Saravanan666/pypi-org huggingface dataset:
Package: toppred
toppredExtension tosklearn.metricsto allow metrics for classifiers that output a topnprediction.
Some classifiers output confidence levels for each class.
Oftentimes, you want to evaluate the performance of such classifiers assuming the correct prediction is the topnpredictions with the highest confidence level.
This library serves as an extension to the functions provided bysklearn.metricsto allow for evaluating classifiers that do not output a single prediction per sample, but rather a range of top predictions per sample.InstallationThe most straightforward way of installingtoppredis via pip:pip3installtoppredDocumentationWe provide an extensive documentation including installation instructions and reference attoppred.readthedocs.io.
Package: topp.utils
A library of generally useful pieces of python for working with zope,
wsgi, pylons, setuptools, dates and the open planning project’s
software offerings.Pu Pu Platter of Python delights‘topp.utils.config.ConfigMap’ – generates a mapping object from an ini file‘topp.utils.detag.detag’ – removes all HTML/XML from a string‘topp.utils.filesystem’ – abspath, makedir, get_args, which‘topp.utils.introspection.dumb_method’ – auto apply staticmethodand classmethod descriptors‘topp.utils.memorycache.Cache’ – simple in memory cache‘topp.utils.modules.uninstall_package’ – remove a python package
from the current environment‘topp.utils.persistence’ – some extensions of ZODB persistence classes‘topp.utils.pretty_date.prettyDate’ – data beautifier‘topp.utils.pretty_text.truncate’ – string truncater‘topp.utils.testing.layer_factory’ – create layers on the fly touse with zope.testing‘topp.utils.uri’ – functions for working with urls‘topp.utils.wenvutils’ –deprecatedfunctions for working with workingenvs‘topp.utils.zutils.aq_iface’ – find objects up the acquisitionchain in Zope2 by interface implemented
Package: top.py
This project is now retiredI do not work on discord bots anymore, and consequently do not use top.gg anymore.This package should continue to work with v0 of the top.gg API, however will not work with v1 or any newer versions,
assuming they are breaking changes to the API.You are welcome to fork and continue developing this code should you wish, however, for a project that is guaranteed
to continue being developed well into the future, I recommend you use theofficial python SDK..I am, however, now creating bots onmatrix, and even have my ownbot library!This repository is indefinitely archived.Top.pyAn alternative wrapper for thetop.gg APIPlease note, this isnot an official package from top.gg. We are not
affiliated with top.gg in any way. If you want to install their official
package, please seetheir repo.IntroductionWarning! top.py is not tested to be compatible with discord.py forks, or any other library than the official
discord.py library. If you encounter issues when using another library, please open an issue with as much detail
and support will be added.top.py is a python wrapper for the top.gg discord bot list API. top.py aims to
be object-oriented, whereas the official top.gg python SDK is more low-level raw
data.InstallationYou can install the latest stable release here:pipinstalltop.pyBut, if you're reading this, you're most likely a developer - you should know
how to install packages by now.ExamplesYou can see examples in theexamples.mdfile.Supported FeaturesFeature NameSupported?Automatic posting of server count✅Searching/Bulk Querying Bots✅Fetching a bot✅Fetching a user✅Fetching last 1000 upvotes✅Fetching a bot's stats✅Checking individual user vote✅Manual posting server count✅Models for all individual endpoints✅In-house ratelimiting✅Vote Webhooks✅Making you a nice slice of toast❌NOTE:We doNOTcurrently provide official support for discord server
list. That's coming soon.top.py featuresObject-Oriented (No-more shall you faff about with dictionaries)Sensible function names & argumentsUseful linkssupport(or mention @eek#7574 in top.gg) |docs|PyPi|examples|(META) Code Of Conduct|(META) Contributing GuidelinesExperiencing an issue?
