', ['Fadd', 'C6A']) Monomer('C6A', ['C8pro']) Monomer('C3pro', ['Apop', 'C8A']) Monomer('CytoCM', ['BaxA']) Monomer('CytoCC') Monomer('BaxA', ['BaxM', 'BaxA_1', 'BaxA_2', 'SmacM', 'CytoCM']) Monomer('ApafI') Monomer('BidU', ['C8A']) Monomer('BidT') Monomer('C3A', ['Xiap', 'ParpU', 'C6pro']) Monomer('ApafA') Monomer('BidM', ['BaxM']) Monomer('Receptor', ['Ligand', 'Fadd']) Monomer('C6pro', ['C3A']) Parameter('bind_0_Ligand_binder_Receptor_binder_target_2kf', 1.0) Parameter('bind_0_Ligand_binder_Receptor_binder_target_1kr', 1.0) Parameter('bind_0_Receptor_binder_Fadd_binder_target_2kf', 1.0) Parameter('bind_0_Receptor_binder_Fadd_binder_target_1kr', 1.0) Parameter('substrate_binding_0_Fadd_catalyzer_C8pro_substrate_2kf', 1.0) Parameter('substrate_binding_0_Fadd_catalyzer_C8pro_substrate_1kr', 1.0) Parameter('catalytic_step_0_Fadd_catalyzer_C8pro_substrate_C8A_product_1kc', 1.0) Parameter('catalysis_0_C8A_catalyzer_BidU_substrate_BidT_product_2kf', 1.0) Parameter('catalysis_0_C8A_catalyzer_BidU_substrate_BidT_product_1kr', 1.0) Parameter('catalysis_1_C8A_catalyzer_BidU_substrate_BidT_product_1kc', 1.0) Parameter('conversion_0_CytoCC_subunit_d_ApafI_subunit_c_ApafA_complex_2kf', 1.0) Parameter('conversion_0_CytoCC_subunit_d_ApafI_subunit_c_ApafA_complex_1kr', 1.0) Parameter('inhibition_0_SmacC_inhibitor_Xiap_inh_target_2kf', 1.0) Parameter('inhibition_0_SmacC_inhibitor_Xiap_inh_target_1kr', 1.0) Parameter('conversion_0_C9_subunit_d_ApafA_subunit_c_Apop_complex_2kf', 1.0) Parameter('conversion_0_C9_subunit_d_ApafA_subunit_c_Apop_complex_1kr', 1.0) Parameter('catalysis_0_Apop_catalyzer_C3pro_substrate_C3A_product_2kf', 1.0) Parameter('catalysis_0_Apop_catalyzer_C3pro_substrate_C3A_product_1kr', 1.0) Parameter('catalysis_1_Apop_catalyzer_C3pro_substrate_C3A_product_1kc', 1.0) Parameter('inhibition_0_Xiap_inhibitor_Apop_inh_target_2kf', 1.0) Parameter('inhibition_0_Xiap_inhibitor_Apop_inh_target_1kr', 1.0) Parameter('catalysis_0_Xiap_catalyzer_C3A_substrate_C3ub_product_2kf', 1.0) Parameter('catalysis_0_Xiap_catalyzer_C3A_substrate_C3ub_product_1kr', 1.0) Parameter('catalysis_1_Xiap_catalyzer_C3A_substrate_C3ub_product_1kc', 1.0) Parameter('catalysis_0_C3A_catalyzer_ParpU_substrate_ParpC_product_2kf', 1.0) Parameter('catalysis_0_C3A_catalyzer_ParpU_substrate_ParpC_product_1kr', 1.0) Parameter('catalysis_1_C3A_catalyzer_ParpU_substrate_ParpC_product_1kc', 1.0) Parameter('equilibration_0_BidT_equil_a_BidM_equil_b_1kf', 1.0) Parameter('equilibration_0_BidT_equil_a_BidM_equil_b_1kr', 1.0) Parameter('catalysis_0_BidM_catalyzer_BaxM_substrate_BaxA_product_2kf', 1.0) Parameter('catalysis_0_BidM_catalyzer_BaxM_substrate_BaxA_product_1kr', 1.0) Parameter('catalysis_1_BidM_catalyzer_BaxM_substrate_BaxA_product_1kc', 1.0) Parameter('self_catalyze_0_BaxA_self_catalyzer_BaxM_self_substrate_2kf', 1.0) Parameter('self_catalyze_0_BaxA_self_catalyzer_BaxM_self_substrate_1kr', 1.0) Parameter('self_catalyze_1_BaxA_self_catalyzer_BaxM_self_substrate_1kc', 1.0) Parameter('pore_formation_0_BaxA_pore_2kf', 1.0) Parameter('pore_formation_0_BaxA_pore_1kr', 1.0) Parameter('pore_formation_1_BaxA_pore_2kf', 1.0) Parameter('pore_formation_1_BaxA_pore_1kr', 1.0) Parameter('pore_formation_2_BaxA_pore_2kf', 1.0) Parameter('pore_formation_2_BaxA_pore_1kr', 1.0) Parameter('transport_0_BaxA_pore_SmacM_cargo_M_SmacC_cargo_C_2kf', 1.0) Parameter('transport_0_BaxA_pore_SmacM_cargo_M_SmacC_cargo_C_1kr', 1.0) Parameter('transport_1_BaxA_pore_SmacM_cargo_M_SmacC_cargo_C_1kc', 1.0) Parameter('transport_0_BaxA_pore_CytoCM_cargo_M_CytoCC_cargo_C_2kf', 1.0) Parameter('transport_0_BaxA_pore_CytoCM_cargo_M_CytoCC_cargo_C_1kr', 1.0) Parameter('transport_1_BaxA_pore_CytoCM_cargo_M_CytoCC_cargo_C_1kc', 1.0) Parameter('catalysis_0_C8A_catalyzer_C3pro_substrate_C3A_product_2kf', 1.0) Parameter('catalysis_0_C8A_catalyzer_C3pro_substrate_C3A_product_1kr', 1.0) Parameter('catalysis_1_C8A_catalyzer_C3pro_substrate_C3A_product_1kc', 1.0) Parameter('catalysis_0_C3A_catalyzer_C6pro_substrate_C6A_product_2kf', 1.0) Parameter('catalysis_0_C3A_catalyzer_C6pro_substrate_C6A_product_1kr', 1.0) Parameter('catalysis_1_C3A_catalyzer_C6pro_substrate_C6A_product_1kc', 1.0) Parameter('catalysis_0_C6A_catalyzer_C8pro_substrate_C8A_product_2kf', 1.0) Parameter('catalysis_0_C6A_catalyzer_C8pro_substrate_C8A_product_1kr', 1.0) Parameter('catalysis_1_C6A_catalyzer_C8pro_substrate_C8A_product_1kc', 1.0) Parameter('Ligand_0', 1000.0) Parameter('ParpU_0', 1000000.0) Parameter('C8A_0', 0.0) Parameter('SmacM_0', 100000.0) Parameter('BaxM_0', 40000.0) Parameter('Apop_0', 0.0) Parameter('Fadd_0', 130000.0) Parameter('SmacC_0', 0.0) Parameter('ParpC_0', 0.0) Parameter('Xiap_0', 153750.0) Parameter('C9_0', 100000.0) Parameter('C3ub_0', 0.0) Parameter('C8pro_0', 130000.0) Parameter('C6A_0', 0.0) Parameter('C3pro_0', 21000.0) Parameter('CytoCM_0', 500000.0) Parameter('CytoCC_0', 0.0) Parameter('BaxA_0', 0.0) Parameter('ApafI_0', 100000.0) Parameter('BidU_0', 171000.0) Parameter('BidT_0', 0.0) Parameter('C3A_0', 0.0) Parameter('ApafA_0', 0.0) Parameter('BidM_0', 0.0) Parameter('Receptor_0', 100.0) Parameter('C6pro_0', 100.0) Observable('Ligand_obs', Ligand()) Observable('ParpU_obs', ParpU()) Observable('C8A_obs', C8A()) Observable('SmacM_obs', SmacM()) Observable('BaxM_obs', BaxM()) Observable('Apop_obs', Apop()) Observable('Fadd_obs', Fadd()) Observable('SmacC_obs', SmacC()) Observable('ParpC_obs', ParpC()) Observable('Xiap_obs', Xiap()) Observable('C9_obs', C9()) Observable('C3ub_obs', C3ub()) Observable('C8pro_obs', C8pro()) Observable('C6A_obs', C6A()) Observable('C3pro_obs', C3pro()) Observable('CytoCM_obs', CytoCM()) Observable('CytoCC_obs', CytoCC()) Observable('BaxA_obs', BaxA()) Observable('ApafI_obs', ApafI()) Observable('BidU_obs', BidU()) Observable('BidT_obs', BidT()) Observable('C3A_obs', C3A()) Observable('ApafA_obs', ApafA()) Observable('BidM_obs', BidM()) Observable('Receptor_obs', Receptor()) Observable('C6pro_obs', C6pro()) Rule('bind_0_Ligand_binder_Receptor_binder_target', Ligand(Receptor=None) + Receptor(Ligand=None, Fadd=None) | Ligand(Receptor=1) % Receptor(Ligand=1, Fadd=None), bind_0_Ligand_binder_Receptor_binder_target_2kf, bind_0_Ligand_binder_Receptor_binder_target_1kr) Rule('bind_0_Receptor_binder_Fadd_binder_target', Receptor(Ligand=ANY, Fadd=None) + Fadd(Receptor=None, C8pro=None) | Receptor(Ligand=ANY, Fadd=1) % Fadd(Receptor=1, C8pro=None), bind_0_Receptor_binder_Fadd_binder_target_2kf, bind_0_Receptor_binder_Fadd_binder_target_1kr) Rule('substrate_binding_0_Fadd_catalyzer_C8pro_substrate', Fadd(Receptor=ANY, C8pro=None) + C8pro(Fadd=None, C6A=None) | Fadd(Receptor=ANY, C8pro=1) % C8pro(Fadd=1, C6A=None), substrate_binding_0_Fadd_catalyzer_C8pro_substrate_2kf, substrate_binding_0_Fadd_catalyzer_C8pro_substrate_1kr) Rule('catalytic_step_0_Fadd_catalyzer_C8pro_substrate_C8A_product', Fadd(Receptor=ANY, C8pro=1) % C8pro(Fadd=1, C6A=None) >> Fadd(Receptor=ANY, C8pro=None) + C8A(BidU=None, C3pro=None), catalytic_step_0_Fadd_catalyzer_C8pro_substrate_C8A_product_1kc) Rule('catalysis_0_C8A_catalyzer_BidU_substrate_BidT_product', C8A(BidU=None, C3pro=None) + BidU(C8A=None) | C8A(BidU=1, C3pro=None) % BidU(C8A=1), catalysis_0_C8A_catalyzer_BidU_substrate_BidT_product_2kf, catalysis_0_C8A_catalyzer_BidU_substrate_BidT_product_1kr) Rule('catalysis_1_C8A_catalyzer_BidU_substrate_BidT_product', C8A(BidU=1, C3pro=None) % BidU(C8A=1) >> C8A(BidU=None, C3pro=None) + BidT(), catalysis_1_C8A_catalyzer_BidU_substrate_BidT_product_1kc) Rule('conversion_0_CytoCC_subunit_d_ApafI_subunit_c_ApafA_complex', ApafI() + CytoCC() | ApafA(), conversion_0_CytoCC_subunit_d_ApafI_subunit_c_ApafA_complex_2kf, conversion_0_CytoCC_subunit_d_ApafI_subunit_c_ApafA_complex_1kr) Rule('inhibition_0_SmacC_inhibitor_Xiap_inh_target', SmacC(Xiap=None) + Xiap(SmacC=None, Apop=None, C3A=None) | SmacC(Xiap=1) % Xiap(SmacC=1, Apop=None, C3A=None), inhibition_0_SmacC_inhibitor_Xiap_inh_target_2kf, inhibition_0_SmacC_inhibitor_Xiap_inh_target_1kr) Rule('conversion_0_C9_subunit_d_ApafA_subunit_c_Apop_complex', ApafA() + C9() | Apop(C3pro=None, Xiap=None), conversion_0_C9_subunit_d_ApafA_subunit_c_Apop_complex_2kf, conversion_0_C9_subunit_d_ApafA_subunit_c_Apop_complex_1kr) Rule('catalysis_0_Apop_catalyzer_C3pro_substrate_C3A_product', Apop(C3pro=None, Xiap=None) + C3pro(Apop=None, C8A=None) | Apop(C3pro=1, Xiap=None) % C3pro(Apop=1, C8A=None), catalysis_0_Apop_catalyzer_C3pro_substrate_C3A_product_2kf, catalysis_0_Apop_catalyzer_C3pro_substrate_C3A_product_1kr) Rule('catalysis_1_Apop_catalyzer_C3pro_substrate_C3A_product', Apop(C3pro=1, Xiap=None) % C3pro(Apop=1, C8A=None) >> Apop(C3pro=None, Xiap=None) + C3A(Xiap=None, ParpU=None, C6pro=None), catalysis_1_Apop_catalyzer_C3pro_substrate_C3A_product_1kc) Rule('inhibition_0_Xiap_inhibitor_Apop_inh_target', Xiap(SmacC=None, Apop=None, C3A=None) + Apop(C3pro=None, Xiap=None) | Xiap(SmacC=None, Apop=1, C3A=None) % Apop(C3pro=None, Xiap=1), inhibition_0_Xiap_inhibitor_Apop_inh_target_2kf, inhibition_0_Xiap_inhibitor_Apop_inh_target_1kr) Rule('catalysis_0_Xiap_catalyzer_C3A_substrate_C3ub_product', Xiap(SmacC=None, Apop=None, C3A=None) + C3A(Xiap=None, ParpU=None, C6pro=None) | Xiap(SmacC=None, Apop=None, C3A=1) % C3A(Xiap=1, ParpU=None, C6pro=None), catalysis_0_Xiap_catalyzer_C3A_substrate_C3ub_product_2kf, catalysis_0_Xiap_catalyzer_C3A_substrate_C3ub_product_1kr) Rule('catalysis_1_Xiap_catalyzer_C3A_substrate_C3ub_product', Xiap(SmacC=None, Apop=None, C3A=1) % C3A(Xiap=1, ParpU=None, C6pro=None) >> Xiap(SmacC=None, Apop=None, C3A=None) + C3ub(), catalysis_1_Xiap_catalyzer_C3A_substrate_C3ub_product_1kc) Rule('catalysis_0_C3A_catalyzer_ParpU_substrate_ParpC_product', C3A(Xiap=None, ParpU=None, C6pro=None) + ParpU(C3A=None) | C3A(Xiap=None, ParpU=1, C6pro=None) % ParpU(C3A=1), catalysis_0_C3A_catalyzer_ParpU_substrate_ParpC_product_2kf, catalysis_0_C3A_catalyzer_ParpU_substrate_ParpC_product_1kr) Rule('catalysis_1_C3A_catalyzer_ParpU_substrate_ParpC_product', C3A(Xiap=None, ParpU=1, C6pro=None) % ParpU(C3A=1) >> C3A(Xiap=None, ParpU=None, C6pro=None) + ParpC(), catalysis_1_C3A_catalyzer_ParpU_substrate_ParpC_product_1kc) Rule('equilibration_0_BidT_equil_a_BidM_equil_b', BidT() | BidM(BaxM=None), equilibration_0_BidT_equil_a_BidM_equil_b_1kf, equilibration_0_BidT_equil_a_BidM_equil_b_1kr) Rule('catalysis_0_BidM_catalyzer_BaxM_substrate_BaxA_product', BidM(BaxM=None) + BaxM(BidM=None, BaxA=None) | BidM(BaxM=1) % BaxM(BidM=1, BaxA=None), catalysis_0_BidM_catalyzer_BaxM_substrate_BaxA_product_2kf, catalysis_0_BidM_catalyzer_BaxM_substrate_BaxA_product_1kr) Rule('catalysis_1_BidM_catalyzer_BaxM_substrate_BaxA_product', BidM(BaxM=1) % BaxM(BidM=1, BaxA=None) >> BidM(BaxM=None) + BaxA(BaxM=None, BaxA_1=None, BaxA_2=None, SmacM=None, CytoCM=None), catalysis_1_BidM_catalyzer_BaxM_substrate_BaxA_product_1kc) Rule('self_catalyze_0_BaxA_self_catalyzer_BaxM_self_substrate', BaxA(BaxM=None, BaxA_1=None, BaxA_2=None, SmacM=None, CytoCM=None) + BaxM(BidM=None, BaxA=None) | BaxA(BaxM=1, BaxA_1=None, BaxA_2=None, SmacM=None, CytoCM=None) % BaxM(BidM=None, BaxA=1), self_catalyze_0_BaxA_self_catalyzer_BaxM_self_substrate_2kf, self_catalyze_0_BaxA_self_catalyzer_BaxM_self_substrate_1kr) Rule('self_catalyze_1_BaxA_self_catalyzer_BaxM_self_substrate', BaxA(BaxM=1, BaxA_1=None, BaxA_2=None, SmacM=None, CytoCM=None) % BaxM(BidM=None, BaxA=1) >> BaxA(BaxM=None, BaxA_1=None, BaxA_2=None, SmacM=None, CytoCM=None) + BaxA(BaxM=None, BaxA_1=None, BaxA_2=None, SmacM=None, CytoCM=None), self_catalyze_1_BaxA_self_catalyzer_BaxM_self_substrate_1kc) Rule('pore_formation_0_BaxA_pore', BaxA(BaxM=None, BaxA_1=None, BaxA_2=None, SmacM=None, CytoCM=None) + BaxA(BaxM=None, BaxA_1=None, BaxA_2=None, SmacM=None, CytoCM=None) | BaxA(BaxM=None, BaxA_1=None, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=None, SmacM=None, CytoCM=None), pore_formation_0_BaxA_pore_2kf, pore_formation_0_BaxA_pore_1kr) Rule('pore_formation_1_BaxA_pore', BaxA(BaxM=None, BaxA_1=None, BaxA_2=None, SmacM=None, CytoCM=None) + BaxA(BaxM=None, BaxA_1=None, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=None, SmacM=None, CytoCM=None) | BaxA(BaxM=None, BaxA_1=3, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=2, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=2, BaxA_2=3, SmacM=None, CytoCM=None), pore_formation_1_BaxA_pore_2kf, pore_formation_1_BaxA_pore_1kr) Rule('pore_formation_2_BaxA_pore', BaxA(BaxM=None, BaxA_1=None, BaxA_2=None, SmacM=None, CytoCM=None) + BaxA(BaxM=None, BaxA_1=3, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=2, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=2, BaxA_2=3, SmacM=None, CytoCM=None) | BaxA(BaxM=None, BaxA_1=4, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=2, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=2, BaxA_2=3, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=3, BaxA_2=4, SmacM=None, CytoCM=None), pore_formation_2_BaxA_pore_2kf, pore_formation_2_BaxA_pore_1kr) Rule('transport_0_BaxA_pore_SmacM_cargo_M_SmacC_cargo_C', BaxA(BaxM=None, BaxA_1=4, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=2, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=2, BaxA_2=3, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=3, BaxA_2=4, SmacM=None, CytoCM=None) + SmacM(BaxA=None) | BaxA(BaxM=None, BaxA_1=4, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=2, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=2, BaxA_2=3, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=3, BaxA_2=4, SmacM=5, CytoCM=None) % SmacM(BaxA=5), transport_0_BaxA_pore_SmacM_cargo_M_SmacC_cargo_C_2kf, transport_0_BaxA_pore_SmacM_cargo_M_SmacC_cargo_C_1kr) Rule('transport_1_BaxA_pore_SmacM_cargo_M_SmacC_cargo_C', BaxA(BaxM=None, BaxA_1=4, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=2, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=2, BaxA_2=3, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=3, BaxA_2=4, SmacM=5, CytoCM=None) % SmacM(BaxA=5) >> BaxA(BaxM=None, BaxA_1=4, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=2, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=2, BaxA_2=3, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=3, BaxA_2=4, SmacM=None, CytoCM=None) + SmacC(Xiap=None), transport_1_BaxA_pore_SmacM_cargo_M_SmacC_cargo_C_1kc) Rule('transport_0_BaxA_pore_CytoCM_cargo_M_CytoCC_cargo_C', BaxA(BaxM=None, BaxA_1=4, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=2, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=2, BaxA_2=3, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=3, BaxA_2=4, SmacM=None, CytoCM=None) + CytoCM(BaxA=None) | BaxA(BaxM=None, BaxA_1=4, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=2, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=2, BaxA_2=3, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=3, BaxA_2=4, SmacM=None, CytoCM=5) % CytoCM(BaxA=5), transport_0_BaxA_pore_CytoCM_cargo_M_CytoCC_cargo_C_2kf, transport_0_BaxA_pore_CytoCM_cargo_M_CytoCC_cargo_C_1kr) Rule('transport_1_BaxA_pore_CytoCM_cargo_M_CytoCC_cargo_C', BaxA(BaxM=None, BaxA_1=4, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=2, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=2, BaxA_2=3, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=3, BaxA_2=4, SmacM=None, CytoCM=5) % CytoCM(BaxA=5) >> BaxA(BaxM=None, BaxA_1=4, BaxA_2=1, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=1, BaxA_2=2, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=2, BaxA_2=3, SmacM=None, CytoCM=None) % BaxA(BaxM=None, BaxA_1=3, BaxA_2=4, SmacM=None, CytoCM=None) + CytoCC(), transport_1_BaxA_pore_CytoCM_cargo_M_CytoCC_cargo_C_1kc) Rule('catalysis_0_C8A_catalyzer_C3pro_substrate_C3A_product', C8A(BidU=None, C3pro=None) + C3pro(Apop=None, C8A=None) | C8A(BidU=None, C3pro=1) % C3pro(Apop=None, C8A=1), catalysis_0_C8A_catalyzer_C3pro_substrate_C3A_product_2kf, catalysis_0_C8A_catalyzer_C3pro_substrate_C3A_product_1kr) Rule('catalysis_1_C8A_catalyzer_C3pro_substrate_C3A_product', C8A(BidU=None, C3pro=1) % C3pro(Apop=None, C8A=1) >> C8A(BidU=None, C3pro=None) + C3A(Xiap=None, ParpU=None, C6pro=None), catalysis_1_C8A_catalyzer_C3pro_substrate_C3A_product_1kc) Rule('catalysis_0_C3A_catalyzer_C6pro_substrate_C6A_product', C3A(Xiap=None, ParpU=None, C6pro=None) + C6pro(C3A=None) | C3A(Xiap=None, ParpU=None, C6pro=1) % C6pro(C3A=1), catalysis_0_C3A_catalyzer_C6pro_substrate_C6A_product_2kf, catalysis_0_C3A_catalyzer_C6pro_substrate_C6A_product_1kr) Rule('catalysis_1_C3A_catalyzer_C6pro_substrate_C6A_product', C3A(Xiap=None, ParpU=None, C6pro=1) % C6pro(C3A=1) >> C3A(Xiap=None, ParpU=None, C6pro=None) + C6A(C8pro=None), catalysis_1_C3A_catalyzer_C6pro_substrate_C6A_product_1kc) Rule('catalysis_0_C6A_catalyzer_C8pro_substrate_C8A_product', C6A(C8pro=None) + C8pro(Fadd=None, C6A=None) | C6A(C8pro=1) % C8pro(Fadd=None, C6A=1), catalysis_0_C6A_catalyzer_C8pro_substrate_C8A_product_2kf, catalysis_0_C6A_catalyzer_C8pro_substrate_C8A_product_1kr) Rule('catalysis_1_C6A_catalyzer_C8pro_substrate_C8A_product', C6A(C8pro=1) % C8pro(Fadd=None, C6A=1) >> C6A(C8pro=None) + C8A(BidU=None, C3pro=None), catalysis_1_C6A_catalyzer_C8pro_substrate_C8A_product_1kc) Initial(Ligand(Receptor=None), Ligand_0) Initial(ParpU(C3A=None), ParpU_0) Initial(C8A(BidU=None, C3pro=None), C8A_0) Initial(SmacM(BaxA=None), SmacM_0) Initial(BaxM(BidM=None, BaxA=None), BaxM_0) Initial(Apop(C3pro=None, Xiap=None), Apop_0) Initial(Fadd(Receptor=None, C8pro=None), Fadd_0) Initial(SmacC(Xiap=None), SmacC_0) Initial(ParpC(), ParpC_0) Initial(Xiap(SmacC=None, Apop=None, C3A=None), Xiap_0) Initial(C9(), C9_0) Initial(C3ub(), C3ub_0) Initial(C8pro(Fadd=None, C6A=None), C8pro_0) Initial(C6A(C8pro=None), C6A_0) Initial(C3pro(Apop=None, C8A=None), C3pro_0) Initial(CytoCM(BaxA=None), CytoCM_0) Initial(CytoCC(), CytoCC_0) Initial(BaxA(BaxM=None, BaxA_1=None, BaxA_2=None, SmacM=None, CytoCM=None), BaxA_0) Initial(ApafI(), ApafI_0) Initial(BidU(C8A=None), BidU_0) Initial(BidT(), BidT_0) Initial(C3A(Xiap=None, ParpU=None, C6pro=None), C3A_0) Initial(ApafA(), ApafA_0) Initial(BidM(BaxM=None), BidM_0) Initial(Receptor(Ligand=None, Fadd=None), Receptor_0) Initial(C6pro(C3A=None), C6pro_0)
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from __future__ import annotations import typing as t from functools import singledispatch from inflection import underscore from sqlalchemy import Date from sqlalchemy import DateTime from sqlalchemy import Text from sqlalchemy import Time from sqlalchemy import Unicode from sqlalchemy import UnicodeText from sqlalchemy.orm import RelationshipProperty from sqlalchemy.types import Boolean from sqlalchemy.types import Float from sqlalchemy.types import Integer from sqlalchemy.types import Numeric from sqlalchemy.types import String from sqlalchemy.types import VARCHAR from sqlalchemy_utils import EmailType from sqlalchemy_utils import get_mapper from sqlalchemy_utils import JSONType from sqlalchemy_utils import PhoneNumberType from sqlalchemy_utils import URLType from sqlalchemy_utils.types import ChoiceType from .definitions import MagqlEnumType from .definitions import MagqlInputField from .definitions import MagqlInputObjectType StringFilter = MagqlInputObjectType( "StringFilter", { "operator": MagqlInputField( MagqlEnumType( "StringOperator", { "INCLUDES": "INCLUDES", "EQUALS": "EQUALS", "EXISTS": "EXISTS", "DOESNOTEXIST": "DOESNOTEXIST", }, ) ), "value": MagqlInputField("String"), }, ) DateFilter = MagqlInputObjectType( "DateFilter", { "operator": MagqlInputField( MagqlEnumType( "DateOperator", {"BEFORE": "BEFORE", "ON": "ON", "AFTER": "AFTER"} ) ), "value": MagqlInputField("String"), }, ) IntFilter = MagqlInputObjectType( "IntFilter", { "operator": MagqlInputField( MagqlEnumType( "IntOperator", { "lt": "lt", "lte": "lte", "eq": "eq", "neq": "neq", "gt": "gt", "gte": "gte", }, ) ), "value": MagqlInputField("Int"), }, ) FloatFilter = MagqlInputObjectType( "FloatFilter", { "operator": MagqlInputField( MagqlEnumType( "FloatOperator", { "lt": "lt", "lte": "lte", "eq": "eq", "neq": "neq", "gt": "gt", "gte": "gte", }, ) ), "value": MagqlInputField("Float"), }, ) RelFilter = MagqlInputObjectType( "RelFilter", { "operator": MagqlInputField( MagqlEnumType("RelOperator", {"INCLUDES": "INCLUDES"}) ), "value": MagqlInputField("Int"), }, ) BooleanFilter = MagqlInputObjectType( "BooleanFilter", { "operator": MagqlInputField( MagqlEnumType( "BooleanOperator", {"EQUALS": "EQUALS", "NOTEQUALS": "NOTEQUALS"} ) ), "value": MagqlInputField("Boolean"), }, ) EnumOperator = MagqlEnumType("EnumOperator", {"INCLUDES": "INCLUDES"}) def EnumFilter(base_type: t.Any) -> MagqlInputObjectType: name = base_type.name + "Filter" input_ = { "operator": MagqlInputField(EnumOperator), "value": MagqlInputField(base_type), } return MagqlInputObjectType(name, input_) @singledispatch def get_filter_comparator(type: t.Any) -> t.Any: raise TypeError(f"No comparator registered for {type.__class__.__name__!r}.") @get_filter_comparator.register(RelationshipProperty) def _get_relationship_comparator(rel: RelationshipProperty) -> t.Optional[t.Callable]: direction = rel.direction.name if "TOONE" in direction: def condition(filter_value: t.Any, filter_operator: str, field: t.Any) -> t.Any: if filter_operator == "INCLUDES": return field == filter_value return None return condition elif "TOMANY" in direction: def condition(filter_value: t.Any, filter_operator: str, field: t.Any) -> t.Any: if filter_operator == "INCLUDES": return field.any(field.contains(filter_value)) return None return condition return None @get_filter_comparator.register(DateTime) @get_filter_comparator.register(Date) def _get_date_comparator(_: t.Union[DateTime, Date]) -> t.Callable: def condition( filter_value: t.Union[DateTime, Date], filter_operator: str, field: t.Union[DateTime, Date], ) -> t.Any: if filter_operator == "BEFORE": return field < filter_value elif filter_operator == "ON": return field == filter_value elif filter_operator == "After": return field > filter_value return None return condition @get_filter_comparator.register(JSONType) @get_filter_comparator.register(Text) @get_filter_comparator.register(UnicodeText) @get_filter_comparator.register(Unicode) @get_filter_comparator.register(URLType) @get_filter_comparator.register(PhoneNumberType) @get_filter_comparator.register(EmailType) @get_filter_comparator.register(Time) @get_filter_comparator.register(String) @get_filter_comparator.register(VARCHAR) def _get_string_comparator(_: t.Any) -> t.Callable: def condition(filter_value: t.Any, filter_operator: str, field: t.Any) -> t.Any: if filter_operator == "INCLUDES": return field.like(f"%{filter_value}%") elif filter_operator == "EQUALS": return field == filter_value elif filter_operator == "EXISTS": return field.like("%") elif filter_operator == "DOESNOTEXIST": return field.is_(None) return condition @get_filter_comparator.register(Float) @get_filter_comparator.register(Numeric) @get_filter_comparator.register(Integer) def _get_number_comparator(_: t.Any) -> t.Callable: def condition(filter_value: t.Any, filter_operator: str, field: t.Any) -> t.Any: if filter_operator == "lt": return field < filter_value elif filter_operator == "lte": return field <= filter_value elif filter_operator == "eq": return field == filter_value elif filter_operator == "neq": return field != filter_value elif filter_operator == "gt": return field > filter_value elif filter_operator == "gte": return field >= filter_value return condition @get_filter_comparator.register(Boolean) def _get_boolean_comparator(_: t.Any) -> t.Callable: def condition(filter_value: t.Any, filter_operator: str, field: t.Any) -> t.Any: if filter_operator == "EQUALS": return field == filter_value elif filter_operator == "NOTEQUALS": return field != filter_value return condition @get_filter_comparator.register(ChoiceType) def _get_choice_comparator(_: t.Any) -> t.Callable: def condition(filter_value: t.Any, filter_operator: str, field: t.Any) -> t.Any: if filter_operator == "INCLUDES": return field == filter_value return condition def generate_filters(table: t.Any, info: t.Any, *args: t.Any, **kwargs: t.Any) -> t.Any: sqla_filters = [] if "filter" in kwargs and kwargs["filter"] is not None: mapper = get_mapper(table) gql_filters = kwargs["filter"] for filter_name, gql_filter in gql_filters.items(): gql_filter_value = gql_filter["value"] filter_name = underscore(filter_name) if filter_name in table.c: filter_type = table.c[filter_name].type elif filter_name in mapper.relationships: rel = mapper.relationships[filter_name] rel_mapper = get_mapper(rel.target) gql_filter_value = ( info.context.query(rel_mapper.class_) .filter_by(id=gql_filter_value) .one() ) filter_type = rel else: raise KeyError(filter_name) sql_filter = get_filter_comparator(filter_type)( gql_filter_value, gql_filter["operator"], getattr(mapper.class_, filter_name), ) sqla_filters.append(sql_filter) return sqla_filters
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from .__main__ import create_app application = create_app()
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# Copyright 2020 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ """comm_helper""" from mindspore.parallel._ps_context import _is_role_pserver, _is_role_sched from ._hccl_management import load_lib as hccl_load_lib _HCCL_AVAILABLE = False _NCCL_AVAILABLE = False try: import mindspore._ms_mpi as mpi _NCCL_AVAILABLE = True except ImportError: _NCCL_AVAILABLE = False try: hccl_load_lib() _HCCL_AVAILABLE = True except RuntimeError: _HCCL_AVAILABLE = False if _HCCL_AVAILABLE: from . import _hccl_management as hccl else: try: import hccl_test.manage.api as hccl _HCCL_AVAILABLE = True except ImportError: _HCCL_AVAILABLE = False HCCL_WORLD_COMM_GROUP = "hccl_world_group" NCCL_WORLD_COMM_GROUP = "nccl_world_group" class Backend: """ Class for available backends. Note: The backends' value should be string, e.g., "hccl". If backend is set to Backend.UNDEFINED, it will be seen as invaliad. Args: name (str): The name of backend. Raises: TypeError: If name is not a string. ValueError: If backend is invalid. Examples: >>> Backend("abc") >>> hccl = Backend("hccl") """ UNDEFINED = "undefined" HCCL = "hccl" NCCL = "nccl" def __new__(cls, name): """Create instance object of Backend.""" if not isinstance(name, str): raise TypeError("Backend name must be a string, but got {}".format(type(name))) value = getattr(Backend, name.upper(), Backend.UNDEFINED) if value == Backend.UNDEFINED: raise ValueError("Invalid backend: '{}'".format(name)) return value def is_hccl_available(): """ Check hccl api is available. Returns: Boolean. Return whether hccl is available or not. """ return _HCCL_AVAILABLE def is_nccl_available(): """ Check nccl api is available. Returns: Boolean. Return whether nccl is available or not. """ return _NCCL_AVAILABLE def check_parameter_available(func): """ Check parameter is available. If not available, raise Error. Args: func (Function): The function to be run. Raises: RuntimeError. Returns: Wrapper. If not available, raise Error. """ def wrapper(*args, **kargs): if _is_role_pserver() or _is_role_sched(): return func(*args, **kargs) group = None if "group" in kargs.keys(): group = kargs.get("group") if group is not None and not isinstance(group, str): raise TypeError("Group should be str or None, " "but got group {}".format(type(group))) if "backend" in kargs.keys(): backend = kargs.get("backend") if backend is Backend.HCCL and not is_hccl_available(): raise RuntimeError("Distributed Communication doesn't have HCCL built in") if backend is Backend.NCCL and not is_nccl_available(): raise RuntimeError("Distributed Communication doesn't have NCCL built in") if group is None: if backend is Backend.HCCL: group = HCCL_WORLD_COMM_GROUP elif backend is Backend.NCCL: group = NCCL_WORLD_COMM_GROUP return func(*args, **kargs) return wrapper @check_parameter_available def _get_rank_helper(group, backend): """ The Helper to do get_rank_id. Args: group (str): The communication group. backend (str): The backend, like "hccl". Raises: ValueError: If backend is invalid. Returns: Integer. The local rank id of the calling process. """ rank_id = None if _is_role_pserver() or _is_role_sched(): rank_id = 0 return rank_id if backend == Backend.HCCL: if group == HCCL_WORLD_COMM_GROUP: rank_id = hccl.get_rank_id() else: rank_id = hccl.get_rank_id(group) elif backend == Backend.NCCL: rank_id = mpi.get_rank_id(group) else: raise ValueError("Invalid backend: '{}'".format(backend)) return rank_id @check_parameter_available def _get_local_rank_helper(group, backend): """ The Helper to do get_local_rank_id. Args: group (str): The communication group. backend (str): The backend, like "hccl". Raises: ValueError: If backend is invalid. Returns: Integer. The local rank id of the calling process. """ rank_id = None if backend == Backend.HCCL: if group == HCCL_WORLD_COMM_GROUP: rank_id = hccl.get_local_rank_id() else: rank_id = hccl.get_local_rank_id(group) elif backend == Backend.NCCL: raise RuntimeError("Nccl doesn't support get_local_rank_id now.") else: raise ValueError("Invalid backend: '{}'".format(backend)) return rank_id @check_parameter_available def _get_size_helper(group, backend): """ The Helper to do get_rank_size. Args: group (str): The communication group. backend (str): The backend, like "hccl". Raises: ValueError: If backend is invalid. Returns: Integer. The rank size of specified group. """ size = None if _is_role_pserver() or _is_role_sched(): size = 1 return size if backend == Backend.HCCL: if group == HCCL_WORLD_COMM_GROUP: size = hccl.get_rank_size() else: size = hccl.get_rank_size(group) elif backend == Backend.NCCL: size = mpi.get_rank_size(group) else: raise ValueError("Invalid backend: '{}'".format(backend)) return size @check_parameter_available def _get_local_size_helper(group, backend): """ The Helper to do get_local_rank_size. Args: group (str): The communication group. backend (str): The backend, like "hccl". Raises: ValueError: If backend is invalid. Returns: Integer. The local rank size where the calling process is being within specified group. """ size = None if backend == Backend.HCCL: if group == HCCL_WORLD_COMM_GROUP: size = hccl.get_local_rank_size() else: size = hccl.get_local_rank_size(group) elif backend == Backend.NCCL: raise RuntimeError("Nccl doesn't support get_local_rank_size now.") else: raise ValueError("Invalid backend: '{}'".format(backend)) return size @check_parameter_available def _get_world_rank_from_group_rank_helper(group, group_rank_id, backend): """ The Helper to do get_world_rank_from_group_rank. Args: group (str): The user communication group. group_rank_id (int): A rank id in user communication group. backend (str): The backend, like "hccl". Raises: TypeError: If group_rank_id is not int. ValueError: If group is "hccl_world_group" or backend is invalid. Returns: Integer. A rank id in world communication group. """ world_rank_id = None if not isinstance(group_rank_id, int): raise TypeError("group_rank_id should be int, but got type {}".format(type(group_rank_id))) if backend == Backend.HCCL: if group == HCCL_WORLD_COMM_GROUP: raise ValueError("Group cannot be 'hccl_world_group'. ") world_rank_id = hccl.get_world_rank_from_group_rank(group, group_rank_id) elif backend == Backend.NCCL: raise RuntimeError("Nccl doesn't support get_world_rank_from_group_rank now.") else: raise ValueError("Invalid backend: '{}'".format(backend)) return world_rank_id @check_parameter_available def _get_group_rank_from_world_rank_helper(world_rank_id, group, backend): """ The Helper to do get_group_rank_from_world_rank. Args: world_rank_id (int): A rank id in world communication group. group (str): The user communication group. backend (str): The backend, like "hccl". Raises: TypeError: If world_rank_id is not int. ValueError: If group is 'hccl_world_group' or backend is invalid. Returns: Integer. A rank id in user communication group. """ group_rank_id = None if not isinstance(world_rank_id, int): raise TypeError("world_rank_id should be int, but got type {}".format(type(world_rank_id))) if backend == Backend.HCCL: if group == HCCL_WORLD_COMM_GROUP: raise ValueError("Group cannot be 'hccl_world_group'. ") group_rank_id = hccl.get_group_rank_from_world_rank(world_rank_id, group) elif backend == Backend.NCCL: raise RuntimeError("Nccl doesn't support get_group_rank_from_world_rank now.") else: raise ValueError("Invalid backend: '{}'".format(backend)) return group_rank_id @check_parameter_available def _create_group_helper(group, rank_ids, backend): """ The Helper to do create_group. Args: group (str): The communication group. rank_ids (list): Rank ids in the group. backend (str): The backend, like "hccl". Raises: TypeError: If rank_ids is not a list. ValueError: If rank_ids size is not larger than 1 or rank_ids has duplicate data or backend is invalid. """ if backend == Backend.HCCL: if not isinstance(rank_ids, list): raise TypeError("Rank_ids {} should be list".format(rank_ids)) rank_size = len(rank_ids) if rank_size < 1: raise ValueError("Rank_ids size {} should be large than 0".format(rank_size)) if len(rank_ids) - len(list(set(rank_ids))) > 0: raise ValueError("List rank_ids in Group {} has duplicate data!".format(group)) hccl.create_group(group, rank_size, rank_ids) elif backend == Backend.NCCL: raise RuntimeError("Nccl doesn't support create_group now.") else: raise ValueError("Invalid backend: '{}'".format(backend)) @check_parameter_available def _destroy_group_helper(group, backend): """ The Helper to do destroy_group. Args: group (str): The user communication group. backend (str): The backend, like "hccl". Raises: ValueError: If group is "hccl_world_group" or backend is invalid. """ if backend == Backend.HCCL: if group == HCCL_WORLD_COMM_GROUP: raise ValueError("The hccl_world_group does not support destruction.") hccl.destroy_group(group) elif backend == Backend.NCCL: raise RuntimeError("Nccl doesn't support destroy_group now.") else: raise ValueError("Invalid backend: '{}'".format(backend))
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from features.arduino_features import BlackrockSerialDIORowByte, SerialDIORowByte from riglib import experiment class par(object): def init(self): pass class F(BlackrockSerialDIORowByte, par): pass f = F() f.init()
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import logging import chevron import re from itertools import dropwhile import snex.util as util logger = logging.getLogger(__name__) DEFAULT = { # :snippet global-default-config lang: python "output_template": "```{{lang}}\n{{{snippet}}}\n```\n", "valid_param_keys": ["name", "lang", "lnum", "fname", "path"], "output_path": "snippets", "line_prefix": "", "comment_prefix": "# ", "comment_suffix": "", "snippet_start": ":snippet", "snippet_end": ":endsnippet", "cloak_start": ":cloak", "cloak_end": ":endcloak", "output_suffix": ".md", # :endsnippet } class Snippet: @classmethod def from_raw_data(cls, params, data, origin=None, prefix=""): (head,) = data[:1] (tail,) = data[-1:] body = data[1:-1] idlvl = util.det_indent_lvl(body) body = (line[idlvl:] for line in body) body = dropwhile(util.is_empty, body) body = util.dropwhile_right(util.is_empty, list(body)) body = (prefix + line for line in body) return cls(params=params, head=head.lstrip(), body=list(body), tail=tail.lstrip(), origin=origin) @property def name(self): return self.params["name"] @property def line_number(self): return self.params.get("lnum", -1) def __init__(self, params=None, head=None, body=None, tail=None, origin=None): self.params = params self.head = head self.body = body self.tail = tail self.origin = origin def __repr__(self): return f"Snippet({self.params!r}, {self.head!r}, {self.body!r}, {self.tail!r}, {self.origin!r})" def render_snippet(template, params, body): return chevron.render(template, {**params, **{"snippet": "\n".join(body)}}) def get_configs(conf): configs = conf["config"] default = configs["default"] if "default" in configs else None for name in [n for n in configs if not n == "default"]: c = util.merge_with_default_conf(configs[name], default, global_default=DEFAULT) # prevent defining a global name for all snippets in the config c.pop("name", None) yield (name, c) def extract_from_path(f, conf, base_path): comment_prefix = re.escape(conf["comment_prefix"]) comment_suffix = re.escape(conf["comment_suffix"]) line_prefix = conf["line_prefix"] cloak_start = re.escape(conf["cloak_start"]) cloak_end = re.escape(conf["cloak_end"]) cloak_start_re = f"^\\s*{comment_prefix}{cloak_start}{comment_suffix}$" cloak_end_re = f"^\\s*{comment_prefix}{cloak_end}{comment_suffix}$" snippet_start = re.escape(conf["snippet_start"]) snippet_end = re.escape(conf["snippet_end"]) snippet_start_re = f"^\\s*{comment_prefix}{snippet_start}(.*){comment_suffix}$" snippet_end_re = f"^\\s*{comment_prefix}{snippet_end}{comment_suffix}$" snippets = [] in_snippet = False cloaked = False data = [] params = {} for idx, line in util.read_path(f): lnum = idx + 1 if re.search(cloak_end_re, line): cloaked = False continue if re.search(cloak_start_re, line): cloaked = True if cloaked: continue if match := re.search(snippet_start_re, line): try: params = util.construct_params(match.group(1), f, base_path, lnum) params = util.sanitize_params(params, conf["valid_param_keys"]) except Exception as ex: logger.error(f"could not parse snippet params: {line} in file {f}:{lnum}") raise ex in_snippet = True if not in_snippet: continue data.append(line.rstrip("\n")) if re.search(snippet_end_re, line): in_snippet = False s = Snippet.from_raw_data(params, data, origin=f, prefix=line_prefix) snippets.append(s) data = [] params = {} return snippets
