Saravanan666/pypi-org huggingface dataset:
Package: py-algorand-sdk
py-algorand-sdkA python library for interacting with the Algorand network.InstallationRun$ pip3 install py-algorand-sdkto install the package.Alternatively, choose adistribution file, and run$ pip3 install [file name].Supported Python versionspy-algorand-sdk's minimum Python version policy attempts to balance several constraints.Make it easy for the community to use py-algorand-sdk by minimizing or excluding the need to customize Python installations.Provide maintainers with access to newer language features that produce more robust software.Given these constraints, the minimum Python version policy is:
Target Python version on newestUbuntu LTSreleased >= 6 months ago.The rationale is:If a major Linux OS distribution bumps a Python version, then it's sufficiently available to the community for us to upgrade.The 6 month time buffer ensures we delay upgrades until the community starts using a recently released LTS version.SDK DevelopmentInstall dependenciespip3 install -r requirements.txtRun testsmake docker-testSet up the Algorand Sandbox based test-harness without running the testsmake harnessFormat codeblack .Updatealgosdk/__init__.pyiwhich allows downstream developers importingalgosdkand using VSCode's PyLance to have improved type analysismake generate-initLint typesmake mypy(ormypy algosdk)Check all lints required by the C.I. processmake lintRun non-test-harness related unit testsmake pytest-unitWe use cucumber testing for all of our SDKs, including this one. Please refer toalgorand-sdk-testingfor guidance and existing tests that you may need to update. Depending on the type of update you wish to contribute, you may also need to have corresponding updates in the other SDKs (Go, JS, and Java). Feel welcome to ask for collaboration on that front.Quick startHere's a simple example you can run without a node.fromalgosdkimportaccount,encoding# generate an accountprivate_key,address=account.generate_account()print("Private key:",private_key)print("Address:",address)# check if the address is validifencoding.is_valid_address(address):print("The address is valid!")else:print("The address is invalid.")Node setupFollow the instructions in Algorand'sdeveloper resourcesto install a node on your computer.
You can also set up a localAlgorand Sandboxwithmake harness.Running examples/example.pyBefore runningexample.py, start kmd on a private network or testnet node:./goalkmdstart-d[datadirectory]Next, create a wallet and an account:./goalwalletnew[walletname]-d[datadirectory]./goalaccountnew-d[datadirectory]-w[walletname]Visit theAlgorand dispenserand enter the account address to fund your account.Next, intokens.py, either update the tokens and addresses, or provide a path to the data directory. Alternatively,tokens.pyalso defaults to the sandbox harness configurations for algod and kmd, which can be brought up by runningmake harness.You're now ready to run example.py!DocumentationDocumentation for the Python SDK is available atpy-algorand-sdk.readthedocs.io.Licensepy-algorand-sdk is licensed under an MIT license. See theLICENSEfile for details.
Package: pyalgos
pyalgos is a package for implementing various algorithms:SortingInsertion SortSelection SortLinksProject:https://github.com/bharadwajyarlagadda/pyalgosDocumentation:http://pyalgos.readthedocs.ioPypi:https://pypi.python.org/pypi/pyalgosTravisCI:https://travis-ci.org/bharadwajyarlagadda/pyalgosFeaturesSupported on Python 2.7 and Python 3.3+.Changelogv0.1.2Added support fortupleof values in bothinsertion()andselection()sorting methods.v0.1.1Added validation for checking whether all the elements in a given list are strings or not in bothinsertion()andselection()sorting methods.v0.1.0First release.Addedinsertion()method for implementing insertion sort algorithm.Addedselection()method for implementing selection sort algorithm.
Package: pyalgostrategypool
pyalgostrategypoolOfficial pool of Algorithmic Trading Strategies powered by the AlgoBulls PlatformFeaturesPowered by theAlgoBulls PlatformCheck complete features onpyalgotrading!Backtesting, Paper Trading and Real Trading (across multiple brokers) can be performed on the same strategy code base!DocumentationYou can find the docshere.PythonPython Support:Python 3.6+.Python Requirements: Seerequirements.txt.We recommend you to use the latest version of Python (v3.8+) to enjoy better performance benefits, especially for pandas. (For Python 3.6, the latest supported Pandas version is v0.25.3. For Python 3.8, the latest supported version is v1.0.x)InstallationPackage can be easily installed usingpip-pip install pyalgostrategypoolSupport / Getting HelpBug Reporting / New Feature Request: Pleasecreate a new issuehere on GitHub.Discussions:AlgoBulls Community ForumWant to learn faster and easier?Purchase our book - Python Algorithmic Trading Cookbook, Published by Packt.Additional Support: If none of the above help, please contactdevelopers@algobulls.com.Contribution GuidelinesHere’s how we suggest you go about adding an algo strategy to this project:Checkout