Package: toppy-python
An API wrapper made for discord.py or any forks for Discord Bot List, DiscordBotsGG, and Top.gg.Documentationhttps://toppy-python.readthedocs.io/en/latest/InstallationPython 3.8 or higher is needed$pipinstall-Utoppy-pythonExampleimporttoppyfromdiscord.extimportcommandsdbl_token='Your Discord Bot List token here'dbgg_token='Your DiscordBotsGG API token here'topgg_token='your Top.gg token here'bot=commands.Bot('!')# or discord.Client()toppy_client=toppy.Client(bot,dbl_token=dbl_token,dbgg_token=dbgg_token,topgg_token=topgg_token)@bot.eventasyncdefon_dbl_autopost_success():# dbl/dbgg/topggprint('Server count posted')print(f'Server count:{len(bot.guilds)}')@bot.eventasyncdefon_dbl_autopost_error(error:toppy.HTTPException):# dbl/dbgg/topggprint(f'Uh oh. An error occurred. Status:{error.resp.status}')bot.run(...)
Package: toproxy
### 介绍用tornado实现的高性能代理服务器，涵盖了基本的method , 性能方面经过我的测试，他每秒平均在300个访问,如果在tornado加入threadpool逻辑，并发估计会破1k 。对于https的支持会有些问题，我后期会增强tornado httpclient对于ssl的支持，另外对于高性能方面会加入gevent。[toproxy 更多介绍](http://xiaorui.cc  "xiaorui.cc")### 原理你通过http client附加proxy地址访问页面，我通常会解析你的访问，然后我自己再去访问你刚才提交的页面，然后返回你结果。当然在协议上来说，这虽然不是最高性能的方法，但是最简单有效的方法....  如果是底层的socket来写，我首先需要解析你的各种各样的header请求，然后还要考虑多任务的模块，或 prefork 或 异步模式， 这都是开发的成本。    我这里是用tornado这异步框架，本身解决了各个流程的堵塞问题，然又用异步的 httpclient,避免了我请求url时的堵塞。New Future1. 加入了白名单功能2. 当访问的地址连接失败的时候，会做重试机制3. support 301 redirect4. 加入了基本认证5. 简单防御AB压测更多的httpclient文档，[httpclient 更多文档](http://tornado.readthedocs.org/en/latest/httpclient.html  "tornado httpclient")### 安装方法1:pip install toproxy方法2:依赖tornadopython setup.py install### 直接使用```python toproxy/proxy.py -husage: proxy.py [-h] [-p PORT] [-w WHITE] [-u USER]python -m toproxy/proxy -p 8888 -w 127.0.0.1,8.8.8.8 -u xiaorui:fengyunoptional arguments:-h, --help            show this help message and exit-p PORT, --port PORT  tonado proxy listen port-w WHITE, --white WHITEwhite ip list ---> 127.0.0.1,215.8.1.3-u USER, --user USER  Base Auth , xiaoming:123123```第一个参数是端口，第二个参数是白名单ip地址。方法1:python  -m toproxy/proxy -p 8888 -w 127.0.0.1 -u xiaorui:123python  -m toproxy/proxy::::Starting HTTP proxy on port 8888方法2:python toproxy### 模块的调用from toproxy import run_proxyrun_proxy(port, start_ioloop=False)...tornado.ioloop.IOLoop.instance().start()### testcurl -vvv -x xiaorui.cc:8888 http://www.google.comab -X xiaorui.cc:8888 -c 200 -n 1000 http://www.hao123.com/```his is ApacheBench, Version 2.3 <$Revision: 655654 $>Copyright 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/Licensed to The Apache Software Foundation, http://www.apache.org/Benchmarking www.hao123.com (be patient)Completed 100 requestsCompleted 200 requestsCompleted 300 requestsCompleted 400 requestsCompleted 500 requestsCompleted 600 requestsCompleted 700 requestsCompleted 800 requestsCompleted 900 requestsCompleted 1000 requestsFinished 1000 requestsServer Software:        BWS/1.0Server Hostname:        www.hao123.comServer Port:            80Document Path:          /Document Length:        750380 bytesConcurrency Level:      200Time taken for tests:   7.967 secondsComplete requests:      1000Failed requests:        10(Connect: 0, Receive: 0, Length: 10, Exceptions: 0)Write errors:           0Total transferred:      752184936 bytesHTML transferred:       751671400 bytesRequests per second:    125.52 [#/sec] (mean)Time per request:       1593.406 [ms] (mean)Time per request:       7.967 [ms] (mean, across all concurrent requests)Transfer rate:          92199.44 [Kbytes/sec] receivedConnection Times (ms)min  mean[+/-sd] median   maxConnect:       24   40  94.6     31    1034Processing:   289 1371 786.8   1223    4028Waiting:       46   57  27.8     55     663Total:        317 1411 791.2   1276    4059Percentage of the requests served within a certain time (ms)50%   127666%   175175%   203080%   220890%   251095%   276898%   318799%   3389100%   4059 (longest request)```### todo1.  提高toproxy的性能2.  加入异步回调通知模式3.  批量传送4.  作为代理安全的基本认证
Package: toproxypdf