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__all__ = ('modulize',) import sys from types import FunctionType, GetSetDescriptorType, MappingProxyType, ModuleType from .docs import has_docs NoneType = type(None) try: from _weakref import ref as WeakrefType except ImportError: from weakref import ref as WeakrefType # This 2 type can be function WrapperDescriptorType = type(object.__ne__) MethodDescriptorType = type(object.__format__) DO_NOT_MODULIZE_TYPES = [MappingProxyType, GetSetDescriptorType] if WrapperDescriptorType is not FunctionType: DO_NOT_MODULIZE_TYPES.append(WrapperDescriptorType) if MethodDescriptorType is not FunctionType: DO_NOT_MODULIZE_TYPES.append(MethodDescriptorType) DO_NOT_MODULIZE_TYPES = tuple(DO_NOT_MODULIZE_TYPES) @has_docs def _modulize_function(old, globals_, source_module, module_name, module_path): """ Changes the given function's scopes and qualname if they were defined inside of a modulized class. Parameters ---------- old : `function` A function present inside of a modulized class. globals_ : `dict` of (`str`, `Any`) Global variables of the respective module. source_module : `module` The module, where the modulized class was defined. module_name : `str` The newly created module's name. module_path : `str` The newly created module's path. Returns ------- new : `function` Newly recreated function if applicable. """ if old.__module__ != source_module: return old new = FunctionType(old.__code__, globals_, old.__name__, old.__defaults__, old.__closure__) new.__module__ = module_path qualname = old.__qualname__ if (qualname is not None) and (len(qualname) > len(module_name)) and qualname[len(module_name)] =='.' and \ qualname.startswith(module_name): new.__qualname__ = qualname[len(module_name) + 1:] return new @has_docs def _modulize_type(klass, globals_, source_module, module_name, module_path): """ Changes the given class's scopes and qualname if they were defined inside of a modulized class. Parameters ---------- klass : `type` A class present inside of a modulized class. globals_ : `dict` of (`str`, `Any`) Global variables of the respective module. source_module : `module` The module, where the modulized class was defined. module_name : `str` The newly created module's name. module_path : `str` The newly created module's path. """ if klass.__module__ != source_module: return qualname = klass.__qualname__ if (qualname is None) or (len(qualname) <= len(module_name)) or qualname[len(module_name)] != '.' \ or not qualname.startswith(module_name): return klass.__qualname__ = qualname[len(module_name) + 1:] klass.__module__ = module_path for name in dir(klass): value = getattr(klass, name) value_type = value.__class__ if value_type is FunctionType: value = _modulize_function(value, globals_, source_module, module_name, module_path) setattr(klass, name, value) if issubclass(value_type, type): _modulize_type(value, globals_, source_module, module_name, module_path) @has_docs def modulize(klass): """ Transforms the given class to a module. Every functions and classes defined inside of given class, which are also present at transformation as well, will have their global scope modified. Parameters ---------- klass : `type` The class to transform to module. Returns ------- result_module : `module` The created module object. Raises ------ TypeError If `klass` is not given as `type`. """ if not isinstance(klass, type): raise TypeError( f'Only types can be modulized, got {klass.__class__.__name__}; {klass!r}.' ) source_module = klass.__module__ module_name = klass.__name__ module_path = f'{klass.__module__}.{module_name}' try: result_module = sys.modules['module_path'] except KeyError: result_module = ModuleType(module_path) sys.modules[module_path] = result_module globals_ = result_module.__dict__ globals_['__builtins__'] = __builtins__ else: globals_ = result_module.__dict__ collected_names = [] for name in globals_.keys(): if name.startswith('__') and name.endswith('__'): continue collected_names.append(name) for name in collected_names: del globals_[name] globals_['__doc__'] = None for name in type.__dir__(klass): if name.startswith('__') and name.endswith('__') and name != '__doc__': continue value = type.__getattribute__(klass, name) value_type = type(value) if value_type in DO_NOT_MODULIZE_TYPES: continue if value_type is FunctionType: value = _modulize_function(value, globals_, source_module, module_name, module_path) if issubclass(value_type, type): _modulize_type(value, globals_, source_module, module_name, module_path) ModuleType.__setattr__(result_module, name, value) return result_module
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import shutil import tempfile from django.conf import settings from django.core.files.uploadedfile import SimpleUploadedFile from django.core.cache import cache from django.contrib.auth import get_user_model from django.test import Client, TestCase, override_settings from django.urls import reverse from django import forms from ..models import Post, Group, Follow User = get_user_model() TEMP_MEDIA_ROOT = tempfile.mkdtemp(dir=settings.BASE_DIR) class PaginatorTest(TestCase): @classmethod def setUpClass(cls): super().setUpClass() cls.user = User.objects.create_user(username='NoName') cls.user_client = Client() cls.user_client.force_login(cls.user) cls.count_posts_on_page = 10 cls.count_posts = 15 cls.rest_posts = cls.count_posts % cls.count_posts_on_page cls.group = Group.objects.create( title='Тестовый заголовок', slug='test-slug', description='Описание...' ) posts = ( Post( text='Тестовый текст поста.', author=cls.user, group=cls.group ) for i in range(cls.count_posts) ) Post.objects.bulk_create(posts, cls.count_posts) def test_paginator_pages(self): pages_paginator = [ reverse( 'posts:index' ), reverse( 'posts:group_list', kwargs={'slug': PaginatorTest.group.slug} ), reverse( 'posts:profile', kwargs={'username': PaginatorTest.user} ) ] for page in pages_paginator: with self.subTest(page=page): response = PaginatorTest.user_client.get(page) self.assertEqual( len(response.context['page_obj']), ( PaginatorTest.count_posts_on_page ) ) response = PaginatorTest.user_client.get( page + '?page=2' ) self.assertEqual( len(response.context['page_obj']), PaginatorTest.rest_posts ) @override_settings(MEDIA_ROOT=TEMP_MEDIA_ROOT) class PostPagesTests(TestCase): @classmethod def setUpClass(cls): super().setUpClass() cls.user = User.objects.create_user(username='NoName') cls.user_client = Client() cls.user_client.force_login(cls.user) small_gif = ( b'\x47\x49\x46\x38\x39\x61\x02\x00' b'\x01\x00\x80\x00\x00\x00\x00\x00' b'\xFF\xFF\xFF\x21\xF9\x04\x00\x00' b'\x00\x00\x00\x2C\x00\x00\x00\x00' b'\x02\x00\x01\x00\x00\x02\x02\x0C' b'\x0A\x00\x3B' ) image = SimpleUploadedFile( name='small.gif', content=small_gif, content_type='image/gif' ) cls.group = Group.objects.create( title='Тестовый заголовок', slug='test-slug', description='Описание...' ) cls.post = Post.objects.create( text='Тестовый текст поста.', image=image, author=cls.user, group=cls.group ) @classmethod def tearDownClass(cls): super().tearDownClass() shutil.rmtree(TEMP_MEDIA_ROOT, ignore_errors=True) def test_pages_uses_correct_template(self): templates_pages_names = { reverse('posts:index'): 'posts/index.html', reverse( 'posts:group_list', kwargs={'slug': PostPagesTests.group.slug} ): 'posts/group_list.html', reverse( 'posts:profile', kwargs={'username': PostPagesTests.user} ): 'posts/profile.html', reverse( 'posts:post_detail', kwargs={'post_id': PostPagesTests.post.id} ): 'posts/post_detail.html', reverse('posts:post_create'): 'posts/create_post.html', reverse( 'posts:post_edit', kwargs={'post_id': PostPagesTests.post.id} ): 'posts/create_post.html' } for reverse_name, template in templates_pages_names.items(): with self.subTest(reverse_name=reverse_name): response = PostPagesTests.user_client.get(reverse_name) self.assertTemplateUsed(response, template) def check_post_context(self, post): self.assertEqual(post.id, PostPagesTests.post.id) self.assertEqual(post.author, PostPagesTests.post.author) self.assertEqual(post.text, PostPagesTests.post.text) self.assertEqual(post.image, PostPagesTests.post.image) self.assertEqual(post.group, PostPagesTests.post.group) def test_index_page_context(self): response = PostPagesTests.user_client.get(reverse('posts:index')) self.check_post_context(response.context['page_obj'][0]) def test_group_list_page_context(self): response = PostPagesTests.user_client.get( reverse( 'posts:group_list', kwargs={'slug': PostPagesTests.group.slug} ) ) self.check_post_context(response.context['page_obj'][0]) self.assertEqual( PostPagesTests.group, response.context['group'] ) def test_new_group_list_none(self): group = Group.objects.create( title='Тестовый заголовок', slug='test-slug-new', description='Описание...' ) response = PostPagesTests.user_client.get( reverse( 'posts:group_list', kwargs={'slug': group.slug} ) ) self.assertEqual(len(response.context['page_obj']), 0) def test_profile_page_context(self): response = PostPagesTests.user_client.get( reverse( 'posts:profile', kwargs={'username': PostPagesTests.user} ) ) self.check_post_context(response.context['page_obj'][0]) self.assertEqual( PostPagesTests.user, response.context['author'] ) self.assertIsNotNone(response.context['following']) def test_post_detail_page_context(self): response = PostPagesTests.user_client.get( reverse( 'posts:post_detail', kwargs={'post_id': PostPagesTests.post.id} ) ) self.check_post_context(response.context['post']) form_fields = {'text': forms.fields.CharField} for value, expected in form_fields.items(): with self.subTest(value=value): form_fields = response.context['form'].fields.get(value) self.assertIsInstance(form_fields, expected) self.assertIsNotNone(response.context['comments']) def test_edit_post_page_context(self): response = PostPagesTests.user_client.get( reverse( 'posts:post_edit', kwargs={'post_id': PostPagesTests.post.id} ) ) self.assertIsNotNone(response.context['form']) self.assertIsNotNone(response.context['is_edit']) self.assertTrue(response.context['is_edit']) form_fields = { 'text': forms.fields.CharField, 'group': forms.fields.ChoiceField, } for value, expected in form_fields.items(): with self.subTest(value=value): form_fields = response.context['form'].fields.get(value) self.assertIsInstance(form_fields, expected) def test_create_post_page_context(self): response = PostPagesTests.user_client.get( reverse('posts:post_create') ) form_fields = { 'text': forms.fields.CharField, 'group': forms.fields.ChoiceField, } for value, expected in form_fields.items(): with self.subTest(value=value): form_fields = response.context['form'].fields.get(value) self.assertIsInstance(form_fields, expected) def test_cache_index(self): post = Post.objects.create( text='Тестовый текст поста.', author=PostPagesTests.user, ) response = PostPagesTests.user_client.get( reverse('posts:index') ) page = response.content post.delete() response = PostPagesTests.user_client.get( reverse('posts:index') ) self.assertEqual(page, response.content) cache.clear() response = PostPagesTests.user_client.get( reverse('posts:index') ) self.assertNotEqual(page, response.content) class FollowTests(TestCase): @classmethod def setUpClass(cls): super().setUpClass() cls.user = User.objects.create_user(username='NoName') cls.user_client = Client() cls.user_client.force_login(cls.user) cls.author = User.objects.create_user(username='Author') cls.author_client = Client() cls.author_client.force_login(cls.author) def test_following_auth(self): #FIXME: connection through ORM FollowTests.user_client.get( reverse( 'posts:profile_follow', kwargs={'username': FollowTests.author} ) ) #FIXME: necessary to calculate that a BD increased by one object follow = Follow.objects.last() self.assertEqual(follow.user, FollowTests.user) self.assertEqual(follow.author, FollowTests.author) def test_unfollow_auth(self): #FIXME: connection through ORM FollowTests.user_client.get( reverse( 'posts:profile_follow', kwargs={'username': FollowTests.author} ) ) follows_count = Follow.objects.count() FollowTests.user_client.get( reverse( 'posts:profile_unfollow', kwargs={'username': FollowTests.author} ) ) self.assertEqual(Follow.objects.count(), follows_count - 1) def test_new_post_follow(self): FollowTests.user_client.get( reverse( 'posts:profile_follow', kwargs={'username': FollowTests.author} ) ) post = Post.objects.create( text='Тестовый текст поста.', author=FollowTests.author, ) response = FollowTests.user_client.get( reverse( 'posts:follow_index' ) ) self.assertEqual( post.id, response.context['page_obj'][0].id ) def test_new_post_unfollow(self): FollowTests.user_client.get( reverse( 'posts:profile_follow', kwargs={'username': FollowTests.author} ) ) Post.objects.create( text='Тестовый текст поста.', author=FollowTests.author, ) user = User.objects.create_user(username='NameNo') user_client = Client() user_client.force_login(user) response = user_client.get( reverse( 'posts:follow_index' ) ) self.assertEqual(len(response.context['page_obj']), 0)
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from sqlalchemy import Column from sqlalchemy import Integer from alembic import command from alembic import op from alembic.testing import config from alembic.testing.env import _no_sql_testing_config from alembic.testing.env import clear_staging_env from alembic.testing.env import staging_env from alembic.testing.env import three_rev_fixture from alembic.testing.fixtures import capture_context_buffer from alembic.testing.fixtures import op_fixture from alembic.testing.fixtures import TestBase from alembic.util import sqla_compat class FullEnvironmentTests(TestBase): @classmethod def setup_class(cls): staging_env() cls.cfg = cfg = _no_sql_testing_config("oracle") cls.a, cls.b, cls.c = three_rev_fixture(cfg) @classmethod def teardown_class(cls): clear_staging_env() def test_begin_comit(self): with capture_context_buffer(transactional_ddl=True) as buf: command.upgrade(self.cfg, self.a, sql=True) assert "SET TRANSACTION READ WRITE\n\n/" in buf.getvalue() assert "COMMIT\n\n/" in buf.getvalue() def test_batch_separator_default(self): with capture_context_buffer() as buf: command.upgrade(self.cfg, self.a, sql=True) assert "/" in buf.getvalue() assert ";" not in buf.getvalue() def test_batch_separator_custom(self): with capture_context_buffer(oracle_batch_separator="BYE") as buf: command.upgrade(self.cfg, self.a, sql=True) assert "BYE" in buf.getvalue() class OpTest(TestBase): def test_add_column(self): context = op_fixture("oracle") op.add_column("t1", Column("c1", Integer, nullable=False)) context.assert_("ALTER TABLE t1 ADD c1 INTEGER NOT NULL") def test_add_column_with_default(self): context = op_fixture("oracle") op.add_column( "t1", Column("c1", Integer, nullable=False, server_default="12") ) context.assert_("ALTER TABLE t1 ADD c1 INTEGER DEFAULT '12' NOT NULL") @config.requirements.comments def test_add_column_with_comment(self): context = op_fixture("oracle") op.add_column( "t1", Column("c1", Integer, nullable=False, comment="c1 comment") ) context.assert_( "ALTER TABLE t1 ADD c1 INTEGER NOT NULL", "COMMENT ON COLUMN t1.c1 IS 'c1 comment'", ) @config.requirements.computed_columns_api def test_add_column_computed(self): context = op_fixture("oracle") op.add_column( "t1", Column("some_column", Integer, sqla_compat.Computed("foo * 5")), ) context.assert_( "ALTER TABLE t1 ADD some_column " "INTEGER GENERATED ALWAYS AS (foo * 5)" ) def test_alter_table_rename_oracle(self): context = op_fixture("oracle") op.rename_table("s", "t") context.assert_("ALTER TABLE s RENAME TO t") def test_alter_table_rename_schema_oracle(self): context = op_fixture("oracle") op.rename_table("s", "t", schema="myowner") context.assert_("ALTER TABLE myowner.s RENAME TO t") def test_alter_column_rename_oracle(self): context = op_fixture("oracle") op.alter_column("t", "c", new_column_name="x") context.assert_("ALTER TABLE t RENAME COLUMN c TO x") def test_alter_column_new_type(self): context = op_fixture("oracle") op.alter_column("t", "c", type_=Integer) context.assert_("ALTER TABLE t MODIFY c INTEGER") def test_alter_column_add_comment(self): context = op_fixture("oracle") op.alter_column("t", "c", type_=Integer, comment="c comment") context.assert_( "ALTER TABLE t MODIFY c INTEGER", "COMMENT ON COLUMN t.c IS 'c comment'", ) def test_alter_column_add_comment_quotes(self): context = op_fixture("oracle") op.alter_column("t", "c", type_=Integer, comment="c 'comment'") context.assert_( "ALTER TABLE t MODIFY c INTEGER", "COMMENT ON COLUMN t.c IS 'c ''comment'''", ) def test_alter_column_drop_comment(self): context = op_fixture("oracle") op.alter_column("t", "c", type_=Integer, comment=None) context.assert_( "ALTER TABLE t MODIFY c INTEGER", "COMMENT ON COLUMN t.c IS ''" ) def test_create_table_comment(self): # this is handled by SQLAlchemy's compilers context = op_fixture("oracle") op.create_table_comment("t2", comment="t2 table", schema="foo") context.assert_("COMMENT ON TABLE foo.t2 IS 't2 table'") def test_drop_table_comment(self): # this is handled by SQLAlchemy's compilers context = op_fixture("oracle") op.drop_table_comment("t2", existing_comment="t2 table", schema="foo") context.assert_("COMMENT ON TABLE foo.t2 IS ''") def test_drop_index(self): context = op_fixture("oracle") op.drop_index("my_idx", "my_table") context.assert_contains("DROP INDEX my_idx") def test_drop_column_w_default(self): context = op_fixture("oracle") op.drop_column("t1", "c1") context.assert_("ALTER TABLE t1 DROP COLUMN c1") def test_drop_column_w_check(self): context = op_fixture("oracle") op.drop_column("t1", "c1") context.assert_("ALTER TABLE t1 DROP COLUMN c1") def test_alter_column_nullable_w_existing_type(self): context = op_fixture("oracle") op.alter_column("t", "c", nullable=True, existing_type=Integer) context.assert_("ALTER TABLE t MODIFY c NULL") def test_alter_column_not_nullable_w_existing_type(self): context = op_fixture("oracle") op.alter_column("t", "c", nullable=False, existing_type=Integer) context.assert_("ALTER TABLE t MODIFY c NOT NULL") def test_alter_column_nullable_w_new_type(self): context = op_fixture("oracle") op.alter_column("t", "c", nullable=True, type_=Integer) context.assert_( "ALTER TABLE t MODIFY c NULL", "ALTER TABLE t MODIFY c INTEGER" ) def test_alter_column_not_nullable_w_new_type(self): context = op_fixture("oracle") op.alter_column("t", "c", nullable=False, type_=Integer) context.assert_( "ALTER TABLE t MODIFY c NOT NULL", "ALTER TABLE t MODIFY c INTEGER" ) def test_alter_add_server_default(self): context = op_fixture("oracle") op.alter_column("t", "c", server_default="5") context.assert_("ALTER TABLE t MODIFY c DEFAULT '5'") def test_alter_replace_server_default(self): context = op_fixture("oracle") op.alter_column( "t", "c", server_default="5", existing_server_default="6" ) context.assert_("ALTER TABLE t MODIFY c DEFAULT '5'") def test_alter_remove_server_default(self): context = op_fixture("oracle") op.alter_column("t", "c", server_default=None) context.assert_("ALTER TABLE t MODIFY c DEFAULT NULL") def test_alter_do_everything(self): context = op_fixture("oracle") op.alter_column( "t", "c", new_column_name="c2", nullable=True, type_=Integer, server_default="5", ) context.assert_( "ALTER TABLE t MODIFY c NULL", "ALTER TABLE t MODIFY c DEFAULT '5'", "ALTER TABLE t MODIFY c INTEGER", "ALTER TABLE t RENAME COLUMN c TO c2", ) @config.requirements.comments def test_create_table_with_column_comments(self): context = op_fixture("oracle") op.create_table( "t2", Column("c1", Integer, primary_key=True), comment="t2 comment" ) context.assert_( "CREATE TABLE t2 (c1 INTEGER NOT NULL, PRIMARY KEY (c1))", "COMMENT ON TABLE t2 IS 't2 comment'", ) # TODO: when we add schema support # def test_alter_column_rename_oracle_schema(self): # context = op_fixture('oracle') # op.alter_column("t", "c", name="x", schema="y") # context.assert_( # 'ALTER TABLE y.t RENAME COLUMN c TO c2' # )
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# Copyright 2017 The Bazel Authors. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Unit tests for shell.bzl.""" load("//lib:shell.bzl", "shell") load("//lib:unittest.bzl", "asserts", "unittest") def _shell_array_literal_test(ctx): """Unit tests for shell.array_literal.""" env = unittest.begin(ctx) asserts.equals(env, "()", shell.array_literal([])) asserts.equals(env, "('1')", shell.array_literal([1])) asserts.equals(env, "('1' '2' '3')", shell.array_literal([1, 2, 3])) asserts.equals(env, "('$foo')", shell.array_literal(["$foo"])) asserts.equals(env, "('qu\"o\"te')", shell.array_literal(['qu"o"te'])) unittest.end(env) shell_array_literal_test = unittest.make(_shell_array_literal_test) def _shell_quote_test(ctx): """Unit tests for shell.quote.""" env = unittest.begin(ctx) asserts.equals(env, "'foo'", shell.quote("foo")) asserts.equals(env, "'foo bar'", shell.quote("foo bar")) asserts.equals(env, "'three spaces'", shell.quote("three spaces")) asserts.equals(env, "' leading'", shell.quote(" leading")) asserts.equals(env, "'trailing '", shell.quote("trailing ")) asserts.equals(env, "'new\nline'", shell.quote("new\nline")) asserts.equals(env, "'tab\tcharacter'", shell.quote("tab\tcharacter")) asserts.equals(env, "'$foo'", shell.quote("$foo")) asserts.equals(env, "'qu\"o\"te'", shell.quote('qu"o"te')) asserts.equals(env, "'it'\\''s'", shell.quote("it's")) asserts.equals(env, "'foo\\bar'", shell.quote("foo\\bar")) asserts.equals(env, "'back`echo q`uote'", shell.quote("back`echo q`uote")) unittest.end(env) shell_quote_test = unittest.make(_shell_quote_test) def _shell_spawn_e2e_test_impl(ctx): """Test spawning a real shell.""" args = [ "foo", "foo bar", "three spaces", " leading", "trailing ", "new\nline", "tab\tcharacter", "$foo", 'qu"o"te', "it's", "foo\\bar", "back`echo q`uote", ] script_content = "\n".join([ "#!/bin/bash", "myarray=" + shell.array_literal(args), 'output=$(echo "${myarray[@]}")', # For logging: 'echo "DEBUG: output=[${output}]" >&2', # The following is a shell representation of what the echo of the quoted # array will look like. It looks a bit confusing considering it's shell # quoted into Python. Shell using single quotes to minimize shell # escaping, so only the single quote needs to be escaped as '\'', all # others are essentially kept literally. "expected='foo foo bar three spaces leading trailing new", "line tab\tcharacter $foo qu\"o\"te it'\\''s foo\\bar back`echo q`uote'", '[[ "${output}" == "${expected}" ]]', ]) script_file = ctx.actions.declare_file("%s.sh" % (ctx.label.name)) ctx.actions.write( output = script_file, content = script_content, is_executable = True, ) return [ DefaultInfo(executable = script_file), ] shell_spawn_e2e_test = rule( test = True, implementation = _shell_spawn_e2e_test_impl, ) def shell_test_suite(): """Creates the test targets and test suite for shell.bzl tests.""" unittest.suite( "shell_tests", shell_array_literal_test, shell_quote_test, shell_spawn_e2e_test, )
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import strax import straxen import wfsim def test_nt_context(register=None, context=None): """ Test a context if it is properly setup. To this end, we perform a simple scan of the field "time" since all plugins should have this field, if there is some option specified badly, we will quickly find out since for this scan, we activate all the plugins. :param register: Register a plugin (optional) :param context: Test with some other context than the nT simulation context """ if not straxen.utilix_is_configured(): return if context is None: context = straxen.contexts.xenonnt_simulation(cmt_run_id_sim='010000', cmt_version='global_ONLINE') assert isinstance(context, strax.Context), f'{context} is not a context' if register is not None: assert issubclass(register, strax.Plugin), f'{register} is not a plugin' # Search all plugins for the time field (each should have one) context.search_field('time') # def test_mc_chain(): # test_nt_context(wfsim.RawRecordsFromMcChain) # def test_fax_nveto(): # test_nt_context(wfsim.RawRecordsFromFaxnVeto) # def test_1t_context(): # test_nt_context(context=straxen.contexts.xenon1t_simulation())
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import glob import datetime import inference import numpy as np flist = [] def run_classifier(): flist = [] list1 = glob.glob("./images/*.jpg") list1.sort() print("Printing the time of Interesting Events.....\n\n") temp = str(inference.run_inference_on_image()) for i in range(len(list1) - 1): inference.imagePath = list1[i] temp2 = str(inference.run_inference_on_image2()) inference.imagePath = list1[i+1] temp = str(inference.run_inference_on_image2()) if temp2 != temp: print("Time : " + str(datetime.timedelta(seconds=(i)))) flist.extend([i]) else: print("." ,) d = np.array(flist) d.sort() diff = [y - x for x, y in zip(*[iter(d)] * 2)] avg = sum(diff) / len(diff) m = [[d[0]]] for x in d[1:]: if x - m[-1][0] < avg: m[-1].append(x) else: m.append([x]) # print(m) # print(type(m)) with open('list.txt' , 'w') as f: print("Writing to file\n") for i in range(0 , (len(m))): with open('list.txt' , 'a') as f: print("\n", file=f) print("start time : " + str(datetime.timedelta(seconds = int((m[i][0])) )) , file=f) print("end time : " + str(datetime.timedelta(seconds = int((m[i][len(m[i]) - 1])) )) , file=f ) print("\n\nFinished Analysis\n\n") print("The timestanps of all interesting events is stored in a File named list.txt ") if __name__ == '__main__': run_classifier()
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import re import sys import inspect _py2 = sys.version_info[0] == 2 _py3 = sys.version_info[0] == 3 # noinspection PyPep8Naming class route(object): def __init__(self, rule, **options): """ Class Initializer - This will only execute if using BottleCBV's original route() style. """ # Not sure if this is needed, need to test what happens when you specify a rule but not options in BottleCBV. if not options: options = dict(method='ANY') self.rule = rule self.options = options def __call__(self, func): f = func rule = self.rule options = self.options def decorator(*_, **__): if not hasattr(f, '_rule_cache') or f._rule_cache is None: f._rule_cache = {f.__name__: [(rule, options)]} elif f.__name__ not in f._rule_cache: f._rule_cache[f.__name__] = [(rule, options)] else: f._rule_cache[f.__name__].append((rule, options)) return f return decorator() @staticmethod def decorate(f, rule, **options): if not hasattr(f, '_rule_cache') or f._rule_cache is None: f._rule_cache = {f.__name__: [(rule, options)]} elif f.__name__ not in f._rule_cache: f._rule_cache[f.__name__] = [(rule, options)] else: f._rule_cache[f.__name__].append((rule, options)) return f @staticmethod def get(rule): """ GET Method CRUD Use Case: Read Example: Request a user profile """ options = dict(method='GET') def decorator(f): return route.decorate(f, rule, **options) return decorator @staticmethod def post(rule): """ POST Method CRUD Use Case: Create Example: Create a new user """ options = dict(method='POST') def decorator(f): return route.decorate(f, rule, **options) return decorator @staticmethod def put(rule): """ PUT Method CRUD Use Case: Update / Replace Example: Set item# 4022 to Red Seedless Grapes, instead of tomatoes """ options = dict(method='PUT') def decorator(f): return route.decorate(f, rule, **options) return decorator @staticmethod def patch(rule): """ PATCH Method CRUD Use Case: Update / Modify Example: Rename then user's name from Jon to John """ options = dict(method='PATCH') def decorator(f): return route.decorate(f, rule, **options) return decorator @staticmethod def delete(rule): """ DELETE Method CRUD Use Case: Delete Example: Delete user# 12403 (John) """ options = dict(method='DELETE') def decorator(f): return route.decorate(f, rule, **options) return decorator @staticmethod def head(rule): """ HEAD Method CRUD Use Case: Read (in-part) Note: This is the same as GET, but without the response body. This is useful for items such as checking if a user exists, such as this example: Request: GET /user/12403 Response: (status code) 404 - Not Found If you are closely following the REST standard, you can also verify if the requested PATCH (update) was successfully applied, in this example: Request: PUT /user/12404 { "name": "John"} Response: (status code) 304 - Not Modified """ options = dict(method='HEAD') def decorator(f): return route.decorate(f, rule, **options) return decorator @staticmethod def any(rule): """ From the Bottle Documentation: The non-standard ANY method works as a low priority fallback: Routes that listen to ANY will match requests regardless of their HTTP method but only if no other more specific route is defined. This is helpful for proxy-routes that redirect requests to more specific sub-applications. """ options = dict(method='ANY') def decorator(f): return route.decorate(f, rule, **options) return decorator class BottleView(object): """ Class based view implementation for bottle (following flask-classy architech) """ decorators = [] DEFAULT_ROUTES = ["get", "put", "post", "delete", "index", "options"] base_route = None route_prefix = None view_identifier = "view" @classmethod def register(cls, app, base_route=None, route_prefix=None): """ Register all the possible routes of the subclass :param app: bottle app instance :param base_route: prepend to the route rule (/base_route/<class_name OR route_prefix>) :param route_prefix: used when want to register custom rule, which is not class name """ if cls is BottleView: raise TypeError("cls must be a subclass of BottleView, not BottleView itself") cls._app = app cls.route_prefix = route_prefix or cls.route_prefix cls.base_route = base_route or cls.base_route # import ipdb; ipdb.set_trace() # get all the valid members of the class to register Endpoints routes = cls._get_interesting_members(BottleView) # initialize the class klass = cls() # Iterate through class members to register Endpoints for func_name, func in routes: # print "*"*50 method_args = inspect.getargspec(func)[0] # Get rule = cls._build_route_rule(func_name, *method_args) method = "GET" if func_name in cls.DEFAULT_ROUTES: if func_name == "index": method = "GET" else: method = func_name.upper() # create name for endpoint endpoint = "%s:%s" % (cls.__name__, func_name) callable_method = getattr(klass, func_name) for decorator in cls.decorators: callable_method = decorator(callable_method) try: # noinspection PyProtectedMember custom_rule = func._rule_cache except AttributeError: method_args = inspect.getargspec(func)[0] rule = cls._build_route_rule(func_name, *method_args) method = "GET" if func_name in cls.DEFAULT_ROUTES: if func_name == "index": method = "GET" else: method = func_name.upper() cls._app.route(callback=callable_method, method=method, path=rule, name=endpoint) else: custom_rule_list = list(custom_rule.values()) if _py3: custom_rule_list = list(custom_rule_list) for cached_rule in custom_rule_list[0]: rule, options = cached_rule try: method = options.pop("method") except KeyError: method = "GET" try: endpoint = options.pop("name") except KeyError: pass cls._app.route(callback=callable_method, path=rule, method=method, name=endpoint, **options) print(("%s : %s, Endpoint: %s" % (method, rule, endpoint))) @classmethod def _build_route_rule(cls, func_name, *method_args): klass_name = cls.__name__.lower() klass_name = (klass_name[:-len(cls.view_identifier)] if klass_name.endswith(cls.view_identifier) else klass_name) rule = klass_name if not (cls.base_route or cls.route_prefix): rule = klass_name elif not cls.base_route and cls.route_prefix: rule = cls.route_prefix elif cls.base_route and not cls.route_prefix: rule = "%s/%s" % (cls.base_route, klass_name) elif cls.base_route and cls.route_prefix: rule = "%s/%s" % (cls.base_route, cls.route_prefix) rule_parts = [rule] if func_name not in cls.DEFAULT_ROUTES: rule_parts.append(func_name.replace("_", "-").lower()) ignored_rule_args = ['self'] if hasattr(cls, 'base_args'): ignored_rule_args += cls.base_args for arg in method_args: if arg not in ignored_rule_args: rule_parts.append("<%s>" % arg) result = "/%s/" % join_paths(*rule_parts) result = re.sub(r'(/)\1+', r'\1', result) result = re.sub("/{2,}", "/", result) return result @classmethod def _get_interesting_members(cls, base_class): """Returns a list of methods that can be routed to""" base_members = dir(base_class) predicate = inspect.ismethod if _py2 else inspect.isfunction all_members = inspect.getmembers(cls, predicate=predicate) return [member for member in all_members if not member[0] in base_members and ((hasattr(member[1], "__self__") and not member[1].__self__ in cls.__class__.__mro__) if _py2 else True) and not member[0].startswith("_")] def join_paths(*path_pieces): """Join parts of a url path""" # Remove blank strings, and make sure everything is a string cleaned_parts = list(map(str, [_f for _f in path_pieces if _f])) if _py3: cleaned_parts = list(cleaned_parts) return "/".join(cleaned_parts)
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#!/usr/bin/python # # Logic for computing missing and duplicate files using Postgresql DB. # import os import fnmatch # from shutil import copy2 # from shutil import copyfile from dbutils import required as db MISSING_FROM_COMP_FOLDER = "missing_from_comp" MISSING_FROM_SRC_FOLDER = "missing_from_source" FILE_NAME_COLUMN = "file" FILE_EXTENSIONS_TO_SKIP = ['.ini', '.db', '.info', '.pdfcp '] def handleDuplicates(conn): # conn = db.getConnection(dbName) cur = conn.cursor try: # duplicates on the source location cur.execute("SELECT * from filehashes WHERE ") # duplicates on the comparison location cur.execute("SELECT * from filehashes ") finally: cur.close # conn.close db.returnConnection(conn) ####################### # Logic for identifying missing files in the source and destination/comparison locations. ####################### def handleMissing(dbName, sourceSchema, compSchema): conn = db.getConnection(dbName) cur = conn.cursor() try: # identify missing files from the comparison location command = "SELECT %s from %s.filehashes where hash in (select hash from %s.filehashes except select hash from %s.filehashes);" %(FILE_NAME_COLUMN, sourceSchema, sourceSchema, compSchema) print("Identifying all missing files in comparison location. Executing: " + command) cur.execute( command ) missingInComp = cur.fetchall() # print("Missing files in comparison location: %s" % missingInComp) # __collectMissingFiles__(list(missingInComp), MISSING_FROM_COMP_FOLDER) try: for missingFile in missingInComp: __collectMissingFiles__(missingFile[0], MISSING_FROM_COMP_FOLDER) except Exception as ce: print("There was a problem locating files on comparison location. The comparison location files may have changed/moved since the scan. ") print(ce) return # identify missing files from the source location command = "SELECT %s from %s.filehashes where hash in (select hash from %s.filehashes except select hash from %s.filehashes);" % (FILE_NAME_COLUMN, compSchema, compSchema, sourceSchema) print("Identifying all missing files in source location. Executing: " + command) cur.execute(command) missingInSource = cur.fetchall() # print("Missing files in source location: %s" % missingInSource) # __collectMissingFiles__(list(missingInSource), MISSING_FROM_SRC_FOLDER) try: for missingFile in missingInSource: __collectMissingFiles__(missingFile[0], MISSING_FROM_SRC_FOLDER) except Exception as se: print("There was a problem locating files on source location. The source location files may have changed/moved since the scan. ") print(se) except Exception as e: print("Unable to identify missing files! Cause: " + e) finally: cur.close() # conn.close db.returnConnection(conn) print("Done processing missing files. Please look at %s and %s folders for missing files." % (MISSING_FROM_SRC_FOLDER, MISSING_FROM_COMP_FOLDER)) ####################### # Utility for copying all of the missing files from the specified result-set into the specified folder. ####################### def __collectMissingFiles__( missingFile, folderName ): # for missingFile in missingFiles: # missingFile.endswith(tuple(set(['.ini', '.db']))) if not missingFile.endswith(tuple(FILE_EXTENSIONS_TO_SKIP)): dst = "./" + folderName + missingFile print("Attempting to copy missing file: " + missingFile + " to destination: " + dst) if not os.path.exists(os.path.dirname(dst)): os.makedirs(os.path.dirname(dst)) # TODO implement file type filtering to only get files we want and skip ones we don't care about like *.txt, *.ini, etc. # if not fnmatch.fnmatch(missingFile, '.*.ini'): # copyfile( missingFile, dst) # copy2(missingFile, dst) os.system('cp -v -p "' + missingFile + '" "' + dst + '"')
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- # Generated file, DO NOT EDIT # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------------------------- from msrest.serialization import Model class PagedGraphUsers(Model): """PagedGraphUsers. :param continuation_token: This will be non-null if there is another page of data. There will never be more than one continuation token returned by a request. :type continuation_token: list of str :param graph_users: The enumerable set of users found within a page. :type graph_users: list of :class:`GraphUser <graph.v4_1.models.GraphUser>` """ _attribute_map = { 'continuation_token': {'key': 'continuationToken', 'type': '[str]'}, 'graph_users': {'key': 'graphUsers', 'type': '[GraphUser]'} } def __init__(self, continuation_token=None, graph_users=None): super(PagedGraphUsers, self).__init__() self.continuation_token = continuation_token self.graph_users = graph_users
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"""Decoder portion of the model.""" import torch import torch.nn.functional as F from torch import nn def _build_base_decoder(): """Builds the base decoder shared by all three decoder types.""" return nn.Sequential(nn.Conv2d(in_channels=1280, out_channels=256, kernel_size=(3, 3), stride=1, padding=1), nn.BatchNorm2d(num_features=256), nn.ReLU()) class Decoders(nn.Module): """Module which contains all three decoders.""" def __init__(self, num_classes: int, enabled_tasks: (bool, bool, bool), output_size=(128, 256)): super().__init__() self._output_size = output_size self._num_classes = num_classes self._enabled_tasks = enabled_tasks self._base_semseg = _build_base_decoder() self._base_insseg = _build_base_decoder() self._base_depth = _build_base_decoder() kernel_size = (1, 1) self._semsegcls = nn.Conv2d(256, self._num_classes, kernel_size) self._inssegcls = nn.Conv2d(256, 2, kernel_size) self._depthcls = nn.Conv2d(256, 1, kernel_size) def set_output_size(self, size): self._output_size = size def forward(self, x): """Returns (sem seg, instance seg, depth).""" # x: [batch x 1280 x H/8 x W/8] sem_seg_enabled, inst_seg_enabled, depth_enabled = self._enabled_tasks if sem_seg_enabled: x1 = self._base_semseg(x) x1 = self._semsegcls(x1) x1 = F.interpolate(x1, size=self._output_size, mode='bilinear', align_corners=True) else: x1 = None if inst_seg_enabled: x2 = self._base_insseg(x) x2 = self._inssegcls(x2) x2 = F.interpolate(x2, size=self._output_size, mode='bilinear', align_corners=True) else: x2 = None if depth_enabled: x3 = self._base_depth(x) x3 = self._depthcls(x3) x3 = F.interpolate(x3, size=self._output_size, mode='bilinear', align_corners=True) else: x3 = None return x1, x2, x3 if __name__ == '__main__': # ### Shape test output_size = (123, 432) model = Decoders(num_classes=20, output_size=output_size) test = torch.zeros(size=(2, 1280, 256, 256)) result = model.forward(test) assert result[0].shape == (2, 20, *output_size), "output shape is {}".format(result[0].shape)
