Saravanan666/pypi-org huggingface dataset:
Package: ccxt-download
CCXT Download UtilityA lightweight wrapper to conventiently and efficiently download
cryptocurrency data usingCCXT.DescriptionWhy is this necessary? Many times I have found myself needing some data,
only to spend some time writing a quick and dirty script to download said
data with no thought about storing it for later. Add multiple symbols across
different time periods to the mix, and things just get worse. Then when I
want to load that data later, its so badly organised (or not at all) that it
is easier to write another quick and dirty script and repeat the cycle. With
this package, the above issues are no longer issues. For me anyway.What makes this useful? The following features:asynchronous downloading (download data in parallel)intelligent file management (won't re-download data if it already exists)if data is downloaded for the current day, it will be marked asincomplete,
which will signal that it should be updated in future downloadsefficient data storage (usingApache Parquet)helpful utilities for loading and processing dataUsageBelow are some brief examples illustrating the basic functionality ofccxt-download.
For more, see theexamples.Downloading datafromccxt_downloadimportpublic,CANDLES# Download candlespublic.download(exchange="bybit",data_types=[CANDLES],symbols=["ETH/USDT:USDT","BTC/USDT:USDT",],start_date="2023-09-01",end_date="2023-09-05",)Data will be downloaded between the dates specified. If the
data already exists, it will not be re-downloaded. The exception to this
is when a dataset has been marked asincomplete, for example when you
download data for the current day (which has not ended yet). When this is
detected, that incomplete dataset will be updated. If it can be completed,
theincompletemarking will be removed.Reading downloaded datafromccxt_downloadimportCANDLESfromccxt_download.utilitiesimportload_datadf=load_data(exchange="bybit",data_type=CANDLES,data_type_id="1m",symbols=["ETH/USDT:USDT"],start_date="2023-09-01",end_date="2023-09-04",)Installationpip install ccxt-downloadNotes and future workSupport for private downloads to assist in accounting, account tracking
and analysis, etc.ContributingContributions toccxt-downloadare welcomed. However, please try follow the
guidelines below.Seek early feedbackPleaseopen an issuebefore apull requestto discuss any changes you wish to make.Code styleThe code in this project is formatted usingBlack.
The Black package is included in thedevdependencies ofccxt-download.
As mentioned below, please runblack .before opening a pull request.Setting up for DevelopmentFork this repository, then install from source using an editable installation.
Additionally, install with the optionaldevdependencies.pip install -e .[dev]If you want to make sure you have formatted the code before commiting, install
the pre-commit hook using the command below. This will check that the code
is formatted whenever you try to make a commit.pre-commit installIf you get a message saying the code isn't formatted correctly, simply run the
command below and try again.black .
Package: ccxt-market-ticker
ccxt-market-tickerThis library can be used to use the ccxt library to get the ticker of all markets of an exchange.
The library also provides a function to get the ticker of all markets of all exchanges
with MQListener and MQPublisher.MQListener Example:frommarketticker.MQListenerimportMQListenerfrommarketticker.SymbolimportSymbollistener=MQListener("localhost",5672,"test","test")listener.connect()classYourListener:defonMarketDataReceived(self,data):print("1: "+str(data))defonMarketTickerReceived(self,data):print("1: "+str(data))listener.followMarketTicker("binance",Symbol("BTC/USDT"),"1m",YourListener())
Package: ccxtools
ccxtoolsCryptoCurrency eXchange TOOLS암호화폐 자동매매 관련 라이브러리인 CCXT를 기반으로 만들어진 암호화폐 자동매매용 Python 3 라이브러리입니다.Installccxtools in PyPIpip install ccxtoolsFeaturesccxtools는 ccxt에서 함수로 구현되지 않은 API와 저 개인적으로 매매 프로그램을 개발할 때 필요한 함수들을 구현한 라이브러리이기 때문에 암호화폐 매매에 필요한 모든 API를 담고있지는 않습니다. 기본적인 API는ccxt를 참조하시기 바랍니다.거래소별로 다른 ticker 형식을 일일이 작성할 필요없이 코인 이름만으로 사용할 수 있습니다.{ticker}USDT,{ticker}-USDT,{ticker}/USDT=>{ticker}만입력하면됩니다.ccxt에서 함수로 구현해놓지 않은 API를 함수로 구현해 놓았습니다.Bybitmax_trading_qtyrisk_limit 관련pytest로 테스트를 구현해놓아 API나 CCXT 내용 변경에 신속히 대응할 수 있습니다.
Package: ccxt-unmerged
ccxt-unmergedExchanges whose open PRs haven't been merged into ccxt yet.import ccxt_unmerged
import ccxt