the list of strategies waiting to be developed on this Google Sheet:https://bit.ly/2H9JaOlAsk for ownership for a strategy development by sending a mail todevelopers@algobulls.com.You may also ask for an explanation of the strategy specifications over a phone call/whatsapp/screen share from Team AlgoBulls based on the strategy complexity.Once you get the ownership, your name will be updated on the excel sheet and you would be given comment access to the Google Sheet.Fork this projectto your account.Create a branchfor the change you intend to make.Make your changes to your fork.Verify that your strategy performs as per the given specifications. You can do this by comparing the P&L Table against the specifications, optionally by using technical charts. A P&L is generated onsubmitting Backtesting jobs.For technical issues, refer to theGetting Helpsection. You can also search for your queries on theAlgoBulls Community Forum. Additionally, you can also post questions on theAlgoBulls Community Forumto get technical help.If you still queries or need additional help, please contact us over anemail/phone call/whatsapp/screen share.Ensure you have followed these coding guidelines:Your code should bePEP-8compliant. You can use tools likePyCharmto help you quickly comply with PEP-8.Send a pull requestfrom your fork’s branch to ourmasterbranch.If your strategy is accepted, your strategy code would be merged with themasterbranch.RewardsThis is our official pool of FREE algorithmic trading strategies. If you are interested in contributing to this repo, please reach out todevelopers@algobulls.com. You can get credits for unlimited trading access on the AlgoBulls platform by contributing to this repo and more benefits!ChangelogSeeCHANGELOG.md.LicenseSeeLICENSE.
Package: pyalgotrade_mootdx
PyAlgoTrade mootdx module=========================此项目是 PyAlgoTrade [mootdx](https://github.com/bopo/mootdx) (基于 pytdx 的二次封装版本) 的一个数据源一个简单的用法:```from pyalgotrade import plotter, strategyfrom pyalgotrade.bar import Frequencyfrom pyalgotrade.barfeed.csvfeed import GenericBarFeedfrom pyalgotrade.stratanalyzer import sharpefrom pyalgotrade.technical import mafrom pyalgotrade_mootdx import toolsclass Strategy(strategy.BacktestingStrategy):def __init__(self, feed, instrument):super(Strategy, self).__init__(feed)self.__position = Noneself.__sma = ma.SMA(feed[instrument].getCloseDataSeries(), 150)self.__instrument = instrumentself.getBroker()def onEnterOk(self, position):execInfo = position.getEntryOrder().getExecutionInfo()self.info("买入 %.2f" % (execInfo.getPrice()))def onEnterCanceled(self, position):self.__position = Nonedef onExitOk(self, position):execInfo = position.getExitOrder().getExecutionInfo()self.info("卖出 %.2f" % (execInfo.getPrice()))self.__position = Nonedef onExitCanceled(self, position):# If the exit was canceled, re-submit it.self.__position.exitMarket()def getSMA(self):return self.__smadef onBars(self, bars):# 每一个数据都会抵达这里，就像becktest中的next# Wait for enough bars to be available to calculate a SMA.if self.__sma[-1] is None:return# bar.getTyoicalPrice = (bar.getHigh() + bar.getLow() + bar.getClose())/ 3.0bar = bars[self.__instrument]# If a position was not opened, check if we should enter a long position.if self.__position is None:if bar.getPrice() > self.__sma[-1]:# 开多头.self.__position = self.enterLong(self.__instrument, 100, True)# 平掉多头头寸.elif bar.getPrice() < self.__sma[-1] and not self.__position.exitActive():self.__position.exitMarket()def main():instruments = ["600036"]feeds = tools.build_feed(instruments, 2017, 2018, "histdata")# 3.实例化策略strat = Strategy(feeds, instruments[0])# 4.设置指标和绘图ratio = sharpe.SharpeRatio()strat.attachAnalyzer(ratio)plter = plotter.StrategyPlotter(strat)# 5.运行策略strat.run()strat.info("最终收益: %.2f" % strat.getResult())# 6.输出夏普率、绘图strat.info("夏普比率: " + str(ratio.getSharpeRatio(0)))# plter.plot()if __name__ == '__main__':main()``````2018-04-03 00:00:00 strategy [INFO] 卖出 28.862018-04-11 00:00:00 strategy [INFO] 买入 30.342018-04-17 00:00:00 strategy [INFO] 卖出 28.252018-05-02 00:00:00 strategy [INFO] 买入 29.982018-05-04 00:00:00 strategy [INFO] 卖出 29.282018-05-09 00:00:00 strategy [INFO] 买入 29.702018-05-24 00:00:00 strategy [INFO] 卖出 29.602018-09-25 00:00:00 strategy [INFO] 买入 29.832018-10-12 00:00:00 strategy [INFO] 卖出 28.702018-10-15 00:00:00 strategy [INFO] 买入 29.162018-10-19 00:00:00 strategy [INFO] 卖出 27.752018-10-22 00:00:00 strategy [INFO] 买入 29.532018-10-30 00:00:00 strategy [INFO] 卖出 28.122018-11-01 00:00:00 strategy [INFO] 买入 29.452018-11-15 00:00:00 strategy [INFO] 卖出 28.242018-11-19 00:00:00 strategy [INFO] 买入 28.702018-11-23 00:00:00 strategy [INFO] 卖出 28.292018-12-03 00:00:00 strategy [INFO] 买入 29.492018-12-11 00:00:00 strategy [INFO] 卖出 28.352018-12-12 00:00:00 strategy [INFO] 买入 29.002018-12-18 00:00:00 strategy [INFO] 卖出 28.052018-12-21 13:48:01,740 strategy [INFO] 最终收益: 999254.002018-12-21 13:48:01,740 strategy [INFO] 夏普比率: -0.6957113853538597```
Package: pyalgotrade_tushare
开源协议: MIT license在线文档:https://pyalgotrade_tushare.readthedocs.io.安装方法# PIP 自动安装方法
pip install pyalgotrade_tushare