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class Queue: """ A class used to represent an Queue for for storing processes ... Attributes ---------- processList : list The list which would store the process currently in line for execution priority : str The type of process (Foreground,Background etc) SchedulingAlgo : object The object for corresponding scheduling algorithm to be used in this queue (FCFS,SJF etc) Methods ------- queue_enqueue(pList,process) Uses the scheduling algorithm object to insert process into process list queue_dequeue(pList,quantum) Uses the scheduling algorithm object to remove process from process list size() Returns the size of process list isEmpty() Checks whether the process list is empty or not front() Returns the first element in process list if its not empty. """ def __init__(self,type): """ Parameters ---------- type : str The type of process (Foreground,Background etc) """ self.processList = [] self.priority = type self.SchedulingAlgo = None def size(self): """Returs the total number of processes left for execution. Returns ------- int : The length of process list """ return len(self.processList) def isEmpty(self): """Checks whether all processes have been executed or not. Returns ------- bool : True if processList has 0 length , False otherwise. """ return self.size() == 0 def front(self): """Returns the first process in list Returns ------- object : The first process if process list is not empty else None """ return self.processList[0] if not self.isEmpty else None def queue_enqueue(self,process): """Uses the queue's scheduling algorithm enqueue method to insert the new process into the process list. Parameters ---------- process : object The Process class object defining the new process to insert. """ self.SchedulingAlgo.enqueue(self.processList,process) def queue_dequeue(self,quantum): """Takes the quantum time elapsed and removes processes from the process list using scheduling algorithim;s dequeue method. Parameters ---------- quantum : int The time elapsed Returns ------- removed : list A list of rocesses removed during the current cycle quantum : int Quantum time updated after being used by each process (Usually 0) """ removed,quantum = self.SchedulingAlgo.dequeue(self.processList,quantum) return removed,quantum
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import numpy as np import editdistance class Decoder(): def __init__(self, vocab): self.vocab_list = [char for char in vocab] def predict(self, batch_size, logits, y, lengths, y_lengths, n_show=5): decoded = self.decode(logits, lengths) cursor = 0 gt = [] n = min(n_show, logits.size(1)) samples = [] for b in range(batch_size): y_str = ''.join([self.vocab_list[ch] for ch in y[cursor: cursor + y_lengths[b]]]) gt.append(y_str) cursor += y_lengths[b] if b < n: samples.append([y_str, decoded[b]]) return decoded, gt, samples def decode(self, logits, seq_lens): raise NotImplementedError def wer(self, s1, s2): s1_words, s2_words = s1.split(), s2.split() distance = editdistance.eval(s1_words, s2_words) return distance / max(len(s1_words), len(s2_words)) def cer(self, s1, s2): s1, s2 = s1.replace(' ', ''), s2.replace(' ', '') distance = editdistance.eval(s1, s2) return distance / max(len(s1), len(s2)) def cer_batch(self, decoded, gt): return self.compare_batch(decoded, gt, self.cer) def wer_batch(self, decoded, gt): return self.compare_batch(decoded, gt, self.wer) def compare_batch(self, decoded, gt, func): assert len(decoded) == len(gt), f'batch size mismatch: {len(decoded)}!={len(gt)}' results = [] for i, batch in enumerate(decoded): for sentence in range(len(batch)): error = func(decoded[i][sentence], gt[i]) results.append(error) return np.mean(results)
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# MIT License # # Copyright (c) 2018-2019 Red Hat, Inc. # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. """ A book with our finest spells """ import shutil import subprocess from pathlib import Path from click.testing import CliRunner from packit.cli.packit_base import packit_base from packit.config import Config from packit.utils import cwd, run_command TESTS_DIR = Path(__file__).parent DATA_DIR = TESTS_DIR / "data" UPSTREAM = DATA_DIR / "upstream_git" UPSTREAM_WITH_MUTLIPLE_SOURCES = DATA_DIR / "upstream_git_with_multiple_sources" EMPTY_CHANGELOG = DATA_DIR / "empty_changelog" DISTGIT = DATA_DIR / "dist_git" UP_COCKPIT_OSTREE = DATA_DIR / "cockpit-ostree" UP_OSBUILD = DATA_DIR / "osbuild" UP_SNAPD = DATA_DIR / "snapd" TARBALL_NAME = "beerware-0.1.0.tar.gz" SOURCEGIT_UPSTREAM = DATA_DIR / "sourcegit" / "upstream" SOURCEGIT_SOURCEGIT = DATA_DIR / "sourcegit" / "source_git" DG_OGR = DATA_DIR / "dg-ogr" SPECFILE = DATA_DIR / "upstream_git/beer.spec" UPSTREAM_SPEC_NOT_IN_ROOT = DATA_DIR / "spec_not_in_root/upstream" def git_set_user_email(directory): subprocess.check_call( ["git", "config", "user.email", "test@example.com"], cwd=directory ) subprocess.check_call( ["git", "config", "user.name", "Packit Test Suite"], cwd=directory ) def get_test_config(): conf = Config() conf._pagure_user_token = "test" conf._github_token = "test" return conf def git_add_and_commit(directory, message): subprocess.check_call(["git", "add", "."], cwd=directory) subprocess.check_call(["git", "commit", "-m", message], cwd=directory) def initiate_git_repo( directory, tag=None, upstream_remote="https://lol.wat", push=False, copy_from: str = None, remotes=None, ): """ Initiate a git repo for testing. :param directory: path to the git repo :param tag: if set, tag the latest commit with this tag :param upstream_remote: name of the origin - upstream remote (not used when remotes are set) :param remotes: provide list of tuples (name, remote_url) :param push: push to the remote? :param copy_from: source tree to copy to the newly created git repo """ if remotes is None: remotes = [("origin", upstream_remote)] if copy_from: shutil.copytree(copy_from, directory) subprocess.check_call(["git", "init", "."], cwd=directory) Path(directory).joinpath("README").write_text("Best upstream project ever!") git_set_user_email(directory) subprocess.check_call(["git", "add", "."], cwd=directory) subprocess.check_call(["git", "commit", "-m", "initial commit"], cwd=directory) if tag: subprocess.check_call( ["git", "tag", "-a", "-m", f"tag {tag}, tests", tag], cwd=directory ) for name, url in remotes: subprocess.check_call(["git", "remote", "add", name, url], cwd=directory) if push: subprocess.check_call(["git", "fetch", "origin"], cwd=directory) # tox strips some env vars so your user gitconfig is not picked up # hence we need to be very explicit with git commands here subprocess.check_call( ["git", "push", "--tags", "-u", "origin", "master:master"], cwd=directory ) def prepare_dist_git_repo(directory, push=True): subprocess.check_call(["git", "branch", "f30"], cwd=directory) if push: subprocess.check_call(["git", "push", "-u", "origin", "f30:f30"], cwd=directory) def call_packit(fnc=None, parameters=None, envs=None, working_dir=None): working_dir = working_dir or "." fnc = fnc or packit_base runner = CliRunner() envs = envs or {} parameters = parameters or [] # catch exceptions enables debugger with cwd(working_dir): return runner.invoke(fnc, args=parameters, env=envs, catch_exceptions=False) def build_srpm(path: Path): run_command(["rpmbuild", "--rebuild", str(path)]) def can_a_module_be_imported(module_name): """ can a module be imported? """ try: __import__(module_name) return True except ImportError: return False
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from django.db import models from accounts.models import Account from store.models import Product, Variation # Create your models here. class Payment(models.Model): user = models.ForeignKey(Account, on_delete=models.CASCADE) payment_id = models.CharField(max_length=100) payment_method = models.CharField(max_length=100) amount_paid = models.CharField(max_length=100) status = models.CharField(max_length=100) created_at = models.DateTimeField(auto_now_add=True) def __str__(self): return self.payment_id class Order(models.Model): STATUS = ( ('New', 'New'), ('Accepted', 'Accepted'), ('Completed', 'Completed'), ('Cancelled', 'Cancelled'), ) user = models.ForeignKey(Account, on_delete=models.SET_NULL, null=True) payment = models.ForeignKey(Payment, on_delete=models.SET_NULL, blank=True, null=True) order_number = models.CharField(max_length=20) first_name = models.CharField(max_length=50) last_name= models.CharField(max_length=50) phone = models.CharField(max_length=15) email = models.EmailField(max_length=50) address_line_1 = models.CharField(max_length=50) address_line_2 = models.CharField(max_length=50, blank=True) country = models.CharField(max_length=50) state = models.CharField(max_length=50) city = models.CharField(max_length=50) order_note = models.CharField(max_length=100, blank=True) order_total = models.FloatField() tax = models.FloatField() status = models.CharField(max_length=10, choices=STATUS, default='New') ip = models.CharField(blank=True, max_length=20) is_ordered = models.BooleanField(default=False) created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now=True) def full_name(self): return f'{self.first_name} {self.last_name}' def full_address(self): return f'{self.address_line_1} {self.address_line_2}' def __str__(self): return self.first_name class OrderProduct(models.Model): order = models.ForeignKey(Order, on_delete=models.CASCADE) payment = models.ForeignKey(Payment, on_delete=models.SET_NULL, blank=True, null=True) user = models.ForeignKey(Account, on_delete=models.CASCADE) product = models.ForeignKey(Product, on_delete=models.CASCADE) variations = models.ManyToManyField(Variation, blank=True) quantity = models.IntegerField() product_price = models.FloatField() ordered = models.BooleanField(default=False) created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now=True) def __str__(self): return self.product.product_name
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from __future__ import absolute_import import os from celery import Celery from django.conf import settings # set the default Django settings module for the 'celery' program. os.environ.setdefault("DJANGO_SETTINGS_MODULE", "Clout9.settings.production") app = Celery('Clout9') # Using a string here means the worker will not have to # pickle the object when using Windows. app.config_from_object('django.conf:settings') # app.autodiscover_tasks(lambda: settings.INSTALLED_APPS) @app.task(bind=True) def debug_task(self): print('Request: {0!r}'.format(self.request))
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# blog/asgi.py import os import django os.environ.setdefault("DJANGO_SETTINGS_MODULE", "blog.settings") from django.conf import settings django.setup() from django.core.asgi import get_asgi_application from channels.security.websocket import OriginValidator from channels.auth import AuthMiddlewareStack from channels.routing import ProtocolTypeRouter, URLRouter from django.urls import re_path from app.website.consumers import ExampleConsumer application = ProtocolTypeRouter( { # Django's ASGI application to handle traditional HTTP requests "http": get_asgi_application(), # WebSocket handler "websocket": OriginValidator(AuthMiddlewareStack( URLRouter( [ re_path(r"^ws/example/$", ExampleConsumer.as_asgi()), ] ) ), settings.ALLOWED_HOSTS) } )
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valor = 0 num = [[],[]] for c in range (0,7): valor = int(input(f'Digite o {c+1}° valor:')) if valor % 2 == 0: num[0].append(valor) else: num[1].append(valor) print('-='*30) print(f'Os numeros pares foram {num[0]}\nOs numeros ímpares foram {num[1]}.')
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# -*- coding: utf-8 -*- # # Configuration file for the Sphinx documentation builder. # # This file does only contain a selection of the most common options. For a # full list see the documentation: # http://www.sphinx-doc.org/en/master/config # -- Path setup -------------------------------------------------------------- # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # # import os # import sys # sys.path.insert(0, os.path.abspath('.')) # -- Project information ----------------------------------------------------- project = 'dnsprovejs' copyright = '2018, Makoto Inoue' author = 'Makoto Inoue' # The short X.Y version version = '' # The full version, including alpha/beta/rc tags release = '' # -- General configuration --------------------------------------------------- # If your documentation needs a minimal Sphinx version, state it here. # # needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = ['sphinx_js', 'sphinx.ext.autodoc'] root_for_relative_js_paths = '../lib' js_source_path = ['../lib', '../lib/oracle', '../lib/dns'] primary_domain = 'js' # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: # source_suffix = ['.rst', '.md'] # The master toctree document. master_doc = 'index' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set "language" from the command line for these cases. language = None # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This pattern also affects html_static_path and html_extra_path. exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] # The name of the Pygments (syntax highlighting) style to use. pygments_style = None # -- Options for HTML output ------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # # html_theme = 'alabaster' html_theme = 'sphinx_rtd_theme' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # # html_theme_options = {} # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # Custom sidebar templates, must be a dictionary that maps document names # to template names. # # The default sidebars (for documents that don't match any pattern) are # defined by theme itself. Builtin themes are using these templates by # default: ``['localtoc.html', 'relations.html', 'sourcelink.html', # 'searchbox.html']``. # # html_sidebars = {} # -- Options for HTMLHelp output --------------------------------------------- # Output file base name for HTML help builder. htmlhelp_basename = 'dnsprovejsdoc' # -- Options for LaTeX output ------------------------------------------------ latex_elements = { # The paper size ('letterpaper' or 'a4paper'). # # 'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). # # 'pointsize': '10pt', # Additional stuff for the LaTeX preamble. # # 'preamble': '', # Latex figure (float) alignment # # 'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'dnsprovejs.tex', 'dnsprovejs Documentation', 'Makoto Inoue', 'manual'), ] # -- Options for manual page output ------------------------------------------ # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'dnsprovejs', 'dnsprovejs Documentation', [author], 1) ] # -- Options for Texinfo output ---------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'dnsprovejs', 'dnsprovejs Documentation', author, 'dnsprovejs', 'One line description of project.', 'Miscellaneous'), ] # -- Options for Epub output ------------------------------------------------- # Bibliographic Dublin Core info. epub_title = project # The unique identifier of the text. This can be a ISBN number # or the project homepage. # # epub_identifier = '' # A unique identification for the text. # # epub_uid = '' # A list of files that should not be packed into the epub file. epub_exclude_files = ['search.html']
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import os import time from membound_cases import memory_bound_cases_list from utils import (arch_name, datatime_with_format, dtype2str, dump2json, geometric_mean, md_table_header, scaled_repeat_times, size2str) import taichi as ti class MemoryBound: suite_name = 'memorybound' supported_archs = [ti.x64, ti.cuda] test_cases = memory_bound_cases_list test_dtype_list = [ti.i32, ti.i64, ti.f32, ti.f64] test_dsize_list = [ (4**i) * 1024 # kibibytes(KiB) = 1024 for i in range(1, 10) # [4KB,16KB...256MB] ] basic_repeat_times = 10 evaluator = [geometric_mean] def __init__(self, arch): self._arch = arch self._cases_impl = [] for case in self.test_cases: for dtype in self.test_dtype_list: impl = CaseImpl(case, arch, dtype, self.test_dsize_list, self.evaluator) self._cases_impl.append(impl) def run(self): for case in self._cases_impl: case.run() def save_as_json(self, arch_dir='./'): #folder of suite suite_path = os.path.join(arch_dir, self.suite_name) os.makedirs(suite_path) #json files self._save_suite_info_as_json(suite_path) self._save_cases_info_as_json(suite_path) def save_as_markdown(self, arch_dir='./'): current_time = datatime_with_format() commit_hash = ti.core.get_commit_hash() #[:8] file_name = f'{self.suite_name}.md' file_path = os.path.join(arch_dir, file_name) with open(file_path, 'w') as f: lines = [ f'commit_hash: {commit_hash}\n', f'datatime: {current_time}\n' ] lines += self._get_markdown_lines() for line in lines: print(line, file=f) def _save_suite_info_as_json(self, suite_path='./'): info_dict = { 'cases': [func.__name__ for func in self.test_cases], 'dtype': [dtype2str(dtype) for dtype in self.test_dtype_list], 'dsize': [size for size in self.test_dsize_list], 'repeat': [ scaled_repeat_times(self._arch, size, self.basic_repeat_times) for size in self.test_dsize_list ], 'evaluator': [func.__name__ for func in self.evaluator] } info_path = os.path.join(suite_path, '_info.json') with open(info_path, 'w') as f: print(dump2json(info_dict), file=f) def _save_cases_info_as_json(self, suite_path='./'): for case in self.test_cases: #for case [fill,saxpy,reduction] results_dict = {} for impl in self._cases_impl: #find [ti.i32, ti.i64, ti.f32, ti.f64] if impl._name != case.__name__: continue result_name = dtype2str(impl._test_dtype) results_dict[result_name] = impl.get_results_dict() case_path = os.path.join(suite_path, (case.__name__ + '.json')) with open(case_path, 'w') as f: case_str = dump2json(results_dict) print(case_str, file=f) def _get_markdown_lines(self): lines = [] lines += md_table_header(self.suite_name, self._arch, self.test_dsize_list, self.basic_repeat_times, self.evaluator) result_header = '|kernel elapsed time(ms)' + ''.join( '|' for i in range( len(self.test_dsize_list) + len(MemoryBound.evaluator))) lines += [result_header] for case in self._cases_impl: lines += case.get_markdown_lines() lines.append('') return lines class CaseImpl: def __init__(self, func, arch, test_dtype, test_dsize_list, evaluator): self._func = func self._name = func.__name__ self._arch = arch self._test_dtype = test_dtype self._test_dsize_list = test_dsize_list self._min_time_in_us = [] #test results self._evaluator = evaluator def run(self): ti.init(kernel_profiler=True, arch=self._arch) print("TestCase[%s.%s.%s]" % (self._func.__name__, arch_name( self._arch), dtype2str(self._test_dtype))) for test_dsize in self._test_dsize_list: print("test_dsize = %s" % (size2str(test_dsize))) self._min_time_in_us.append( self._func(self._arch, self._test_dtype, test_dsize, MemoryBound.basic_repeat_times)) time.sleep(0.2) ti.reset() def get_markdown_lines(self): string = '|' + self._name + '.' + dtype2str(self._test_dtype) + '|' string += ''.join( str(round(time, 4)) + '|' for time in self._min_time_in_us) string += ''.join( str(round(item(self._min_time_in_us), 4)) + '|' for item in self._evaluator) return [string] def get_results_dict(self): results_dict = {} for i in range(len(self._test_dsize_list)): dsize = self._test_dsize_list[i] repeat = scaled_repeat_times(self._arch, dsize, MemoryBound.basic_repeat_times) elapsed_time = self._min_time_in_us[i] item_name = size2str(dsize).replace('.0', '') item_dict = { 'dsize_byte': dsize, 'repeat': repeat, 'elapsed_time_ms': elapsed_time } results_dict[item_name] = item_dict return results_dict
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from flask_security.utils import hash_password from flask_smorest import Blueprint, abort from ..models.user import User from ..schemas.paging import PageInSchema, paginate from ..schemas.user import UserPageOutSchema, UserSchema from .methodviews import ProtectedMethodView blueprint = Blueprint('users', 'user') @blueprint.route('', endpoint='list') class UserListAPI(ProtectedMethodView): @blueprint.arguments(PageInSchema(), location='headers') @blueprint.response(UserPageOutSchema) def get(self, pagination): """List users""" return paginate(User.select(), pagination) @blueprint.arguments(UserSchema) @blueprint.response(UserSchema) def post(self, args): """Create user""" user = User(**args) user.password = hash_password(user.password) user.save() return user @blueprint.route('/<user_id>', endpoint='detail') class UserAPI(ProtectedMethodView): @blueprint.response(UserSchema) def get(self, user_id): """Get user details""" try: user = User.get(id=user_id) except User.DoesNotExist: abort(404, message='User not found') return user @blueprint.arguments(UserSchema(partial=True)) @blueprint.response(UserSchema) def patch(self, args, user_id): try: user = User.get(id=user_id) except User.DoesNotExist: abort(404, message='User not found') for field in args: setattr(user, field, args[field]) if 'password' in args: user.password = hash_password(user.password) user.save() return user @blueprint.response(UserSchema) def delete(self, user_id): try: user = User.get(id=user_id) except User.DoesNotExist: abort(404, message='User not found') user.delete_instance() return user
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# -*- coding: utf-8 -*- """ Created on Fri Dec 22 18:44:02 2017 @author: Tirthajyoti Sarkar Simple selection sort with counter for total number of operations (finding minimum and swapping) Accepts user input on minimum and maximum bound of the array and the size of the array. """ import random def find_min(array): n=len(array) r = array[0] count=0 for i in range(1,n): count+=1 if r>array[i]: r=array[i] return(r,count) def selection_sort(array): n=len(array) num_op=0 # Iterate over the length of the array, pushing smaller values to the left for i in range(n): # Scan the array from i-th element (where the iterator is currently) to the end for minimum m,c_min=find_min(array[i:n]) # IMPORTANT: Get the index of the minimum element w.r.t. to the main array m_index=array[i:n].index(m)+i # If the first element of the unsorted portion i.e. i-th element> minimum, then SWAP if (array[i]>m): # Print statement for examining minimum and its index, Troubleshooting #print("Minimum found {} at position {}. Swapping positions {} and {}".format(m,m_index,i,m_index)) temp=array[i] array[i]=m array[m_index]=temp num_op+=(c_min+1) print(array) else: pass return (array,num_op) # User inputs for generating the random arrays mini = int(input("Enter the minimum bound:")) maxi = int(input("Enter the maximum bound:")) num = int(input("Enter the size:")) # Create random array based on user-specified minimum/maximum bounds and number of elements a= [] for i in range(num): a.append(random.randint(mini,maxi)) print("\nInitial array:",a) # Get the sorted array back along with the count of # of operations it took to sort sorted_array,n_op=selection_sort(a) print("Sorted array: {}\nTook {} operations".format(sorted_array,n_op))
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############################################################################### # # Tests for XlsxWriter. # # SPDX-License-Identifier: BSD-2-Clause # Copyright (c), 2013-2022, John McNamara, jmcnamara@cpan.org # from ..excel_comparison_test import ExcelComparisonTest from ...workbook import Workbook class TestCompareXLSXFiles(ExcelComparisonTest): """ Test file created by XlsxWriter against a file created by Excel. """ def setUp(self): self.set_filename('hyperlink23.xlsx') def test_create_file(self): """Test the creation of a simple XlsxWriter file with hyperlinks.""" workbook = Workbook(self.got_filename) # Turn off default URL format for testing. workbook.default_url_format = None worksheet = workbook.add_worksheet() worksheet.write_url('A1', 'https://en.wikipedia.org/wiki/Microsoft_Excel#Data_storage_and_communication', None, 'Display text') workbook.close() self.assertExcelEqual()
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import boto3 import pickle import logging from datetime import date from pyspark.sql.functions import udf from pyspark.sql.types import ArrayType, StringType from generate_common_words import dump_pickle import config as conf ''' Assign Top 500 Stackoverflow tags to job postings ''' # ===== Logger Configs ===== TS = date.today().strftime('%y%m%d') logger = logging.getLogger('jd_logger') logger.setLevel(logging.INFO) fh = logging.FileHandler(conf.LOG_DIR + TS + '_batch_process.log') fh.setLevel(logging.INFO) logger.addHandler(fh) def read_pickle(bucket, key): s3 = boto3.resource('s3') pickled = pickle.loads(s3.Bucket(bucket)\ .Object(key)\ .get()['Body']\ .read()) return pickled def filter_common_words(tokens, word_list): """ Filter out words that appear in many of the documents Args: tokens: a list of word lemmas word_list: a list of common words Returns: a set of word lemmas with the common words removed """ return list(set([word for word in tokens if word not in word_list])) def select_tag_words(tokens, tag_list): """ Match Stackoverflow tags to word lemmas Args: tokens: a list of word lemmas tag_list: a list of tags Returns: a list of tags for each job posting """ return [tag for tag in tag_list if tag in tokens] def assign_tags(jd): """ Assign Stackoverflow tags and construct a set of keywords Args: jd: cleaned job posting dataframe Returns: a dataframe with columns containing keywords and tags """ logger.info('[STARTING]: Assigning Tags') common_words = read_pickle(conf.PARQUET_BUCKET, conf.COMMON_WORDS_PATH) stack_tags = read_pickle(conf.PARQUET_BUCKET, conf.TAG_PATH) logger.info('[PROCESSING]: Removing Common Words') cw_remover = udf(lambda body: filter_common_words(body, common_words), ArrayType(StringType())) jd_keywords = jd.withColumn('keywords', cw_remover('stemmed')) logger.info('[PROCESSING]: Getting Tags') tagger = udf(lambda body: select_tag_words(body, stack_tags), ArrayType(StringType())) jd_tags = jd_keywords.withColumn('tags', tagger('keywords')) logger.info('[Finished]: Assigning Tags') return jd_tags
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""" WSGI config for simplerest project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/1.10/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault("DJANGO_SETTINGS_MODULE", "simplerest.settings") application = get_wsgi_application()
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import json import os from mako.template import Template from models.pomodoro_model import PomodoroModel from datetime import datetime class ExportPomsResource: def on_get(self, req, resp): """Handles GET requests""" resp.content_type = 'text/html' dir_path = os.path.dirname(os.path.realpath(__file__)) user_login_template = Template( filename=dir_path + '/export_poms_view.mako') resp.body = user_login_template.render() def on_post(self, req, resp): """Handles POST requests""" start_date = req.get_param('start_date') end_date = req.get_param('end_date') # Query poms within start and end dates poms = req.context['session'].query( PomodoroModel).filter(PomodoroModel.created <= end_date). \ filter(PomodoroModel.created >= start_date).filter_by( user_id=req.context['user'].id).order_by( PomodoroModel.created, PomodoroModel.start_time).all() data = {'poms': []} for row in poms: pom = { 'created': datetime.strftime(row.created, '%Y-%m-%d'), 'title': row.task, 'start_time': row.start_time.strftime('%I:%M%p'), 'end_time': row.end_time.strftime('%I:%M%p'), 'distractions': row.distractions, 'pom_success': row.pom_success, 'review': row.review, 'flags': [] } for flag in row.flags: pom['flags'].append(flag.flag_type) data['poms'].append(pom) filename = str(start_date) + '-' + str( end_date) + '_Arin_Pom_Sheets.json' resp.body = json.dumps(data, indent=2) resp.downloadable_as = filename resp.content_type = 'application/octet-stream'
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import csv import json def read_data_file(filename): all_records = [] with open(filename, mode='r') as csv_file: csv_reader = csv.reader(csv_file) row_count = 0 for row in csv_reader: all_records.append(row) return all_records def parse_play_fields(play_fields): plays = [] for p in play_fields: temp = {} temp["event_count"] = int(p[0]) temp["inning_number"] = int(p[1]) temp["home_field_indicator"] = int(p[2]) temp["player_code"] = p[3] temp["count_at_action"] = p[4] temp["all_pitches"] = p[5] temp["play_events"] = p[6] plays.append(temp) return plays def parse_sub_fields(sub_fields): subs = [] for s in sub_fields: temp = {} temp["event_count"] = int(s[0]) temp["player_code"] = s[1] temp["name"] = s[2] temp["home_field_indicator"] = int(s[3]) temp["batting_order"] = int(s[4]) temp["field_position"] = int(s[5]) subs.append(temp) return subs def parse_info_fields(info_fields): infos = [] for i in info_fields: temp = {} temp[i[0]] = i[1] infos.append(temp) return infos def parse_start_fields(start_fields): starts = [] for s in start_fields: temp = {} temp["player_code"] = s[0] temp["name"] = s[1] temp["home_field_indicator"] = int(s[2]) temp["batting_order"] = int(s[3]) temp["field_position"] = int(s[4]) starts.append(temp) return starts def parse_data_fields(data_fields): datas = [] for d in data_fields: temp = {} temp["type"] = d[0] temp["player_code"] = d[1] temp["earned_runs"] = int(d[2]) datas.append(temp) return datas def get_fields(records): id = "" version = "" play = [] info = [] start = [] data = [] sub = [] event_count = 0 for r in records: if r[0] == "play": r[0] = event_count event_count += 1 play.append(r) elif r[0] == "info": info.append(r[1:]) elif r[0] == "start": start.append(r[1:]) elif r[0] == "data": data.append(r[1:]) elif r[0] == "sub": r[0] = event_count event_count += 1 sub.append(r) elif r[0] == "com": continue # This one we should ignore elif r[0].endswith("adj"): continue # This one we should ignore elif r[0] == "id": id = r[1] elif r[0] == "version": version = r[1] else: print("ERROR") print(r) return id, version, play, info, start, data, sub def get_game(game_records): id, version, plays, infos, starts, datas, subs = get_fields(game_records) play_list = parse_play_fields(plays) info_list = parse_info_fields(infos) start_list = parse_start_fields(starts) data_list = parse_data_fields(datas) sub_list = parse_sub_fields(subs) game = {} game["id"] = id game["version"] = version game["plays"] = play_list game["info"] = info_list game["start"] = start_list game["data"] = data_list game["subs"] = sub_list return game def get_all_games(all_game_records): all_games = [] for g in all_game_records: all_games.append(get_game(g)) return json.dumps(all_games) # path = "./../storage/ANA201808100.in" # game_records = read_data_file(path) # game = get_game(game_records) # # out = json.loads(game) # print(out["id"])
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from rubicon.java.android_events import Handler, PythonRunnable from rubicon.java.jni import java from travertino.size import at_least from ..libs.android import R__color from ..libs.android.graphics import BitmapFactory, Rect from ..libs.android.view import Gravity, OnClickListener, View__MeasureSpec from ..libs.android.widget import ( ImageView, ImageView__ScaleType, LinearLayout, LinearLayout__LayoutParams, RelativeLayout, RelativeLayout__LayoutParams, ScrollView, TextView ) from ..libs.androidx.swiperefreshlayout import ( SwipeRefreshLayout, SwipeRefreshLayout__OnRefreshListener ) from .base import Widget class DetailedListOnClickListener(OnClickListener): def __init__(self, impl, row_number): super().__init__() self._impl = impl self._row_number = row_number def onClick(self, _view): row = self._impl.interface.data[self._row_number] self._impl._selection = row if self._impl.interface.on_select: self._impl.interface.on_select(self._impl.interface, row=self._impl.interface.data[self._row_number]) class OnRefreshListener(SwipeRefreshLayout__OnRefreshListener): def __init__(self, interface): super().__init__() self._interface = interface def onRefresh(self): if self._interface.on_refresh: self._interface.on_refresh(self._interface) class DetailedList(Widget): ROW_HEIGHT = 250 _swipe_refresh_layout = None _scroll_view = None _dismissable_container = None _selection = None def create(self): # DetailedList is not a specific widget on Android, so we build it out # of a few pieces. if self.native is None: self.native = LinearLayout(self._native_activity) self.native.setOrientation(LinearLayout.VERTICAL) else: # If create() is called a second time, clear the widget and regenerate it. self.native.removeAllViews() scroll_view = ScrollView(self._native_activity) self._scroll_view = ScrollView( __jni__=java.NewGlobalRef(scroll_view)) scroll_view_layout_params = LinearLayout__LayoutParams( LinearLayout__LayoutParams.MATCH_PARENT, LinearLayout__LayoutParams.MATCH_PARENT ) scroll_view_layout_params.gravity = Gravity.TOP swipe_refresh_wrapper = SwipeRefreshLayout(self._native_activity) swipe_refresh_wrapper.setOnRefreshListener(OnRefreshListener(self.interface)) self._swipe_refresh_layout = SwipeRefreshLayout( __jni__=java.NewGlobalRef(swipe_refresh_wrapper)) swipe_refresh_wrapper.addView(scroll_view) self.native.addView(swipe_refresh_wrapper, scroll_view_layout_params) dismissable_container = LinearLayout(self._native_activity) self._dismissable_container = LinearLayout( __jni__=java.NewGlobalRef(dismissable_container) ) dismissable_container.setOrientation(LinearLayout.VERTICAL) dismissable_container_params = LinearLayout__LayoutParams( LinearLayout__LayoutParams.MATCH_PARENT, LinearLayout__LayoutParams.MATCH_PARENT ) scroll_view.addView( dismissable_container, dismissable_container_params ) for i in range(len((self.interface.data or []))): self._make_row(dismissable_container, i) def _make_row(self, container, i): # Create the foreground. row_foreground = RelativeLayout(self._native_activity) container.addView(row_foreground) # Add user-provided icon to layout. icon_image_view = ImageView(self._native_activity) icon = self.interface.data[i].icon if icon is not None: icon.bind(self.interface.factory) bitmap = BitmapFactory.decodeFile(str(icon._impl.path)) icon_image_view.setImageBitmap(bitmap) icon_layout_params = RelativeLayout__LayoutParams( RelativeLayout__LayoutParams.WRAP_CONTENT, RelativeLayout__LayoutParams.WRAP_CONTENT) icon_layout_params.width = 150 icon_layout_params.setMargins(25, 0, 25, 0) icon_layout_params.height = self.ROW_HEIGHT icon_image_view.setScaleType(ImageView__ScaleType.FIT_CENTER) row_foreground.addView(icon_image_view, icon_layout_params) # Create layout to show top_text and bottom_text. text_container = LinearLayout(self._native_activity) text_container_params = RelativeLayout__LayoutParams( RelativeLayout__LayoutParams.WRAP_CONTENT, RelativeLayout__LayoutParams.WRAP_CONTENT) text_container_params.height = self.ROW_HEIGHT text_container_params.setMargins(25 + 25 + 150, 0, 0, 0) row_foreground.addView(text_container, text_container_params) text_container.setOrientation(LinearLayout.VERTICAL) text_container.setWeightSum(2.0) # Create top & bottom text; add them to layout. top_text = TextView(self._native_activity) top_text.setText(str(getattr(self.interface.data[i], 'title', ''))) top_text.setTextSize(20.0) top_text.setTextColor(self._native_activity.getResources().getColor(R__color.black)) bottom_text = TextView(self._native_activity) bottom_text.setTextColor(self._native_activity.getResources().getColor(R__color.black)) bottom_text.setText(str(getattr(self.interface.data[i], 'subtitle', ''))) bottom_text.setTextSize(16.0) top_text_params = LinearLayout__LayoutParams( RelativeLayout__LayoutParams.WRAP_CONTENT, RelativeLayout__LayoutParams.MATCH_PARENT) top_text_params.weight = 1.0 top_text.setGravity(Gravity.BOTTOM) text_container.addView(top_text, top_text_params) bottom_text_params = LinearLayout__LayoutParams( RelativeLayout__LayoutParams.WRAP_CONTENT, RelativeLayout__LayoutParams.MATCH_PARENT) bottom_text_params.weight = 1.0 bottom_text.setGravity(Gravity.TOP) bottom_text_params.gravity = Gravity.TOP text_container.addView(bottom_text, bottom_text_params) # Apply an onclick listener so that clicking anywhere on the row triggers Toga's on_select(row). row_foreground.setOnClickListener(DetailedListOnClickListener(self, i)) def change_source(self, source): # If the source changes, re-build the widget. self.create() def set_on_refresh(self, handler): # No special handling needed. pass def after_on_refresh(self): if self._swipe_refresh_layout: self._swipe_refresh_layout.setRefreshing(False) def insert(self, index, item): # If the data changes, re-build the widget. Brutally effective. self.create() def change(self, item): # If the data changes, re-build the widget. Brutally effective. self.create() def remove(self, index, item): # If the data changes, re-build the widget. Brutally effective. self.create() def clear(self): # If the data changes, re-build the widget. Brutally effective. self.create() def get_selection(self): return self._selection def set_on_select(self, handler): # No special handling required. pass def set_on_delete(self, handler): # This widget currently does not implement event handlers for data change. self.interface.factory.not_implemented("DetailedList.set_on_delete()") def scroll_to_row(self, row): def scroll(): row_obj = self._dismissable_container.getChildAt(row) hit_rect = Rect() row_obj.getHitRect(hit_rect) self._scroll_view.requestChildRectangleOnScreen( self._dismissable_container, hit_rect, False, ) Handler().post(PythonRunnable(scroll)) def rehint(self): # Android can crash when rendering some widgets until they have their layout params set. Guard for that case. if self.native.getLayoutParams() is None: return self.native.measure( View__MeasureSpec.UNSPECIFIED, View__MeasureSpec.UNSPECIFIED, ) self.interface.intrinsic.width = at_least(self.native.getMeasuredWidth()) self.interface.intrinsic.height = self.native.getMeasuredHeight()
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# -*- coding: utf-8 -*- # # This file is part of Invenio. # # Copyright (C) 2021 Graz University of Technology. # # Invenio-Records-Marc21 is free software; you can redistribute it and/or # modify it under the terms of the MIT License; see LICENSE file for more # details. """Permissions for Invenio Marc21 Records.""" from invenio_records_permissions.generators import AnyUser, SystemProcess from invenio_records_permissions.policies.records import RecordPermissionPolicy class Marc21RecordPermissionPolicy(RecordPermissionPolicy): """Access control configuration for records. Note that even if the array is empty, the invenio_access Permission class always adds the ``superuser-access``, so admins will always be allowed. - Create action given to everyone for now. - Read access given to everyone if public record and given to owners always. (inherited) - Update access given to record owners. (inherited) - Delete access given to admins only. (inherited) """ # TODO: Change all below when permissions settled can_create = [AnyUser()] can_update_files = [AnyUser()] can_publish = [AnyUser()] can_read = [AnyUser()] can_update = [AnyUser()] can_new_version = [AnyUser()] can_edit = [AnyUser()] can_lift_embargo = [AnyUser()] # Draft permissions can_read_draft = [AnyUser()] can_delete_draft = [AnyUser()] can_update_draft = [AnyUser()] can_search_drafts = [AnyUser()] can_draft_read_files = [AnyUser()] can_draft_create_files = [AnyUser(), SystemProcess()] can_draft_update_files = [AnyUser()] can_draft_delete_files = [AnyUser()] # Files permissions can_read_files = [AnyUser()] can_create_files = [AnyUser(), SystemProcess()] can_update_files = [AnyUser()] can_delete_files = [AnyUser()]