toproxypdftoproxypdf creates a printable pdf of Magic the Gathering proxies from a folder of imagesThe user needs to provie a folder including images and a pdf that while printed on US printer paper(8.5"x 11") can be covered over a 2R MTG card(2.5" * 3.5 ") as a proxyMore detailed explanations can be seen inexamplesInstallationWithpipmodule you can download toproxypdf with platform-varied versions ofpip install toproxypdfand an executable will be added to your $PATHUsageusage: toproxypdf [-h] [-o OUTPUT] [-e EXCLUDED [EXCLUDED ...]] [-d DPI] [-c--corner] [-r REPEAT] [--overwrite] [-v | -q] folderBug TrackingPlease open an issue overhereContributionsPull requests are welcome : )Additional Notestoproxypdf works extremely well withmpcfillDownloading a deck of photos into a folder can then be easily converted into a pdf for you to print at home.LicenseMIT
Package: tops
TOPS (Tiny open power system simulator)This is a package for performing dynamic power system simulations in Python. The aim is to provide a simple and lightweight tool which is easy to install, run and modify, to be used by researchers and in education. Performance is not the main priority. The only dependencies are numpy, scipy, pandas and matplotlib (the core functionality only uses numpy and scipy).The package is being developed as part of ongoing research, and thus contains experimental features. Use at your own risk!Some features:Newton-Rhapson power flowDynamic time domain simulation (RMS/phasor approximation)Linearization, eigenvalue analysis/modal analysisInstallationThe package can be installed using pip, as follows:pip install git+https://github.com/hallvar-h/topsCitingIf you use this code for your research, please citethis paper.Example notebooksContactHallvar Haugdal
Package: topshape
Library for easily creating text interfaces that look like Linux’s top program.It is built on top ofurwidbut requires no knowledge of urwid itself.Free software: MIT licenseDocumentation:https://topshape.readthedocs.io.Python versions supported: 2.7, 3.3, 3.4, 3.5, 3.6QuickstartHere’s an example of how to use TopShape:fromtopshapeimportTopShape# The columns are a list (or tuple) of dictionaries. Each# dictionary defines a column in the bodycolumns=({'label':'header1'},{'label':'header2'},{'label':'header3'})# The body function will be passed as a callback that must# return a 2-dimensional array everytime it's called.defbody():return[[str(i*j)foriinrange(3)]forjinrange(10)]# The header function will be passed as a callback that must# return a string everytime it's called.defheader():return'This is the header!'# The footer function will be passed as a callback that must# return a string everytime it's called.deffooter():return'This is the footer!'defhandle_q(app):app.exit()defhandle_f(app,answer):# do something with the answer# ...# key_map maps keys pressed to callbackskey_map={'q':handle_q,'f':(handle_f,'Enter some text here:'}app=TopShape.create_app(columns,body,header,footer,key_mapping=key_map)app.run()Output:Output (waiting for input from user):There is also a more complete exampleherewhich is a clone of the linux top program.Screenshot:CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.