# 手动下载源码安装
git clone https://github.com/bopo/pyalgotrade_tushare.git
cd pyalgotrade_tushare
python setup.py install使用说明不多话，简单一个例子from pyalgotrade import plotter, strategy
from pyalgotrade.stratanalyzer import sharpe
from pyalgotrade.technical import ma

from pyalgotrade_tushare import tools


class MyStrategy(strategy.BacktestingStrategy):
    def __init__(self, feed, instrument):
        super().__init__(feed)

        self.__position = None
        self.__sma = ma.SMA(feed[instrument].getCloseDataSeries(), 150)
        self.__instrument = instrument
        self.getBroker()

    def onEnterOk(self, position):
        execInfo = position.getEntryOrder().getExecutionInfo()
        self.info("买入 %.2f" % (execInfo.getPrice()))

    def onEnterCanceled(self, position):
        self.__position = None

    def onExitOk(self, position):
        execInfo = position.getExitOrder().getExecutionInfo()
        self.info("卖出 %.2f" % (execInfo.getPrice()))
        self.__position = None

    def onExitCanceled(self, position):
        # If the exit was canceled, re-submit it.
        self.__position.exitMarket()

    def getSMA(self):
        return self.__sma

    def onBars(self, bars):
        # 每一个数据都会抵达这里，就像becktest中的next
        # Wait for enough bars to be available to calculate a SMA.
        if self.__sma[-1] is None:
            return

        # bar.getTyoicalPrice = (bar.getHigh() + bar.getLow() + bar.getClose())/ 3.0
        bar = bars[self.__instrument]

        # If a position was not opened, check if we should enter a long position.
        if self.__position is None:
            if bar.getPrice() > self.__sma[-1]:
                # 开多头.
                self.__position = self.enterLong(self.__instrument, 100, True)