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#!/usr/bin/env python import os import sys if __name__ == "__main__": os.environ.setdefault("DJANGO_SETTINGS_MODULE", "animalRescue.settings") try: from django.core.management import execute_from_command_line except ImportError: # The above import may fail for some other reason. Ensure that the # issue is really that Django is missing to avoid masking other # exceptions on Python 2. try: import django except ImportError: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) raise execute_from_command_line(sys.argv)
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import http.server import threading import testPackage class MyHTTPRequestHandler(http.server.BaseHTTPRequestHandler): def _set_headers(self): self.send_response(200) self.send_header('Content-type', 'text/html') self.end_headers() def do_GET(self): self._set_headers() self.wfile.write(b"<html><head><title>My Title</title></head>") self.wfile.write(bytes("<body><p>You accessed path: %s</p>" % self.path,"utf-8")) self.wfile.write(bytes("Light Value: %d" % testPackage.LIGHT_VALUE,"utf-8")) self.wfile.write(b"</body></html>") print("Sent light value") def do_POST(self): testPackage.increase_light() self._set_headers() self.wfile.write(b"Success") print("Increasing Light value") class serverThread (threading.Thread) : def __init__(self, threadID): threading.Thread.__init__(self) self.threadID = threadID def run(self): print ("Starting serverThread: %d" % self.threadID) httpd = http.server.HTTPServer(server_address, request_handler) httpd.serve_forever() print ("Exiting thread") port = 30000 server_address = ('',port) request_handler = MyHTTPRequestHandler thread_server = serverThread(1) thread_server.start() testPackage.polling_forever() print('After serve_forever()')
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import sys from datetime import datetime from app import filters from app.misc.execute import run def main(args: list[str]): from app.handlers import dp # Сохраняем нынешнее время для подсчёта времени безотказной работы dp.bot['start_time'] = datetime.now() dp['args'] = args run(dp) if __name__ == '__main__': filters.setup() main(sys.argv[1:])
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import cv2 import threading class RecordingThread (threading.Thread): def __init__(self, name, camera): threading.Thread.__init__(self) self.name = name self.isRunning = True self.cap = camera fourcc = cv2.VideoWriter_fourcc(*'MJPG') self.out = cv2.VideoWriter('./static/video.avi',fourcc, 20.0, (640,480)) def run(self): while self.isRunning: ret, frame = self.cap.read() if ret: self.out.write(frame) self.out.release() def stop(self): self.isRunning = False def __del__(self): self.out.release() class VideoCamera(object): def __init__(self): # Open a camera self.cap = cv2.VideoCapture(2) # Initialize video recording environment self.is_record = False self.out = None # Thread for recording self.recordingThread = None def __del__(self): self.cap.release() def get_frame(self): ret, frame = self.cap.read() if ret: ret, jpeg = cv2.imencode('.jpg', frame) # Record video # if self.is_record: # if self.out == None: # fourcc = cv2.VideoWriter_fourcc(*'MJPG') # self.out = cv2.VideoWriter('./static/video.avi',fourcc, 20.0, (640,480)) # ret, frame = self.cap.read() # if ret: # self.out.write(frame) # else: # if self.out != None: # self.out.release() # self.out = None return jpeg.tobytes() else: return None def start_record(self): self.is_record = True self.recordingThread = RecordingThread("Video Recording Thread", self.cap) self.recordingThread.start() def stop_record(self): self.is_record = False if self.recordingThread != None: self.recordingThread.stop()
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from __future__ import absolute_import import datetime import os from socket import error as SocketError, timeout as SocketTimeout import socket import sys import warnings from .exceptions import ( NewConnectionError, ConnectTimeoutError, SubjectAltNameWarning, SystemTimeWarning, ) from .packages import six from .packages.ssl_match_hostname import match_hostname from .util import connection from .util.ssl_ import ( resolve_cert_reqs, resolve_ssl_version, ssl_wrap_socket, assert_fingerprint, ) try: # Python 3 from http.client import HTTPConnection as _HTTPConnection from http.client import HTTPException # noqa: unused in this module except ImportError: from httplib import HTTPConnection as _HTTPConnection from httplib import HTTPException # noqa: unused in this module try: # Compiled with SSL? import ssl BaseSSLError = ssl.SSLError except (ImportError, AttributeError): # Platform-specific: No SSL. ssl = None class BaseSSLError(BaseException): pass try: # Python 3: # Not a no-op, we're adding this to the namespace so it can be imported. ConnectionError = ConnectionError except NameError: # Python 2: class ConnectionError(Exception): pass port_by_scheme = { 'http': 80, 'https': 443, } RECENT_DATE = datetime.date(2014, 1, 1) class DummyConnection(object): """Used to detect a failed ConnectionCls import.""" pass class HTTPConnection(_HTTPConnection, object): """ Based on httplib.HTTPConnection but provides an extra constructor backwards-compatibility layer between older and newer Pythons. Additional keyword parameters are used to configure attributes of the connection. Accepted parameters include: - ``strict``: See the documentation on :class:`urllib3.connectionpool.HTTPConnectionPool` - ``source_address``: Set the source address for the current connection. .. note:: This is ignored for Python 2.6. It is only applied for 2.7 and 3.x - ``socket_options``: Set specific options on the underlying socket. If not specified, then defaults are loaded from ``HTTPConnection.default_socket_options`` which includes disabling Nagle's algorithm (sets TCP_NODELAY to 1) unless the connection is behind a proxy. For example, if you wish to enable TCP Keep Alive in addition to the defaults, you might pass:: HTTPConnection.default_socket_options + [ (socket.SOL_SOCKET, socket.SO_KEEPALIVE, 1), ] Or you may want to disable the defaults by passing an empty list (e.g., ``[]``). """ default_port = port_by_scheme['http'] #: Disable Nagle's algorithm by default. #: ``[(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)]`` default_socket_options = [(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)] #: Whether this connection verifies the host's certificate. is_verified = False def __init__(self, *args, **kw): if six.PY3: # Python 3 kw.pop('strict', None) # Pre-set source_address in case we have an older Python like 2.6. self.source_address = kw.get('source_address') if sys.version_info < (2, 7): # Python 2.6 # _HTTPConnection on Python 2.6 will balk at this keyword arg, but # not newer versions. We can still use it when creating a # connection though, so we pop it *after* we have saved it as # self.source_address. kw.pop('source_address', None) #: The socket options provided by the user. If no options are #: provided, we use the default options. self.socket_options = kw.pop('socket_options', self.default_socket_options) # Superclass also sets self.source_address in Python 2.7+. _HTTPConnection.__init__(self, *args, **kw) def _new_conn(self): """ Establish a socket connection and set nodelay settings on it. :return: New socket connection. """ extra_kw = {} if self.source_address: extra_kw['source_address'] = self.source_address if self.socket_options: extra_kw['socket_options'] = self.socket_options try: conn = connection.create_connection( (self.host, self.port), self.timeout, **extra_kw) except SocketTimeout as e: raise ConnectTimeoutError( self, "Connection to %s timed out. (connect timeout=%s)" % (self.host, self.timeout)) except SocketError as e: raise NewConnectionError( self, "Failed to establish a new connection: %s" % e) return conn def _prepare_conn(self, conn): self.sock = conn # the _tunnel_host attribute was added in python 2.6.3 (via # http://hg.python.org/cpython/rev/0f57b30a152f) so pythons 2.6(0-2) do # not have them. if getattr(self, '_tunnel_host', None): # TODO: Fix tunnel so it doesn't depend on self.sock state. self._tunnel() # Mark this connection as not reusable self.auto_open = 0 def connect(self): conn = self._new_conn() self._prepare_conn(conn) class HTTPSConnection(HTTPConnection): default_port = port_by_scheme['https'] def __init__(self, host, port=None, key_file=None, cert_file=None, strict=None, timeout=socket._GLOBAL_DEFAULT_TIMEOUT, **kw): HTTPConnection.__init__(self, host, port, strict=strict, timeout=timeout, **kw) self.key_file = key_file self.cert_file = cert_file # Required property for Google AppEngine 1.9.0 which otherwise causes # HTTPS requests to go out as HTTP. (See Issue #356) self._protocol = 'https' def connect(self): conn = self._new_conn() self._prepare_conn(conn) self.sock = ssl.wrap_socket(conn, self.key_file, self.cert_file) class VerifiedHTTPSConnection(HTTPSConnection): """ Based on httplib.HTTPSConnection but wraps the socket with SSL certification. """ cert_reqs = None ca_certs = None ca_cert_dir = None ssl_version = None assert_fingerprint = None def set_cert(self, key_file=None, cert_file=None, cert_reqs=None, ca_certs=None, assert_hostname=None, assert_fingerprint=None, ca_cert_dir=None): if (ca_certs or ca_cert_dir) and cert_reqs is None: cert_reqs = 'CERT_REQUIRED' self.key_file = key_file self.cert_file = cert_file self.cert_reqs = cert_reqs self.assert_hostname = assert_hostname self.assert_fingerprint = assert_fingerprint self.ca_certs = ca_certs and os.path.expanduser(ca_certs) self.ca_cert_dir = ca_cert_dir and os.path.expanduser(ca_cert_dir) def connect(self): # Add certificate verification conn = self._new_conn() resolved_cert_reqs = resolve_cert_reqs(self.cert_reqs) resolved_ssl_version = resolve_ssl_version(self.ssl_version) hostname = self.host if getattr(self, '_tunnel_host', None): # _tunnel_host was added in Python 2.6.3 # (See: http://hg.python.org/cpython/rev/0f57b30a152f) self.sock = conn # Calls self._set_hostport(), so self.host is # self._tunnel_host below. self._tunnel() # Mark this connection as not reusable self.auto_open = 0 # Override the host with the one we're requesting data from. hostname = self._tunnel_host is_time_off = datetime.date.today() < RECENT_DATE if is_time_off: warnings.warn(( 'System time is way off (before {0}). This will probably ' 'lead to SSL verification errors').format(RECENT_DATE), SystemTimeWarning ) # Wrap socket using verification with the root certs in # trusted_root_certs self.sock = ssl_wrap_socket(conn, self.key_file, self.cert_file, cert_reqs=resolved_cert_reqs, ca_certs=self.ca_certs, ca_cert_dir=self.ca_cert_dir, server_hostname=hostname, ssl_version=resolved_ssl_version) if self.assert_fingerprint: assert_fingerprint(self.sock.getpeercert(binary_form=True), self.assert_fingerprint) elif resolved_cert_reqs != ssl.CERT_NONE \ and self.assert_hostname is not False: cert = self.sock.getpeercert() if not cert.get('subjectAltName', ()): warnings.warn(( 'Certificate for {0} has no `subjectAltName`, falling back to check for a ' '`commonName` for now. This feature is being removed by major browsers and ' 'deprecated by RFC 2818. (See https://github.com/shazow/urllib3/issues/497 ' 'for details.)'.format(hostname)), SubjectAltNameWarning ) # In case the hostname is an IPv6 address, strip the square # brackets from it before using it to validate. This is because # a certificate with an IPv6 address in it won't have square # brackets around that address. Sadly, match_hostname won't do this # for us: it expects the plain host part without any extra work # that might have been done to make it palatable to httplib. asserted_hostname = self.assert_hostname or hostname asserted_hostname = asserted_hostname.strip('[]') match_hostname(cert, asserted_hostname) self.is_verified = (resolved_cert_reqs == ssl.CERT_REQUIRED or self.assert_fingerprint is not None) if ssl: # Make a copy for testing. UnverifiedHTTPSConnection = HTTPSConnection HTTPSConnection = VerifiedHTTPSConnection else: HTTPSConnection = DummyConnection
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 import shutil import subprocess from pre_wigs_validation.enums import ValidationEnforcement, ValidationResult from pre_wigs_validation.instance import ValidationInstance from pre_wigs_validation.dataclasses import ValidationOutput from pre_wigs_validation.utils import check_validation_config, get_ld_library_orig class RepoAccess: """Validate that an instance has access to Yum Repositories.""" validation = "Repo Access" enforcement = ValidationEnforcement.REQUIRED @classmethod def validate( cls, *, enabled: bool = True, instance: ValidationInstance ) -> ValidationOutput: """ Parameters: enabled (bool): whether or not to run this validation function instance (ValidationInstance): the instance object being validated Returns: ValidationOutput: output of validation """ if not enabled: return ValidationOutput( validation=cls.validation, result=ValidationResult.NOT_RUN, enforcement=cls.enforcement, ) if instance.distribution == "sles": repo_check_command = ["zypper", "refresh"] verbose_error_message = "Command 'zypper' not in $PATH" package_manager_found = not shutil.which("zypper") == None else: repo_check_command = ["yum", "check-update"] verbose_error_message = "Command 'yum' not in $PATH" package_manager_found = not shutil.which("yum") == None error_message = "Unable to validate due to unsupported environment" fail_message = "Unable to access repositories" config = check_validation_config( default_params=cls.validate.__kwdefaults__, local_params=locals() ) if not package_manager_found: return ValidationOutput( validation=cls.validation, result=ValidationResult.FAIL, enforcement=cls.enforcement, config=config, message=error_message, verbose_message=verbose_error_message, ) proc = subprocess.run( repo_check_command, env=get_ld_library_orig(), stdout=subprocess.DEVNULL, stderr=subprocess.PIPE, ) if proc.returncode == 1: verbose_message = proc.stderr.decode("utf-8") return ValidationOutput( validation=cls.validation, result=ValidationResult.FAIL, enforcement=cls.enforcement, config=config, message=fail_message, verbose_message=verbose_message, ) return ValidationOutput( validation=cls.validation, result=ValidationResult.PASS, enforcement=cls.enforcement, config=config, )
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from numpy.random import RandomState from typing import Any, Optional, List from numpy import arange from copy import deepcopy from pydeeprecsys.rl.neural_networks.dueling import DuelingDDQN from pydeeprecsys.rl.experience_replay.priority_replay_buffer import ( PrioritizedExperienceReplayBuffer, ) from pydeeprecsys.rl.experience_replay.buffer_parameters import ( PERBufferParameters, ExperienceReplayBufferParameters, ) from pydeeprecsys.rl.agents.agent import ReinforcementLearning from pydeeprecsys.rl.learning_statistics import LearningStatistics class RainbowDQNAgent(ReinforcementLearning): """Instead of sampling randomly from the buffer we prioritize experiences with PER Instead of epsilon-greedy we use gaussian noisy layers for exploration Instead of the Q value we calculate Value and Advantage (Dueling DQN). This implementation does not include the Categorical DQN part (yet).""" def __init__( self, input_size: int, output_size: int, network_update_frequency: int = 5, network_sync_frequency: int = 200, priority_importance: float = 0.6, priority_weigth_growth: float = 0.001, buffer_size: int = 10000, buffer_burn_in: int = 1000, batch_size: int = 32, noise_sigma: float = 0.017, discount_factor: float = 0.99, learning_rate: float = 0.0001, hidden_layers: List[int] = None, random_state: RandomState = RandomState(), statistics: Optional[LearningStatistics] = None, ): self.network = DuelingDDQN( n_input=input_size, n_output=output_size, learning_rate=learning_rate, noise_sigma=noise_sigma, discount_factor=discount_factor, statistics=statistics, hidden_layers=hidden_layers, ) self.target_network = deepcopy(self.network) self.buffer = PrioritizedExperienceReplayBuffer( ExperienceReplayBufferParameters( max_experiences=buffer_size, minimum_experiences_to_start_predicting=buffer_burn_in, batch_size=batch_size, random_state=random_state, ), PERBufferParameters( alpha=priority_importance, beta_growth=priority_weigth_growth, ), ) self.step_count = 0 self.network_update_frequency = network_update_frequency self.network_sync_frequency = network_sync_frequency self.actions = arange(output_size) self.random_state = random_state def _check_update_network(self): # we only start training the network once the buffer is ready # (the burn in is filled) if self.buffer.ready_to_predict(): self.step_count += 1 if self.step_count % self.network_update_frequency == 0: # we train at every K steps self.network.learn_with(self.buffer, self.target_network) if self.step_count % self.network_sync_frequency == 0: # at every N steps replaces the target network with the main network self.target_network.load_state_dict(self.network.state_dict()) def top_k_actions_for_state(self, state: Any, k: int = 1) -> Any: state_flat = state.flatten() if self.buffer.ready_to_predict(): actions = self.target_network.top_k_actions_for_state(state_flat, k=k) else: actions = self.random_state.choice(self.actions, size=k) self._check_update_network() return actions def action_for_state(self, state: Any) -> Any: return self.top_k_actions_for_state(state, k=1)[0] def store_experience( self, state: Any, action: Any, reward: float, done: bool, new_state: Any ): state_flat = state.flatten() new_state_flat = new_state.flatten() self.buffer.store_experience(state_flat, action, reward, done, new_state_flat)
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#grad_cam #[keras-grad-cam/grad-cam.py](https://github.com/jacobgil/keras-grad-cam/blob/master/grad-cam.py) from keras.applications.vgg16 import (VGG16, preprocess_input, decode_predictions) from keras.models import Model from keras.preprocessing import image from keras.layers.core import Lambda from keras.models import Sequential from tensorflow.python.framework import ops import keras.backend as K import tensorflow as tf import numpy as np import keras import sys import cv2 #from keras.applications.resnet50 import ResNet50, preprocess_input, decode_predictions #from keras.applications.vgg19 import VGG19, preprocess_input, decode_predictions #from keras.applications.inception_v3 import InceptionV3, preprocess_input, decode_predictions def target_category_loss(x, category_index, nb_classes): return tf.multiply(x, K.one_hot([category_index], nb_classes)) def target_category_loss_output_shape(input_shape): return input_shape def normalize(x): # utility function to normalize a tensor by its L2 norm return x / (K.sqrt(K.mean(K.square(x))) + 1e-5) def load_image(path): img_path = sys.argv[1] img = image.load_img(img_path, target_size=(224,224)) #299,299)) #224, 224)) x = image.img_to_array(img) x = np.expand_dims(x, axis=0) x = preprocess_input(x) return x def register_gradient(): if "GuidedBackProp" not in ops._gradient_registry._registry: @ops.RegisterGradient("GuidedBackProp") def _GuidedBackProp(op, grad): dtype = op.inputs[0].dtype return grad * tf.cast(grad > 0., dtype) * \ tf.cast(op.inputs[0] > 0., dtype) def compile_saliency_function(model, activation_layer='block5_conv3'): #mixed10 'activation_49' add_16 add_32 activation_98 input_img = model.input layer_dict = dict([(layer.name, layer) for layer in model.layers[1:]]) #print(layer_dict) layer_output = layer_dict[activation_layer].output max_output = K.max(layer_output, axis=3) saliency = K.gradients(K.sum(max_output), input_img)[0] return K.function([input_img, K.learning_phase()], [saliency]) def modify_backprop(model, name): g = tf.get_default_graph() with g.gradient_override_map({'Relu': name}): # get layers that have an activation layer_dict = [layer for layer in model.layers[1:] if hasattr(layer, 'activation')] # replace relu activation for layer in layer_dict: if layer.activation == keras.activations.relu: layer.activation = tf.nn.relu # re-instanciate a new model new_model = VGG16(weights='imagenet') #new_model = ResNet50(weights='imagenet') new_model.summary() return new_model def deprocess_image(x): ''' Same normalization as in: https://github.com/fchollet/keras/blob/master/examples/conv_filter_visualization.py ''' if np.ndim(x) > 3: x = np.squeeze(x) # normalize tensor: center on 0., ensure std is 0.1 x -= x.mean() x /= (x.std() + 1e-5) x *= 0.1 # clip to [0, 1] x += 0.5 x = np.clip(x, 0, 1) # convert to RGB array x *= 255 if K.image_dim_ordering() == 'th': x = x.transpose((1, 2, 0)) x = np.clip(x, 0, 255).astype('uint8') return x def _compute_gradients(tensor, var_list): grads = tf.gradients(tensor, var_list) return [grad if grad is not None else tf.zeros_like(var) for var, grad in zip(var_list, grads)] def grad_cam(input_model, image, category_index, layer_name): nb_classes = 1000 target_layer = lambda x: target_category_loss(x, category_index, nb_classes) x = Lambda(target_layer, output_shape = target_category_loss_output_shape)(input_model.output) model = Model(inputs=input_model.input, outputs=x) #model.summary() loss = K.sum(model.output) conv_output = [l for l in model.layers if l.name == layer_name][0].output #is grads = normalize(_compute_gradients(loss, [conv_output])[0]) gradient_function = K.function([model.input], [conv_output, grads]) output, grads_val = gradient_function([image]) output, grads_val = output[0, :], grads_val[0, :, :, :] weights = np.mean(grads_val, axis = (0, 1)) cam = np.ones(output.shape[0 : 2], dtype = np.float32) for i, w in enumerate(weights): cam += w * output[:, :, i] cam = cv2.resize(cam, (224,224)) #299,299)) #224, 224)) cam = np.maximum(cam, 0) heatmap = cam / np.max(cam) #Return to BGR [0..255] from the preprocessed image image = image[0, :] image -= np.min(image) image = np.minimum(image, 255) cam = cv2.applyColorMap(np.uint8(255*heatmap), cv2.COLORMAP_JET) cam = np.float32(cam) + np.float32(image) cam = 255 * cam / np.max(cam) return np.uint8(cam), heatmap preprocessed_input = load_image(sys.argv[1]) model = VGG16(weights='imagenet') #model = VGG19(weights='imagenet') #model = InceptionV3(weights='imagenet') #model = ResNet50(weights = 'imagenet') #model.summary() target_layer = 'block5_conv3' #'activation_49' add_16 "block5_conv3" predictions = model.predict(preprocessed_input) register_gradient() guided_model = modify_backprop(model, 'GuidedBackProp') guided_model.summary() for i in range(5): top_1 = decode_predictions(predictions)[0][i] print(predictions.argsort()[0][::-1][i]) print('Predicted class:') print('%s (%s) with probability %.2f' % (top_1[1], top_1[0], top_1[2])) predicted_class = predictions.argsort()[0][::-1][i] #np.argmax(predictions) cam, heatmap = grad_cam(model, preprocessed_input, predicted_class, target_layer) cv2.imwrite("gradcam"+str(top_1[1])+".jpg", cam) saliency_fn = compile_saliency_function(guided_model) saliency = saliency_fn([preprocessed_input, 0]) gradcam = saliency[0] * heatmap[..., np.newaxis] cv2.imwrite("guided_gradcam"+str(top_1[1])+".jpg", deprocess_image(gradcam))
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import os import hashlib from constants import TEX_DIR from constants import TEX_TEXT_TO_REPLACE from constants import TEX_USE_CTEX from constants import TEX_FIX_SVG def tex_hash(expression, template_tex_file_body): id_str = str(expression + template_tex_file_body) hasher = hashlib.sha256() hasher.update(id_str.encode()) # Truncating at 16 bytes for cleanliness return hasher.hexdigest()[:16] def tex_to_svg_file(expression, template_tex_file_body): tex_file = generate_tex_file(expression, template_tex_file_body) dvi_file = tex_to_dvi(tex_file) return dvi_to_svg(dvi_file) def generate_tex_file(expression, template_tex_file_body): result = os.path.join( TEX_DIR, tex_hash(expression, template_tex_file_body) ) + ".tex" if not os.path.exists(result): print("Writing \"%s\" to %s" % ( "".join(expression), result )) new_body = template_tex_file_body.replace( TEX_TEXT_TO_REPLACE, expression ) with open(result, "w") as outfile: outfile.write(new_body) return result def get_null(): if os.name == "nt": return "NUL" return "/dev/null" def tex_to_dvi(tex_file): result = tex_file.replace(".tex", ".dvi" if not TEX_USE_CTEX else ".xdv") if not os.path.exists(result): commands = [ "latex", "-interaction=batchmode", "-halt-on-error", "-output-directory=" + TEX_DIR, tex_file, ">", get_null() ] if not TEX_USE_CTEX else [ "xelatex", "-no-pdf", "-interaction=batchmode", "-halt-on-error", "-output-directory=" + TEX_DIR, tex_file, ">", get_null() ] exit_code = os.system(" ".join(commands)) if exit_code != 0: log_file = tex_file.replace(".tex", ".log") raise Exception( ("Latex error converting to dvi. " if not TEX_USE_CTEX else "Xelatex error converting to xdv. ") + "See log output above or the log file: %s" % log_file) return result def dvi_to_svg(dvi_file, regen_if_exists=False): """ Converts a dvi, which potentially has multiple slides, into a directory full of enumerated pngs corresponding with these slides. Returns a list of PIL Image objects for these images sorted as they where in the dvi """ result = dvi_file.replace(".dvi" if not TEX_USE_CTEX else ".xdv", ".svg") if not os.path.exists(result): commands = [ "dvisvgm", dvi_file, "-n", "-v", "0", "-o", result, ">", get_null() ] os.system(" ".join(commands)) if TEX_FIX_SVG: commands = [ "cairosvg", result, "-f", "svg", "-o", result ] os.system(" ".join(commands)) return result
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from django.forms.models import model_to_dict from django.test import TestCase from ..forms import EmailChangePasswordForm, ProfileForm from .factories import StaffFactory, UserFactory class BaseTestProfileForm(TestCase): def form_data(self, user, **values): fields = ProfileForm.Meta.fields data = model_to_dict(user, fields) data.update(**values) return data def submit_form(self, instance, **extra_data): form = ProfileForm(instance=instance, data=self.form_data(instance, **extra_data)) if form.is_valid(): form.save() return form class TestProfileForm(BaseTestProfileForm): def setUp(self): self.user = UserFactory() def test_email_unique(self): other_user = UserFactory() form = self.submit_form(self.user, email=other_user.email) self.assertFalse(form.is_valid()) self.user.refresh_from_db() self.assertNotEqual(self.user.email, other_user.email) def test_can_change_email(self): new_email = 'me@another.com' self.submit_form(self.user, email=new_email) self.user.refresh_from_db() self.assertEqual(self.user.email, new_email) def test_cant_set_slack_name(self): slack_name = '@foobar' self.submit_form(self.user, slack=slack_name) self.user.refresh_from_db() self.assertNotEqual(self.user.slack, slack_name) class TestStaffProfileForm(BaseTestProfileForm): def setUp(self): self.staff = StaffFactory() def test_cant_change_email(self): new_email = 'me@this.com' self.submit_form(self.staff, email=new_email) self.staff.refresh_from_db() self.assertNotEqual(new_email, self.staff.email) def test_can_set_slack_name(self): slack_name = '@foobar' self.submit_form(self.staff, slack=slack_name) self.staff.refresh_from_db() self.assertEqual(self.staff.slack, slack_name) def test_can_set_slack_name_with_trailing_space(self): slack_name = '@foobar' self.submit_form(self.staff, slack=slack_name) self.staff.refresh_from_db() self.assertEqual(self.staff.slack, slack_name) def test_cant_set_slack_name_with_space(self): slack_name = '@ foobar' form = self.submit_form(self.staff, slack=slack_name) self.assertFalse(form.is_valid()) self.staff.refresh_from_db() self.assertNotEqual(self.staff.slack, slack_name) def test_auto_prepend_at(self): slack_name = 'foobar' self.submit_form(self.staff, slack=slack_name) self.staff.refresh_from_db() self.assertEqual(self.staff.slack, '@' + slack_name) def test_can_clear_slack_name(self): slack_name = '' self.submit_form(self.staff, slack=slack_name) self.staff.refresh_from_db() self.assertEqual(self.staff.slack, slack_name) class TestEmailChangePasswordForm(TestCase): def setUp(self): self.user = UserFactory() def test_doesnt_error_on_null_slack_field(self): form = EmailChangePasswordForm(self.user) form.save('', '', None) def test_can_update_slack(self): slack_name = 'foobar' form = EmailChangePasswordForm(self.user) form.save('', '', slack_name) self.assertEqual(self.user.slack, slack_name)
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from daoRefactor2 import DAO from rssTickerInfo import rssTickerInfo import json import boto3 table = 'CompanyRSSFeed' dao = DAO(table) def main(): tickerValues = dao.getRssTickerValues('UNP') print(tickerValues) if __name__ == "__main__": # calling main function main()
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############################################################################## # Copyright (c) 2015 Orange # guyrodrigue.koffi@orange.com / koffirodrigue@gmail.com # All rights reserved. This program and the accompanying materials # are made available under the terms of the Apache License, Version 2.0 # which accompanies this distribution, and is available at # http://www.apache.org/licenses/LICENSE-2.0 ############################################################################## from opnfv_testapi.tornado_swagger import swagger @swagger.model() class ProjectCreateRequest(object): def __init__(self, name, description=''): self.name = name self.description = description def format(self): return { "name": self.name, "description": self.description, } @swagger.model() class ProjectUpdateRequest(object): def __init__(self, name='', description=''): self.name = name self.description = description def format(self): return { "name": self.name, "description": self.description, } @swagger.model() class Project(object): def __init__(self, name=None, _id=None, description=None, create_date=None): self._id = _id self.name = name self.description = description self.creation_date = create_date @staticmethod def from_dict(res_dict): if res_dict is None: return None t = Project() t._id = res_dict.get('_id') t.creation_date = res_dict.get('creation_date') t.name = res_dict.get('name') t.description = res_dict.get('description') return t def format(self): return { "name": self.name, "description": self.description, "creation_date": str(self.creation_date) } def format_http(self): return { "_id": str(self._id), "name": self.name, "description": self.description, "creation_date": str(self.creation_date), } @swagger.model() class Projects(object): """ @property projects: @ptype projects: C{list} of L{Project} """ def __init__(self): self.projects = list() @staticmethod def from_dict(res_dict): if res_dict is None: return None res = Projects() for project in res_dict.get('projects'): res.projects.append(Project.from_dict(project)) return res
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"""Random walk routines """ from .._ffi.function import _init_api from .. import backend as F from ..base import DGLError from .. import ndarray as nd from .. import utils __all__ = [ 'random_walk', 'pack_traces'] def random_walk(g, nodes, *, metapath=None, length=None, prob=None, restart_prob=None): """Generate random walk traces from an array of starting nodes based on the given metapath. For a single starting node, ``num_traces`` traces would be generated. A trace would 1. Start from the given node and set ``t`` to 0. 2. Pick and traverse along edge type ``metapath[t]`` from the current node. 3. If no edge can be found, halt. Otherwise, increment ``t`` and go to step 2. The returned traces all have length ``len(metapath) + 1``, where the first node is the starting node itself. If a random walk stops in advance, DGL pads the trace with -1 to have the same length. Parameters ---------- g : DGLGraph The graph. Must be on CPU. nodes : Tensor Node ID tensor from which the random walk traces starts. The tensor must be on CPU, and must have the same dtype as the ID type of the graph. metapath : list[str or tuple of str], optional Metapath, specified as a list of edge types. Mutually exclusive with :attr:`length`. If omitted, DGL assumes that ``g`` only has one node & edge type. In this case, the argument ``length`` specifies the length of random walk traces. length : int, optional Length of random walks. Mutually exclusive with :attr:`metapath`. Only used when :attr:`metapath` is None. prob : str, optional The name of the edge feature tensor on the graph storing the (unnormalized) probabilities associated with each edge for choosing the next node. The feature tensor must be non-negative and the sum of the probabilities must be positive for the outbound edges of all nodes (although they don't have to sum up to one). The result will be undefined otherwise. If omitted, DGL assumes that the neighbors are picked uniformly. restart_prob : float or Tensor, optional Probability to terminate the current trace before each transition. If a tensor is given, :attr:`restart_prob` should have the same length as :attr:`metapath` or :attr:`length`. Returns ------- traces : Tensor A 2-dimensional node ID tensor with shape ``(num_seeds, len(metapath) + 1)`` or ``(num_seeds, length + 1)`` if :attr:`metapath` is None. types : Tensor A 1-dimensional node type ID tensor with shape ``(len(metapath) + 1)`` or ``(length + 1)``. The type IDs match the ones in the original graph ``g``. Notes ----- The returned tensors are on CPU. Examples -------- The following creates a homogeneous graph: >>> g1 = dgl.graph([(0, 1), (1, 2), (1, 3), (2, 0), (3, 0)], 'user', 'follow') Normal random walk: >>> dgl.sampling.random_walk(g1, [0, 1, 2, 0], length=4) (tensor([[0, 1, 2, 0, 1], [1, 3, 0, 1, 3], [2, 0, 1, 3, 0], [0, 1, 2, 0, 1]]), tensor([0, 0, 0, 0, 0])) The first tensor indicates the random walk path for each seed node. The j-th element in the second tensor indicates the node type ID of the j-th node in every path. In this case, it is returning all 0 (``user``). Random walk with restart: >>> dgl.sampling.random_walk_with_restart(g1, [0, 1, 2, 0], length=4, restart_prob=0.5) (tensor([[ 0, -1, -1, -1, -1], [ 1, 3, 0, -1, -1], [ 2, -1, -1, -1, -1], [ 0, -1, -1, -1, -1]]), tensor([0, 0, 0, 0, 0])) Non-uniform random walk: >>> g1.edata['p'] = torch.FloatTensor([1, 0, 1, 1, 1]) # disallow going from 1 to 2 >>> dgl.sampling.random_walk(g1, [0, 1, 2, 0], length=4, prob='p') (tensor([[0, 1, 3, 0, 1], [1, 3, 0, 1, 3], [2, 0, 1, 3, 0], [0, 1, 3, 0, 1]]), tensor([0, 0, 0, 0, 0])) Metapath-based random walk: >>> g2 = dgl.heterograph({ ... ('user', 'follow', 'user'): [(0, 1), (1, 2), (1, 3), (2, 0), (3, 0)], ... ('user', 'view', 'item'): [(0, 0), (0, 1), (1, 1), (2, 2), (3, 2), (3, 1)], ... ('item', 'viewed-by', 'user'): [(0, 0), (1, 0), (1, 1), (2, 2), (2, 3), (1, 3)]}) >>> dgl.sampling.random_walk( ... g2, [0, 1, 2, 0], metapath=['follow', 'view', 'viewed-by'] * 2) (tensor([[0, 1, 1, 1, 2, 2, 3], [1, 3, 1, 1, 2, 2, 2], [2, 0, 1, 1, 3, 1, 1], [0, 1, 1, 0, 1, 1, 3]]), tensor([0, 0, 1, 0, 0, 1, 0])) Metapath-based random walk, with restarts only on items (i.e. after traversing a "view" relationship): >>> dgl.sampling.random_walk( ... g2, [0, 1, 2, 0], metapath=['follow', 'view', 'viewed-by'] * 2, ... restart_prob=torch.FloatTensor([0, 0.5, 0, 0, 0.5, 0])) (tensor([[ 0, 1, -1, -1, -1, -1, -1], [ 1, 3, 1, 0, 1, 1, 0], [ 2, 0, 1, 1, 3, 2, 2], [ 0, 1, 1, 3, 0, 0, 0]]), tensor([0, 0, 1, 0, 0, 1, 0])) """ assert g.device == F.cpu(), "Graph must be on CPU." n_etypes = len(g.canonical_etypes) n_ntypes = len(g.ntypes) if metapath is None: if n_etypes > 1 or n_ntypes > 1: raise DGLError("metapath not specified and the graph is not homogeneous.") if length is None: raise ValueError("Please specify either the metapath or the random walk length.") metapath = [0] * length else: metapath = [g.get_etype_id(etype) for etype in metapath] gidx = g._graph nodes = F.to_dgl_nd(utils.prepare_tensor(g, nodes, 'nodes')) metapath = F.to_dgl_nd(utils.prepare_tensor(g, metapath, 'metapath')) # Load the probability tensor from the edge frames if prob is None: p_nd = [nd.array([], ctx=nodes.ctx) for _ in g.canonical_etypes] else: p_nd = [] for etype in g.canonical_etypes: if prob in g.edges[etype].data: prob_nd = F.to_dgl_nd(g.edges[etype].data[prob]) if prob_nd.ctx != nodes.ctx: raise ValueError( 'context of seed node array and edges[%s].data[%s] are different' % (etype, prob)) else: prob_nd = nd.array([], ctx=nodes.ctx) p_nd.append(prob_nd) # Actual random walk if restart_prob is None: traces, types = _CAPI_DGLSamplingRandomWalk(gidx, nodes, metapath, p_nd) elif F.is_tensor(restart_prob): restart_prob = F.to_dgl_nd(restart_prob) traces, types = _CAPI_DGLSamplingRandomWalkWithStepwiseRestart( gidx, nodes, metapath, p_nd, restart_prob) else: traces, types = _CAPI_DGLSamplingRandomWalkWithRestart( gidx, nodes, metapath, p_nd, restart_prob) traces = F.from_dgl_nd(traces) types = F.from_dgl_nd(types) return traces, types def pack_traces(traces, types): """Pack the padded traces returned by ``random_walk()`` into a concatenated array. The padding values (-1) are removed, and the length and offset of each trace is returned along with the concatenated node ID and node type arrays. Parameters ---------- traces : Tensor A 2-dimensional node ID tensor. Must be on CPU and either ``int32`` or ``int64``. types : Tensor A 1-dimensional node type ID tensor. Must be on CPU and either ``int32`` or ``int64``. Returns ------- concat_vids : Tensor An array of all node IDs concatenated and padding values removed. concat_types : Tensor An array of node types corresponding for each node in ``concat_vids``. Has the same length as ``concat_vids``. lengths : Tensor Length of each trace in the original traces tensor. offsets : Tensor Offset of each trace in the originial traces tensor in the new concatenated tensor. Notes ----- The returned tensors are on CPU. Examples -------- >>> g2 = dgl.heterograph({ ... ('user', 'follow', 'user'): [(0, 1), (1, 2), (1, 3), (2, 0), (3, 0)], ... ('user', 'view', 'item'): [(0, 0), (0, 1), (1, 1), (2, 2), (3, 2), (3, 1)], ... ('item', 'viewed-by', 'user'): [(0, 0), (1, 0), (1, 1), (2, 2), (2, 3), (1, 3)]}) >>> traces, types = dgl.sampling.random_walk( ... g2, [0, 0], metapath=['follow', 'view', 'viewed-by'] * 2, ... restart_prob=torch.FloatTensor([0, 0.5, 0, 0, 0.5, 0])) >>> traces, types (tensor([[ 0, 1, -1, -1, -1, -1, -1], [ 0, 1, 1, 3, 0, 0, 0]]), tensor([0, 0, 1, 0, 0, 1, 0])) >>> concat_vids, concat_types, lengths, offsets = dgl.sampling.pack_traces(traces, types) >>> concat_vids tensor([0, 1, 0, 1, 1, 3, 0, 0, 0]) >>> concat_types tensor([0, 0, 0, 0, 1, 0, 0, 1, 0]) >>> lengths tensor([2, 7]) >>> offsets tensor([0, 2])) The first tensor ``concat_vids`` is the concatenation of all paths, i.e. flattened array of ``traces``, excluding all padding values (-1). The second tensor ``concat_types`` stands for the node type IDs of all corresponding nodes in the first tensor. The third and fourth tensor indicates the length and the offset of each path. With these tensors it is easy to obtain the i-th random walk path with: >>> vids = concat_vids.split(lengths.tolist()) >>> vtypes = concat_vtypes.split(lengths.tolist()) >>> vids[1], vtypes[1] (tensor([0, 1, 1, 3, 0, 0, 0]), tensor([0, 0, 1, 0, 0, 1, 0])) """ assert F.is_tensor(traces) and F.context(traces) == F.cpu(), "traces must be a CPU tensor" assert F.is_tensor(types) and F.context(types) == F.cpu(), "types must be a CPU tensor" traces = F.to_dgl_nd(traces) types = F.to_dgl_nd(types) concat_vids, concat_types, lengths, offsets = _CAPI_DGLSamplingPackTraces(traces, types) concat_vids = F.from_dgl_nd(concat_vids) concat_types = F.from_dgl_nd(concat_types) lengths = F.from_dgl_nd(lengths) offsets = F.from_dgl_nd(offsets) return concat_vids, concat_types, lengths, offsets _init_api('dgl.sampling.randomwalks', __name__)