krakenfu = ccxt.krakenfu()List of exchanges_58coinbciobeaxybikibitcludebitforexfubitkubbitoprobitruebitzfubkexbtseceochangellyprocoinbenecoindcxcoinsupercossdexcryptocomdragonexduedexfelixofoblgategateiofukrakenfumultimxcnominexprimexbtremitanosilgonexslicextokenomytokensnettradeogretxbitvinexvitexwazirxyunex
Package: ccxw
CCXW - CryptoCurrency eXchange Websocket LibraryThis library is designed to fetch data from exchange WebSocket APIs and store or update data in a temporary SQLite database in the background, making it readily accessible for retrieval.Currently, it is available for several exchanges, including Binance, Bybit, and more. You can find a complete list of supported exchanges usingCcxw.get_supported_exchanges().Furthermore, the library supports a variety of endpoints, such as order_book, kline, and more. A comprehensive list of supported endpoints can be found viaCcxw.get_supported_endpoints().Example:###Installpipinstallccxw###UseimporttimeimportpprintfromccxwimportCcxwsymbol='BTC/USDT'streams=[\{\'endpoint':'order_book',\'symbol':symbol},\{\'endpoint':'kline',\'symbol':symbol,\'interval':interval\},\{\'endpoint':'trades',\'symbol':symbol},\{\'endpoint':'ticker',\'symbol':symbol}\]wsm=Ccxw('binance',\streams,\result_max_len=5,\data_max_len=10)wsm.start()# Start getting datatime.sleep(2)# Wait for available dataforiinrange(0,10):forstreaminstreams:interval='none'if'interval'instream:interval=stream['interval']data=wsm.get_current_data(stream['endpoint'],stream['symbol'],interval)pprint.pprint(data,sort_dicts=False)print('----------------------------------')time.sleep(1)print('============================================================')wsm.stop()# Stop getting dataImportant InformationPlease be aware that each instance opens a new connection to websockets. If you create multiple instances for the same exchange, you may exceed the websockets connection limits set by exchanges. Make sure to check the connection limits of exchanges before opening numerous instances.View License
Package: ccxxv
CCXXV====CCXXV is a crossword assistant, intended to help you find the right word to fill out your missing squares.In addition to the normal functionality to help fill out a single answer, it can also help in those tricky cornerswhere you have two clues that cross on an unknown letter.Installation------------ccxxv is available through pip::$ pip install ccxxvUsage-----To find a word with missing letters, use '.' to represent any missing letters::$ ccxxv ba..nabananaTo find a pair of words that cross on an unknown letter, use '+' to represent the crossing letter::$ ccxxv ba+.na u+clenbanana  uncleThese commands use the default wordlist, `UKACD <http://www.crosswordman.com/wordlist.html>`_.  To use a differentwordlist, pipe it to stdin::$ echo xxx | ccxxv ...xxxWhy the name?-------------CCXXV is 225 in Roman numerals.  Crosswords typically occupy a 15x15 grid, 15x15 is 225 and Roman numerals are a common device in crosswords(e.g. "Drink for about 50 notes (3)", ALE).Wordlist========The default word list is UKACD 2009, Copyright (c) 2009 J Ross Beresford, All rights reserved.This is a wordlist designed for crosswords, and contains commonly used phrases and Proper Nouns.
Package: ccy-dynamic-image
ccy_dynamic_imageAdd dynamic effect to imageccy_dynamic_image是一个给图片添加动态效果的库示例原图转换后的代码图片使用方式usage: ccy_dynamic_image [-h] [--image IMAGEFILE] [--out OUTIMAGE]