Package: topside
Topside: Technical Operations Procedures Simulator & Integrated Development EnvironmentWaterloo Rocketry's operations simulator is a tool for modelling and simulating rocket launch systems and procedures.RequirementsPython 3.7 or newer is required.Required Python packages can be installed usingpip install -r requirements.txt.Building a standalone applicationThetools/directory contains two scripts for building a standalone application:build_cxfreeze.shandbuild_pyinstaller.sh. However, currently only the PyInstaller build is functional due to upstream bugs in the interaction between SciPy, cx_Freeze, and Cython.Building a standalone application should be as simple as runningbuild_pyinstaller.sh. The resulting application can be found atdist/Topside/Topside.exe.
Package: topsis-101703100-101703100
-- coding: utf-8 --"""
Created on Sun Jan 19 17:22:38 2020@author: arnav
"""Example PackageTOPSIS
The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, which was originally developed by Ching-Lai Hwang and Yoon in 1981 with further developments by Yoon in 1987
Package: topsis-101703161-A-deven
TOPSIS-PythonProject 1 : UCS633Submitted By:topsis-101703161-devenpypi:https://pypi.org/project/topsis-101703161-devenWhat is TOPSISTechnique forOrderPreference bySimilarity toIdealSolution (TOPSIS) originated in the 1980s as a multi-criteria decision
making method. TOPSIS chooses the alternative of shortest Euclidean distance
from the ideal solution, and greatest distance from the negative-ideal
solution. More details atwikipedia.How to use this package:TOPSIS-topsis-101703161-deven  can be run as in the following example:In Command Prompt>> topsis data.csv "1,1,1,1" "+,+,-,+"
Package: topsis-101703166-COE8
topsis-pythonTopsis analysis of a csv file""UCS633 Project Submission""Name - Dhriti JindalRoll no. - 101703166About TopsisThe Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, which was originally developed by Ching-Lai Hwang and Yoon in 1981 with further developments by Yoon in 1987, and Hwang, Lai and Liu in 1993. TOPSIS is based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution (PIS) and the longest geometric distance from the negative ideal solution (NIS).Installationpipinstalltopsis-101703166_COE8UsageFollowing query on terminal will provide you the topsis analysis for input csv file.topsis-101703166_COE8 -n "dataset-name.csv" -w "w1,w2,w3,w4,..." -i "i1,i2,i3,i4,..."w1,w2,w3,w4 represent weights, and i1,i2,i3,i4 represent impacts where 1 is used for maximize and 0 for minimize.
Size of w and i is equal to number of features.Note that the first row and first column of dataset is droppedRank 1 signifies best decisionContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.LicenseMIT
Package: topsis-101703189-garvita-chhabra
TOPSIS-PythonProject 1 : UCS633Submitted By:topsis-101703189-garvita-chhabrapypi:https://pypi.org/project/topsis-101703189-garvitaWhat is TOPSISTechnique forOrderPreference bySimilarity toIdealSolution (TOPSIS) originated in the 1980s as a multi-criteria decision
making method. TOPSIS chooses the alternative of shortest Euclidean distance
from the ideal solution, and greatest distance from the negative-ideal
solution. More details atwikipedia.How to use this package:topsis-101703189-garvita-chhabra  can be run as in the following example:In Command Prompt>> topsis data.csv "1,1,1,1" "+,+,-,+"
Package: topsis-101703191
#TOPSIS-PythonProject 1 : UCS633Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, numerical data, interval data, positive ideal solution, negative ideal solution. Introduction. Multi-criteria decision making (MCDM) refers to making choice of the best alternative from among a finite set of decision alternatives in terms of multiple, usually conflicting criteria.Run from Command linepython  <your-dataset-name.csv>  ("w1,w2,w3,w4,...") ("i1,i2,i3,i4,...")