        # 平掉多头头寸.
        elif bar.getPrice() < self.__sma[-1] and not self.__position.exitActive():
            self.__position.exitMarket()


if __name__ == '__main__':
    instruments = ["600036"]

    feeds = tools.build_feed(instruments, 2013, 2018, "histdata")

    # 3.实例化策略
    strat = MyStrategy(feeds, instruments[0])

    # 4.设置指标和绘图
    ratio = sharpe.SharpeRatio()
    strat.attachAnalyzer(ratio)
    plter = plotter.StrategyPlotter(strat)

    # 5.运行策略
    strat.run()
    strat.info("最终收益: %.2f" % strat.getResult())

    # 6.输出夏普率、绘图
    strat.info("夏普比率: " + str(ratio.getSharpeRatio(0)))
    plter.plot()版本更新修改了 PIP 安装程序问题本程序只支持 python3.贡献名单bopo.wang
Package: pyalgotrading
pyalgotradingOfficial Python Package for Algorithmic Trading APIs powered by AlgoBulls!FeaturesPowered by theAlgoBulls PlatformEverything related to Algorithmic Trading Strategies!Free pool of Strategies are available atpyalgostrategypool!Create & upload strategies easily on the cloudSupport for all 150+ Technical Indicators provided byTA-LibSupport for multiple candlesticks patterns - Japanese OHLC, Renko, Heikin-Ashi, LinebreakSupport for multiple candle intervals - 1 minute, 3 minutes, 5 minutes, 10 minutes, 15 minutes, 30 minutes, 1 hour, 1 day.Support forRegular Orders,Bracket OrdersandCover OrdersSupport forMARKET,LIMIT,STOPLOSS-LIMIT,STOPLOSS-MARKETordersSupport forINTRADAYandDELIVERYordersSupport forBacktestingSupport forPaper TradingSupport forLive Trading/Real TradingSupport for multiple brokers for Live Trading. Check list of supported brokershere.Real-time Logs for Backtesting, Paper Trading, Live TradingMultiple real-time Reports available for Backtesting, Paper Trading and Live Trading:Profit-&-Loss report (P&L report)Statistics ReportOrder History Log for each order with state transitions & timestampsDetailed analytics with chartsSupport for calculating SlippageSupport for calculating BrokerageSupport for importing external P&L table and generating analytics on the samePlot Candlestick charts usingplotly.pyBacktesting, Paper Trading and Real Trading can be performed on the same strategy code base!DocumentationYou can find the docshere.Jupyter NotebooksEasily access and use complete Jupyter Notebook for NASDSAQ and NSE marketshere.
You can:Easily view them on the web usingnbviewer, without installing Python or Jupyter Notebooks.Easily execute them on the web usingBinder, without installing Python or Jupyter Notebooks.Download and use them on your local machine, and installing Python & Jupyter NotebooksPythonPython Support:Python 3.8+.Python Requirements: Seerequirements.txt.We recommend you to use the latest version of Python (v3.8+) to enjoy better performance benefits, especially for pandas.InstallationPackage can be easily installed usingpip-pip install pyalgotradingSupport / Getting HelpBug Reporting / New Feature Request: Pleasecreate a new issuehere on GitHub.Discussion Community:SlackAdditional Support: If none of the above help, please contactpushpak@algobulls.com.Contribution GuidelinesHere’s how we suggest you go about proposing a change to this project:Fork this projectto your account.Create a branchfor the change you intend to make.Make your changes to your fork.Send a pull requestfrom your fork’s branch to ourmasterbranch.RewardsIf you are interested in contributing to this repo,pyalgotradingorpyalgostrategypool, our official pool of FREE algorithmic trading strategies, please join our officialSlackcommunity.
You would be provided with credits for unlimited trading access on the AlgoBulls platform.ChangelogSeeCHANGELOG.md.LicenseSeeLICENSE.
Package: pyalias
Define shell shortcut and execute it.How to useInstall pyalias$: pip install pyaliasAdd a configure file at~/.config/pyalias.yaml.. code:- name: test
  description: functional test
  command: echo 'test'
- name: ssh
  description: test ssh
  command: sshpass -p "password" ssh user@host4List shortcut$ pyalias list
* [test] functional test
* [ssh] test sshExecute shortcut$ pyalias ssh
Welcome to Ubuntu 20.04.1 LTS (GNU/Linux x86_64)