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import vdomr as vd import spikeforest as sf from cairio import client as ca import pandas as pd import numpy as np from matplotlib import pyplot as plt class AccuracyPlot(vd.components.Pyplot): def __init__(self, snrs, accuracies): vd.components.Pyplot.__init__(self) self._snrs = snrs self._accuracies = accuracies def plot(self): plt.scatter(self._snrs, self._accuracies) class StudySorterFigure(vd.Component): def __init__(self, sfdata): vd.Component.__init__(self) self._plot = None self._SF_data = sfdata self._study = None self._sorter = None def setStudySorter(self, *, study, sorter): self._study = study self._sorter = sorter self._update_plot() def _update_plot(self): SF = self._SF_data study = SF.study(self._study) b = _get_study_sorting_results(study) a = b[self._sorter] snrs = a['true_unit_snrs'] accuracies = a['num_matches'] / \ (a['num_matches']+a['num_false_positives']+a['num_false_negatives']) self._plot = AccuracyPlot(snrs, accuracies) self.refresh() def render(self): if self._plot is None: return vd.div('Nothing') return vd.div( vd.div('test '+self._study+' '+self._sorter), self._plot ) class SFBrowser(vd.Component): def __init__(self, output_id): vd.Component.__init__(self) self._output_id = output_id a = ca.loadObject( key=dict(name='spikeforest_results'), subkey=output_id ) if not a: print('ERROR: unable to open results: '+output_id) return if ('recordings' not in a) or ('studies' not in a) or ('sorting_results' not in a): print('ERROR: problem with output: '+output_id) return studies = a['studies'] recordings = a['recordings'] sorting_results = a['sorting_results'] SF = sf.SFData() SF.loadStudies(studies) SF.loadRecordings2(recordings) SF.loadSortingResults(sorting_results) # sorter_names=[] # for SR in sorting_results: # sorter_names.append(SR['sorter']['name']) # sorter_names=list(set(sorter_names)) # sorter_names.sort() self._SF_data = SF self._accuracy_threshold_input = vd.components.LineEdit( value=0.8, dtype=float, style=dict(width='70px')) self._update_button = vd.components.Button( onclick=self._on_update, class_='button', label='Update') self._study_sorter_fig = StudySorterFigure(SF) self._study_sorter_table = vd.div() # dummy vd.devel.loadBootstrap() self._update_accuracy_table() def _on_update(self): self._update_accuracy_table() def _update_accuracy_table(self): accuracy_threshold = self._accuracy_threshold_input.value() self._accuracy_table_data, self._sorters = self._get_accuracy_table_data( accuracy_threshold=accuracy_threshold) self._accuracy_table = self._to_table( self._accuracy_table_data, ['study']+self._sorters) print(self._accuracy_table_data) self.refresh() def _open_study_sorter_fig(self, *, sorter, study): self._study_sorter_fig.setStudySorter(study=study, sorter=sorter) def _get_accuracy_table_data(self, *, accuracy_threshold): SF = self._SF_data accuracy_table = [] sorters = set() for sname in SF.studyNames(): print('STUDY: '+sname) study = SF.study(sname) b = _get_study_sorting_results(study) tmp = dict( study=dict( # first column text=sname ) ) for sorter in b: sorters.add(sorter) a = b[sorter] accuracies = a['num_matches'] / \ (a['num_matches']+a['num_false_positives'] + a['num_false_negatives']) tmp[sorter] = dict( text=str(np.count_nonzero( accuracies >= accuracy_threshold)), callback=lambda sorter=sorter, study=sname: self._open_study_sorter_fig( sorter=sorter, study=study) ) accuracy_table.append(tmp) sorters = list(sorters) sorters.sort() return accuracy_table, sorters def _to_table(self, X, column_names): rows = [] rows.append(vd.tr([vd.th(cname) for cname in column_names])) for x in X: elmts = [] for cname in column_names: tmp = x.get(cname) if tmp: if 'callback' in tmp: elmt = vd.a(tmp['text'], onclick=tmp['callback']) else: elmt = vd.span(tmp['text']) else: elmt = vd.span('N/A') elmts.append(elmt) rows.append(vd.tr([vd.td(elmt) for elmt in elmts])) return vd.table(rows, class_='table') def render(self): return vd.div( vd.table( vd.tr( vd.td('Accuracy threshold:'), vd.td(self._accuracy_threshold_input), vd.td(self._update_button) ), class_='table', style={'max-width': '200px'} ), vd.components.ScrollArea( self._accuracy_table, height=500 ), self._study_sorter_fig, style=dict(padding='15px') ) def _get_study_sorting_results(study): results = [] for rname in study.recordingNames(): rec = study.recording(rname) true_units_info = rec.trueUnitsInfo(format='json') true_units_info_by_id = dict() for true_unit in true_units_info: true_units_info_by_id[true_unit['unit_id']] = true_unit for srname in rec.sortingResultNames(): a = rec.sortingResult(srname) res0 = dict(sorter=srname, recording=rname, study=study.name()) tmp = a.comparisonWithTruth(format='json') for i in tmp: tmp[i]['true_unit_info'] = true_units_info_by_id[tmp[i]['unit_id']] res0['comparison_with_truth'] = tmp results.append(res0) sorters = list(set([a['sorter'] for a in results])) sorters.sort() units_by_sorter = dict() for sorter in sorters: units_by_sorter[sorter] = [] for obj in results: sorter0 = obj['sorter'] units = [obj['comparison_with_truth'][i] for i in obj['comparison_with_truth']] units_by_sorter[sorter0] = units_by_sorter[sorter0]+units ret = dict() for sorter in sorters: units = units_by_sorter[sorter] try: ret[sorter] = dict( true_unit_ids=[unit['unit_id'] for unit in units], true_unit_snrs=np.array( [unit['true_unit_info']['snr'] for unit in units]), true_unit_firing_rates=np.array( [unit['true_unit_info']['firing_rate'] for unit in units]), num_matches=np.array([unit['num_matches'] for unit in units]), num_false_positives=np.array( [unit['num_false_positives'] for unit in units]), num_false_negatives=np.array( [unit['num_false_negatives'] for unit in units]) ) except: print('WARNING: Problem loading results for sorter: '+sorter) ret[sorter] = dict( true_unit_ids=[], true_unit_snrs=np.array([]), true_unit_firing_rates=np.array([]), num_matches=np.array([]), num_false_positives=np.array([]), num_false_negatives=np.array([]) ) return ret
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import sys import unittest from unittest import mock from warnings import catch_warnings from scrapy.exceptions import ScrapyDeprecationWarning from scrapy.item import ABCMeta, DictItem, Field, Item, ItemMeta PY36_PLUS = (sys.version_info.major >= 3) and (sys.version_info.minor >= 6) class ItemTest(unittest.TestCase): def assertSortedEqual(self, first, second, msg=None): return self.assertEqual(sorted(first), sorted(second), msg) def test_simple(self): class TestItem(Item): name = Field() i = TestItem() i['name'] = u'name' self.assertEqual(i['name'], u'name') def test_init(self): class TestItem(Item): name = Field() i = TestItem() self.assertRaises(KeyError, i.__getitem__, 'name') i2 = TestItem(name=u'john doe') self.assertEqual(i2['name'], u'john doe') i3 = TestItem({'name': u'john doe'}) self.assertEqual(i3['name'], u'john doe') i4 = TestItem(i3) self.assertEqual(i4['name'], u'john doe') self.assertRaises(KeyError, TestItem, {'name': u'john doe', 'other': u'foo'}) def test_invalid_field(self): class TestItem(Item): pass i = TestItem() self.assertRaises(KeyError, i.__setitem__, 'field', 'text') self.assertRaises(KeyError, i.__getitem__, 'field') def test_repr(self): class TestItem(Item): name = Field() number = Field() i = TestItem() i['name'] = u'John Doe' i['number'] = 123 itemrepr = repr(i) self.assertEqual(itemrepr, "{'name': 'John Doe', 'number': 123}") i2 = eval(itemrepr) self.assertEqual(i2['name'], 'John Doe') self.assertEqual(i2['number'], 123) def test_private_attr(self): class TestItem(Item): name = Field() i = TestItem() i._private = 'test' self.assertEqual(i._private, 'test') def test_raise_getattr(self): class TestItem(Item): name = Field() i = TestItem() self.assertRaises(AttributeError, getattr, i, 'name') def test_raise_setattr(self): class TestItem(Item): name = Field() i = TestItem() self.assertRaises(AttributeError, setattr, i, 'name', 'john') def test_custom_methods(self): class TestItem(Item): name = Field() def get_name(self): return self['name'] def change_name(self, name): self['name'] = name i = TestItem() self.assertRaises(KeyError, i.get_name) i['name'] = u'lala' self.assertEqual(i.get_name(), u'lala') i.change_name(u'other') self.assertEqual(i.get_name(), 'other') def test_metaclass(self): class TestItem(Item): name = Field() keys = Field() values = Field() i = TestItem() i['name'] = u'John' self.assertEqual(list(i.keys()), ['name']) self.assertEqual(list(i.values()), ['John']) i['keys'] = u'Keys' i['values'] = u'Values' self.assertSortedEqual(list(i.keys()), ['keys', 'values', 'name']) self.assertSortedEqual(list(i.values()), [u'Keys', u'Values', u'John']) def test_metaclass_with_fields_attribute(self): class TestItem(Item): fields = {'new': Field(default='X')} item = TestItem(new=u'New') self.assertSortedEqual(list(item.keys()), ['new']) self.assertSortedEqual(list(item.values()), [u'New']) def test_metaclass_inheritance(self): class BaseItem(Item): name = Field() keys = Field() values = Field() class TestItem(BaseItem): keys = Field() i = TestItem() i['keys'] = 3 self.assertEqual(list(i.keys()), ['keys']) self.assertEqual(list(i.values()), [3]) def test_metaclass_multiple_inheritance_simple(self): class A(Item): fields = {'load': Field(default='A')} save = Field(default='A') class B(A): pass class C(Item): fields = {'load': Field(default='C')} save = Field(default='C') class D(B, C): pass item = D(save='X', load='Y') self.assertEqual(item['save'], 'X') self.assertEqual(item['load'], 'Y') self.assertEqual(D.fields, {'load': {'default': 'A'}, 'save': {'default': 'A'}}) # D class inverted class E(C, B): pass self.assertEqual(E(save='X')['save'], 'X') self.assertEqual(E(load='X')['load'], 'X') self.assertEqual(E.fields, {'load': {'default': 'C'}, 'save': {'default': 'C'}}) def test_metaclass_multiple_inheritance_diamond(self): class A(Item): fields = {'update': Field(default='A')} save = Field(default='A') load = Field(default='A') class B(A): pass class C(A): fields = {'update': Field(default='C')} save = Field(default='C') class D(B, C): fields = {'update': Field(default='D')} load = Field(default='D') self.assertEqual(D(save='X')['save'], 'X') self.assertEqual(D(load='X')['load'], 'X') self.assertEqual(D.fields, {'save': {'default': 'C'}, 'load': {'default': 'D'}, 'update': {'default': 'D'}}) # D class inverted class E(C, B): load = Field(default='E') self.assertEqual(E(save='X')['save'], 'X') self.assertEqual(E(load='X')['load'], 'X') self.assertEqual(E.fields, {'save': {'default': 'C'}, 'load': {'default': 'E'}, 'update': {'default': 'C'}}) def test_metaclass_multiple_inheritance_without_metaclass(self): class A(Item): fields = {'load': Field(default='A')} save = Field(default='A') class B(A): pass class C(object): fields = {'load': Field(default='C')} not_allowed = Field(default='not_allowed') save = Field(default='C') class D(B, C): pass self.assertRaises(KeyError, D, not_allowed='value') self.assertEqual(D(save='X')['save'], 'X') self.assertEqual(D.fields, {'save': {'default': 'A'}, 'load': {'default': 'A'}}) # D class inverted class E(C, B): pass self.assertRaises(KeyError, E, not_allowed='value') self.assertEqual(E(save='X')['save'], 'X') self.assertEqual(E.fields, {'save': {'default': 'A'}, 'load': {'default': 'A'}}) def test_to_dict(self): class TestItem(Item): name = Field() i = TestItem() i['name'] = u'John' self.assertEqual(dict(i), {'name': u'John'}) def test_copy(self): class TestItem(Item): name = Field() item = TestItem({'name': 'lower'}) copied_item = item.copy() self.assertNotEqual(id(item), id(copied_item)) copied_item['name'] = copied_item['name'].upper() self.assertNotEqual(item['name'], copied_item['name']) def test_deepcopy(self): class TestItem(Item): tags = Field() item = TestItem({'tags': ['tag1']}) copied_item = item.deepcopy() item['tags'].append('tag2') assert item['tags'] != copied_item['tags'] def test_dictitem_deprecation_warning(self): """Make sure the DictItem deprecation warning is not issued for Item""" with catch_warnings(record=True) as warnings: item = Item() self.assertEqual(len(warnings), 0) class SubclassedItem(Item): pass subclassed_item = SubclassedItem() self.assertEqual(len(warnings), 0) class ItemMetaTest(unittest.TestCase): def test_new_method_propagates_classcell(self): new_mock = mock.Mock(side_effect=ABCMeta.__new__) base = ItemMeta.__bases__[0] with mock.patch.object(base, '__new__', new_mock): class MyItem(Item): if not PY36_PLUS: # This attribute is an internal attribute in Python 3.6+ # and must be propagated properly. See # https://docs.python.org/3.6/reference/datamodel.html#creating-the-class-object # In <3.6, we add a dummy attribute just to ensure the # __new__ method propagates it correctly. __classcell__ = object() def f(self): # For rationale of this see: # https://github.com/python/cpython/blob/ee1a81b77444c6715cbe610e951c655b6adab88b/Lib/test/test_super.py#L222 return __class__ # noqa https://github.com/scrapy/scrapy/issues/2836 MyItem() (first_call, second_call) = new_mock.call_args_list[-2:] mcs, class_name, bases, attrs = first_call[0] assert '__classcell__' not in attrs mcs, class_name, bases, attrs = second_call[0] assert '__classcell__' in attrs class ItemMetaClassCellRegression(unittest.TestCase): def test_item_meta_classcell_regression(self): class MyItem(Item, metaclass=ItemMeta): def __init__(self, *args, **kwargs): # This call to super() trigger the __classcell__ propagation # requirement. When not done properly raises an error: # TypeError: __class__ set to <class '__main__.MyItem'> # defining 'MyItem' as <class '__main__.MyItem'> super(MyItem, self).__init__(*args, **kwargs) class DictItemTest(unittest.TestCase): def test_deprecation_warning(self): with catch_warnings(record=True) as warnings: dict_item = DictItem() self.assertEqual(len(warnings), 1) self.assertEqual(warnings[0].category, ScrapyDeprecationWarning) with catch_warnings(record=True) as warnings: class SubclassedDictItem(DictItem): pass subclassed_dict_item = SubclassedDictItem() self.assertEqual(len(warnings), 1) self.assertEqual(warnings[0].category, ScrapyDeprecationWarning) if __name__ == "__main__": unittest.main()
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""" A CapitalT class and methods that use the Cross class. Authors: David Mutchler, Vibha Alangar, Dave Fisher, Amanda Stouder, their colleagues and Xiaolong Chen (Harry). """ # DONE: 1. PUT YOUR NAME IN THE ABOVE LINE. import rosegraphics as rg import math def main(): """ Calls the test functions. As you implement CapitalT method uncomment the appropriate tests. """ # -------------------------------------------------------------- # Uncomment only 1 test at a time as you develop your code. # -------------------------------------------------------------- print('Un-comment the calls in MAIN one by one') print(' to run the testing code as you complete the TODOs.') run_test_simple_t() run_test_set_colors() run_test_move_by() run_test_clone() def run_test_simple_t(): """ Tests for the __init__ method and attach_to method. See the simple_t PDF for expected output. """ print() print('--------------------------------------------------') print('Testing __init__ and attach_to ') print('--------------------------------------------------') window = rg.RoseWindow(600, 400, 'Test 1 - Simple Ts') t1 = CapitalT(rg.Point(300, 50), 100, 200, 20) print("Expected: Point(250.0, 40.0) Point(350.0, 60.0)") print("Actual: ", t1.h_rect.get_upper_left_corner(), t1.h_rect.get_lower_right_corner()) print("Expected: Point(290.0, 40.0) Point(310.0, 240.0)") print("Actual: ", t1.v_rect.get_upper_left_corner(), t1.v_rect.get_lower_right_corner()) t1.attach_to(window) t2 = CapitalT(rg.Point(150, 150), 100, 150, 40) t2.attach_to(window) t3 = CapitalT(rg.Point(450, 150), 10, 15, 4) t3.attach_to(window) window.render() print("See graphics window and compare to the simple_t PDF") window.close_on_mouse_click() def run_test_set_colors(): """ Tests for the set_colors method. See the set_colors PDF for expected output. """ window = rg.RoseWindow(600, 400, 'Test 2 - Colorful Ts') t1 = CapitalT(rg.Point(300, 50), 100, 200, 20) t1.set_colors('red', 'magenta') t1.attach_to(window) t2 = CapitalT(rg.Point(150, 150), 100, 150, 40) t2.set_colors('green', 'purple') t2.attach_to(window) t3 = CapitalT(rg.Point(450, 150), 10, 15, 4) t3.set_colors('blue', 'gray') t3.attach_to(window) window.render() window.close_on_mouse_click() def run_test_move_by(): """ Tests for the move_by method. See the move_by PDF for expected output. """ window = rg.RoseWindow(600, 400, 'Test 3 - Moving T') little_red_t = CapitalT(rg.Point(300, 50), 60, 80, 5) little_red_t.set_colors('red', 'gray') little_red_t.attach_to(window) window.render(0.5) little_red_t.move_by(0, 100) window.render(0.5) little_red_t.move_by(0, 100) window.render(0.5) for k in range(40): little_red_t.move_by(5, -2) window.render(0.05) window.close_on_mouse_click() def run_test_clone(): """ Tests for the clone method. See the clone PDF for expected output. """ window = rg.RoseWindow(650, 400, 'Test 4 - Cloning Ts') first_t = CapitalT(rg.Point(75, 50), 80, 80, 40) first_t.set_colors('blue', 'cyan') for k in range(6): t = first_t.clone() if k < 2: t.set_colors('white', 'black') t.move_by(100 * k, 20 * k) t.attach_to(window) first_t.move_by(0, 200) first_t.attach_to(window) window.render() window.close_on_mouse_click() ######################################################################## # The CapitalT class (and its methods) begins here. ######################################################################## class CapitalT(object): """ Manages a CapitalT graphics object which is made up of two rectangles. See the PDFs, especially dimenstions.pdf, to help you understand this. """ def __init__(self, intersection_center, width, height, letter_thickness): """ What comes in: -- self -- an rg.Point for the intersection center of the CapitalT -- This point is also center of the horizontal rectangle. -- a int for the width of the CapitalT (the width of the horizontal rectangle) -- a int for the height of the CapitalT (the height of the vertical rectangle) -- a int for the thickness of each rectangle (the letter's thickness) What goes out: Nothing (i.e., None). Side effects: Sets two instance variables named: -- h_rect (to represent the horizontal rectangle in the T, the top bar) -- v_rect (to represent the vertical rectangle in the T, the | part of the T) *** See the dimensions PDF for the exact placement of the rectangles in the T. *** Each rectangle is an rg.Rectangle. Unlike prior modules you are NOT allowed to make any other instance variables. You may only use exactly these two and must figure out how to do the problem with ONLY those two instance variables. Example: t1 = CapitalT(rg.Point(300, 50), 100, 200, 20) -- t1.h_rect would have an upper left corner of (250, 40) -- t1.h_rect would have an lower right corner of (350, 60) -- t1.v_rect would have an upper left corner of (290, 40) -- t1.v_rect would have an lower right corner of (310, 240) Type hints: :type intersection_center: rg.Point :type width: int :type height: int :type letter_thickness: int """ hupperright = rg.Point(intersection_center.x+(1/2)*width, intersection_center.y-(1/2)*letter_thickness) hlowerleft = rg.Point(intersection_center.x-(1/2)*width,intersection_center.y+(1/2)*letter_thickness) self.h_rect = rg.Rectangle(hupperright,hlowerleft) vupperright = rg.Point(intersection_center.x + (1/2)*letter_thickness,hupperright.y) vlowerleft = rg.Point(intersection_center.x-(1/2)*letter_thickness,hlowerleft.y+(height-letter_thickness)) self.v_rect = rg.Rectangle(vupperright, vlowerleft) # -------------------------------------------------------------- # DONE: 3. # READ the above specification, including the Example. # Implement this method # Note: you will need to also implement attach_to before testing # -------------------------------------------------------------- def attach_to(self, window): """ What comes in: -- self -- an rg.RoseWindow What goes out: Nothing (i.e., None). Side effects: -- Attaches both instance rectangles to the given window. -- Hint: Attach h_rect second to make it draw in front of v_rect Example: window = rg.RoseWindow() t1 = CapitalT(rg.Point(300, 50), 100, 200, 20) t1.attach_to(window) Type hints: :type window: rg.RoseWindow """ self.v_rect.attach_to(window) self.h_rect.attach_to(window) # -------------------------------------------------------------- # DONE: 4. # READ the above specification, including the Example. # Implement and test this method by looking at the console and # the graphics window (compare it to simple_t.pdf) # -------------------------------------------------------------- def set_colors(self, fill_color, outline_color): """ What comes in: -- self -- a string that represents a valid rosegraphics color -- a string that represents a valid rosegraphics color What goes out: Nothing (i.e., None). Side effects: -- sets the fill_color of both rectangles to the given fill color -- sets the outline_color of both rectangles to the given outline color Example: window = rg.RoseWindow() t1 = CapitalT(rg.Point(300, 50), 100, 200, 20) t1.set_color('red', 'blue') Type hints: :type fill_color: str :type outline_color: str """ self.h_rect.fill_color = fill_color self.v_rect.fill_color = fill_color self.h_rect.outline_color = outline_color self.v_rect.outline_color =outline_color # -------------------------------------------------------------- # DONE: 5. # READ the above specification, including the Example. # Implement and test this method by uncommenting the appropriate # run_test method in main. Compare the graphics window to # set_colors.pdf. # -------------------------------------------------------------- def move_by(self, dx, dy): """ What comes in: -- self -- an int amount to move in the x direction -- an int amount to move in the y direction What goes out: Nothing (i.e., None). Side effects: -- Moves both h_rect and v_rect the specified dx and dy amounts. Example: window = rg.RoseWindow() t1 = CapitalT(rg.Point(300, 50), 100, 200, 20) t1.attach_to(window) window.render(0.5) t1.move_by(100, 200) # Moves the T 100 pixels right and 200 down. window.render() # necessary to see the change Type hints: :type dx: int :type dy: int """ self.h_rect.corner_1.x +=dx self.h_rect .corner_2.x +=dx self.h_rect.corner_1.y += dy self.h_rect.corner_2.y += dy self.v_rect.corner_1.x += dx self.v_rect.corner_2.x += dx self.v_rect.corner_1.y += dy self.v_rect.corner_2.y += dy # -------------------------------------------------------------- # DONE: 6. # READ the above specification, including the Example. # Implement and test this method by uncommenting the appropriate # run_test method in main. Compare the graphics window to # move_by.pdf. Note: the pdf shows the different locations # that the T moves through, but there is only 1 T at any moment. # -------------------------------------------------------------- def clone(self): """ What comes in: -- self What goes out: -- Returns a new CapitalT that is located in the same position as this CapitalT with the same colors for the rectangles. Side effects: -- None Example: window = rg.RoseWindow() t1 = CapitalT(rg.Point(300, 50), 100, 200, 20) t1.set_color('red', 'blue') t2 = t1.clone() # t2 is at the same location WITH THE SAME COLORS Type hints: :rtype: CapitalT """ h = self.h_rect v = self.v_rect intersect = rg.Point((1/2)*h.get_upper_right_corner().x,(1/2)*h.get_upper_right_corner().y+h.get_lower_left_corner().y) thickness = math.fabs(h.get_upper_right_corner().y-h.get_lower_left_corner().y) clone = CapitalT(intersect,h.get_width(),v.get_height(),thickness) clone.set_colors(self.h_rect.fill_color,self.h_rect .outline_color) return clone # -------------------------------------------------------------- # DONE: 7. # READ the above specification, including the Example. # Implement and test this method by uncommenting the appropriate # run_test method in main. Compare the graphics window to # clone.pdf. # -------------------------------------------------------------- # ---------------------------------------------------------------------- # If this module is running at the top level (as opposed to being # imported by another module), then call the 'main' function. # ---------------------------------------------------------------------- if __name__ == '__main__': main()
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import time from collections import deque from datetime import datetime import backtrader as bt from backtrader.feed import DataBase from backtrader.utils.py3 import with_metaclass from .cryptostore import CryptoStore class MetaCryptoFeed(DataBase.__class__): def __init__(cls, name, bases, dct): '''Class has already been created ... register''' # Initialize the class super(MetaCryptoFeed, cls).__init__(name, bases, dct) # Register with the store CryptoStore.DataCls = cls class CryptoFeed(with_metaclass(MetaCryptoFeed, DataBase)): """ CryptoCurrency eXchange Trading Library Data Feed. Params: - ``historical`` (default: ``False``) If set to ``True`` the data feed will stop after doing the first download of data. The standard data feed parameters ``fromdate`` and ``todate`` will be used as reference. - ``backfill_start`` (default: ``True``) Perform backfilling at the start. The maximum possible historical data will be fetched in a single request. Changes From Ed's pacakge - Added option to send some additional fetch_ohlcv_params. Some exchanges (e.g Bitmex) support sending some additional fetch parameters. - Added drop_newest option to avoid loading incomplete candles where exchanges do not support sending ohlcv params to prevent returning partial data """ params = ( ('historical', False), # only historical download ('backfill_start', False), # do backfilling at the start ('fetch_ohlcv_params', {}), ('ohlcv_limit', 20), ('drop_newest', False), ('debug', False) ) _store = CryptoStore # States for the Finite State Machine in _load _ST_LIVE, _ST_HISTORBACK, _ST_OVER = range(3) # def __init__(self, exchange, symbol, ohlcv_limit=None, config={}, retries=5): def __init__(self, **kwargs): # self.store = CryptoStore(exchange, config, retries) self.store = self._store(**kwargs) self._data = deque() # data queue for price data self._last_id = '' # last processed trade id for ohlcv self._last_ts = 0 # last processed timestamp for ohlcv self._ts_delta = None # timestamp delta for ohlcv def start(self, ): DataBase.start(self) if self.p.fromdate: self._state = self._ST_HISTORBACK self.put_notification(self.DELAYED) self._fetch_ohlcv(self.p.fromdate) else: self._state = self._ST_LIVE self.put_notification(self.LIVE) def _load(self): if self._state == self._ST_OVER: return False while True: if self._state == self._ST_LIVE: if self._timeframe == bt.TimeFrame.Ticks: return self._load_ticks() else: # INFO: Fix to address slow loading time after enter into LIVE state. if len(self._data) == 0: # INFO: Only call _fetch_ohlcv when self._data is fully consumed as it will cause execution # inefficiency due to network latency. Furthermore it is extremely inefficiency to fetch # an amount of bars but only load one bar at a given time. self._fetch_ohlcv() ret = self._load_ohlcv() if self.p.debug: print('---- LOAD ----') print('{} Load OHLCV Returning: {}'.format(datetime.utcnow(), ret)) return ret elif self._state == self._ST_HISTORBACK: ret = self._load_ohlcv() if ret: return ret else: # End of historical data if self.p.historical: # only historical self.put_notification(self.DISCONNECTED) self._state = self._ST_OVER return False # end of historical else: self._state = self._ST_LIVE self.put_notification(self.LIVE) def _fetch_ohlcv(self, fromdate=None): """Fetch OHLCV data into self._data queue""" granularity = self.store.get_granularity(self._timeframe, self._compression) if self.store.cache is not None and self.p.todate: print("Loading from cache", self.p.dataname, granularity, fromdate, self.p.todate) data = sorted(self.store.cache.query(self.p.dataname, granularity, fromdate, self.p.todate)) if self.p.drop_newest: del data[-1] if len(data) > 0: self._data.extend(data) self._last_ts = data[-1][0] else: till = int((self.p.todate - datetime(1970, 1, 1)).total_seconds() * 1000) if self.p.todate else None if fromdate: since = int((fromdate - datetime(1970, 1, 1)).total_seconds() * 1000) else: if self._last_ts > 0: if self._ts_delta is None: since = self._last_ts else: since = self._last_ts + self._ts_delta else: since = None limit = self.p.ohlcv_limit while True: dlen = len(self._data) if self.p.debug: # TESTING since_dt = datetime.utcfromtimestamp(since // 1000) if since is not None else 'NA' print('---- NEW REQUEST ----') print('{} - Requesting: Since TS:{} Since date:{} granularity:{}, limit:{}, params:{}'.format( datetime.utcnow(), since, since_dt, granularity, limit, self.p.fetch_ohlcv_params)) data = sorted(self.store.fetch_ohlcv(self.p.dataname, timeframe=granularity, since=since, limit=limit, params=self.p.fetch_ohlcv_params)) try: for i, ohlcv in enumerate(data): tstamp, open_, high, low, close, volume = ohlcv print('{} - Data {}: {} - TS {} Time {}'.format(datetime.utcnow(), i, datetime.utcfromtimestamp(tstamp // 1000), tstamp, (time.time() * 1000))) # ------------------------------------------------------------------ except IndexError: print('Index Error: Data = {}'.format(data)) print('---- REQUEST END ----') else: data = sorted(self.store.fetch_ohlcv(self.p.dataname, timeframe=granularity, since=since, limit=limit, params=self.p.fetch_ohlcv_params)) # Check to see if dropping the latest candle will help with # exchanges which return partial data if self.p.drop_newest: del data[-1] prev_tstamp = None tstamp = None for ohlcv in data: if None in ohlcv: continue tstamp = ohlcv[0] if prev_tstamp is not None and self._ts_delta is None: # INFO: Record down the TS delta so that it can be used to increment since TS self._ts_delta = tstamp - prev_tstamp # Prevent from loading incomplete data # if tstamp > (time.time() * 1000): # continue if tstamp > self._last_ts: if self.p.debug: print('Adding: {}'.format(ohlcv)) self._data.append(ohlcv) self._last_ts = tstamp if till and tstamp >= till: break if prev_tstamp is None: prev_tstamp = tstamp # print("?", tstamp, till, dlen, len(self._data)) if till and tstamp is not None: if tstamp >= till: break since = tstamp if dlen == len(self._data): break def _load_ticks(self): if self._last_id is None: # first time get the latest trade only trades = [self.store.fetch_trades(self.p.dataname)[-1]] else: trades = self.store.fetch_trades(self.p.dataname) if len(trades) <= 1: if len(trades) == 1: trade = trades[0] trade_time = datetime.strptime(trade['datetime'], '%Y-%m-%dT%H:%M:%S.%fZ') self._data.append((trade_time, float(trade['price']), float(trade['amount']))) else: trade_dict_list = [] index = 0 # Since we only need the last 2 trades, just loop through the last 2 trades to speed up the for loop for trade in trades[-2:]: trade_id = trade['id'] if trade_id > self._last_id: trade_time = datetime.strptime(trade['datetime'], '%Y-%m-%dT%H:%M:%S.%fZ') trade_dict = dict(index=index, trade_time=trade_time, price=float(trade['price']), amount=float(trade['amount'])) trade_dict_list.append(trade_dict) self._last_id = trade_id index += 1 if len(trade_dict_list) > 0: # The order of self._data should be in reversed order by trade datetime reverse = True selection_key = 'index' trade_dict_list.sort(key = lambda k: k[selection_key], reverse = reverse) # sorts in place for trade_dict in trade_dict_list: self._data.append((trade_dict['trade_time'], trade_dict['price'], trade_dict['amount'])) # Break here once we got the first data is sufficient as we only look for the first data break try: trade = self._data.popleft() except IndexError: return None # no data in the queue trade_time, price, size = trade self.lines.datetime[0] = bt.date2num(trade_time) self.lines.open[0] = price self.lines.high[0] = price self.lines.low[0] = price self.lines.close[0] = price self.lines.volume[0] = size return True def _load_ohlcv(self): try: ohlcv = self._data.popleft() except IndexError: return None # no data in the queue tstamp, open_, high, low, close, volume = ohlcv dtime = datetime.utcfromtimestamp(tstamp // 1000) self.lines.datetime[0] = bt.date2num(dtime) self.lines.open[0] = open_ self.lines.high[0] = high self.lines.low[0] = low self.lines.close[0] = close self.lines.volume[0] = volume return True def haslivedata(self): return self._state == self._ST_LIVE and self._data def islive(self): return not self.p.historical
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"""This script creates some informative graphs on subgroups of income quartile, gender, and race.""" # %% import os import matplotlib.pyplot as plt import seaborn as sns from pathlib import Path # %% # Set up folder path code_folder = Path(os.path.abspath('')) print(code_folder) project_dir = os.path.dirname(code_folder) os.chdir(project_dir) print(project_dir) # %% from setup_fin_dataset import get_dataset # %% os.chdir(code_folder) print(code_folder) # %% '''Plot scores by income quartile ''' df = get_dataset() #%% df.dropna(axis=0, how='any', subset=['AFQT_1','ROSENBERG_SCORE', 'ROTTER_SCORE'], inplace=True) # %% ax = plt.figure().add_subplot(111) for group in ['first quartile', 'second quartile', 'third quartile', 'fourth quartile']: cond = df['FAMILY_INCOME_QUARTILE'] == group dat = df.loc[df['SURVEY_YEAR'] == 1978, ['AFQT_1']].loc[cond].dropna() sns.distplot(dat, label=group.capitalize()) csfont = {'fontname':'Times New Roman'} ax.yaxis.get_major_ticks()[0].set_visible(False) ax.set_xlabel('AFQT Scores', **csfont) ax.set_xlim([0, 120]) ax.legend() ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.savefig('fig-inc-quartile-afqt.png') for score in ['ROTTER', 'ROSENBERG']: ax = plt.figure().add_subplot(111) for group in ['first quartile', 'second quartile', 'third quartile', 'fourth quartile']: label = score + '_SCORE' cond = df['FAMILY_INCOME_QUARTILE'] == group dat = df[cond].loc[df['SURVEY_YEAR'] == 1978, [label]].dropna() sns.distplot(dat, label=group) ax.set_xlabel(score.lower().capitalize() + ' Scores', **csfont) if score == 'ROTTER': plt.gca().invert_xaxis() ax.yaxis.get_major_ticks()[0].set_visible(False) ax.legend() ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.savefig('fig-inc-quartile-' + score.lower() + '.png') # %% '''Plot scores by gender ''' df = get_dataset() #%% df.dropna(axis=0, how='any', subset=['AFQT_1','ROSENBERG_SCORE', 'ROTTER_SCORE'], inplace=True) ax = plt.figure().add_subplot(111) for group in [1, 2]: cond = df['GENDER'] == group dat = df.loc[df['SURVEY_YEAR'] == 1978, ['AFQT_1']].loc[cond].dropna() sns.distplot(dat, label=group) csfont = {'fontname':'Times New Roman'} ax.yaxis.get_major_ticks()[0].set_visible(False) ax.set_xlabel('AFQT Scores', **csfont) ax.set_xlim([0, 120]) ax.legend() ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.savefig('fig-aptitude-gender.png') for score in ['ROTTER', 'ROSENBERG']: ax = plt.figure().add_subplot(111) for group in [1, 2]: label = score + '_SCORE' cond = df['GENDER'] == group dat = df[cond].loc[df['SURVEY_YEAR'] == 1978, [label]].dropna() sns.distplot(dat, label=group) ax.set_xlabel(score.lower().capitalize() + ' Scores', **csfont) if score == 'ROTTER': plt.gca().invert_xaxis() ax.yaxis.get_major_ticks()[0].set_visible(False) ax.legend() ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.savefig('fig-attitude-gender-' + score.lower() + '.png') # %% '''Plot scores by race ''' df = get_dataset() #%% df.dropna(axis=0, how='any', subset=['AFQT_1','ROSENBERG_SCORE', 'ROTTER_SCORE'], inplace=True) ax = plt.figure().add_subplot(111) for group in [1, 2, 3]: cond = df['RACE'] == group dat = df.loc[df['SURVEY_YEAR'] == 1978, ['AFQT_1']].loc[cond].dropna() sns.distplot(dat, label=group) csfont = {'fontname':'Times New Roman'} ax.yaxis.get_major_ticks()[0].set_visible(False) ax.set_xlabel('AFQT Scores', **csfont) ax.set_xlim([0, 120]) ax.legend() ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.savefig('fig-aptitude-race.png') for score in ['ROTTER', 'ROSENBERG']: ax = plt.figure().add_subplot(111) for group in [1, 2, 3]: label = score + '_SCORE' cond = df['RACE'] == group dat = df[cond].loc[df['SURVEY_YEAR'] == 1978, [label]].dropna() sns.distplot(dat, label=group) ax.set_xlabel(score.lower().capitalize() + ' Scores', **csfont) if score == 'ROTTER': plt.gca().invert_xaxis() ax.yaxis.get_major_ticks()[0].set_visible(False) ax.legend() ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.savefig('fig-attitude-race-' + score.lower() + '.png') # %% '''Plot by parental educational attainment, mother ''' df = get_dataset() #%% df.dropna(axis=0, how='any', subset=['AFQT_1','ROSENBERG_SCORE', 'ROTTER_SCORE'], inplace=True) # %% df['MOTHER_EDU'].nunique() # %% df['FATHER_EDU'].nunique() # %% df_mother = df.groupby('MOTHER_EDU')['IDENTIFIER'].nunique().sort_values(ascending=False) df_mother # %% df_father = df.groupby('FATHER_EDU')['IDENTIFIER'].nunique().sort_values(ascending=False) df_father # %% ax = plt.figure().add_subplot(111) for group in ['Less than HS', 'HS or more']: cond = df['MOTHER_EDU'] == group dat = df['AFQT_1'].loc[cond].dropna() sns.distplot(dat, label=group) csfont = {'fontname':'Times New Roman'} ax.yaxis.get_major_ticks()[0].set_visible(False) ax.set_xlabel('AFQT Scores', **csfont) ax.set_xlim([0, 120]) ax.legend() ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.savefig('fig-aptitude-mother-edu.png') for score in ['ROTTER', 'ROSENBERG']: ax = plt.figure().add_subplot(111) for group in ['Less than HS', 'HS or more']: label = score + '_SCORE' cond = df['MOTHER_EDU'] == group dat = df[cond].loc[df['SURVEY_YEAR'] == 1978, [label]].dropna() sns.distplot(dat, label=group) ax.set_xlabel(score.lower().capitalize() + ' Scores', **csfont) if score == 'ROTTER': plt.gca().invert_xaxis() ax.yaxis.get_major_ticks()[0].set_visible(False) ax.legend() ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.savefig('fig-attitude-mother-edu-' + score.lower() + '.png') # %% '''Plot by parental educational attainment, father ''' # %% df = get_dataset() #%% df.dropna(axis=0, how='any', subset=['AFQT_1','ROSENBERG_SCORE', 'ROTTER_SCORE'], inplace=True) ax = plt.figure().add_subplot(111) for group in ['Less than HS', 'HS or more']: cond = df['FATHER_EDU'] == group dat = df['AFQT_1'].loc[cond].dropna() sns.distplot(dat, label=group) csfont = {'fontname':'Times New Roman'} ax.yaxis.get_major_ticks()[0].set_visible(False) ax.set_xlabel('AFQT Scores', **csfont) ax.set_xlim([0, 120]) ax.legend() ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.savefig('fig-aptitude-father-edu.png') for score in ['ROTTER', 'ROSENBERG']: ax = plt.figure().add_subplot(111) for group in ['Less than HS', 'HS or more']: label = score + '_SCORE' cond = df['FATHER_EDU'] == group dat = df[cond].loc[df['SURVEY_YEAR'] == 1978, [label]].dropna() sns.distplot(dat, label=group) ax.set_xlabel(score.lower().capitalize() + ' Scores', **csfont) if score == 'ROTTER': plt.gca().invert_xaxis() ax.yaxis.get_major_ticks()[0].set_visible(False) ax.legend() ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.savefig('fig-attitude-father-edu-' + score.lower() + '.png') # %%