optional arguments:
  -h, --help         show this help message and exit
  --image IMAGEFILE  path of image to add effect
  --out OUTIMAGE     path of output image安装$ pip install ccy_dynamic_image
Package: cd4py
IntroCD4Pyis a code de-duplication tool for Python programming language.
It detectsnearandexactduplicate source code files. To train a machine learning model on source code files,
it is essential to identify and remove duplicate source code files from the dataset. Otherwise, code duplication
significantly affects the practicality of machine learning-based tools, especially on unseen data.Quick InstallationUsageExamplesApproachQuick Installation$ git clone https://github.com/saltudelft/CD4Py.git & cd CD4Py
$ pip install .Usage$ cd4py --help
usage: cd4py [-h] --p P --od OD --ot OT [--d D] [--th TH] [--k K] [--tr TR]

Code De-Duplication for Python

optional arguments:
  -h, --help  show this help message and exit
  --p P       Path to Python projects
  --od OD     Output folder to store detected duplicate files.
  --ot OT     Output folder to store tokenized files.
  --d D       Dimension of TF-IDF vectors [default: 2048].
  --th TH     Threshold to identify duplicate files [default: 0.95].
  --k K       Number of nearest neighbor [default: 10].
  --tr TR     Number trees to build the index. More trees gives higher
              precision but slower [default: 20].ExamplesRunCD4Pyto identify duplicate files for a Python dataset$ cd4py --p $PYHON_DATASET --ot $TOKENS --od py_dataset_duplicates.jsonl.gz --d 1024Replace$PYHON_DATASETwith the path to the Python project folders and$TOKENSwith the path to store
tokenized project files. Also, note that detected duplicate files will be stored in
the filepy_dataset_duplicates.jsonl.gz.The following code example shows the removal of duplicate files using the example filepy_dataset_duplicates.jsonl.gz:fromdpu_utils.utils.dataloadingimportload_jsonl_gzimportrandom# Selects randomly a file from each cluster of duplicate filesclusters_rand_files=[l.pop(random.randrange(len(l)))forlinload_jsonl_gz('py_dataset_duplicates.jsonl.gz')]duplicate_files=[fforlinload_jsonl_gz('py_dataset_duplicates.jsonl.gz')forfinl]duplicate_files=set(duplicate_files).difference(set(clusters_rand_files))ApproachTheCD4Pycode de-duplication tool uses the following procedure to identify duplicate files in a Python code corpus:Tokenize all the source code files in the code corpus usingtokenizemodule of Python standard library.Preprocess tokenized source files by only selecting identifier tokens and removing language keywords.Convert pre-processed tokenized files to a vector representation using the TF-IDF method.Performk-nearest neighbor search to findkcandidate duplicate files for each source code file.
Next, filter out candidate duplicate files by considering the thresholdt.Find clusters of duplicate source code files while assuming that similarity is transitive.
Package: cda-dl
cda-dlCLI downloader do filmów i folderów zcda.plInstalacja z PyPIpip install cda-dlInstalacja manualnaSklonuj repozytoriumgit clone https://github.com/H4wk507/cda-dl.gitWejdź do katalogu i zainstalujcd cda-dl && pip install .Opcje$ cda-dl --help
usage: cda-dl [OPCJE] URL [URL...]