Package: topsis-101703192-girish-1.0.0
TOPSIS-PythonProject 1 : UCS633Submitted By:Girish Julka 101703192What is TOPSISTechnique forOrderPreference bySimilarity toIdealSolution (TOPSIS) originated in the 1980s as a multi-criteria decision
making method. TOPSIS chooses the alternative of shortest Euclidean distance
from the ideal solution, and greatest distance from the negative-ideal
solution. More details atwikipedia.How to use this package:TOPSIS-Girish Julka 101703192  can be run as in the following example:In Command Prompt>> topsis data.csv "1,1,1,1" "+,+,-,+"In Python IDLE:>>> import pandas as pd
>>> from topsis_python.topsis import topsis
>>> dataset = pd.read_csv('data.csv').values
>>> d = dataset[:,1:]
>>> w = [1,1,1,1]
>>> im = ["+" , "+" , "-" , "+" ]
>>> topsis(d,w,im)Sample datasetThe decision matrix (a) should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R2, Root Mean Squared Error, Correlation, and many more.ModelCorrelationR2RMSEAccuracyM10.790.621.2560.89M20.660.442.8963.07M30.560.311.5762.87M40.820.672.6870.19M50.750.561.380.39Weights (w) is not already normalised will be normalised later in the code.Information of benefit positive(+) or negative(-) impact criteria should be provided inI.OutputModel   Score    Rank
-----  --------  ----
  1    0.77221     2
  2    0.225599    5
  3    0.438897    4
  4    0.523878    3
  5    0.811389    1The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.
Package: topsis-101703250-COE12
topsis-pythonTopsis analysis of a csv file""UCS633 Project Submission""Name -Jahnavi MarjaraRoll no. - 101703250About TopsisThe Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, which was originally developed by Ching-Lai Hwang and Yoon in 1981 with further developments by Yoon in 1987, and Hwang, Lai and Liu in 1993. TOPSIS is based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution (PIS) and the longest geometric distance from the negative ideal solution (NIS).Installationpipinstalltopsis-101703250_COE12UsageFollowing query on terminal will provide you the topsis analysis for input csv file.topsis-101703250_COE12 -n "dataset-name.csv" -w "w1,w2,w3,w4,..." -i "i1,i2,i3,i4,..."w1,w2,w3,w4 represent weights, and i1,i2,i3,i4 represent impacts where 1 is used for maximize and 0 for minimize.
Size of w and i is equal to number of features.Note that the first row and first column of dataset is droppedRank 1 signifies best decisionContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.LicenseMIT
Package: topsis-101703289-khushnuma
TOPSIS-PythonProject 1 : UCS633Submitted By:Khushnuma Grover 101703289pypi:https://pypi.org/project/topsis-khushnuma-101703289git:https://github.com/khushgrover/topsis-python.gitWhat is TOPSISTechnique forOrderPreference bySimilarity toIdealSolution (TOPSIS) originated in the 1980s as a multi-criteria decision
making method. TOPSIS chooses the alternative of shortest Euclidean distance
from the ideal solution, and greatest distance from the negative-ideal
solution. More details atwikipedia.How to use this package:TOPSIS-KHUSHNUMA-101703289  can be run as in the following example:In Command Prompt>> topsis data.csv "1,1,1,1" "+,+,-,+"In Python IDLE:>>> import pandas as pd
>>> from topsis_python.topsis import topsis
>>> dataset = pd.read_csv('data.csv').values
>>> d = dataset[:,1:]
>>> w = [1,1,1,1]
>>> im = ["+" , "+" , "-" , "+" ]
>>> topsis(d,w,im)Sample datasetThe decision matrix (a) should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R2, Root Mean Squared Error, Correlation, and many more.ModelCorrelationR2RMSEAccuracyM10.790.621.2560.89M20.660.442.8963.07M30.560.311.5762.87M40.820.672.6870.19M50.750.561.380.39Weights (w) is not already normalised will be normalised later in the code.Information of benefit positive(+) or negative(-) impact criteria should be provided inI.OutputModel   Score    Rank
-----  --------  ----
  1    0.77221     2
  2    0.225599    5
  3    0.438897    4
  4    0.523878    3
  5    0.811389    1The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.