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import pytest import logging from traitlets.config.loader import PyFileConfigLoader from traitlets import TraitError from jupyter_telemetry.eventlog import EventLog GOOD_CONFIG = """ import logging c.EventLog.handlers = [ logging.StreamHandler() ] """ BAD_CONFIG = """ import logging c.EventLog.handlers = [ 0 ] """ def get_config_from_file(path, content): # Write config file filename = 'config.py' config_file = path / filename config_file.write_text(content) # Load written file. loader = PyFileConfigLoader(filename, path=str(path)) cfg = loader.load_config() return cfg def test_good_config_file(tmp_path): cfg = get_config_from_file(tmp_path, GOOD_CONFIG) # Pass config to EventLog e = EventLog(config=cfg) # Assert the assert len(e.handlers) > 0 assert isinstance(e.handlers[0], logging.Handler) def test_bad_config_file(tmp_path): cfg = get_config_from_file(tmp_path, BAD_CONFIG) with pytest.raises(TraitError): e = EventLog(config=cfg)
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""" Definition of the :class:`NativeRegistration` class. """ from pathlib import Path from typing import Tuple from typing import Union import nibabel as nib from brain_parts.parcellation.parcellations import ( Parcellation as parcellation_manager, ) from nilearn.image.resampling import resample_to_img from nipype.interfaces.base import TraitError from tqdm import tqdm from dmriprep_analyses.manager import DmriprepManager from dmriprep_analyses.registrations.messages import REFERENCE_FILE_MISSING from dmriprep_analyses.registrations.utils import DEFAULT_PARCELLATION_NAMING from dmriprep_analyses.registrations.utils import PROBSEG_THRESHOLD from dmriprep_analyses.registrations.utils import QUERIES from dmriprep_analyses.registrations.utils import TRANSFORMS class NativeRegistration(DmriprepManager): QUERIES = QUERIES #: Naming DEFAULT_PARCELLATION_NAMING = DEFAULT_PARCELLATION_NAMING #: Types of transformations TRANSFORMS = TRANSFORMS #: Default probability segmentations' threshold PROBSEG_THRESHOLD = PROBSEG_THRESHOLD def __init__( self, base_dir: Path, participant_labels: Union[str, list] = None, ) -> None: super().__init__(base_dir, participant_labels) self.parcellation_manager = parcellation_manager() def initiate_subject( self, participant_label: str ) -> Tuple[dict, Path, Path]: """ Query initially-required patricipant's files Parameters ---------- participant_label : str Specific participant's label to be queried Returns ------- Tuple[dict,Path,Path] A tuple of required files for parcellation registration. """ return [ grabber(participant_label, queries=self.QUERIES) for grabber in [ self.get_transforms, self.get_reference, self.get_probseg, ] ] def build_output_dictionary( self, parcellation_scheme: str, reference: Path, reference_type: str, ) -> dict: """ Based on a *reference* image, reconstruct output names for native parcellation naming. Parameters ---------- reference : Path The reference image. reference_type : str The reference image type (either "anat" or "dwi") Returns ------- dict A dictionary with keys of "whole-brain" and "gm-cropped" and their corresponding paths """ basic_query = dict( atlas=parcellation_scheme, resolution=reference_type, **self.DEFAULT_PARCELLATION_NAMING.copy(), ) outputs = dict() for key, label in zip(["whole_brain", "gm_cropped"], ["", "GM"]): query = basic_query.copy() query["label"] = label outputs[key] = self.data_grabber.build_path(reference, query) return outputs def register_to_anatomical( self, parcellation_scheme: str, participant_label: str, probseg_threshold: float = None, force: bool = False, ) -> dict: """ Register a *parcellation scheme* from standard to native anatomical space. # noqa Parameters ---------- parcellation_scheme : str A string representing existing key within *self.parcellation_manager.parcellations*. participant_label : str Specific participant's label probseg_threshold : float, optional Threshold for probability segmentation masking, by default None force : bool, optional Whether to re-write existing files, by default False Returns ------- dict A dictionary with keys of "whole_brain" and "gm_cropped" native-spaced parcellation schemes. """ transforms, reference, gm_probseg = self.initiate_subject( participant_label ) whole_brain, gm_cropped = [ self.build_output_dictionary( parcellation_scheme, reference, "anat" ).get(key) for key in ["whole_brain", "gm_cropped"] ] self.parcellation_manager.register_parcellation_scheme( parcellation_scheme, participant_label, reference, transforms.get("mni2native"), whole_brain, force=force, ) self.parcellation_manager.crop_to_probseg( parcellation_scheme, participant_label, whole_brain, gm_probseg, gm_cropped, masking_threshold=probseg_threshold or self.PROBSEG_THRESHOLD, force=force, ) return whole_brain, gm_cropped def register_dwi( self, parcellation_scheme: str, participant_label: str, session: str, anatomical_whole_brain: Path, anatomical_gm_cropped: Path, force: bool = False, ): """ Resample parcellation scheme from anatomical to DWI space. Parameters ---------- parcellation_scheme : str A string representing existing key within *self.parcellation_manager.parcellations*. # noqa participant_label : str Specific participant's label anatomical_whole_brain : Path Participant's whole-brain parcellation scheme in anatomical space anatomical_gm_cropped : Path Participant's GM-cropped parcellation scheme in anatomical space force : bool, optional Whether to re-write existing files, by default False """ reference = self.get_reference( participant_label, "dwi", {"session": session}, queries=self.QUERIES, ) if not reference: raise FileNotFoundError( REFERENCE_FILE_MISSING.format( participant_label=participant_label ) ) whole_brain, gm_cropped = [ self.build_output_dictionary( parcellation_scheme, reference, "dwi" ).get(key) for key in ["whole_brain", "gm_cropped"] ] for source, target in zip( [anatomical_whole_brain, anatomical_gm_cropped], [whole_brain, gm_cropped], ): if not target.exists() or force: img = resample_to_img( str(source), str(reference), interpolation="nearest" ) nib.save(img, target) return whole_brain, gm_cropped def run_single_subject( self, parcellation_scheme: str, participant_label: str, session: Union[str, list] = None, probseg_threshold: float = None, force: bool = False, ) -> dict: """ Parameters ---------- parcellation_scheme : str A string representing existing key within *self.parcellation_manager.parcellations*. # noqa participant_label : str Specific participant's label session : Union[str, list], optional Specific sessions available for *participant_label*, by default None # noqa probseg_threshold : float, optional Threshold for probability segmentation masking, by default None force : bool, optional Whether to re-write existing files, by default False Returns ------- dict A dictionary with keys of "anat" and available or requested sessions, and corresponding natice parcellations as keys. """ outputs = {} anat_whole_brain, anat_gm_cropped = self.register_to_anatomical( parcellation_scheme, participant_label, probseg_threshold, force ) outputs["anat"] = { "whole_brain": anat_whole_brain, "gm_cropped": anat_gm_cropped, } sessions = self.subjects.get(participant_label) or session if isinstance(sessions, str): sessions = [sessions] for session in sessions: whole_brain, gm_cropped = self.register_dwi( parcellation_scheme, participant_label, session, anat_whole_brain, anat_gm_cropped, force, ) outputs[session] = { "whole_brain": whole_brain, "gm_cropped": gm_cropped, } return outputs def run_dataset( self, parcellation_scheme: str, participant_label: Union[str, list] = None, probseg_threshold: float = None, force: bool = False, ): """ Register *parcellation_scheme* to all available (or requested) subjects' native space. Parameters ---------- parcellation_scheme : str A string representing existing key within *self.parcellation_manager.parcellations*. # noqa participant_label : Union[str, list], optional Specific subject/s within the dataset to run, by default None probseg_threshold : float, optional Threshold for probability segmentation masking, by default None force : bool, optional Whether to remove existing products and generate new ones, by default False # noqa """ native_parcellations = {} if participant_label: if isinstance(participant_label, str): participant_labels = [participant_label] elif isinstance(participant_label, list): participant_labels = participant_label else: participant_labels = list(sorted(self.subjects.keys())) for participant_label in tqdm(participant_labels): try: native_parcellations[ participant_label ] = self.run_single_subject( parcellation_scheme, participant_label, probseg_threshold=probseg_threshold, force=force, ) except (FileNotFoundError, TraitError): continue return native_parcellations
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""" Copyright (C) Microsoft Corporation. All rights reserved.​ ​ Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, royalty-free right to use, copy, and modify the software code provided by us ("Software Code"). You may not sublicense the Software Code or any use of it (except to your affiliates and to vendors to perform work on your behalf) through distribution, network access, service agreement, lease, rental, or otherwise. This license does not purport to express any claim of ownership over data you may have shared with Microsoft in the creation of the Software Code. Unless applicable law gives you more rights, Microsoft reserves all other rights not expressly granted herein, whether by implication, estoppel or otherwise. ​ ​ THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ import repackage repackage.add("../../azure-enterprise-scale-ml/esml/common/") import azureml.core from azureml.core.authentication import AzureCliAuthentication from esml import ESMLProject from baselayer_azure_ml import AutoMLFactory, azure_metric_regression,azure_metric_classification print("SDK Version:", azureml.core.VERSION) p = ESMLProject.get_project_from_env_command_line() p.describe() cli_auth = AzureCliAuthentication() ws = p.get_workspace_from_config(cli_auth) # Reads the current environment (dev,test, prod)config.json | Use CLI auth if MLOps p.init(ws) # Automapping from datalake to Azure ML datasets, prints status # FEATURE ENGINEERING # Feture engineering: Bronze 2 Gold - working with Azure ML Datasets with Bronze, Silver, Gold concept print("DEMO MLOPS FOLDER settings - remove this after you copies this folder)") # remove this after you copies this folder esml_dataset = p.DatasetByName("ds01_diabetes") # Get dataset df_bronze = esml_dataset.Bronze.to_pandas_dataframe() p.save_silver(esml_dataset,df_bronze) #Bronze -> Silver df = esml_dataset.Silver.to_pandas_dataframe() df_filtered = df[df.AGE > 0.015] gold_train = p.save_gold(df_filtered) #Silver -> Gold # SAVE GOLD - Last step that must happen gold_train = p.save_gold(df_filtered)
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''' This file defines the testing module. This needs the following: 1. The system under test 2. The specification or the function which we are trying to minimize 3. Domains of the uncertainities ''' from .optimizers import * from .func_tree import * from .utils import * from sklearn.decomposition import KernelPCA import copy import GPy class test_module: def __init__(self, sut, bounds, spec=None,f_tree=None, optimizer=None, normalizer=False,seed=None, **kwargs): self.system_under_test = sut # Choosing the optimizer function if spec is None: self.f_acqu = f_tree else: self.spec = spec # To implement parser to convert from specification to the function f self.bounds = bounds self.normalizer=normalizer self.seed=seed if 'cost_model' in kwargs: self.cost_model = kwargs['cost_model'] else: self.cost_model = lambda x: 1 # Choosing the optimizers if 'opt_name' in kwargs: self.optimizer = select_opt(kwargs[opt_name])(bounds, **kwargs) elif optimizer is None: self.optimizer = sample_opt(bounds=bounds, cost=self.cost_model) else: self.optimizer = optimizer # Number of samples for initializing GPs if 'init_sample' in kwargs: self.init_sample = kwargs['init_sample'] else: self.init_sample = 2*len(bounds) # Model GPs for the smooth functions if 'with_smooth' in kwargs: self.with_smooth = kwargs['with_smooth'] else: self.with_smooth = True # Model GPs for the top level requirement, potentially modeling # non-smooth function if 'with_ns' in kwargs: self.with_ns = kwargs['with_ns'] else: self.with_ns = False # Random sampling if 'with_random' in kwargs: self.with_random = kwargs['with_random'] else: self.with_random = False # Exploration weight for GP-LCB if 'exp_weight' in kwargs: self.k = kwargs['exp_weight'] else: self.k = 10 # Optimize retsrats for hyper parameter optimization for GPs if 'optimize_restarts' in kwargs: self.optimize_restarts = kwargs['optimize_restarts'] else: self.optimize_restarts = 1 # Search in lower dimension if 'low_dim' in kwargs: self.using_kpca=True self.low_dim = kwargs['low_dim'] if 'kernel_type' in kwargs: self.kernel = kwargs['kernel_type'](self.low_dim) elif 'kernel' in kwargs: self.kernel = kwargs['kernel'] self.using_kpca = True self.low_dim = self.kernel.input_dim else: self.using_kpca=False if 'kernel_type' in kwargs: self.kernel = kwargs['kernel_type'](len(bounds)) else: self.kernel = GPy.kern.Matern32(len(bounds), ARD=True) if self.using_kpca: if isinstance(self.optimizer, lbfgs_opt) or \ isinstance(self.optimizer, direct_opt): print('Can use only sample_opt or delta_opt!') print('Changing optimizer to sample_opt!') self.optimizer = sample_opt(bounds, **kwargs) # Sending in pre sampled data if 'X' in kwargs: self.X = kwargs['X'] else: self.X = [] def initialize(self): if len(self.X) == 0: X = sample_from(self.init_sample, self.bounds) self.X = X trajs = [] for x in self.X: trajs.append(self.system_under_test(x)) Y = self.f_acqu.eval_robustness(trajs) if self.with_smooth: self.smooth_X = copy.deepcopy(self.X) if self.using_kpca: self.kpca_s = KernelPCA(kernel='rbf', fit_inverse_transform=True, copy_X=True, n_components=self.low_dim) X_s = self.kpca_s.fit_transform(self.smooth_X) else: X_s = self.smooth_X self.f_acqu.init_GPs(X_s, trajs, kernel=copy.deepcopy(self.kernel), optimize_restarts=self.optimize_restarts, normalizer=self.normalizer) if self.with_ns: self.ns_X = copy.deepcopy(self.X) if self.using_kpca: self.kpca_ns = KernelPCA(kernel='rbf', fit_inverse_transform=True, copy_X=True, n_components=self.low_dim) X_ns = self.kpca_ns.fit_transform(self.ns_X) else: X_ns = copy.deepcopy(self.ns_X) self.ns_GP = GPy.models.GPRegression(X_ns, Y, kernel=copy.deepcopy(self.kernel), normalizer=self.normalizer) self.ns_GP.optimize_restarts(self.optimize_restarts) if self.with_random: self.random_X = copy.deepcopy(self.X) self.random_Y = Y def run_BO(self, iters_BO): for ib in range(iters_BO): print('BO iteration:', ib) if self.with_smooth: def f(x): if self.using_kpca: x_s = self.kpca_s.transform(x) else: x_s = x if isinstance(self.optimizer, lbfgs_opt): df = self.f_acqu.eval_df(x_s, k = self.k) else: df=None return self.f_acqu.evaluate(x_s, k=self.k), df x,f= self.optimizer.optimize(f=lambda x:f(x)[0], df = lambda x:f(x)[1]) self.smooth_X = np.vstack((self.smooth_X, np.atleast_2d(x))) trajs = [self.system_under_test(x_i) for x_i in x] if self.using_kpca: X_s = self.kpca_s.fit_transform(self.smooth_X) else: X_s = self.smooth_X self.f_acqu.update_GPs(X_s, trajs, optimize_restarts=self.optimize_restarts) if self.with_ns: def f(X): if self.using_kpca: X_ns = self.kpca_ns.transform(X) else: X_ns = X m,v = self.ns_GP.predict(X_ns) if isinstance(self.optimizer, lbfgs_opt): dm,dv = self.ns_GP.predictive_gradients(X_ns) dm = dm[:,:,0] df = dm - (self.k/2)*(dv/np.sqrt(v)) else: df =None return m - self.k*np.sqrt(v), df x,f = self.optimizer.optimize(f=lambda x: f(x)[0], df = lambda x:f(x)[1]) trajs = [self.system_under_test(x_i) for x_i in x] f_x = self.f_acqu.eval_robustness(trajs) self.ns_X = np.vstack((self.ns_X, np.atleast_2d(x))) if self.using_kpca: X_ns = self.kpca_ns.fit_transform(self.ns_X) else: X_ns = self.ns_X self.ns_GP.set_XY(X_ns, np.vstack((self.ns_GP.Y, np.atleast_2d(f_x)))) self.ns_GP.optimize_restarts(self.optimize_restarts) if self.with_random: if self.seed is not None: np.random.seed(self.seed) sample_from(self.init_sample, self.bounds) rand_x = sample_from(iters_BO, self.bounds) trajs = [] for x in rand_x: trajs.append(self.system_under_test(x)) self.random_X = np.vstack((self.random_X, rand_x)) rand_y = self.f_acqu.eval_robustness(trajs) self.random_Y = np.vstack((self.random_Y, rand_y)) if self.with_smooth: vals = self.f_acqu.find_GP_func() self.smooth_min_val = np.array(vals).min() self.smooth_min_loc = np.array(vals).argmin() self.smooth_min_x = self.smooth_X[self.smooth_min_loc] self.smooth_count = np.sum(np.array(vals) < 0) self.smooth_ce = np.flatnonzero(np.array(vals) < 0) if self.with_ns: self.ns_min_val = self.ns_GP.Y.min() self.ns_min_loc = self.ns_GP.Y.argmin() self.ns_min_x = self.ns_GP.X[self.ns_min_loc] self.ns_count = np.sum(self.ns_GP.Y < 0) self.ns_ce = np.flatnonzero(self.ns_GP.Y < 0) if self.with_random: self.rand_min_val = self.random_Y.min() self.rand_min_loc = self.random_Y.argmin() self.rand_min_x = self.random_X[self.rand_min_loc] self.rand_count = np.sum(self.random_Y < 0) self.rand_ce = np.flatnonzero(self.random_Y < 0)
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import argparse from suzieq.cli.sqcmds import * from suzieq.cli.sqcmds import context_commands from suzieq.cli.sqcmds import sqcmds_all from suzieq.cli.sq_nubia_context import NubiaSuzieqContext from suzieq.cli.sq_nubia_statusbar import NubiaSuzieqStatusBar from nubia import PluginInterface, CompletionDataSource from nubia.internal.blackcmd import CommandBlacklist from nubia.internal.cmdbase import AutoCommand class NubiaSuzieqPlugin(PluginInterface): """ The PluginInterface class is a way to customize nubia for every customer use case. It allowes custom argument validation, control over command loading, custom context objects, and much more. """ def create_context(self): """ Must create an object that inherits from `Context` parent class. The plugin can return a custom context but it has to inherit from the correct parent class. """ return NubiaSuzieqContext() def validate_args(self, args): """ This will be executed when starting nubia, the args passed is a dict-like object that contains the argparse result after parsing the command line arguments. The plugin can choose to update the context with the values, and/or decide to raise `ArgsValidationError` with the error message. """ pass def get_commands(self): cmds = [AutoCommand(getattr(globals()[x], x)) for x in sqcmds_all if not x.startswith('_')] cmds.append(AutoCommand(context_commands.set_ctxt)) cmds.append(AutoCommand(context_commands.clear_ctxt)) return cmds def get_opts_parser(self, add_help=True): """ Builds the ArgumentParser that will be passed to , use this to build your list of arguments that you want for your shell. """ opts_parser = argparse.ArgumentParser( description="Suzieq CLI", formatter_class=argparse.ArgumentDefaultsHelpFormatter, add_help=add_help, ) opts_parser.add_argument( "--config", "-c", default="", type=str, help="Configuration File" ) opts_parser.add_argument( "--verbose", "-v", action="count", default=0, help="Increase verbosity, can be specified " "multiple times", ) opts_parser.add_argument( "--stderr", "-s", action="store_true", default=True, help="By default the logging output goes to stderr " "Enable this feature to send it to a temporary logfile" ) # we only support pandas now, so we don't want this option # opts_parser.add_argument( # "--use-engine", "-e", help="Which analysis engine to use", default="pandas" # ) return opts_parser def get_completion_datasource_for_global_argument(self, argument): if argument == "--config": return ConfigFileCompletionDataSource() if argument == "--use-engine": return ConfigEngineCompletionDataSource() return None def create_usage_logger(self, context): """ Override this and return you own usage logger. Must be a subtype of UsageLoggerInterface. """ return None def get_status_bar(self, context): """ This returns the StatusBar object that handles the bottom status bar and the right-side per-line status """ return NubiaSuzieqStatusBar(context) def getBlacklistPlugin(self): blacklister = CommandBlacklist() blacklister.add_blocked_command("topcpu") blacklister.add_blocked_command("topmem") return blacklister class ConfigFileCompletionDataSource(CompletionDataSource): def get_all(self): return ["/tmp/c1", "/tmp/c2"] class ConfigEngineCompletionDataSource(CompletionDataSource): def get_all(self): return ["pandas"]
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from django.db import models from django.contrib.auth.models import User from django.template.defaultfilters import slugify import os from django.urls import reverse class standard(models.Model): name = models.CharField(max_length=100, unique=True) slug = models.SlugField(null=True,blank=True) description = models.TextField(max_length=550,blank=True) def __str__(self): return self.name def save(self, *args, **kwargs): self.slug = slugify(self.name) super().save(*args, **kwargs) def save_subject_image(instance,filename): upload_to = 'images' ext = filename.split('.')[-1] #get filename if instance.subject_id: filename = 'Subject_Pictures/{}'.format(instance.subject_id,ext) return os.path.join(upload_to, filename) class subject(models.Model): subject_id =models.CharField(max_length=100,unique=True) name = models.CharField(max_length=100) slug = models.SlugField(null=True,blank=True) standard = models.ForeignKey(standard,on_delete = models.CASCADE, related_name='subjects') image = models.ImageField(upload_to = save_subject_image,blank=True,verbose_name ='subject image') description = models.TextField(max_length=550, blank=True) def __str__(self): return self.name def save(self, *args, **kwargs): self.slug = slugify(self.subject_id) super().save(*args, **kwargs) def save_lesson_files(instance,filename): upload_to = 'images' ext = filename.split('.')[-1] #get filename if instance.lesson_id: filename = 'lesson_files/{}/{}.{}'.format(instance.lesson_id,instance.lesson_id,ext) if os.path.exists(filename): new_name = str(instance.lesson_id) + str('1') filename = 'lesson_images/{}/{}.{}'.format(instance.lesson_id, new_name,ext) return os.path.join(upload_to, filename) class lesson(models.Model): lesson_id = models.CharField(max_length=100, unique=True) standard = models.ForeignKey(standard,on_delete=models.CASCADE) created_by = models.ForeignKey(User,on_delete=models.CASCADE) created_at = models.DateTimeField(auto_now_add=True) subject= models.ForeignKey(subject, on_delete=models.CASCADE, related_name='lessons') name = models.CharField(max_length=150) position = models.PositiveSmallIntegerField(verbose_name= 'Chapter No') slug = models.SlugField(null=True,blank=True) video = models.FileField(upload_to=save_lesson_files,verbose_name='video',blank=True,null=True) ppt = models.FileField(upload_to=save_lesson_files,verbose_name='ppt',blank=True) notes = models.FileField(upload_to=save_lesson_files,verbose_name='notes',blank=True) class Meta: ordering = ['position'] def __str__(self): return self.name def save(self, *args, **kwargs): self.slug = slugify(self.name) super().save(*args, **kwargs) def get_absolute_url(self): return reverse("curriculum:lesson_list", kwargs={'slug':self.subject.slug, 'standard':self.standard.slug}) class comment(models.Model): lesson_name = models.ForeignKey(lesson,null=True,on_delete=models.CASCADE,related_name='comments') comment_name = models.CharField(max_length=150, blank=True) #reply = models.ForeignKey("Comment",null=True, blank = True, on_delete = models.CASCADE, related_name='replies') author = models.ForeignKey(User,on_delete=models.CASCADE) body = models.TextField(max_length=500) date_added = models.DateTimeField(auto_now_add=True) def save(self, *args, **kwargs): self.comment_name = slugify("Comment by"+"-"+str(self.author)+str(self.date_added)) super().save(*args, **kwargs) def __str__(self): return self.comment_name class Meta: ordering = ['-date_added'] class reply(models.Model): comment_name = models.ForeignKey(comment,on_delete=models.CASCADE,related_name='replies') reply_body = models.TextField(max_length=500) author = models.ForeignKey(User, on_delete=models.CASCADE) date_added = models.DateTimeField(auto_now_add=True) def __str__(self): return "reply to "+str(self.comment_name.comment_name)
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from django.shortcuts import render from rest_framework import generics, authentication, permissions from rest_framework.authtoken.views import ObtainAuthToken from rest_framework.settings import api_settings from user.serializers import UserSerializer, AuthTokenSerializer class CreateUserView(generics.CreateAPIView): """Create a new user in the system""" serializer_class = UserSerializer class CreateTokenview(ObtainAuthToken): """Create a new auth token for user""" serializer_class = AuthTokenSerializer renderer_classes = api_settings.DEFAULT_RENDERER_CLASSES class ManageUserView(generics.RetrieveUpdateAPIView): """Manage the authenticated user""" serializer_class = UserSerializer authentication_classes = (authentication.TokenAuthentication,) permission_classes = (permissions.IsAuthenticated,) def get_object(self): """Retrieve and return authentication user""" return self.request.user
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import requests import numpy as np import collections import matplotlib.pyplot as plt from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas from PIL import Image from io import BytesIO class Image_Data: image = None @property def Array(self) -> np.ndarray: """ Return image array (RGB) """ return self.image @property def Color_Hex(self) -> list: hex = [] def convert_RGB2HEX(color): return "#{:02x}{:02x}{:02x}".format(int(color[0]), int(color[1]), int(color[2])) image = self.image image_height = len(image) for y in range(image_height): for x in image[y]: hex.append(convert_RGB2HEX(x)) return hex def __init__(self, image_path: str): if 'http' in image_path: # Online image image_req = requests.get(image_path, stream=True) if image_req.status_code == 200: self.image = np.array(Image.open(BytesIO(image_req.content))) else: # Local image self.image = np.array(Image.open(image_path)) def show(self): Image.fromarray(self.image, 'RGB').show() class Color: color = [] @property def Total(self) -> int: return len(self.color) @property def Count(self) -> dict: """ Return total unique color """ color_count = dict(collections.Counter(self.color)) # Sort dict by highest value color_count = { key: value for key, value in sorted(color_count.items(), key=lambda x: x[1], reverse=True) } return color_count @property def Listed_Count(self) -> list[dict]: """ Return total unique color in list of dictionary """ list_colors = [] colors = self.Count.items() # List each dict item for key, val in colors: item = "{'%(key)s' : %(val)s}" % {'key': key, 'val': val} list_colors.append(eval(item)) return list_colors def __init__(self, color: list): self.color = color def plot(self, min_value = 1): """ Plot color data with value more than min_value """ color_count = self.Count color_count = {key : value for key, value in color_count.items() if value >= min_value} color = list(color_count.keys()) count = list(color_count.values()) bar_colors = color # Draw plot #fig_width = len(color) #fig_height figure = plt.figure('Color Distribution', tight_layout=True) plt.barh(color, count, color=bar_colors, edgecolor='#aaaaaa') plt.title('Color Distribution') plt.ylabel('Color') plt.xlabel('Count') plt.show() # Render figure canvas = FigureCanvas(figure) canvas.draw() width, height = figure.get_size_inches() * figure.get_dpi() image = np.frombuffer(canvas.tostring_rgb(), dtype='uint8').reshape(int(height), int(width), 3) return image
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from pymongo import MongoClient client = MongoClient() # carPricingDB = client["carPricing"] # firstOffersCollection = carPricingDB.create_collection("firstOffers") # firstOffersCollection.insert_one({"item":"initialone"}) carPricingDB = client.carPricing firstOffersCollection = carPricingDB.firstOffers firstOffersCollection.insert_one( {"item": "canvas", "qty": 100, "tags": ["cotton"], "size": {"h": 28, "w": 35.5, "uom": "cm"}}) coss = firstOffersCollection.find({"item":"canvas"})[0] print(coss)
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# coding: utf-8 # -------------------------------------------------------- # Fast R-CNN # Copyright (c) 2015 Microsoft # Licensed under The MIT License [see LICENSE for details] # Written by Ross Girshick # -------------------------------------------------------- from __future__ import print_function import xml.dom.minidom as minidom import os # import PIL import numpy as np import scipy.sparse import subprocess try: import cPickle except ImportError: import pickle as cPickle import math import glob import uuid import scipy.io as sio import xml.etree.ElementTree as ET from .imdb import imdb from .imdb import ROOT_DIR from . import ds_utils from .adas_eval import adas_eval # TODO: make fast_rcnn irrelevant # >>>> obsolete, because it depends on sth outside of this project from model.utils.config import cfg # <<<< obsolete class adas(imdb): def __init__(self, image_set, year, devkit_path=None, sub_type='car'): imdb.__init__(self, 'adas_' + year + '_' + image_set) self._year = year self._image_set = image_set self._devkit_path = self._get_default_path() if devkit_path is None \ else devkit_path self._data_path = os.path.join(self._devkit_path, 'ADAS' + self._year) if sub_type == 'car': self._classes = ('__background__', #always index 0 'car',) elif sub_type == 'tired': self._classes = ('__background__', #always index 0 'o','s','w') self._class_to_ind = dict(zip(self.classes, range(self.num_classes))) self._image_ext = '.jpg' self._image_index = self._load_image_set_index() # Default to roidb handler # self._roidb_handler = self.selective_search_roidb self._roidb_handler = self.gt_roidb self._salt = str(uuid.uuid4()) self._comp_id = 'comp4' # PASCAL specific config options self.config = {'cleanup': True, 'use_salt': True, 'use_diff': False, 'matlab_eval': False, 'rpn_file': None, 'min_size': 2} assert os.path.exists(self._devkit_path), \ 'ADASdevkit path does not exist: {}'.format(self._devkit_path) assert os.path.exists(self._data_path), \ 'Path does not exist: {}'.format(self._data_path) def image_path_at(self, i): """ Return the absolute path to image i in the image sequence. """ return self.image_path_from_index(self._image_index[i]) def image_id_at(self, i): """ Return the absolute path to image i in the image sequence. """ return i def image_path_from_index(self, index): """ Construct an image path from the image's "index" identifier. """ image_path = os.path.join(self._data_path, 'JPEGImages', index + self._image_ext) assert os.path.exists(image_path), \ 'Path does not exist: {}'.format(image_path) return image_path def _load_image_set_index(self): """ Load the indexes listed in this dataset's image set file. """ # Example path to image set file: # self._devkit_path + /ADASdevkit2007/ADAS2007/ImageSets/Main/val.txt image_set_file = os.path.join(self._data_path, 'ImageSets', 'Main', self._image_set + '.txt') assert os.path.exists(image_set_file), \ 'Path does not exist: {}'.format(image_set_file) with open(image_set_file) as f: image_index = [x.strip() for x in f.readlines()] return image_index def _get_default_path(self): """ Return the default path where PASCAL ADAS is expected to be installed. """ return os.path.join(cfg.DATA_DIR, 'ADASdevkit' + self._year) def gt_roidb(self): """ Return the database of ground-truth regions of interest. This function loads/saves from/to a cache file to speed up future calls. """ cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl') if os.path.exists(cache_file): print(cache_file) with open(cache_file, 'rb') as fid: roidb = cPickle.load(fid) print('{} gt roidb loaded from {}'.format(self.name, cache_file)) return roidb gt_roidb = [self._load_pascal_annotation(index) for index in self.image_index] with open(cache_file, 'wb') as fid: cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL) print('wrote gt roidb to {}'.format(cache_file)) return gt_roidb def selective_search_roidb(self): """ Return the database of selective search regions of interest. Ground-truth ROIs are also included. This function loads/saves from/to a cache file to speed up future calls. """ cache_file = os.path.join(self.cache_path, self.name + '_selective_search_roidb.pkl') if os.path.exists(cache_file): with open(cache_file, 'rb') as fid: roidb = cPickle.load(fid) print('{} ss roidb loaded from {}'.format(self.name, cache_file)) return roidb if int(self._year) == 2007 or self._image_set != 'test': gt_roidb = self.gt_roidb() ss_roidb = self._load_selective_search_roidb(gt_roidb) roidb = imdb.merge_roidbs(gt_roidb, ss_roidb) else: roidb = self._load_selective_search_roidb(None) with open(cache_file, 'wb') as fid: cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL) print('wrote ss roidb to {}'.format(cache_file)) return roidb def rpn_roidb(self): if int(self._year) == 2007 or self._image_set != 'test': gt_roidb = self.gt_roidb() rpn_roidb = self._load_rpn_roidb(gt_roidb) roidb = imdb.merge_roidbs(gt_roidb, rpn_roidb) else: roidb = self._load_rpn_roidb(None) return roidb def _load_rpn_roidb(self, gt_roidb): filename = self.config['rpn_file'] print('loading {}'.format(filename)) assert os.path.exists(filename), \ 'rpn data not found at: {}'.format(filename) with open(filename, 'rb') as f: box_list = cPickle.load(f) return self.create_roidb_from_box_list(box_list, gt_roidb) def _load_selective_search_roidb(self, gt_roidb): filename = os.path.abspath(os.path.join(cfg.DATA_DIR, 'selective_search_data', self.name + '.mat')) assert os.path.exists(filename), \ 'Selective search data not found at: {}'.format(filename) raw_data = sio.loadmat(filename)['boxes'].ravel() box_list = [] for i in range(raw_data.shape[0]): boxes = raw_data[i][:, (1, 0, 3, 2)] - 1 keep = ds_utils.unique_boxes(boxes) boxes = boxes[keep, :] keep = ds_utils.filter_small_boxes(boxes, self.config['min_size']) boxes = boxes[keep, :] box_list.append(boxes) return self.create_roidb_from_box_list(box_list, gt_roidb) def _load_pascal_annotation(self, index): """ Load image and bounding boxes info from XML file in the PASCAL ADAS format. """ filename = os.path.join(self._data_path, 'Annotations', index + '.xml') tree = ET.parse(filename) objs = tree.findall('object') # if not self.config['use_diff']: # # Exclude the samples labeled as difficult # non_diff_objs = [ # obj for obj in objs if int(obj.find('difficult').text) == 0] # # if len(non_diff_objs) != len(objs): # # print 'Removed {} difficult objects'.format( # # len(objs) - len(non_diff_objs)) # objs = non_diff_objs num_objs = len(objs) boxes = np.zeros((num_objs, 4), dtype=np.uint16) gt_classes = np.zeros((num_objs), dtype=np.int32) overlaps = np.zeros((num_objs, self.num_classes), dtype=np.float32) # "Seg" area for pascal is just the box area seg_areas = np.zeros((num_objs), dtype=np.float32) ishards = np.zeros((num_objs), dtype=np.int32) # Load object bounding boxes into a data frame. for ix, obj in enumerate(objs): bbox = obj.find('bndbox') # Make pixel indexes 0-based x1 = float(bbox.find('xmin').text) - 1 y1 = float(bbox.find('ymin').text) - 1 x2 = float(bbox.find('xmax').text) - 1 y2 = float(bbox.find('ymax').text) - 1 diffc = obj.find('difficult') difficult = 0 if diffc == None else int(diffc.text) ishards[ix] = difficult cls = self._class_to_ind[obj.find('name').text.lower().strip()] boxes[ix, :] = [x1, y1, x2, y2] gt_classes[ix] = cls overlaps[ix, cls] = 1.0 seg_areas[ix] = (x2 - x1 + 1) * (y2 - y1 + 1) overlaps = scipy.sparse.csr_matrix(overlaps) return {'boxes': boxes, 'gt_classes': gt_classes, 'gt_ishard': ishards, 'gt_overlaps': overlaps, 'flipped': False, 'seg_areas': seg_areas} def _get_comp_id(self): comp_id = (self._comp_id + '_' + self._salt if self.config['use_salt'] else self._comp_id) return comp_id def _get_adas_results_file_template(self): # ADASdevkit/results/ADAS2007/Main/<comp_id>_det_test_aeroplane.txt filename = self._get_comp_id() + '_det_' + self._image_set + '_{:s}.txt' filedir = os.path.join(self._devkit_path, 'results', 'ADAS' + self._year, 'Main') if not os.path.exists(filedir): os.makedirs(filedir) path = os.path.join(filedir, filename) return path def _write_adas_results_file(self, all_boxes): for cls_ind, cls in enumerate(self.classes): if cls == '__background__': continue print('Writing {} ADAS results file'.format(cls)) filename = self._get_adas_results_file_template().format(cls) with open(filename, 'wt') as f: for im_ind, index in enumerate(self.image_index): dets = all_boxes[cls_ind][im_ind] if dets == []: continue # the ADASdevkit expects 1-based indices for k in range(dets.shape[0]): f.write('{:s} {:.3f} {:.1f} {:.1f} {:.1f} {:.1f}\n'. format(index, dets[k, -1], dets[k, 0] + 1, dets[k, 1] + 1, dets[k, 2] + 1, dets[k, 3] + 1)) def _do_python_eval(self, output_dir='output'): annopath = os.path.join( self._devkit_path, 'ADAS' + self._year, 'Annotations', '{:s}.xml') imagesetfile = os.path.join( self._devkit_path, 'ADAS' + self._year, 'ImageSets', 'Main', self._image_set + '.txt') cachedir = os.path.join(self._devkit_path, 'annotations_cache') aps = [] if not os.path.isdir(output_dir): os.mkdir(output_dir) for i, cls in enumerate(self._classes): if cls == '__background__': continue filename = self._get_adas_results_file_template().format(cls) rec, prec, ap = adas_eval( filename, annopath, imagesetfile, cls, cachedir, ovthresh=0.5) aps += [ap] print('AP for {} = {:.4f}'.format(cls, ap)) with open(os.path.join(output_dir, cls + '_pr.pkl'), 'w') as f: cPickle.dump({'rec': rec, 'prec': prec, 'ap': ap}, f) print('Mean AP = {:.4f}'.format(np.mean(aps))) print('~~~~~~~~') print('Results:') for ap in aps: print('{:.3f}'.format(ap)) print('{:.3f}'.format(np.mean(aps))) print('~~~~~~~~') print('') print('--------------------------------------------------------------') print('Results computed with the **unofficial** Python eval code.') print('Results should be very close to the official MATLAB eval code.') print('Recompute with `./tools/reval.py --matlab ...` for your paper.') print('-- Thanks, The Management') print('--------------------------------------------------------------') def _do_matlab_eval(self, output_dir='output'): print('-----------------------------------------------------') print('Computing results with the official MATLAB eval code.') print('-----------------------------------------------------') path = os.path.join(cfg.ROOT_DIR, 'lib', 'datasets', 'ADASdevkit-matlab-wrapper') cmd = 'cd {} && '.format(path) cmd += '{:s} -nodisplay -nodesktop '.format(cfg.MATLAB) cmd += '-r "dbstop if error; ' cmd += 'adas_eval(\'{:s}\',\'{:s}\',\'{:s}\',\'{:s}\'); quit;"' \ .format(self._devkit_path, self._get_comp_id(), self._image_set, output_dir) print('Running:\n{}'.format(cmd)) status = subprocess.call(cmd, shell=True) def evaluate_detections(self, all_boxes, output_dir): self._write_adas_results_file(all_boxes) self._do_python_eval(output_dir) if self.config['matlab_eval']: self._do_matlab_eval(output_dir) if self.config['cleanup']: for cls in self._classes: if cls == '__background__': continue filename = self._get_adas_results_file_template().format(cls) os.remove(filename) def competition_mode(self, on): if on: self.config['use_salt'] = False self.config['cleanup'] = False else: self.config['use_salt'] = True self.config['cleanup'] = True if __name__ == '__main__': d = adas('trainval', '2017') res = d.roidb from IPython import embed; embed()