Downloader do filmów i folderów z cda.pl

positional arguments:
  URL                   URL(y) do filmu(ów)/folder(ów) do pobrania

options:
  -h, --help            Wyświetl tę pomoc i wyjdź
  --version             Wyświetl wersję programu
  -q, --quiet           Wyświetlaj tylko błędy i ostrzeżenia
  -l, --login USER      Zaloguj się do konta
  -d, --directory PATH  Ustaw docelowy katalog (domyślnie '.')
  -R, --resolutions     Wyświetl dostępne rozdzielczości (dla filmu)
  -r, --resolution RES  Pobierz film w podanej rozdzielczości (domyślnie
                        'najlepsza')
  -o, --overwrite       Nadpisz pliki, jeśli istnieją
  -t, --threads N       Ustaw liczbę wątków (domyślnie 3)LicencjaLicencjonowany podMIT License.
Package: cda-downloader
CDA DownloaderGetting Startedpip install cda_downloaderBasic usageImport CDA class from the packagefrom cda_downloader import CDA:Create an instance. You can specify number of thread, api usage and progress bar:cda = CDA(multithreading=0, use_api=True, progress_bar=True)To download video usedownload_videomethod. You can provide string or Iterable of strings:cda.download_videos(path="/download", urls="https://www.cda.pl/video/13617843")
cda.download_videos(path="/download", urls=("https://www.cda.pl/video/13617843",))You can also useget_video_urlsmethod instead to get uls without a download:cda.get_video_urls(path="/download", urls="https://www.cda.pl/video/13617843")
cda.get_video_urls(path="/download", urls=("https://www.cda.pl/video/13617843",))
Package: cdapsutil
CDAPS Python UtilitiesLibrary that enables invocation ofCommunity Detection APplication and Servicealgorithms via PythonWarningcdapsutil is experimental and may contain errors and interfaces may changeDependenciesndex2requeststqdmCompatibilityPython 3.4+Installationpip install cdapsutilor directly via:git clone https://github.com/idekerlab/cdapsutil
cd cdapsutil
python setup.py installUsageRun Community Detectionimport json
import cdapsutil
import ndex2


# Download BioGRID: Protein-Protein Interactions (SARS-CoV) from NDEx
client = ndex2.client.Ndex2()
client_resp = client.get_network_as_cx_stream('669f30a3-cee6-11ea-aaef-0ac135e8bacf')
net_cx = ndex2.create_nice_cx_from_raw_cx(json.loads(client_resp.content))