 * Documentation:  https://help.ubuntu.com
 * Management:     https://landscape.canonical.com
 * Support:        https://ubuntu.com/advantage

Welcome to Alibaba Cloud Elastic Compute Service !
Package: pyalic
Pyalic: Advanced Licensing python moduleInstall package usingpipfrom this GitHub repositorypipinstallpyalicPython examplefrompyalicimportLicenseManagerimporttimelm=LicenseManager("https://LICENSE_SERVER_URL.ORG",ssl_public_key='./trusted_cert.pem')defmy_program():print("Access granted!")time.sleep(30)key=input("Enter your license key: ")check_response=lm.check_key(key)ifcheck_response.success:my_program()lm.end_session()else:print("Access denied:",check_response.error)
Package: pyaliceya
pyAlicepyAlice - framework for simplifying work with Yandex AliceGetting startedpip install pyaliceyaexample of an empty dialogdetailed documentationHandlerexample of the "handler" functionfrom pyAlice.py_alice import PyAlice
import settings

def handler(event, context):
  return PyAlice(params_alice=event, settings=settings).get_params_for_alice()
Package: pyaliner
PyalinerLibrary for aligning and visually comparing sequential data in the terminal.paired ground-truth vs predicted comparisoncompactclassicinlined ground-truth vs predicted comparisoncompactclassicpaired input vs ground-truth vs predicted comparisoncompactclassicpaired ground-truth vs 1st predicted vs 2nd predicted comparisonalignment>>>frompyalinerimportalign,COMPACT>>>align('Example invalid invalid sentence'.split(),'Example sentence'.split())(('Example','invalid','invalid','sentence'),('Example','⎵','⎵','sentence'))>>>align('Example invalid invalid sentence'.split(),'Example sentence'.split(),kind=COMPACT)(('Example','invalid∙invalid','sentence'),('Example','⎵','sentence'))LimitationsThree-way alignment uses a slow heuristic.Wide characters, e.g., East Asian scripts,  are not properly aligned with narrow onesInstallingInstall with pip:pipinstallpyalinerTestingUnit tests are written withpytestandhypothesis.
Run with:pipinstallpytesthypothesis

pytestChangelogCheck theChangelogfor fixes and enhancements of each version.LicenseCopyright Jose Llarena 2022Distributed under the terms of theMITlicense, Pyaliner is free
and open source software.
Package: pyalink
AlinkAlink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.More information about Alink and PyAlink tutorials can be found athttps://github.com/alibaba/Alink.This packagepyalinkalways maintains Alink Python API against the latest Flink version that Alink supports, which is Flink-1.13 now.
To use PyAlink with older-version Flink, please check package pyalink-flink-[version].
Right now,pyalink-flink-1.9,pyalink-flink-1.10,pyalink-flink-1.11andpyalink-flink-1.12are provided.
Package: pyalink-flink-1.10
AlinkAlink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.More information about Alink and PyAlink tutorials can be found athttps://github.com/alibaba/Alink.This package maintains Alink Python API against Flink 1.10.
To use PyAlink with latest Flink version, please check packagepyalink.
Package: pyalink-flink-1.11
AlinkAlink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.More information about Alink and PyAlink tutorials can be found athttps://github.com/alibaba/Alink.This package maintains Alink Python API against Flink 1.11.
To use PyAlink with latest Flink version, please check packagepyalink.
Package: pyalink-flink-1.12
AlinkAlink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.More information about Alink and PyAlink tutorials can be found athttps://github.com/alibaba/Alink.This package maintains Alink Python API against Flink 1.12.
To use PyAlink with latest Flink version, please check packagepyalink.
Package: pyalink-flink-1.9
AlinkAlink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.More information about Alink and PyAlink tutorials can be found athttps://github.com/alibaba/Alink.This package maintains Alink Python API against Flink 1.9.
To use PyAlink with latest Flink version, please check packagepyalink.
Package: pyalko
PyAlkoAsynchronous python client for AL-KO Robolinho Mowers.
This package allows you to interact with AL-KO API to control your robolinho mower.Tested with:AL-KO Robolinho 800WInstallationpipinstallpyalkoAttributions@timmo001for source of inspiration with hisaiolyric package.@ludeeusfor his generator class.⭐️ this repository if you found it useful ❤️
Package: pyAllegro
allegro-apipyAllegro is a framework, that provides a simple way to use AllegroWeb APIandRest AP. You don't need to know how RESTful, SOAP or oauth 2.0 works.As for now it's prepared for getting data from allegro - not for managing your account or bidding.Get started:Go tohttps://apps.developer.allegro.pl/and register your app.You need to setup redirecion url tohttp://localhost:8000- it will be your local server that recive your autorization data (oauth 2.0),Generate your app passwordhere,Install pyAllegro withpip install pyAllegroImportfrom pyAllegro.api import AllegroRestApi, AllegroWebApiSetup credentials that you recived from allegro (by default it's saved here: '/Users/{user}/.allegroApiConfig'):WebApi = AllegroWebApi()