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# Copyright (c) Twisted Matrix Laboratories. # See LICENSE for details. """ Tests for lots of functionality provided by L{twisted.internet}. """ from __future__ import division, absolute_import import os import sys import time from twisted.python.compat import _PY3 from twisted.trial import unittest from twisted.internet import reactor, protocol, error, abstract, defer from twisted.internet import interfaces, base try: from twisted.internet import ssl except ImportError: ssl = None if ssl and not ssl.supported: ssl = None from twisted.internet.defer import Deferred if not _PY3: from twisted.python import util class ThreePhaseEventTests(unittest.TestCase): """ Tests for the private implementation helpers for system event triggers. """ def setUp(self): """ Create a trigger, an argument, and an event to be used by tests. """ self.trigger = lambda x: None self.arg = object() self.event = base._ThreePhaseEvent() def test_addInvalidPhase(self): """ L{_ThreePhaseEvent.addTrigger} should raise L{KeyError} when called with an invalid phase. """ self.assertRaises( KeyError, self.event.addTrigger, 'xxx', self.trigger, self.arg) def test_addBeforeTrigger(self): """ L{_ThreePhaseEvent.addTrigger} should accept C{'before'} as a phase, a callable, and some arguments and add the callable with the arguments to the before list. """ self.event.addTrigger('before', self.trigger, self.arg) self.assertEqual( self.event.before, [(self.trigger, (self.arg,), {})]) def test_addDuringTrigger(self): """ L{_ThreePhaseEvent.addTrigger} should accept C{'during'} as a phase, a callable, and some arguments and add the callable with the arguments to the during list. """ self.event.addTrigger('during', self.trigger, self.arg) self.assertEqual( self.event.during, [(self.trigger, (self.arg,), {})]) def test_addAfterTrigger(self): """ L{_ThreePhaseEvent.addTrigger} should accept C{'after'} as a phase, a callable, and some arguments and add the callable with the arguments to the after list. """ self.event.addTrigger('after', self.trigger, self.arg) self.assertEqual( self.event.after, [(self.trigger, (self.arg,), {})]) def test_removeTrigger(self): """ L{_ThreePhaseEvent.removeTrigger} should accept an opaque object previously returned by L{_ThreePhaseEvent.addTrigger} and remove the associated trigger. """ handle = self.event.addTrigger('before', self.trigger, self.arg) self.event.removeTrigger(handle) self.assertEqual(self.event.before, []) def test_removeNonexistentTrigger(self): """ L{_ThreePhaseEvent.removeTrigger} should raise L{ValueError} when given an object not previously returned by L{_ThreePhaseEvent.addTrigger}. """ self.assertRaises(ValueError, self.event.removeTrigger, object()) def test_removeRemovedTrigger(self): """ L{_ThreePhaseEvent.removeTrigger} should raise L{ValueError} the second time it is called with an object returned by L{_ThreePhaseEvent.addTrigger}. """ handle = self.event.addTrigger('before', self.trigger, self.arg) self.event.removeTrigger(handle) self.assertRaises(ValueError, self.event.removeTrigger, handle) def test_removeAlmostValidTrigger(self): """ L{_ThreePhaseEvent.removeTrigger} should raise L{ValueError} if it is given a trigger handle which resembles a valid trigger handle aside from its phase being incorrect. """ self.assertRaises( KeyError, self.event.removeTrigger, ('xxx', self.trigger, (self.arg,), {})) def test_fireEvent(self): """ L{_ThreePhaseEvent.fireEvent} should call I{before}, I{during}, and I{after} phase triggers in that order. """ events = [] self.event.addTrigger('after', events.append, ('first', 'after')) self.event.addTrigger('during', events.append, ('first', 'during')) self.event.addTrigger('before', events.append, ('first', 'before')) self.event.addTrigger('before', events.append, ('second', 'before')) self.event.addTrigger('during', events.append, ('second', 'during')) self.event.addTrigger('after', events.append, ('second', 'after')) self.assertEqual(events, []) self.event.fireEvent() self.assertEqual(events, [('first', 'before'), ('second', 'before'), ('first', 'during'), ('second', 'during'), ('first', 'after'), ('second', 'after')]) def test_asynchronousBefore(self): """ L{_ThreePhaseEvent.fireEvent} should wait for any L{Deferred} returned by a I{before} phase trigger before proceeding to I{during} events. """ events = [] beforeResult = Deferred() self.event.addTrigger('before', lambda: beforeResult) self.event.addTrigger('during', events.append, 'during') self.event.addTrigger('after', events.append, 'after') self.assertEqual(events, []) self.event.fireEvent() self.assertEqual(events, []) beforeResult.callback(None) self.assertEqual(events, ['during', 'after']) def test_beforeTriggerException(self): """ If a before-phase trigger raises a synchronous exception, it should be logged and the remaining triggers should be run. """ events = [] class DummyException(Exception): pass def raisingTrigger(): raise DummyException() self.event.addTrigger('before', raisingTrigger) self.event.addTrigger('before', events.append, 'before') self.event.addTrigger('during', events.append, 'during') self.event.fireEvent() self.assertEqual(events, ['before', 'during']) errors = self.flushLoggedErrors(DummyException) self.assertEqual(len(errors), 1) def test_duringTriggerException(self): """ If a during-phase trigger raises a synchronous exception, it should be logged and the remaining triggers should be run. """ events = [] class DummyException(Exception): pass def raisingTrigger(): raise DummyException() self.event.addTrigger('during', raisingTrigger) self.event.addTrigger('during', events.append, 'during') self.event.addTrigger('after', events.append, 'after') self.event.fireEvent() self.assertEqual(events, ['during', 'after']) errors = self.flushLoggedErrors(DummyException) self.assertEqual(len(errors), 1) def test_synchronousRemoveAlreadyExecutedBefore(self): """ If a before-phase trigger tries to remove another before-phase trigger which has already run, a warning should be emitted. """ events = [] def removeTrigger(): self.event.removeTrigger(beforeHandle) beforeHandle = self.event.addTrigger('before', events.append, ('first', 'before')) self.event.addTrigger('before', removeTrigger) self.event.addTrigger('before', events.append, ('second', 'before')) self.assertWarns( DeprecationWarning, "Removing already-fired system event triggers will raise an " "exception in a future version of Twisted.", __file__, self.event.fireEvent) self.assertEqual(events, [('first', 'before'), ('second', 'before')]) def test_synchronousRemovePendingBefore(self): """ If a before-phase trigger removes another before-phase trigger which has not yet run, the removed trigger should not be run. """ events = [] self.event.addTrigger( 'before', lambda: self.event.removeTrigger(beforeHandle)) beforeHandle = self.event.addTrigger( 'before', events.append, ('first', 'before')) self.event.addTrigger('before', events.append, ('second', 'before')) self.event.fireEvent() self.assertEqual(events, [('second', 'before')]) def test_synchronousBeforeRemovesDuring(self): """ If a before-phase trigger removes a during-phase trigger, the during-phase trigger should not be run. """ events = [] self.event.addTrigger( 'before', lambda: self.event.removeTrigger(duringHandle)) duringHandle = self.event.addTrigger('during', events.append, 'during') self.event.addTrigger('after', events.append, 'after') self.event.fireEvent() self.assertEqual(events, ['after']) def test_asynchronousBeforeRemovesDuring(self): """ If a before-phase trigger returns a L{Deferred} and later removes a during-phase trigger before the L{Deferred} fires, the during-phase trigger should not be run. """ events = [] beforeResult = Deferred() self.event.addTrigger('before', lambda: beforeResult) duringHandle = self.event.addTrigger('during', events.append, 'during') self.event.addTrigger('after', events.append, 'after') self.event.fireEvent() self.event.removeTrigger(duringHandle) beforeResult.callback(None) self.assertEqual(events, ['after']) def test_synchronousBeforeRemovesConspicuouslySimilarDuring(self): """ If a before-phase trigger removes a during-phase trigger which is identical to an already-executed before-phase trigger aside from their phases, no warning should be emitted and the during-phase trigger should not be run. """ events = [] def trigger(): events.append('trigger') self.event.addTrigger('before', trigger) self.event.addTrigger( 'before', lambda: self.event.removeTrigger(duringTrigger)) duringTrigger = self.event.addTrigger('during', trigger) self.event.fireEvent() self.assertEqual(events, ['trigger']) def test_synchronousRemovePendingDuring(self): """ If a during-phase trigger removes another during-phase trigger which has not yet run, the removed trigger should not be run. """ events = [] self.event.addTrigger( 'during', lambda: self.event.removeTrigger(duringHandle)) duringHandle = self.event.addTrigger( 'during', events.append, ('first', 'during')) self.event.addTrigger( 'during', events.append, ('second', 'during')) self.event.fireEvent() self.assertEqual(events, [('second', 'during')]) def test_triggersRunOnce(self): """ A trigger should only be called on the first call to L{_ThreePhaseEvent.fireEvent}. """ events = [] self.event.addTrigger('before', events.append, 'before') self.event.addTrigger('during', events.append, 'during') self.event.addTrigger('after', events.append, 'after') self.event.fireEvent() self.event.fireEvent() self.assertEqual(events, ['before', 'during', 'after']) def test_finishedBeforeTriggersCleared(self): """ The temporary list L{_ThreePhaseEvent.finishedBefore} should be emptied and the state reset to C{'BASE'} before the first during-phase trigger executes. """ events = [] def duringTrigger(): events.append('during') self.assertEqual(self.event.finishedBefore, []) self.assertEqual(self.event.state, 'BASE') self.event.addTrigger('before', events.append, 'before') self.event.addTrigger('during', duringTrigger) self.event.fireEvent() self.assertEqual(events, ['before', 'during']) class SystemEventTests(unittest.TestCase): """ Tests for the reactor's implementation of the C{fireSystemEvent}, C{addSystemEventTrigger}, and C{removeSystemEventTrigger} methods of the L{IReactorCore} interface. @ivar triggers: A list of the handles to triggers which have been added to the reactor. """ def setUp(self): """ Create an empty list in which to store trigger handles. """ self.triggers = [] def tearDown(self): """ Remove all remaining triggers from the reactor. """ while self.triggers: trigger = self.triggers.pop() try: reactor.removeSystemEventTrigger(trigger) except (ValueError, KeyError): pass def addTrigger(self, event, phase, func): """ Add a trigger to the reactor and remember it in C{self.triggers}. """ t = reactor.addSystemEventTrigger(event, phase, func) self.triggers.append(t) return t def removeTrigger(self, trigger): """ Remove a trigger by its handle from the reactor and from C{self.triggers}. """ reactor.removeSystemEventTrigger(trigger) self.triggers.remove(trigger) def _addSystemEventTriggerTest(self, phase): eventType = 'test' events = [] def trigger(): events.append(None) self.addTrigger(phase, eventType, trigger) self.assertEqual(events, []) reactor.fireSystemEvent(eventType) self.assertEqual(events, [None]) def test_beforePhase(self): """ L{IReactorCore.addSystemEventTrigger} should accept the C{'before'} phase and not call the given object until the right event is fired. """ self._addSystemEventTriggerTest('before') def test_duringPhase(self): """ L{IReactorCore.addSystemEventTrigger} should accept the C{'during'} phase and not call the given object until the right event is fired. """ self._addSystemEventTriggerTest('during') def test_afterPhase(self): """ L{IReactorCore.addSystemEventTrigger} should accept the C{'after'} phase and not call the given object until the right event is fired. """ self._addSystemEventTriggerTest('after') def test_unknownPhase(self): """ L{IReactorCore.addSystemEventTrigger} should reject phases other than C{'before'}, C{'during'}, or C{'after'}. """ eventType = 'test' self.assertRaises( KeyError, self.addTrigger, 'xxx', eventType, lambda: None) def test_beforePreceedsDuring(self): """ L{IReactorCore.addSystemEventTrigger} should call triggers added to the C{'before'} phase before it calls triggers added to the C{'during'} phase. """ eventType = 'test' events = [] def beforeTrigger(): events.append('before') def duringTrigger(): events.append('during') self.addTrigger('before', eventType, beforeTrigger) self.addTrigger('during', eventType, duringTrigger) self.assertEqual(events, []) reactor.fireSystemEvent(eventType) self.assertEqual(events, ['before', 'during']) def test_duringPreceedsAfter(self): """ L{IReactorCore.addSystemEventTrigger} should call triggers added to the C{'during'} phase before it calls triggers added to the C{'after'} phase. """ eventType = 'test' events = [] def duringTrigger(): events.append('during') def afterTrigger(): events.append('after') self.addTrigger('during', eventType, duringTrigger) self.addTrigger('after', eventType, afterTrigger) self.assertEqual(events, []) reactor.fireSystemEvent(eventType) self.assertEqual(events, ['during', 'after']) def test_beforeReturnsDeferred(self): """ If a trigger added to the C{'before'} phase of an event returns a L{Deferred}, the C{'during'} phase should be delayed until it is called back. """ triggerDeferred = Deferred() eventType = 'test' events = [] def beforeTrigger(): return triggerDeferred def duringTrigger(): events.append('during') self.addTrigger('before', eventType, beforeTrigger) self.addTrigger('during', eventType, duringTrigger) self.assertEqual(events, []) reactor.fireSystemEvent(eventType) self.assertEqual(events, []) triggerDeferred.callback(None) self.assertEqual(events, ['during']) def test_multipleBeforeReturnDeferred(self): """ If more than one trigger added to the C{'before'} phase of an event return L{Deferred}s, the C{'during'} phase should be delayed until they are all called back. """ firstDeferred = Deferred() secondDeferred = Deferred() eventType = 'test' events = [] def firstBeforeTrigger(): return firstDeferred def secondBeforeTrigger(): return secondDeferred def duringTrigger(): events.append('during') self.addTrigger('before', eventType, firstBeforeTrigger) self.addTrigger('before', eventType, secondBeforeTrigger) self.addTrigger('during', eventType, duringTrigger) self.assertEqual(events, []) reactor.fireSystemEvent(eventType) self.assertEqual(events, []) firstDeferred.callback(None) self.assertEqual(events, []) secondDeferred.callback(None) self.assertEqual(events, ['during']) def test_subsequentBeforeTriggerFiresPriorBeforeDeferred(self): """ If a trigger added to the C{'before'} phase of an event calls back a L{Deferred} returned by an earlier trigger in the C{'before'} phase of the same event, the remaining C{'before'} triggers for that event should be run and any further L{Deferred}s waited on before proceeding to the C{'during'} events. """ eventType = 'test' events = [] firstDeferred = Deferred() secondDeferred = Deferred() def firstBeforeTrigger(): return firstDeferred def secondBeforeTrigger(): firstDeferred.callback(None) def thirdBeforeTrigger(): events.append('before') return secondDeferred def duringTrigger(): events.append('during') self.addTrigger('before', eventType, firstBeforeTrigger) self.addTrigger('before', eventType, secondBeforeTrigger) self.addTrigger('before', eventType, thirdBeforeTrigger) self.addTrigger('during', eventType, duringTrigger) self.assertEqual(events, []) reactor.fireSystemEvent(eventType) self.assertEqual(events, ['before']) secondDeferred.callback(None) self.assertEqual(events, ['before', 'during']) def test_removeSystemEventTrigger(self): """ A trigger removed with L{IReactorCore.removeSystemEventTrigger} should not be called when the event fires. """ eventType = 'test' events = [] def firstBeforeTrigger(): events.append('first') def secondBeforeTrigger(): events.append('second') self.addTrigger('before', eventType, firstBeforeTrigger) self.removeTrigger( self.addTrigger('before', eventType, secondBeforeTrigger)) self.assertEqual(events, []) reactor.fireSystemEvent(eventType) self.assertEqual(events, ['first']) def test_removeNonExistentSystemEventTrigger(self): """ Passing an object to L{IReactorCore.removeSystemEventTrigger} which was not returned by a previous call to L{IReactorCore.addSystemEventTrigger} or which has already been passed to C{removeSystemEventTrigger} should result in L{TypeError}, L{KeyError}, or L{ValueError} being raised. """ b = self.addTrigger('during', 'test', lambda: None) self.removeTrigger(b) self.assertRaises( TypeError, reactor.removeSystemEventTrigger, None) self.assertRaises( ValueError, reactor.removeSystemEventTrigger, b) self.assertRaises( KeyError, reactor.removeSystemEventTrigger, (b[0], ('xxx',) + b[1][1:])) def test_interactionBetweenDifferentEvents(self): """ L{IReactorCore.fireSystemEvent} should behave the same way for a particular system event regardless of whether Deferreds are being waited on for a different system event. """ events = [] firstEvent = 'first-event' firstDeferred = Deferred() def beforeFirstEvent(): events.append(('before', 'first')) return firstDeferred def afterFirstEvent(): events.append(('after', 'first')) secondEvent = 'second-event' secondDeferred = Deferred() def beforeSecondEvent(): events.append(('before', 'second')) return secondDeferred def afterSecondEvent(): events.append(('after', 'second')) self.addTrigger('before', firstEvent, beforeFirstEvent) self.addTrigger('after', firstEvent, afterFirstEvent) self.addTrigger('before', secondEvent, beforeSecondEvent) self.addTrigger('after', secondEvent, afterSecondEvent) self.assertEqual(events, []) # After this, firstEvent should be stuck before 'during' waiting for # firstDeferred. reactor.fireSystemEvent(firstEvent) self.assertEqual(events, [('before', 'first')]) # After this, secondEvent should be stuck before 'during' waiting for # secondDeferred. reactor.fireSystemEvent(secondEvent) self.assertEqual(events, [('before', 'first'), ('before', 'second')]) # After this, firstEvent should have finished completely, but # secondEvent should be at the same place. firstDeferred.callback(None) self.assertEqual(events, [('before', 'first'), ('before', 'second'), ('after', 'first')]) # After this, secondEvent should have finished completely. secondDeferred.callback(None) self.assertEqual(events, [('before', 'first'), ('before', 'second'), ('after', 'first'), ('after', 'second')]) class TimeTests(unittest.TestCase): """ Tests for the IReactorTime part of the reactor. """ def test_seconds(self): """ L{twisted.internet.reactor.seconds} should return something like a number. 1. This test specifically does not assert any relation to the "system time" as returned by L{time.time} or L{twisted.python.runtime.seconds}, because at some point we may find a better option for scheduling calls than wallclock-time. 2. This test *also* does not assert anything about the type of the result, because operations may not return ints or floats: For example, datetime-datetime == timedelta(0). """ now = reactor.seconds() self.assertEqual(now-now+now, now) def test_callLaterUsesReactorSecondsInDelayedCall(self): """ L{reactor.callLater<twisted.internet.interfaces.IReactorTime.callLater>} should use the reactor's seconds factory to produce the time at which the DelayedCall will be called. """ oseconds = reactor.seconds reactor.seconds = lambda: 100 try: call = reactor.callLater(5, lambda: None) self.assertEqual(call.getTime(), 105) finally: reactor.seconds = oseconds def test_callLaterUsesReactorSecondsAsDelayedCallSecondsFactory(self): """ L{reactor.callLater<twisted.internet.interfaces.IReactorTime.callLater>} should propagate its own seconds factory to the DelayedCall to use as its own seconds factory. """ oseconds = reactor.seconds reactor.seconds = lambda: 100 try: call = reactor.callLater(5, lambda: None) self.assertEqual(call.seconds(), 100) finally: reactor.seconds = oseconds def test_callLater(self): """ Test that a DelayedCall really calls the function it is supposed to call. """ d = Deferred() reactor.callLater(0, d.callback, None) d.addCallback(self.assertEqual, None) return d def test_cancelDelayedCall(self): """ Test that when a DelayedCall is cancelled it does not run. """ called = [] def function(): called.append(None) call = reactor.callLater(0, function) call.cancel() # Schedule a call in two "iterations" to check to make sure that the # above call never ran. d = Deferred() def check(): try: self.assertEqual(called, []) except: d.errback() else: d.callback(None) reactor.callLater(0, reactor.callLater, 0, check) return d def test_cancelCancelledDelayedCall(self): """ Test that cancelling a DelayedCall which has already been cancelled raises the appropriate exception. """ call = reactor.callLater(0, lambda: None) call.cancel() self.assertRaises(error.AlreadyCancelled, call.cancel) def test_cancelCalledDelayedCallSynchronous(self): """ Test that cancelling a DelayedCall in the DelayedCall's function as that function is being invoked by the DelayedCall raises the appropriate exception. """ d = Deferred() def later(): try: self.assertRaises(error.AlreadyCalled, call.cancel) except: d.errback() else: d.callback(None) call = reactor.callLater(0, later) return d def test_cancelCalledDelayedCallAsynchronous(self): """ Test that cancelling a DelayedCall after it has run its function raises the appropriate exception. """ d = Deferred() def check(): try: self.assertRaises(error.AlreadyCalled, call.cancel) except: d.errback() else: d.callback(None) def later(): reactor.callLater(0, check) call = reactor.callLater(0, later) return d def testCallLaterTime(self): d = reactor.callLater(10, lambda: None) try: self.assertTrue(d.getTime() - (time.time() + 10) < 1) finally: d.cancel() def testDelayedCallStringification(self): # Mostly just make sure str() isn't going to raise anything for # DelayedCalls within reason. dc = reactor.callLater(0, lambda x, y: None, 'x', y=10) str(dc) dc.reset(5) str(dc) dc.cancel() str(dc) dc = reactor.callLater(0, lambda: None, x=[({'hello': u'world'}, 10j), reactor], *range(10)) str(dc) dc.cancel() str(dc) def calledBack(ignored): str(dc) d = Deferred().addCallback(calledBack) dc = reactor.callLater(0, d.callback, None) str(dc) return d def testDelayedCallSecondsOverride(self): """ Test that the C{seconds} argument to DelayedCall gets used instead of the default timing function, if it is not None. """ def seconds(): return 10 dc = base.DelayedCall(5, lambda: None, (), {}, lambda dc: None, lambda dc: None, seconds) self.assertEqual(dc.getTime(), 5) dc.reset(3) self.assertEqual(dc.getTime(), 13) class CallFromThreadStopsAndWakeUpTests(unittest.TestCase): def testWakeUp(self): # Make sure other threads can wake up the reactor d = Deferred() def wake(): time.sleep(0.1) # callFromThread will call wakeUp for us reactor.callFromThread(d.callback, None) reactor.callInThread(wake) return d if interfaces.IReactorThreads(reactor, None) is None: testWakeUp.skip = "Nothing to wake up for without thread support" def _stopCallFromThreadCallback(self): self.stopped = True def _callFromThreadCallback(self, d): reactor.callFromThread(self._callFromThreadCallback2, d) reactor.callLater(0, self._stopCallFromThreadCallback) def _callFromThreadCallback2(self, d): try: self.assertTrue(self.stopped) except: # Send the error to the deferred d.errback() else: d.callback(None) def testCallFromThreadStops(self): """ Ensure that callFromThread from inside a callFromThread callback doesn't sit in an infinite loop and lets other things happen too. """ self.stopped = False d = defer.Deferred() reactor.callFromThread(self._callFromThreadCallback, d) return d class DelayedTests(unittest.TestCase): def setUp(self): self.finished = 0 self.counter = 0 self.timers = {} self.deferred = defer.Deferred() def tearDown(self): for t in self.timers.values(): t.cancel() def checkTimers(self): l1 = self.timers.values() l2 = list(reactor.getDelayedCalls()) # There should be at least the calls we put in. There may be other # calls that are none of our business and that we should ignore, # though. missing = [] for dc in l1: if dc not in l2: missing.append(dc) if missing: self.finished = 1 self.assertFalse(missing, "Should have been missing no calls, instead " + "was missing " + repr(missing)) def callback(self, tag): del self.timers[tag] self.checkTimers() def addCallback(self, tag): self.callback(tag) self.addTimer(15, self.callback) def done(self, tag): self.finished = 1 self.callback(tag) self.deferred.callback(None) def addTimer(self, when, callback): self.timers[self.counter] = reactor.callLater(when * 0.01, callback, self.counter) self.counter += 1 self.checkTimers() def testGetDelayedCalls(self): if not hasattr(reactor, "getDelayedCalls"): return # This is not a race because we don't do anything which might call # the reactor until we have all the timers set up. If we did, this # test might fail on slow systems. self.checkTimers() self.addTimer(35, self.done) self.addTimer(20, self.callback) self.addTimer(30, self.callback) which = self.counter self.addTimer(29, self.callback) self.addTimer(25, self.addCallback) self.addTimer(26, self.callback) self.timers[which].cancel() del self.timers[which] self.checkTimers() self.deferred.addCallback(lambda x : self.checkTimers()) return self.deferred def test_active(self): """ L{IDelayedCall.active} returns False once the call has run. """ dcall = reactor.callLater(0.01, self.deferred.callback, True) self.assertTrue(dcall.active()) def checkDeferredCall(success): self.assertFalse(dcall.active()) return success self.deferred.addCallback(checkDeferredCall) return self.deferred resolve_helper = """ from __future__ import print_function import %(reactor)s %(reactor)s.install() from twisted.internet import reactor class Foo: def __init__(self): reactor.callWhenRunning(self.start) self.timer = reactor.callLater(3, self.failed) def start(self): reactor.resolve('localhost').addBoth(self.done) def done(self, res): print('done', res) reactor.stop() def failed(self): print('failed') self.timer = None reactor.stop() f = Foo() reactor.run() """ class ChildResolveProtocol(protocol.ProcessProtocol): def __init__(self, onCompletion): self.onCompletion = onCompletion def connectionMade(self): self.output = [] self.error = [] def outReceived(self, out): self.output.append(out) def errReceived(self, err): self.error.append(err) def processEnded(self, reason): self.onCompletion.callback((reason, self.output, self.error)) self.onCompletion = None class ResolveTests(unittest.TestCase): def testChildResolve(self): # I've seen problems with reactor.run under gtk2reactor. Spawn a # child which just does reactor.resolve after the reactor has # started, fail if it does not complete in a timely fashion. helperPath = os.path.abspath(self.mktemp()) with open(helperPath, 'w') as helperFile: # Eeueuuggg reactorName = reactor.__module__ helperFile.write(resolve_helper % {'reactor': reactorName}) env = os.environ.copy() env['PYTHONPATH'] = os.pathsep.join(sys.path) helperDeferred = Deferred() helperProto = ChildResolveProtocol(helperDeferred) reactor.spawnProcess(helperProto, sys.executable, ("python", "-u", helperPath), env) def cbFinished(result): (reason, output, error) = result # If the output is "done 127.0.0.1\n" we don't really care what # else happened. output = b''.join(output) if output != b'done 127.0.0.1\n': self.fail(( "The child process failed to produce the desired results:\n" " Reason for termination was: %r\n" " Output stream was: %r\n" " Error stream was: %r\n") % (reason.getErrorMessage(), output, b''.join(error))) helperDeferred.addCallback(cbFinished) return helperDeferred if not interfaces.IReactorProcess(reactor, None): ResolveTests.skip = ( "cannot run test: reactor doesn't support IReactorProcess") class CallFromThreadTests(unittest.TestCase): """ Task scheduling from threads tests. """ if interfaces.IReactorThreads(reactor, None) is None: skip = "Nothing to test without thread support" def setUp(self): self.counter = 0 self.deferred = Deferred() def schedule(self, *args, **kwargs): """ Override in subclasses. """ reactor.callFromThread(*args, **kwargs) def test_lotsOfThreadsAreScheduledCorrectly(self): """ L{IReactorThreads.callFromThread} can be used to schedule a large number of calls in the reactor thread. """ def addAndMaybeFinish(): self.counter += 1 if self.counter == 100: self.deferred.callback(True) for i in range(100): self.schedule(addAndMaybeFinish) return self.deferred def test_threadsAreRunInScheduledOrder(self): """ Callbacks should be invoked in the order they were scheduled. """ order = [] def check(_): self.assertEqual(order, [1, 2, 3]) self.deferred.addCallback(check) self.schedule(order.append, 1) self.schedule(order.append, 2) self.schedule(order.append, 3) self.schedule(reactor.callFromThread, self.deferred.callback, None) return self.deferred def test_scheduledThreadsNotRunUntilReactorRuns(self): """ Scheduled tasks should not be run until the reactor starts running. """ def incAndFinish(): self.counter = 1 self.deferred.callback(True) self.schedule(incAndFinish) # Callback shouldn't have fired yet. self.assertEqual(self.counter, 0) return self.deferred class MyProtocol(protocol.Protocol): """ Sample protocol. """ class MyFactory(protocol.Factory): """ Sample factory. """ protocol = MyProtocol class ProtocolTests(unittest.TestCase): def testFactory(self): factory = MyFactory() protocol = factory.buildProtocol(None) self.assertEqual(protocol.factory, factory) self.assertIsInstance(protocol, factory.protocol) class DummyProducer(object): """ Very uninteresting producer implementation used by tests to ensure the right methods are called by the consumer with which it is registered. @type events: C{list} of C{str} @ivar events: The producer/consumer related events which have happened to this producer. Strings in this list may be C{'resume'}, C{'stop'}, or C{'pause'}. Elements are added as they occur. """ def __init__(self): self.events = [] def resumeProducing(self): self.events.append('resume') def stopProducing(self): self.events.append('stop') def pauseProducing(self): self.events.append('pause') class SillyDescriptor(abstract.FileDescriptor): """ A descriptor whose data buffer gets filled very fast. Useful for testing FileDescriptor's IConsumer interface, since the data buffer fills as soon as at least four characters are written to it, and gets emptied in a single doWrite() cycle. """ bufferSize = 3 connected = True def writeSomeData(self, data): """ Always write all data. """ return len(data) def startWriting(self): """ Do nothing: bypass the reactor. """ stopWriting = startWriting class ReentrantProducer(DummyProducer): """ Similar to L{DummyProducer}, but with a resumeProducing method which calls back into an L{IConsumer} method of the consumer against which it is registered. @ivar consumer: The consumer with which this producer has been or will be registered. @ivar methodName: The name of the method to call on the consumer inside C{resumeProducing}. @ivar methodArgs: The arguments to pass to the consumer method invoked in C{resumeProducing}. """ def __init__(self, consumer, methodName, *methodArgs): super(ReentrantProducer, self).__init__() self.consumer = consumer self.methodName = methodName self.methodArgs = methodArgs def resumeProducing(self): super(ReentrantProducer, self).resumeProducing() getattr(self.consumer, self.methodName)(*self.methodArgs) class ProducerTests(unittest.TestCase): """ Test abstract.FileDescriptor's consumer interface. """ def test_doubleProducer(self): """ Verify that registering a non-streaming producer invokes its resumeProducing() method and that you can only register one producer at a time. """ fd = abstract.FileDescriptor() fd.connected = 1 dp = DummyProducer() fd.registerProducer(dp, 0) self.assertEqual(dp.events, ['resume']) self.assertRaises(RuntimeError, fd.registerProducer, DummyProducer(), 0) def test_unconnectedFileDescriptor(self): """ Verify that registering a producer when the connection has already been closed invokes its stopProducing() method. """ fd = abstract.FileDescriptor() fd.disconnected = 1 dp = DummyProducer() fd.registerProducer(dp, 0) self.assertEqual(dp.events, ['stop']) def _dontPausePullConsumerTest(self, methodName): """ Pull consumers don't get their C{pauseProducing} method called if the descriptor buffer fills up. @param _methodName: Either 'write', or 'writeSequence', indicating which transport method to write data to. """ descriptor = SillyDescriptor() producer = DummyProducer() descriptor.registerProducer(producer, streaming=False) self.assertEqual(producer.events, ['resume']) del producer.events[:] # Fill up the descriptor's write buffer so we can observe whether or # not it pauses its producer in that case. if methodName == "writeSequence": descriptor.writeSequence([b'1', b'2', b'3', b'4']) else: descriptor.write(b'1234') self.assertEqual(producer.events, []) def test_dontPausePullConsumerOnWrite(self): """ Verify that FileDescriptor does not call producer.pauseProducing() on a non-streaming pull producer in response to a L{IConsumer.write} call which results in a full write buffer. Issue #2286. """ return self._dontPausePullConsumerTest('write') def test_dontPausePullConsumerOnWriteSequence(self): """ Like L{test_dontPausePullConsumerOnWrite}, but for a call to C{writeSequence} rather than L{IConsumer.write}. C{writeSequence} is not part of L{IConsumer}, but L{abstract.FileDescriptor} has supported consumery behavior in response to calls to L{writeSequence} forever. """ return self._dontPausePullConsumerTest('writeSequence') def _reentrantStreamingProducerTest(self, methodName): descriptor = SillyDescriptor() if methodName == "writeSequence": data = [b's', b'p', b'am'] else: data = b"spam" producer = ReentrantProducer(descriptor, methodName, data) descriptor.registerProducer(producer, streaming=True) # Start things off by filling up the descriptor's buffer so it will # pause its producer. getattr(descriptor, methodName)(data) # Sanity check - make sure that worked. self.assertEqual(producer.events, ['pause']) del producer.events[:] # After one call to doWrite, the buffer has been emptied so the # FileDescriptor should resume its producer. That will result in an # immediate call to FileDescriptor.write which will again fill the # buffer and result in the producer being paused. descriptor.doWrite() self.assertEqual(producer.events, ['resume', 'pause']) del producer.events[:] # After a second call to doWrite, the exact same thing should have # happened. Prior to the bugfix for which this test was written, # FileDescriptor would have incorrectly believed its producer was # already resumed (it was paused) and so not resume it again. descriptor.doWrite() self.assertEqual(producer.events, ['resume', 'pause']) def test_reentrantStreamingProducerUsingWrite(self): """ Verify that FileDescriptor tracks producer's paused state correctly. Issue #811, fixed in revision r12857. """ return self._reentrantStreamingProducerTest('write') def test_reentrantStreamingProducerUsingWriteSequence(self): """ Like L{test_reentrantStreamingProducerUsingWrite}, but for calls to C{writeSequence}. C{writeSequence} is B{not} part of L{IConsumer}, however C{abstract.FileDescriptor} has supported consumery behavior in response to calls to C{writeSequence} forever. """ return self._reentrantStreamingProducerTest('writeSequence') class PortStringificationTests(unittest.TestCase): if interfaces.IReactorTCP(reactor, None) is not None: def testTCP(self): p = reactor.listenTCP(0, protocol.ServerFactory()) portNo = p.getHost().port self.assertNotEqual(str(p).find(str(portNo)), -1, "%d not found in %s" % (portNo, p)) return p.stopListening() if interfaces.IReactorUDP(reactor, None) is not None: def testUDP(self): p = reactor.listenUDP(0, protocol.DatagramProtocol()) portNo = p.getHost().port self.assertNotEqual(str(p).find(str(portNo)), -1, "%d not found in %s" % (portNo, p)) return p.stopListening() if interfaces.IReactorSSL(reactor, None) is not None and ssl: def testSSL(self, ssl=ssl): pem = util.sibpath(__file__, 'server.pem') p = reactor.listenSSL(0, protocol.ServerFactory(), ssl.DefaultOpenSSLContextFactory(pem, pem)) portNo = p.getHost().port self.assertNotEqual(str(p).find(str(portNo)), -1, "%d not found in %s" % (portNo, p)) return p.stopListening() if _PY3: testSSL.skip = ("Re-enable once the Python 3 SSL port is done.")