Package: topsis-101703295
Topsis_101703295 PackageYou can use this topsis package to rank diiferent machine learning models according to accuracy,RMS error etc,which will help you to find best fit model for your dataset.Run from Command linepython  <your-dataset-name.csv>  ("w1,w2,w3,w4,...") ("i1,i2,i3,i4,...")
Package: topsis-101703325
TOPSIS-PythonProject 1 : UCS633Submitted By:Maninder 101703325What is TOPSISTechnique forOrderPreference bySimilarity toIdealSolution (TOPSIS) originated in the 1980s as a multi-criteria decision
making method. TOPSIS chooses the alternative of shortest Euclidean distance
from the ideal solution, and greatest distance from the negative-ideal
solution. More details atwikipedia.How to use this package:TOPSIS-Maninder 101703325  can be run as in the following example:In Command Prompt>> topsis data.csv "1,1,1,1" "+,+,-,+"In Python IDLE:>>> import pandas as pd
>>> from topsis_python.topsis import topsis
>>> dataset = pd.read_csv('data.csv').values
>>> d = dataset[:,1:]
>>> w = [1,1,1,1]
>>> im = ["+" , "+" , "-" , "+" ]
>>> topsis(d,w,im)Sample datasetThe decision matrix (a) should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R2, Root Mean Squared Error, Correlation, and many more.ModelCorrelationR2RMSEAccuracyM10.790.621.2560.89M20.660.442.8963.07M30.560.311.5762.87M40.820.672.6870.19M50.750.561.380.39Weights (w) is not already normalised will be normalised later in the code.Information of benefit positive(+) or negative(-) impact criteria should be provided inI.OutputModel   Score    Rank
-----  --------  ----
  1    0.77221     2
  2    0.225599    5
  3    0.438897    4
  4    0.523878    3
  5    0.811389    1The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.
Package: topsis-101703382
TOPSIS implementationClass project for DATA ANALYSIS AND VISUALISATION 2020 - UCS633 Thapar University, Patiala
Submitted by: Paras Arora
101703382 (COE 18)Output is a dataframe with 3 columnsAlternativesScoreRankInstallationpip install topsis-101703382To use via command linetopsis-101703382-cli data.csv 25,25,25,25 -+++First argument after run.py is filename with .csv extension. The .csv file is assumed to have a structure similar to one provided in topsis-101703382/data.csvThat is, the .csv file should have a header with column names and first column should only list alternatives and not attribute values.To use in .py scriptfrom topsis-101703382 import topsis
"""
decision_matrix is 2D numpy array, weights is a 1D array and impacts is a string of the form +-+-- 
where + implies benefit and - implies cost
"""
output_dataframe = topsis(decision_matrix,weights,impacts)
Package: topsis-101703550
This package is implementation of topsis technique of multi-criteria decision analysis.
This package will accept three parameters:data.csv //file which contains the models and parametersstring of weights separated by commas(,)string of requirements (+/-) separated by commas(,)
// important
install pandas,sys and math libraries before installing this
//
You can install this package using following command
pip install topsis-101703550
Package: topsis-101703551
This package is implementation of topsis technique of multi-criteria decision analysis.
This package will accept three parameters:data.csv //file which contains the models and parametersstring of weights separated by commas(,)string of requirements (+/-) separated by commas(,)
// important
install pandas,sys and math libraries before installing this
//
You can install this package using following command
pip install topsis-101703550