WebApi.credentials_set(
        appName='<credentials from allegro>',
        clientId='<credentials from allegro>',
        clientSecred='<credentials from allegro>',
        userLogin='<allegro login>',
        redirectUrl='<redirect uri - the same you provided during app registration on allegro >',
        appPassword='<app password>'
        )

RestApi = AllegroRestApi()

RestApi.credentials_set(
        appName='<credentials from allegro>',
        clientId='<credentials from allegro>',
        clientSecred='<credentials from allegro>',
        redirectUrl='http://localhost:8000'
        )How to use pyAllegro:WebApiRestApiAllegro api documentation:Rest ApiWeb ApiReferencesThanks to:https://cwsi.pl/ecommerce/allegro/podstawy-obslugi-web-api-allegro-pl-web-services-i-modul-suds-jurko-w-pythoniehttps://cwsi.pl/ecommerce/allegro/allegro-pl-rest-api-w-pythonie-wprowadzenie/To dopublish package on pypiRestApi putRestApi deleterestApi postChangelogver. 0.1.0:automatic token refreshingver. 0.1.1, 0.2.0:load token automatically inRestApi.resource_get()methodver. 0.3.0:addedresponse2JSON()function in WebApi - convert suds response to JSON.
Package: pyallel
PyallelRun and handle the output of multiple executables inpyallel(as in parallel)https://github.com/Danthewaann/pyallel/assets/22531177/8685eb92-aac5-440a-9170-30fd1460c53fRequires Python >=3.8Tested on Linux and MacOS onlyQuick startpyallelcan be installed using pip:pipinstallpyallelOnce installed, you can runpyallelto see usage information, like so:usage: pyallel [-h] [-t] [-n] [-V] [-v] [--colour {yes,no,auto}] [commands ...]

Run and handle the output of multiple executables in pyallel (as in parallel)

positional arguments:
  commands              list of quoted commands to run e.g "mypy ." "black ."

                        can provide environment variables to each command like so:

                             "MYPY_FORCE_COLOR=1 mypy ."

options:
  -h, --help            show this help message and exit
  -t, --no-timer        don't time how long each command is taking
  -n, --non-interactive
                        run in non-interactive mode
  -V, --verbose         run in verbose mode
  -v, --version         print version and exit
  --colour {yes,no,auto}
                        colour terminal output, defaults to "auto"Currently you can provide a variable number ofcommandsto run topyallel, like so:[!IMPORTANT]
If you need to provide arguments to a command, you must surround the command and it's arguments in quotes!pyallel"MYPY_FORCE_COLOR=1 mypy ."\"black --check --diff ."\"pytest ."TODOsAdd custom parsing of command output to support filtering for errors (like vim'serrorformat)Allow list of files to be provided to supply as input arguments to each commandAllow input to be piped intopyallelvia stdin to supply as standard input to each
command