# Create CommunityDetection object
cd = cdapsutil.CommunityDetection()

# Run HiDeF on CDAPS REST service
hier_net = cd.run_community_detection(net_cx, algorithm='hidef')Run Functional EnrichmentComing soon…Cite CDAPSIf you find this utility and service useful, please cite:Singhal A, Cao S, Churas C, Pratt D, Fortunato S, Zheng F, et al. (2020) Multiscale community detection in Cytoscape. PLoS Comput Biol 16(10): e1008239.https://doi.org/10.1371/journal.pcbi.1008239CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.2.2 (2024-02-09)Removed the “DISCLAIMER: cdapsutil is experimental…” warning level log message0.2.1 (2023-10-04)Removed scale, x, y, and z coordinates from visual properties aspect of default style
stored in this tool. Done so UI tools will just fit content0.2.0 (2022-10-04)Fixed bug where not setting a name on a network
would causeCommunityDetection.run_community_detection()to raise aTypeError. When encountered code now sets network
name tounknownIssue #10.2.0a1 (2021-03-30)First release on PyPI.
Package: cdaptools
CDAPTools : Climate data Downloading And Processing Tools)Tools for downloading and processing climatic data for analyzing multi-hazards risk and compound weather and climate extreme events.CDAPToolsis a collection of functions that allows you to download atmospheric data from different sources, extract data from a NetCDF file for a particular region, process the data for further analysis, visualizing the data and apply two different methodologies we developed for analyzing multi-hazard risks and estimating compound effects of different weather and climate extreme events.Free software: MIT licenseDocumentation:https://javedali99.github.io/CDAPTools/FeaturesTODOTO DOAdd following:Functions developed for data downloading and processingFunctions for estimating quantiles of climate driversFunctions for method-1 and method-2Functions for mapping and visualizing the dataCreditsThis package was created withCookiecutterand thegiswqs/pypackageproject template.
Package: cdasws
SynopsisThis library provides a simple python interface to the data and services of
NASA'sCoordinated Data Analysis System(CDAS).  This library implements the client side of theCDAS RESTful web servicesand can return data in theSpacePy data modelor anxarray.Datasetwith all the originalISTP/SPDF metadata.
Frequently asked questions concerning this library are atFAQ.
For more general details about the CDAS web services, seehttps://cdaweb.gsfc.nasa.gov/WebServices/REST/.Code ExampleThis package contains example code calling most of the available web services.
To run the included example, do the followingpython -m cdaswsAlso, the followingJupyter notebooksdemonstrate
different features of the library:Basic Example(ipynb file) demonstrating use of library with results returned inSpacePy data model.Basic Example(ipynb file) demonstrating use of library with results returned in anxarray.Dataset.Launch on Binder.Magnetic Field Line Conjunction Example(ipynb file) with related data retrieval/plotting usingcdasws.Launch on Binder.And at the bottom of eachCDAWeb dataset descriptionis a "Data Access Code Examples" link that contains dataset-specific code
utilizing this package to access the data.MotivationThis library hides the HTTP, JSON/XML, and CDF details of the CDAS web
services. A python developer only has to deal with python objects and
methods (primarily the SpacePy data model or xarray.Dataset object with
full ISTP/SPDF metadata).DependenciesThe only required dependencies are python-dateutil and requests.  If you
call the get_data method thenoneof the following two sets of additional
dependencies are required:To have get_data return the data in the SpacePy data model.SpacePy. Refer to the SpacePy
documentation for the details of SpacePy's dependencies.CDFwhich is not (at the time of this
writing) automatically installed with SpacePy.To have get_data return the data in an xarray dataset.cdflib.xarray.InstallationAs noted in the dependencies above, if you intend to call the get_data
method, you must install eitherSpacePyand theCDFlibrary (following the
procedures at the SpacePy and CDF web sites).cdflibandxarray.$ pip install -U cdflib
$ pip install -U xarrayThen, to install this package$ pip install -U cdaswsAPI ReferenceRefer tocdasws package API referenceor use the standard python help mechanism.from cdasws import CdasWs
help(CdasWs)TestsThe tests directory containsunittesttests.ContributorsBernie Harris.e-mailfor support.LicenseThis code is licensed under theNASA Open Source Agreement(NOSA).
Package: cdata
cdata-------------"see data", see data, handy snippets for conversion, cleaning and integration.install-------------pip install cdatajson data manipulation-------------* json (and json stream) file IO, e.g.  items2file(...)* json data access, e.g. json_get(...), any2utf8, json_dict_copy* json array statistics, e.g. stat(...).. code-block:: pythonfrom cdata.core import any2utf8the_input = {"hello": u"世界"}the_output = any2utf8(the_input)logging.info((the_input, the_output)).. code-block:: pythonproperty_list = [{ "name":"name", "alternateName": ["name","title"]},{ "name":"birthDate", "alternateName": ["dob","dateOfBirth"] },{ "name":"description" }]json_object = {"dob":"2010-01-01","title":"John","interests":"data","description":"a person"}ret = json_dict_copy(json_object, property_list)table data manipulation-------------* json array to/from excel.. code-block:: pythonimport jsonfrom cdata.table import excel2json,json2excelfilename = "test.xls"items = [{"first":"hello", "last":"world" }]json2excel(items, ["first","last"], filename)ret = excel2json(filename)print json.dumps(ret)JSON data from reading a single sheet excel file.. code-block:: json{"fields": {"00": ["name","年龄","notes"]},"data": {"00": [{"notes": "","年龄": 18.0,"name": "张三"},{"notes": "this is li si","年龄": 18.0,"name": "李四"}]}}web stuff-------------* url domain extractionentity manipulation-------------* entity.SimpleEntity.ner().. code-block:: pythonfrom cdata.entity import SimpleEntityentity_list = [{"@id":"1","name":u"张三"},{"@id":"2","name":u"李四"}]ner = SimpleEntity(entity_list)sentence = "张三给了李四一个苹果"ret = ner.ner(sentence)logging.info(json.dumps(ret, ensure_ascii=False, indent=4))"""[{"text": "张三","entities": [{"@id": "1","name": "张三"}],"index": 0},{"text": "李四","entities": [{"@id": "2","name": "李四"}],"index": 4}]"""* region.RegionEntity.guess_all().. code-block:: pythonfrom cdata.region import RegionEntityaddresses = ["北京海淀区阜成路52号（定慧寺）", "北京大学肿瘤医院"]city_data = RegionEntity()result = city_data.guess_all(addresses)logging.info(json.dumps(result, ensure_ascii=False))"""{"province": "北京市","city": "市辖区","name": "海淀区","district": "海淀区","cityid": "110108","type": "district"}"""wikification-------------* 通过wikidata搜索，定位对应实体，查找实体中文名，别名等属性。wikidata_search (item/property) and wikidata_get.. code-block:: pythonquery = u"居里夫人"ret = wikidata_search(query, lang="zh")logging.info(ret)nodeid = ret["itemList"][0]["identifier"]ret = wikidata_get(nodeid)lable_zh = ret["entities"][nodeid]["labels"]["zh"]["value"]logging.info(lable_zh)misc-------------* support simple cli function using argparsenotes-------------release package using https://github.com/pypa/twine
Package: cdatastructs
Simple data structures accessible from both Python and C. Data in structures
are stored as a primitive C types, so in C you can compute data without Python
overhead.Python code:>>> import array
>>> import itertools
>>> import math
>>> import random