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import setuptools with open('README.md') as file: readme = file.read() name = 'aio4chan' module = __import__(name) version = module.__version__ author = 'Exahilosys' url = f'https://github.com/{author}/{name}' download_url = f'{url}/archive/v{version}.tar.gz' setuptools.setup( name = name, version = version, author = author, url = url, download_url = download_url, packages = setuptools.find_packages(), license = 'MIT', description = 'API wrapper for 4chan.', long_description = readme, long_description_content_type = 'text/markdown', include_package_data = True, install_requires = ['aiohttp'], py_modules = [name], classifiers = [ 'License :: OSI Approved :: MIT License', 'Intended Audience :: Developers', 'Natural Language :: English', 'Operating System :: OS Independent', 'Programming Language :: Python :: 3.6', 'Topic :: Internet', 'Topic :: Software Development :: Libraries', 'Topic :: Software Development :: Libraries :: Python Modules', 'Topic :: Utilities', ] )
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# coding: utf-8 """ Signing Today Web *Signing Today* is the perfect Digital Signature Gateway. Whenever in Your workflow You need to add one or more Digital Signatures to Your document, *Signing Today* is the right choice. You prepare Your documents, *Signing Today* takes care of all the rest: send invitations (`signature tickets`) to signers, collects their signatures, send You back the signed document. Integrating *Signing Today* in Your existing applications is very easy. Just follow these API specifications and get inspired by the many examples presented hereafter. # noqa: E501 The version of the OpenAPI document: 2.0.0 Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import unittest import signing_today_client from signing_today_client.api.bit4id_pathgroup_digital_signature_transactions_api import Bit4idPathgroupDigitalSignatureTransactionsApi # noqa: E501 from signing_today_client.rest import ApiException class TestBit4idPathgroupDigitalSignatureTransactionsApi(unittest.TestCase): """Bit4idPathgroupDigitalSignatureTransactionsApi unit test stubs""" def setUp(self): self.api = signing_today_client.api.bit4id_pathgroup_digital_signature_transactions_api.Bit4idPathgroupDigitalSignatureTransactionsApi() # noqa: E501 def tearDown(self): pass def test_d_s_ts_get(self): """Test case for d_s_ts_get Retrieve DSTs # noqa: E501 """ pass def test_d_s_ts_post(self): """Test case for d_s_ts_post Create a new DST # noqa: E501 """ pass def test_d_st_id_audit_get(self): """Test case for d_st_id_audit_get Retrieve the audit records associated to the DST # noqa: E501 """ pass def test_d_st_id_delete(self): """Test case for d_st_id_delete Delete a DST # noqa: E501 """ pass def test_d_st_id_fill_patch(self): """Test case for d_st_id_fill_patch Fill a form of a DST # noqa: E501 """ pass def test_d_st_id_get(self): """Test case for d_st_id_get Retrieve a DST # noqa: E501 """ pass def test_d_st_id_instantiate_post(self): """Test case for d_st_id_instantiate_post Instantiate a DST from a template # noqa: E501 """ pass def test_d_st_id_modify_post(self): """Test case for d_st_id_modify_post Modify a published DST template # noqa: E501 """ pass def test_d_st_id_notify_post(self): """Test case for d_st_id_notify_post Send notifications for a DST # noqa: E501 """ pass def test_d_st_id_publish_post(self): """Test case for d_st_id_publish_post Publish a DST # noqa: E501 """ pass def test_d_st_id_put(self): """Test case for d_st_id_put Update a DST # noqa: E501 """ pass def test_d_st_id_replace_post(self): """Test case for d_st_id_replace_post Replace a rejected DST # noqa: E501 """ pass def test_d_st_id_sign_doc_id_sign_id_get(self): """Test case for d_st_id_sign_doc_id_sign_id_get Return the address for signing # noqa: E501 """ pass def test_d_st_id_templatize_post(self): """Test case for d_st_id_templatize_post Create a template from a DST # noqa: E501 """ pass if __name__ == '__main__': unittest.main()
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import os import sys import traceback from _pydev_bundle.pydev_imports import xmlrpclib, _queue, Exec from _pydev_bundle._pydev_calltip_util import get_description from _pydev_imps._pydev_saved_modules import thread from _pydevd_bundle import pydevd_vars from _pydevd_bundle import pydevd_xml from _pydevd_bundle.pydevd_constants import (IS_JYTHON, dict_iter_items, NEXT_VALUE_SEPARATOR, Null, get_global_debugger) import signal from contextlib import contextmanager from _pydev_bundle import pydev_log try: import cStringIO as StringIO # may not always be available @UnusedImport except: try: import StringIO # @Reimport except: import io as StringIO # ======================================================================================================================= # BaseStdIn # ======================================================================================================================= class BaseStdIn: def __init__(self, original_stdin=sys.stdin, *args, **kwargs): try: self.encoding = sys.stdin.encoding except: # Not sure if it's available in all Python versions... pass self.original_stdin = original_stdin try: self.errors = sys.stdin.errors # Who knew? sys streams have an errors attribute! except: # Not sure if it's available in all Python versions... pass def readline(self, *args, **kwargs): # sys.stderr.write('Cannot readline out of the console evaluation\n') -- don't show anything # This could happen if the user had done input('enter number).<-- upon entering this, that message would appear, # which is not something we want. return '\n' def write(self, *args, **kwargs): pass # not available StdIn (but it can be expected to be in the stream interface) def flush(self, *args, **kwargs): pass # not available StdIn (but it can be expected to be in the stream interface) def read(self, *args, **kwargs): # in the interactive interpreter, a read and a readline are the same. return self.readline() def close(self, *args, **kwargs): pass # expected in StdIn def __iter__(self): # BaseStdIn would not be considered as Iterable in Python 3 without explicit `__iter__` implementation return self.original_stdin.__iter__() def __getattr__(self, item): # it's called if the attribute wasn't found if hasattr(self.original_stdin, item): return getattr(self.original_stdin, item) raise AttributeError("%s has no attribute %s" % (self.original_stdin, item)) # ======================================================================================================================= # StdIn # ======================================================================================================================= class StdIn(BaseStdIn): ''' Object to be added to stdin (to emulate it as non-blocking while the next line arrives) ''' def __init__(self, interpreter, host, client_port, original_stdin=sys.stdin): BaseStdIn.__init__(self, original_stdin) self.interpreter = interpreter self.client_port = client_port self.host = host def readline(self, *args, **kwargs): # Ok, callback into the client to get the new input try: server = xmlrpclib.Server('http://%s:%s' % (self.host, self.client_port)) requested_input = server.RequestInput() if not requested_input: return '\n' # Yes, a readline must return something (otherwise we can get an EOFError on the input() call). else: # readline should end with '\n' (not doing so makes IPython 5 remove the last *valid* character). requested_input += '\n' return requested_input except KeyboardInterrupt: raise # Let KeyboardInterrupt go through -- #PyDev-816: Interrupting infinite loop in the Interactive Console except: return '\n' def close(self, *args, **kwargs): pass # expected in StdIn #======================================================================================================================= # DebugConsoleStdIn #======================================================================================================================= class DebugConsoleStdIn(BaseStdIn): ''' Object to be added to stdin (to emulate it as non-blocking while the next line arrives) ''' def __init__(self, py_db, original_stdin): ''' :param py_db: If None, get_global_debugger() is used. ''' BaseStdIn.__init__(self, original_stdin) self._py_db = py_db self._in_notification = 0 def __send_input_requested_message(self, is_started): try: py_db = self._py_db if py_db is None: py_db = get_global_debugger() cmd = py_db.cmd_factory.make_input_requested_message(is_started) py_db.writer.add_command(cmd) except Exception: pydev_log.exception() @contextmanager def notify_input_requested(self): self._in_notification += 1 if self._in_notification == 1: self.__send_input_requested_message(True) try: yield finally: self._in_notification -= 1 if self._in_notification == 0: self.__send_input_requested_message(False) def readline(self, *args, **kwargs): with self.notify_input_requested(): return self.original_stdin.readline(*args, **kwargs) def read(self, *args, **kwargs): with self.notify_input_requested(): return self.original_stdin.read(*args, **kwargs) class CodeFragment: def __init__(self, text, is_single_line=True): self.text = text self.is_single_line = is_single_line def append(self, code_fragment): self.text = self.text + "\n" + code_fragment.text if not code_fragment.is_single_line: self.is_single_line = False # ======================================================================================================================= # BaseInterpreterInterface # ======================================================================================================================= class BaseInterpreterInterface: def __init__(self, mainThread, connect_status_queue=None): self.mainThread = mainThread self.interruptable = False self.exec_queue = _queue.Queue(0) self.buffer = None self.banner_shown = False self.connect_status_queue = connect_status_queue self.mpl_modules_for_patching = {} self.init_mpl_modules_for_patching() def build_banner(self): return 'print({0})\n'.format(repr(self.get_greeting_msg())) def get_greeting_msg(self): return 'PyDev console: starting.\n' def init_mpl_modules_for_patching(self): from pydev_ipython.matplotlibtools import activate_matplotlib, activate_pylab, activate_pyplot self.mpl_modules_for_patching = { "matplotlib": lambda: activate_matplotlib(self.enableGui), "matplotlib.pyplot": activate_pyplot, "pylab": activate_pylab } def need_more_for_code(self, source): # PyDev-502: PyDev 3.9 F2 doesn't support backslash continuations # Strangely even the IPython console is_complete said it was complete # even with a continuation char at the end. if source.endswith('\\'): return True if hasattr(self.interpreter, 'is_complete'): return not self.interpreter.is_complete(source) try: # At this point, it should always be single. # If we don't do this, things as: # # for i in range(10): print(i) # # (in a single line) don't work. # Note that it won't give an error and code will be None (so, it'll # use execMultipleLines in the next call in this case). symbol = 'single' code = self.interpreter.compile(source, '<input>', symbol) except (OverflowError, SyntaxError, ValueError): # Case 1 return False if code is None: # Case 2 return True # Case 3 return False def need_more(self, code_fragment): if self.buffer is None: self.buffer = code_fragment else: self.buffer.append(code_fragment) return self.need_more_for_code(self.buffer.text) def create_std_in(self, debugger=None, original_std_in=None): if debugger is None: return StdIn(self, self.host, self.client_port, original_stdin=original_std_in) else: return DebugConsoleStdIn(py_db=debugger, original_stdin=original_std_in) def add_exec(self, code_fragment, debugger=None): # In case sys.excepthook called, use original excepthook #PyDev-877: Debug console freezes with Python 3.5+ # (showtraceback does it on python 3.5 onwards) sys.excepthook = sys.__excepthook__ try: original_in = sys.stdin try: help = None if 'pydoc' in sys.modules: pydoc = sys.modules['pydoc'] # Don't import it if it still is not there. if hasattr(pydoc, 'help'): # You never know how will the API be changed, so, let's code defensively here help = pydoc.help if not hasattr(help, 'input'): help = None except: # Just ignore any error here pass more = False try: sys.stdin = self.create_std_in(debugger, original_in) try: if help is not None: # This will enable the help() function to work. try: try: help.input = sys.stdin except AttributeError: help._input = sys.stdin except: help = None if not self._input_error_printed: self._input_error_printed = True sys.stderr.write('\nError when trying to update pydoc.help.input\n') sys.stderr.write('(help() may not work -- please report this as a bug in the pydev bugtracker).\n\n') traceback.print_exc() try: self.start_exec() if hasattr(self, 'debugger'): self.debugger.enable_tracing() more = self.do_add_exec(code_fragment) if hasattr(self, 'debugger'): self.debugger.disable_tracing() self.finish_exec(more) finally: if help is not None: try: try: help.input = original_in except AttributeError: help._input = original_in except: pass finally: sys.stdin = original_in except SystemExit: raise except: traceback.print_exc() finally: sys.__excepthook__ = sys.excepthook return more def do_add_exec(self, codeFragment): ''' Subclasses should override. @return: more (True if more input is needed to complete the statement and False if the statement is complete). ''' raise NotImplementedError() def get_namespace(self): ''' Subclasses should override. @return: dict with namespace. ''' raise NotImplementedError() def __resolve_reference__(self, text): """ :type text: str """ obj = None if '.' not in text: try: obj = self.get_namespace()[text] except KeyError: pass if obj is None: try: obj = self.get_namespace()['__builtins__'][text] except: pass if obj is None: try: obj = getattr(self.get_namespace()['__builtins__'], text, None) except: pass else: try: last_dot = text.rindex('.') parent_context = text[0:last_dot] res = pydevd_vars.eval_in_context(parent_context, self.get_namespace(), self.get_namespace()) obj = getattr(res, text[last_dot + 1:]) except: pass return obj def getDescription(self, text): try: obj = self.__resolve_reference__(text) if obj is None: return '' return get_description(obj) except: return '' def do_exec_code(self, code, is_single_line): try: code_fragment = CodeFragment(code, is_single_line) more = self.need_more(code_fragment) if not more: code_fragment = self.buffer self.buffer = None self.exec_queue.put(code_fragment) return more except: traceback.print_exc() return False def execLine(self, line): return self.do_exec_code(line, True) def execMultipleLines(self, lines): if IS_JYTHON: more = False for line in lines.split('\n'): more = self.do_exec_code(line, True) return more else: return self.do_exec_code(lines, False) def interrupt(self): self.buffer = None # Also clear the buffer when it's interrupted. try: if self.interruptable: called = False try: # Fix for #PyDev-500: Console interrupt can't interrupt on sleep if os.name == 'posix': # On Linux we can't interrupt 0 as in Windows because it's # actually owned by a process -- on the good side, signals # work much better on Linux! os.kill(os.getpid(), signal.SIGINT) called = True elif os.name == 'nt': # Stupid windows: sending a Ctrl+C to a process given its pid # is absurdly difficult. # There are utilities to make it work such as # http://www.latenighthacking.com/projects/2003/sendSignal/ # but fortunately for us, it seems Python does allow a CTRL_C_EVENT # for the current process in Windows if pid 0 is passed... if we needed # to send a signal to another process the approach would be # much more difficult. # Still, note that CTRL_C_EVENT is only Python 2.7 onwards... # Also, this doesn't seem to be documented anywhere!? (stumbled # upon it by chance after digging quite a lot). os.kill(0, signal.CTRL_C_EVENT) called = True except: # Many things to go wrong (from CTRL_C_EVENT not being there # to failing import signal)... if that's the case, ask for # forgiveness and go on to the approach which will interrupt # the main thread (but it'll only work when it's executing some Python # code -- not on sleep() for instance). pass if not called: if hasattr(thread, 'interrupt_main'): # Jython doesn't have it thread.interrupt_main() else: self.mainThread._thread.interrupt() # Jython self.finish_exec(False) return True except: traceback.print_exc() return False def close(self): sys.exit(0) def start_exec(self): self.interruptable = True def get_server(self): if getattr(self, 'host', None) is not None: return xmlrpclib.Server('http://%s:%s' % (self.host, self.client_port)) else: return None server = property(get_server) def ShowConsole(self): server = self.get_server() if server is not None: server.ShowConsole() def finish_exec(self, more): self.interruptable = False server = self.get_server() if server is not None: return server.NotifyFinished(more) else: return True def getFrame(self): xml = StringIO.StringIO() hidden_ns = self.get_ipython_hidden_vars_dict() xml.write("<xml>") xml.write(pydevd_xml.frame_vars_to_xml(self.get_namespace(), hidden_ns)) xml.write("</xml>") return xml.getvalue() def getVariable(self, attributes): xml = StringIO.StringIO() xml.write("<xml>") val_dict = pydevd_vars.resolve_compound_var_object_fields(self.get_namespace(), attributes) if val_dict is None: val_dict = {} keys = val_dict.keys() for k in keys: val = val_dict[k] evaluate_full_value = pydevd_xml.should_evaluate_full_value(val) xml.write(pydevd_vars.var_to_xml(val, k, evaluate_full_value=evaluate_full_value)) xml.write("</xml>") return xml.getvalue() def getArray(self, attr, roffset, coffset, rows, cols, format): name = attr.split("\t")[-1] array = pydevd_vars.eval_in_context(name, self.get_namespace(), self.get_namespace()) return pydevd_vars.table_like_struct_to_xml(array, name, roffset, coffset, rows, cols, format) def evaluate(self, expression): xml = StringIO.StringIO() xml.write("<xml>") result = pydevd_vars.eval_in_context(expression, self.get_namespace(), self.get_namespace()) xml.write(pydevd_vars.var_to_xml(result, expression)) xml.write("</xml>") return xml.getvalue() def loadFullValue(self, seq, scope_attrs): """ Evaluate full value for async Console variables in a separate thread and send results to IDE side :param seq: id of command :param scope_attrs: a sequence of variables with their attributes separated by NEXT_VALUE_SEPARATOR (i.e.: obj\tattr1\tattr2NEXT_VALUE_SEPARATORobj2\attr1\tattr2) :return: """ frame_variables = self.get_namespace() var_objects = [] vars = scope_attrs.split(NEXT_VALUE_SEPARATOR) for var_attrs in vars: if '\t' in var_attrs: name, attrs = var_attrs.split('\t', 1) else: name = var_attrs attrs = None if name in frame_variables: var_object = pydevd_vars.resolve_var_object(frame_variables[name], attrs) var_objects.append((var_object, name)) else: var_object = pydevd_vars.eval_in_context(name, frame_variables, frame_variables) var_objects.append((var_object, name)) from _pydevd_bundle.pydevd_comm import GetValueAsyncThreadConsole t = GetValueAsyncThreadConsole(self.get_server(), seq, var_objects) t.start() def changeVariable(self, attr, value): def do_change_variable(): Exec('%s=%s' % (attr, value), self.get_namespace(), self.get_namespace()) # Important: it has to be really enabled in the main thread, so, schedule # it to run in the main thread. self.exec_queue.put(do_change_variable) def connectToDebugger(self, debuggerPort, debugger_options=None): ''' Used to show console with variables connection. Mainly, monkey-patches things in the debugger structure so that the debugger protocol works. ''' if debugger_options is None: debugger_options = {} env_key = "PYDEVD_EXTRA_ENVS" if env_key in debugger_options: for (env_name, value) in dict_iter_items(debugger_options[env_key]): existing_value = os.environ.get(env_name, None) if existing_value: os.environ[env_name] = "%s%c%s" % (existing_value, os.path.pathsep, value) else: os.environ[env_name] = value if env_name == "PYTHONPATH": sys.path.append(value) del debugger_options[env_key] def do_connect_to_debugger(): try: # Try to import the packages needed to attach the debugger import pydevd from _pydev_imps._pydev_saved_modules import threading except: # This happens on Jython embedded in host eclipse traceback.print_exc() sys.stderr.write('pydevd is not available, cannot connect\n') from _pydevd_bundle.pydevd_constants import set_thread_id from _pydev_bundle import pydev_localhost set_thread_id(threading.currentThread(), "console_main") VIRTUAL_FRAME_ID = "1" # matches PyStackFrameConsole.java VIRTUAL_CONSOLE_ID = "console_main" # matches PyThreadConsole.java f = FakeFrame() f.f_back = None f.f_globals = {} # As globals=locals here, let's simply let it empty (and save a bit of network traffic). f.f_locals = self.get_namespace() self.debugger = pydevd.PyDB() self.debugger.add_fake_frame(thread_id=VIRTUAL_CONSOLE_ID, frame_id=VIRTUAL_FRAME_ID, frame=f) try: pydevd.apply_debugger_options(debugger_options) self.debugger.connect(pydev_localhost.get_localhost(), debuggerPort) self.debugger.prepare_to_run() self.debugger.disable_tracing() except: traceback.print_exc() sys.stderr.write('Failed to connect to target debugger.\n') # Register to process commands when idle self.debugrunning = False try: import pydevconsole pydevconsole.set_debug_hook(self.debugger.process_internal_commands) except: traceback.print_exc() sys.stderr.write('Version of Python does not support debuggable Interactive Console.\n') # Important: it has to be really enabled in the main thread, so, schedule # it to run in the main thread. self.exec_queue.put(do_connect_to_debugger) return ('connect complete',) def handshake(self): if self.connect_status_queue is not None: self.connect_status_queue.put(True) return "PyCharm" def get_connect_status_queue(self): return self.connect_status_queue def hello(self, input_str): # Don't care what the input string is return ("Hello eclipse",) def enableGui(self, guiname): ''' Enable the GUI specified in guiname (see inputhook for list). As with IPython, enabling multiple GUIs isn't an error, but only the last one's main loop runs and it may not work ''' def do_enable_gui(): from _pydev_bundle.pydev_versioncheck import versionok_for_gui if versionok_for_gui(): try: from pydev_ipython.inputhook import enable_gui enable_gui(guiname) except: sys.stderr.write("Failed to enable GUI event loop integration for '%s'\n" % guiname) traceback.print_exc() elif guiname not in ['none', '', None]: # Only print a warning if the guiname was going to do something sys.stderr.write("PyDev console: Python version does not support GUI event loop integration for '%s'\n" % guiname) # Return value does not matter, so return back what was sent return guiname # Important: it has to be really enabled in the main thread, so, schedule # it to run in the main thread. self.exec_queue.put(do_enable_gui) def get_ipython_hidden_vars_dict(self): return None # ======================================================================================================================= # FakeFrame # ======================================================================================================================= class FakeFrame: ''' Used to show console with variables connection. A class to be used as a mock of a frame. '''
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from .writer import saveMeshTracks from .reader import loadMeshTracks from .meshdata import Track, Mesh
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"""Utilities for setting up a project's settings. The default way to use this is to import and call :func:`init_settings` in a project's settings module: # project/top_level_package/settings.py from arcutils.settings import init_settings init_settings() This adds a few default settings for bootstrapping purposes and then loads the project's local settings--the django-local-settings variety. Pass ``local_settings=False`` to :func:`init_settings` if the project doesn't use django-local-settings. """ import base64 import inspect import ipaddress import os import pkg_resources from datetime import datetime from django import VERSION as DJANGO_VERSION from django.conf import settings as django_settings from django.utils import timezone from local_settings import NO_DEFAULT, load_and_check_settings, LocalSetting, SecretSetting from local_settings.settings import DottedAccessDict, Settings as LocalSettings ARCUTILS_PACKAGE_DIR = pkg_resources.resource_filename('arcutils', '') class _InternalIPsType: """Used to construct a convenient INTERNAL_IPS setting for dev. An *instance* of this type considers any standard loopback or private IP address a valid internal IP address. """ def __contains__(self, addr): addr = ipaddress.ip_address(addr) return addr.is_loopback or addr.is_private INTERNAL_IPS = _InternalIPsType() def init_settings(settings=None, local_settings=True, prompt=None, quiet=None, package_level=0, stack_level=2, drop=(), settings_processors=()): """Initialize project settings. Basic Usage =========== By default, it's assumed that the project is structured like so, with the settings module in the top level package:: project/ package/ __init__.py settings.py README setup.py It's also assumed that :func:`init_settings` will be called from the global scope of the project's settings module:: # package/settings.py from arcutils.settings import init_settings init_settings() A few default settings that are commonly used in local settings files will be added (if not explicitly set before calling this function): - ARCUTILS_PACKAGE_DIR - PACKAGE (top level project package) - PACKAGE_DIR (top level project package directory) - ROOT_DIR (project directory; should only be used in dev) - START_TIME (current date/time; will be an "aware" UTC datetime object if the project has time zone support enabled) If the project has additional local settings, they must be defined *before* this function is called. Advanced Usage ============== Generally, you won't need to pass ``settings``, but if you do, it should be a dict of settings as you'd get from calling ``globals()`` in the project's settings module. If the settings module is in a sub-package, ``package_level`` will need to be adjusted accordingly. If :func:`init_settings` is being called from another function, ``stack_level`` will have to be adjusted accordingly. See :func:`derive_top_level_package_name` for more info about these args. The ``PACKAGE``, ``PACKAGE_DIR``, and ``ROOT_DIR`` settings will be derived based on the location of the settings module this function is called from. If this isn't working, ensure the ``package_level`` and ``stack_level`` options are correct; or, set the ``PACKAGE`` setting explicitly before calling this function:: PACKAGE = 'quickticket' init_settings() ``PACKAGE_DIR`` and ``ROOT_DIR`` can also be set explicitly if necessary. .. note:: If the package name and related settings can't be derived automatically, that indicates a bug in this function. To drop unused default settings, specify a list of such settings via the ``drop`` arg. To process settings in any custom manner needed, pass a list of functions via ``settings_processors``. Each processor will be passed the settings to be manipulated as necessary. """ settings = settings if settings is not None else get_module_globals(stack_level) if not settings.get('ARCUTILS_PACKAGE_DIR'): settings['ARCUTILS_PACKAGE_DIR'] = ARCUTILS_PACKAGE_DIR if not settings.get('PACKAGE'): # The default value for PACKAGE is derived by figuring out where # init_settings was called from in terms of package and scope. settings['PACKAGE'] = derive_top_level_package_name(package_level, stack_level) if not settings.get('PACKAGE_DIR'): # The default value for PACKAGE_DIR is simply the directory # corresponding to PACKAGE. settings['PACKAGE_DIR'] = pkg_resources.resource_filename(settings['PACKAGE'], '') if not settings.get('ROOT_DIR'): # The default value for ROOT_DIR is the directory N levels up # from PACKAGE_DIR, where N is equal to the package depth of the # top level package. Note that in most cases N is 1; it will be # greater than 1 when the top level package is contained in a # namespace package. package_depth = len(settings['PACKAGE'].split('.')) parts = os.path.split(settings['PACKAGE_DIR']) root_dir = os.path.join(*parts[:package_depth]) settings['ROOT_DIR'] = root_dir if local_settings: init_local_settings(settings, prompt=prompt, quiet=quiet) # NOTE: We can't simply use Django's timezone.now() here because it # accesses settings.USE_TZ, but at this point the settings # may not be considered fully configured by Django, so we have # to do this to avoid an ImproperlyConfigured exception. use_tz = settings.get('USE_TZ', False) now = datetime.utcnow().replace(tzinfo=timezone.utc) if use_tz else datetime.now() settings.setdefault('START_TIME', now) # Remove the MIDDLEWARE_CLASSES setting on Django >= 1.10, but only # if the MIDDLEWARE setting is present *and* set. if DJANGO_VERSION[:2] >= (1, 10): if settings.get('MIDDLEWARE'): settings.pop('MIDDLEWARE_CLASSES', None) # Drop irrelevant settings. for name in drop: del settings[name] for processor in settings_processors: processor(settings) return settings def init_local_settings(settings, prompt=None, quiet=None): """Initialize the local settings defined in ``settings``. Args: settings (dict): A dict of settings as you'd get from calling ``globals()`` in a Django settings module. quiet (bool): Squelch standard out when loading local settings. .. note:: If your project has additional local settings, they must be defined *before* this function is called. """ suggested_secret_key = base64.b64encode(os.urandom(64)).decode('utf-8') defaults = { 'DEBUG': LocalSetting(False), 'ADMINS': LocalSetting([]), 'ALLOWED_HOSTS': LocalSetting([]), 'GOOGLE': { 'analytics': { 'tracking_id': LocalSetting( None, doc='Enter Google Analytics tracking ID (UA-NNNNNNNN-N)' ), }, }, 'MANAGERS': LocalSetting([]), 'SECRET_KEY': SecretSetting(doc='Suggested: "{suggested_secret_key}"'.format(**locals())), 'DATABASES': { 'default': { 'ENGINE': LocalSetting('django.db.backends.postgresql'), 'NAME': LocalSetting(settings.get('PACKAGE', NO_DEFAULT)), 'USER': LocalSetting(''), 'PASSWORD': SecretSetting(), 'HOST': LocalSetting(''), }, }, } for k, v in defaults.items(): settings.setdefault(k, v) settings.update(load_and_check_settings(settings, prompt=prompt, quiet=quiet)) def get_setting(name, default=NO_DEFAULT, settings=None): """Get setting for ``name``, falling back to ``default`` if passed. ``name`` should be a string like 'ARC.cdn.hosts' or 'X.Y.0'. The name is split on dots into path segments, then the settings are traversed like this: - Set current value to django.conf.settings.{first segment} - For each other segment - Get current_value[segment] if current value is a dict - Get current_value[int(segment)] if current value is a list If the setting isn't found, the ``default`` value will be returned if specified; otherwise, a ``KeyError`` will be raised. ``settings`` can be used to retrieve the setting from a settings object other than the default ``django.conf.settings``. :class:`local_settings.settings.DottedAccessDict` is used to implement this functionality. See the django-local-settings project for more details about settings traversal. """ if settings is None: settings = django_settings if not isinstance(settings, LocalSettings): settings = DottedAccessDict(get_settings_dict(settings)) return settings.get_dotted(name, default) class PrefixedSettings: """Read-only settings for a given ``prefix``. Args: prefix: An upper case setting name such as "CAS" or "LDAP" defaults: A dict of defaults for the prefix The idea is to make it easy to fetch sub-settings within a given package. For example:: >>> DEFAULT_CAS_SETTINGS = { ... 'base_url': 'https://example.com/cas/', ... # plus a bunch more CAS settings... ... } >>> cas_settings = PrefixedSettings('CAS', DEFAULT_CAS_SETTINGS) >>> cas_settings.get('base_url') 'https://example.com/cas/' >>> cas_settings.get('logout_path', default='/default/logout/path') '/default/logout/path' See the ``cas``, ``ldap``, and ``masquerade`` packages for concrete examples of how this is used. """ def __init__(self, prefix, defaults=None, settings=None): defaults = get_settings_dict(defaults) settings = get_settings_dict(settings if settings is not None else django_settings) self.__prefix = prefix self.__defaults = DottedAccessDict(defaults) self.__settings = DottedAccessDict(settings) def get(self, name, default=NO_DEFAULT): """Get setting for configured ``prefix``. Args: name: setting name without ``prefix`` default: value to use if setting isn't present in the project's settings or in the ``defaults`` Returns: object: Value of setting Attempt to get setting from: 1. Project settings for ``prefix`` 2. Default settings from ``defaults`` 3. ``default`` arg Raises: KeyError: When the setting isn't found in the project's settings or in the ``defaults`` and no fallback is passed via the ``default`` keyword arg """ qualified_name = '{prefix}.{name}'.format(prefix=self.__prefix, name=name) try: return self.__settings.get_dotted(qualified_name) except KeyError: return self.__defaults.get_dotted(name, default=default) def __getitem__(self, key): return PrefixedSettings.get(self, key, NO_DEFAULT) # Internal helper functions def get_settings_dict(settings): """For a given settings object, return a dict. Args: settings (object): Usually either a Django settings object or a dict; can also be a sequence that can be converted to a dict or some other non-dict mapping Returns: empty dict: ``settings`` is ``None`` vars(settings._wrapped): ``settings`` is (or appears to be) a Django settings object dict(settings): ``settings`` is any other type of object """ if settings is None: return {} if hasattr(settings, '_wrapped'): # A Django settings object # TODO: Find a better way to check for Django settings? return vars(settings._wrapped) return dict(settings) def derive_top_level_package_name(package_level=0, stack_level=1): """Return top level package name. Args: package_level (int): How many package levels down the caller is. 0 indicates this function is being called from the top level package, 1 indicates that it's being called from a sub-package, etc. stack_level (int): How many levels down the stack the caller is from here. 1 indicates this function is being called from module scope, 2 indicates this function is being called from another function, etc. This will first get the package name of the module containing the caller. ``package_level`` segments will be then be chopped off of the package name. If this is called from a sub-package, ``package_level`` will have to be adjusted accordingly (add 1 for each sub-package). If this is called indirectly (e.g., via :func:`init_settings`) ``stack_level`` will have to be adjusted accordingly (add 1 for each nested function). """ assert package_level >= 0, 'Package level should be greater than or equal to 0' assert stack_level > 0, 'Stack level should be greater than 0' frame = inspect.stack()[stack_level][0] package = frame.f_globals['__package__'] package = package.rsplit('.', package_level)[0] return package def get_module_globals(stack_level=2): frame = inspect.stack()[stack_level][0] return frame.f_globals
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# Copyright (c) 2010-2012 OpenStack Foundation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or # implied. # See the License for the specific language governing permissions and # limitations under the License. from swift import gettext_ as _ from urllib import unquote from swift.account.utils import account_listing_response from swift.common.request_helpers import get_listing_content_type from swift.common.utils import public from swift.common.constraints import check_metadata, MAX_ACCOUNT_NAME_LENGTH from swift.common.http import HTTP_NOT_FOUND, HTTP_GONE from swift.proxy.controllers.base import Controller, clear_info_cache from swift.common.swob import HTTPBadRequest, HTTPMethodNotAllowed class AccountController(Controller): """WSGI controller for account requests""" server_type = 'Account' def __init__(self, app, account_name, **kwargs): Controller.__init__(self, app) self.account_name = unquote(account_name) if not self.app.allow_account_management: self.allowed_methods.remove('PUT') self.allowed_methods.remove('DELETE') def GETorHEAD(self, req): """Handler for HTTP GET/HEAD requests.""" if len(self.account_name) > MAX_ACCOUNT_NAME_LENGTH: resp = HTTPBadRequest(request=req) resp.body = 'Account name length of %d longer than %d' % \ (len(self.account_name), MAX_ACCOUNT_NAME_LENGTH) return resp partition, nodes = self.app.account_ring.get_nodes(self.account_name) resp = self.GETorHEAD_base( req, _('Account'), self.app.account_ring, partition, req.path_info.rstrip('/')) if resp.status_int == HTTP_NOT_FOUND: if resp.headers.get('X-Account-Status', '').lower() == 'deleted': resp.status = HTTP_GONE elif self.app.account_autocreate: resp = account_listing_response(self.account_name, req, get_listing_content_type(req)) if not req.environ.get('swift_owner', False): for key in self.app.swift_owner_headers: if key in resp.headers: del resp.headers[key] return resp @public def PUT(self, req): """HTTP PUT request handler.""" if not self.app.allow_account_management: return HTTPMethodNotAllowed( request=req, headers={'Allow': ', '.join(self.allowed_methods)}) error_response = check_metadata(req, 'account') if error_response: return error_response if len(self.account_name) > MAX_ACCOUNT_NAME_LENGTH: resp = HTTPBadRequest(request=req) resp.body = 'Account name length of %d longer than %d' % \ (len(self.account_name), MAX_ACCOUNT_NAME_LENGTH) return resp account_partition, accounts = \ self.app.account_ring.get_nodes(self.account_name) headers = self.generate_request_headers(req, transfer=True) clear_info_cache(self.app, req.environ, self.account_name) resp = self.make_requests( req, self.app.account_ring, account_partition, 'PUT', req.path_info, [headers] * len(accounts)) return resp @public def POST(self, req): """HTTP POST request handler.""" if len(self.account_name) > MAX_ACCOUNT_NAME_LENGTH: resp = HTTPBadRequest(request=req) resp.body = 'Account name length of %d longer than %d' % \ (len(self.account_name), MAX_ACCOUNT_NAME_LENGTH) return resp error_response = check_metadata(req, 'account') if error_response: return error_response account_partition, accounts = \ self.app.account_ring.get_nodes(self.account_name) headers = self.generate_request_headers(req, transfer=True) clear_info_cache(self.app, req.environ, self.account_name) resp = self.make_requests( req, self.app.account_ring, account_partition, 'POST', req.path_info, [headers] * len(accounts)) if resp.status_int == HTTP_NOT_FOUND and self.app.account_autocreate: self.autocreate_account(req.environ, self.account_name) resp = self.make_requests( req, self.app.account_ring, account_partition, 'POST', req.path_info, [headers] * len(accounts)) return resp @public def DELETE(self, req): """HTTP DELETE request handler.""" # Extra safety in case someone typos a query string for an # account-level DELETE request that was really meant to be caught by # some middleware. if req.query_string: return HTTPBadRequest(request=req) if not self.app.allow_account_management: return HTTPMethodNotAllowed( request=req, headers={'Allow': ', '.join(self.allowed_methods)}) account_partition, accounts = \ self.app.account_ring.get_nodes(self.account_name) headers = self.generate_request_headers(req) clear_info_cache(self.app, req.environ, self.account_name) resp = self.make_requests( req, self.app.account_ring, account_partition, 'DELETE', req.path_info, [headers] * len(accounts)) return resp
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# -*- coding: utf-8 -*- """ Created on Thu Apr 9 21:03:57 2020 @author: Mehul """ #importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd import random import warnings from matplotlib import style from collections import Counter from math import sqrt style.use('fivethirtyeight') #defining knn function def k_nearest_neighbors(data,predict,k=3): distances=[] if(len(data)>=k): #this is not an error it is just a warning , the algorithm still works warnings.warn('The value of k is less than the number of voting groups.') for group in data: #data is a dictionary of lists with different groups of classes for features in data[group]: #features represent the points in the dataset #original way #euclidean_distance=sqrt((features[0]-predict[0])**2+(features[1]-predict[1])**2) #faster way euclidean_distance=np.linalg.norm(np.array(features)-np.array(predict)) distances.append([euclidean_distance,group]) #once we have the distances we dont care about them #we populate the list of votes which has the top k neighbors to the prediction point votes=[i[1] for i in sorted(distances)[:k] ] #using counter we calculate the most common out of the nearest neighbors vote_result=Counter(votes).most_common(1)[0][0] #we can also give our confidence,confidence is the probability of your prediction being right #confidence=Counter(votes).most_common(1)[0][1]/k return vote_result def accuracy_of_result(train_set,test_set): #intialising correct=0 total=0 #testing and finding accuracy for group in test_set: for data in test_set[group]: #iterating through all the data in a class result=k_nearest_neighbors(train_set,data,k=5) if (group==result): correct=correct+1 total=total+1 accuracy=correct/total return accuracy '''' #trial data #our data is in form of dictionary of lists dataset={'k':[[1,2],[2,3,],[3,1]],'r':[[6,5],[7,7],[8,6]]} new_features=[5,7] #plotting the data plt.scatter(new_features[0],new_features[1],s=50) for i in dataset: for j in dataset[i]: print(j) plt.scatter(j[0],j[1],s=100,color=i) #applying knn model result=k_nearest_neighbors(dataset,new_features,k=3)#result represents the class the prediction point belongs to #plotting the prediction plt.scatter(new_features[0],new_features[1],s=50,color=result) for i in dataset: for j in dataset[i]: print(j) plt.scatter(j[0],j[1],s=100,color=i) ''' #Implmenting the model on the test dataset #importing the dataset dataset=pd.read_csv('breast-cancer-wisconsin.data.txt') #replacing missing instances with large numbers dataset.replace('?',-99999,inplace=True) dataset.drop(['id'],1,inplace=True) dataset=dataset.astype(float).values.tolist() #shuffling to data to include some randomness #this does not change the raltionship between the data #this is what can be used for cross-validation random.shuffle(dataset) #splitting the dataset into test set and train set test_size=0.2 #the train set and the test set are dictionary of lists train_set={2:[],4:[]} test_set={2:[],4:[]} #slicing the data into train_data and test_data train_data=dataset[:-int(test_size*len(dataset))] #all the data upto the last 20% test_data=dataset[-int(test_size*len(dataset)):] #the last 20% #populating the dictionary #here we take the data from the train_data and the test_data and use it to populate our dictionaries for i in train_data: train_set[i[-1]].append(i[:-1])# i[-1] represents the class of the particular row for i in test_data: test_set[i[-1]].append(i[:-1])# i[-1] represents the class of the particular row #getting the accuracy of our knn model on the dataset print('Accuracy of the result:',accuracy_of_result(train_set,test_set))
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# -*- coding:utf-8 -*- from mongoengine import (IntField, DateTimeField, StringField, ReferenceField, DictField) from model import BaseModel # from ext import db class Account(BaseModel): name = StringField(max_length=5000, null=False) tel = IntField(null=False) password = StringField(max_length=5000, null=False) head_img_key = StringField(max_length=5000, null=False) meta = {'collection': 'account'}
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import autofit as af import autolens as al from test_autolens.integration.tests.interferometer import runner test_type = "lens_only" test_name = "lens_x2_light__hyper" data_type = "lens_x2_light" data_resolution = "sma" def make_pipeline( name, phase_folders, real_space_shape_2d=(100, 100), real_space_pixel_scales=(0.1, 0.1), non_linear_class=af.MultiNest, ): class LensPlaneGalaxyX2Phase(al.PhaseInterferometer): def customize_priors(self, results): self.galaxies.lens_0.light.centre_0 = -1.0 self.galaxies.lens_0.light.centre_1 = -1.0 self.galaxies.lens_1.light.centre_0 = 1.0 self.galaxies.lens_1.light.centre_1 = 1.0 phase1 = LensPlaneGalaxyX2Phase( phase_name="phase_1", phase_folders=phase_folders, galaxies=dict( lens_0=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic), lens_1=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic), ), real_space_shape_2d=real_space_shape_2d, real_space_pixel_scales=real_space_pixel_scales, non_linear_class=non_linear_class, ) phase1.optimizer.const_efficiency_mode = True phase1.optimizer.n_live_points = 40 phase1.optimizer.sampling_efficiency = 0.8 phase1 = phase1.extend_with_multiple_hyper_phases(hyper_galaxy=True) phase2 = al.PhaseInterferometer( phase_name="phase_2", phase_folders=phase_folders, galaxies=dict( lens_0=al.GalaxyModel( redshift=0.5, light=phase1.result.model.galaxies.lens_0.light, hyper_galaxy=phase1.result.hyper_combined.instance.galaxies.lens_0.hyper_galaxy, ), lens_1=al.GalaxyModel( redshift=0.5, light=phase1.result.model.galaxies.lens_1.light, hyper_galaxy=phase1.result.hyper_combined.instance.galaxies.lens_1.hyper_galaxy, ), ), real_space_shape_2d=real_space_shape_2d, real_space_pixel_scales=real_space_pixel_scales, non_linear_class=non_linear_class, ) phase2.optimizer.const_efficiency_mode = True phase2.optimizer.n_live_points = 40 phase2.optimizer.sampling_efficiency = 0.8 return al.PipelineDataset(name, phase1, phase2) if __name__ == "__main__": import sys runner.run(sys.modules[__name__])
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from django.test import TestCase, override_settings from model_bakery import baker from rest_framework.test import APIClient from accounts.models import User from core.models import CoreSettings from rest_framework.authtoken.models import Token class TacticalTestCase(TestCase): def authenticate(self): self.john = User(username="john") self.john.set_password("hunter2") self.john.save() self.alice = User(username="alice") self.alice.set_password("hunter2") self.alice.save() self.client_setup() self.client.force_authenticate(user=self.john) def setup_agent_auth(self, agent): agent_user = User.objects.create_user( username=agent.agent_id, password=User.objects.make_random_password(60) ) Token.objects.create(user=agent_user) def client_setup(self): self.client = APIClient() # fixes tests waiting 2 minutes for mesh token to appear @override_settings( MESH_TOKEN_KEY="41410834b8bb4481446027f87d88ec6f119eb9aa97860366440b778540c7399613f7cabfef4f1aa5c0bd9beae03757e17b2e990e5876b0d9924da59bdf24d3437b3ed1a8593b78d65a72a76c794160d9" ) def setup_coresettings(self): self.coresettings = CoreSettings.objects.create() def check_not_authenticated(self, method, url): self.client.logout() switch = { "get": self.client.get(url), "post": self.client.post(url), "put": self.client.put(url), "patch": self.client.patch(url), "delete": self.client.delete(url), } r = switch.get(method) self.assertEqual(r.status_code, 401) def create_checks(self, policy=None, agent=None, script=None): if not policy and not agent: return # will create 1 of every check and associate it with the policy object passed check_recipes = [ "checks.diskspace_check", "checks.ping_check", "checks.cpuload_check", "checks.memory_check", "checks.winsvc_check", "checks.script_check", "checks.eventlog_check", ] checks = list() for recipe in check_recipes: if not script: checks.append(baker.make_recipe(recipe, policy=policy, agent=agent)) else: checks.append( baker.make_recipe(recipe, policy=policy, agent=agent, script=script) ) return checks
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# # Copyright (c) 2017 Intel Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from typing import Union import numpy as np import scipy.signal from rl_coach.agents.policy_optimization_agent import PolicyOptimizationAgent, PolicyGradientRescaler from rl_coach.architectures.tensorflow_components.heads.policy_head import PolicyHeadParameters from rl_coach.architectures.tensorflow_components.heads.v_head import VHeadParameters from rl_coach.architectures.tensorflow_components.middlewares.fc_middleware import FCMiddlewareParameters from rl_coach.base_parameters import AlgorithmParameters, NetworkParameters, \ AgentParameters from rl_coach.logger import screen from rl_coach.memories.episodic.single_episode_buffer import SingleEpisodeBufferParameters from rl_coach.spaces import DiscreteActionSpace from rl_coach.utils import last_sample from rl_coach.architectures.tensorflow_components.embedders.embedder import InputEmbedderParameters class ActorCriticAlgorithmParameters(AlgorithmParameters): def __init__(self): super().__init__() self.policy_gradient_rescaler = PolicyGradientRescaler.A_VALUE self.apply_gradients_every_x_episodes = 5 self.beta_entropy = 0 self.num_steps_between_gradient_updates = 5000 # this is called t_max in all the papers self.gae_lambda = 0.96 self.estimate_state_value_using_gae = False class ActorCriticNetworkParameters(NetworkParameters): def __init__(self): super().__init__() self.input_embedders_parameters = {'observation': InputEmbedderParameters()} self.middleware_parameters = FCMiddlewareParameters() self.heads_parameters = [VHeadParameters(), PolicyHeadParameters()] self.loss_weights = [0.5, 1.0] self.rescale_gradient_from_head_by_factor = [1, 1] self.optimizer_type = 'Adam' self.clip_gradients = 40.0 self.async_training = True class ActorCriticAgentParameters(AgentParameters): def __init__(self): super().__init__(algorithm=ActorCriticAlgorithmParameters(), exploration=None, #TODO this should be different for continuous (ContinuousEntropyExploration) # and discrete (CategoricalExploration) action spaces. memory=SingleEpisodeBufferParameters(), networks={"main": ActorCriticNetworkParameters()}) @property def path(self): return 'rl_coach.agents.actor_critic_agent:ActorCriticAgent' # Actor Critic - https://arxiv.org/abs/1602.01783 class ActorCriticAgent(PolicyOptimizationAgent): def __init__(self, agent_parameters, parent: Union['LevelManager', 'CompositeAgent']=None): super().__init__(agent_parameters, parent) self.last_gradient_update_step_idx = 0 self.action_advantages = self.register_signal('Advantages') self.state_values = self.register_signal('Values') self.value_loss = self.register_signal('Value Loss') self.policy_loss = self.register_signal('Policy Loss') # Discounting function used to calculate discounted returns. def discount(self, x, gamma): return scipy.signal.lfilter([1], [1, -gamma], x[::-1], axis=0)[::-1] def get_general_advantage_estimation_values(self, rewards, values): # values contain n+1 elements (t ... t+n+1), rewards contain n elements (t ... t + n) bootstrap_extended_rewards = np.array(rewards.tolist() + [values[-1]]) # Approximation based calculation of GAE (mathematically correct only when Tmax = inf, # although in practice works even in much smaller Tmax values, e.g. 20) deltas = rewards + self.ap.algorithm.discount * values[1:] - values[:-1] gae = self.discount(deltas, self.ap.algorithm.discount * self.ap.algorithm.gae_lambda) if self.ap.algorithm.estimate_state_value_using_gae: discounted_returns = np.expand_dims(gae + values[:-1], -1) else: discounted_returns = np.expand_dims(np.array(self.discount(bootstrap_extended_rewards, self.ap.algorithm.discount)), 1)[:-1] return gae, discounted_returns def learn_from_batch(self, batch): # batch contains a list of episodes to learn from network_keys = self.ap.network_wrappers['main'].input_embedders_parameters.keys() # get the values for the current states result = self.networks['main'].online_network.predict(batch.states(network_keys)) current_state_values = result[0] self.state_values.add_sample(current_state_values) # the targets for the state value estimator num_transitions = batch.size state_value_head_targets = np.zeros((num_transitions, 1)) # estimate the advantage function action_advantages = np.zeros((num_transitions, 1)) if self.policy_gradient_rescaler == PolicyGradientRescaler.A_VALUE: if batch.game_overs()[-1]: R = 0 else: R = self.networks['main'].online_network.predict(last_sample(batch.next_states(network_keys)))[0] for i in reversed(range(num_transitions)): R = batch.rewards()[i] + self.ap.algorithm.discount * R state_value_head_targets[i] = R action_advantages[i] = R - current_state_values[i] elif self.policy_gradient_rescaler == PolicyGradientRescaler.GAE: # get bootstraps bootstrapped_value = self.networks['main'].online_network.predict(last_sample(batch.next_states(network_keys)))[0] values = np.append(current_state_values, bootstrapped_value) if batch.game_overs()[-1]: values[-1] = 0 # get general discounted returns table gae_values, state_value_head_targets = self.get_general_advantage_estimation_values(batch.rewards(), values) action_advantages = np.vstack(gae_values) else: screen.warning("WARNING: The requested policy gradient rescaler is not available") action_advantages = action_advantages.squeeze(axis=-1) actions = batch.actions() if not isinstance(self.spaces.action, DiscreteActionSpace) and len(actions.shape) < 2: actions = np.expand_dims(actions, -1) # train result = self.networks['main'].online_network.accumulate_gradients({**batch.states(network_keys), 'output_1_0': actions}, [state_value_head_targets, action_advantages]) # logging total_loss, losses, unclipped_grads = result[:3] self.action_advantages.add_sample(action_advantages) self.unclipped_grads.add_sample(unclipped_grads) self.value_loss.add_sample(losses[0]) self.policy_loss.add_sample(losses[1]) return total_loss, losses, unclipped_grads def get_prediction(self, states): tf_input_state = self.prepare_batch_for_inference(states, "main") return self.networks['main'].online_network.predict(tf_input_state)[1:] # index 0 is the state value
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