>>> from cdatastructs.hashmap import Int2Int

>>> from my_c_extension import calculate_data

    # Create instance of the Int2Int, it will be mapping from ID
    # to position in array
>>> id2index = Int2Int()

# Instance of the id2index is mapping, so you can use it same as dict
>>> id2index[72351277] = 0
>>> id2index[98092127498] = 1
>>> id2index[126987499] = 2
>>> id2index[36] = 3
>>> id2index[980980] = 4
>>> len(id2index)
5
>>> id2index[980980]
4
>>> id2index.buffer_ptr
94691713534960

# Prepare two arrays with numbers for calculate and one array for results
>>> a = array.array('d', (random.random() for _ in id2index))
>>> b = array.array('d', (random.random() for _ in id2index))
>>> results = array.array('d', (math.nan for _ in id2index))

# Calculate data for IDs 98092127498, 126987499 and 36
>>> ids = array.array('Q', [98092127498, 126987499, 36])
>>> calculate_data(id2index, ids, a, b, results)

    # Obtaint results
>>> results[id2index[72351277]]
nan
>>> results[id2index[98092127498]]
0.8163673050897404C code:#include <hashmap.h>

static PyObject * my_c_extension_compute_data(
        PyObject *id2index, PyObject *args) {

    Int2IntHashTable_t *id2position;
    unsigned long long *ids;
    size_t *ids_count;
    double *a;
    double *b;
    double *res;

    // Parse args, obtain pointers to buffers and cast them to C types
    ...

    // Calculate data, there are only pure C types, no Python overhead
    for (size_t i=0; i<ids_count; ++i) {
        unsigned long long id = ids[i];
        size_t *position;
        if (int2int_get(id2position, id, position) != 0) {
            goto error;
        }
        res[*position] = a[*position] + b[*position];
    }

    ...
    Py_RETURN_NONE;
error:
    ...
    return NULL;
}Seedemos/for more examples and details.License3-clause BSD