Saravanan666/pypi-org huggingface dataset:
Package: trademark-marker
Class for use https://markerapi.com/=======Install=======.. code-block:: bashpip install trademark-marker=======Example=======.. code-block:: pythonfrom trademark import markerparams = {'username': 'TRADEMARK_USERNAME','password': 'TRADEMARK_PASSWORD','search': 'word'}trademark = marker.API(params)print trademark.result()=======Donation=======.. image:: https://img.shields.io/badge/Donate-PayPal-green.svg:target: https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=YYZQ6ZRZ3EW5C
Package: trademasterntu
TradeMaster: An RL Platform for TradingTradeMaster is a first-of-its kind, best-in-classopen-source platformforquantitative trading (QT)empowered byreinforcement learning (RL), which covers thefull pipelinefor the design, implementation, evaluation and deployment of RL-based algorithms.Contact UsIf you have any further questions of this project, please contactTradeMaster.NTU@gmail.com
Package: tradenity
Python SDK for the Tradenity ecommerce REST APIFree software: Apache licenseDocumentation: (COMING SOON!)https://tradenity.readthedocs.org.FeaturesTODOHistoryVersion 1.0.0Improvement: Completely new SDK for the final v1 Tradenity REST API protocolFeature: Various new classes for new Tradenity resources.Version 0.1.2Workaround: move overridden __getitem__ from Base entity to Identifiable to work with django.Bug fix: fix Order#refund operationVersion 0.1.1Feature: New Exception: SessionExpiredExceptionFeature: Add Tradenity.reset_current_session()Improvement: Add entity base class IdentifiableBug fix: LineItem.id always return NoneVersion 0.1.0Initial release
Package: tradenity-django-ext
==========This extension library facilitates integration between Django applications and [Python SDK](https://github.com/tradenity/python-sdk) for [Tradenity ecommerce API](https://www.tradenity.com).## InstallationThis package is available through PyPI (Python Package Index), to install it type the following on the command line:$ pip install tradenity-django-extOr, add this line to your application's requirements.txt:```pythontradenity-django-ext==0.7.0```And then execute:$ pip install -r requirements.txt## DocumentationDetailed documentation can be found on our [knowledge base site:](http://docs.tradenity.com/kb/sdk/python/)## Contributing1. Fork it ( https://github.com/tradenity/python-sdk-django-ext/fork )2. Create your feature branch (`git checkout -b my-new-feature`)3. Commit your changes (`git commit -am 'Add some feature'`)4. Push to the branch (`git push origin my-new-feature`)5. Create a new Pull RequestHistory-------version 0.7.0-------------Update the library to be compatible with Tradenity python sdk v1.0.xVersion 0.1.0-------------Initial releasePlatform: UNKNOWNClassifier: Development Status :: 5 - Production/StableClassifier: Intended Audience :: DevelopersClassifier: License :: OSI Approved :: Apache Software LicenseClassifier: Natural Language :: EnglishClassifier: Programming Language :: Python :: 2Classifier: Programming Language :: Python :: 2.7
Package: tradenity-flask-ext
History-------version 0.7.0-------------Update the library to be compatible with Tradenity python sdk v1.0.xversion 0.1.0-------------Initial releasePlatform: UNKNOWNClassifier: Development Status :: 5 - Production/StableClassifier: Intended Audience :: DevelopersClassifier: License :: OSI Approved :: Apache Software LicenseClassifier: Natural Language :: EnglishClassifier: Programming Language :: Python :: 2Classifier: Programming Language :: Python :: 2.7
Package: traderep
TradeRepublic-OverviewWhy was this made ?Currently there is no web/desktop app for Trade Republic, meaning it's pretty hard to follow your depot without your phone. With this application
it's really convenient to watch your depot grow while working on your computer.What does it do ?There are two options to read in your depot, one is to specify a folder with all your pdf you exported out of Trade Republic. It then automatically
parses them for their ISINs and quantity. Other option is to specify a .csv file where you can explicitly state your positions. After the positions are read
it periodically displays your positions with their current price and total worth.This is what the output will look like:How do I use it ?Install viapip install traderepRun the script with-hor--helpto get following message:usage: traderep [-h] [--folder FOLDER] [--csv CSV]

optional arguments:
-h, --help       show this help message and exit
--folder FOLDER  Specify folder you want to parse the pdfs in
--csv CSV        Specify the .csv file you want to useWhat does the .csv file have to look like?Example:ISIN;QUANTITY;PRICE;
IE00B4L5Y983;50.0;62.28
...
Package: trade-republic-api
Trade Republic API (Unofficial)Free software: BSD 2-Clause LicenseInstallationpip install trade-republic-apiYou can also install the in-development version with:pip install https://github.com/unimun/trade-republic-api/archive/main.zipDocumentationhttps://trade-republic-api.readthedocs.io/DevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.0 (2023-05-01)First release on PyPI.
Package: traderhelper
证券交易助手 Stock Trader Helper本仓库目前处于开发内测阶段, 敬请期待TODOLIST免责条款合作协议交易接口UI库可行性开发指南安装软件pip install traderhelperhelloworld#!/usr/bin/env python
# -*- coding: utf-8 -*-
__time__ = '2020/10/26 0:45'

from stocktrader import StockTrader

if __name__ == '__main__':
   trader = StockTrader()

   '''
   trader.login()
   trader.insert_order()
   trader...
   '''运行以上程序,python helloworld.py
Package: tradermade
tradermade is Python SDK for getting forex data via REST API or
Websocket.InstallationUse the package managerpipto install foobar.pipinstalltradermadeGet API key by signing up forfreeUsageREST APIimporttradermadeastm# set api keytm.set_rest_api_key(api_key)tm.live(currency='EURUSD,GBPUSD',fields=["bid","mid","ask"])# returns live data - fields is optionaltm.historical(currency='EURUSD,GBPUSD',date="2021-04-22",interval="daily",fields=["open","high","low","close"])# returns historical data for the currency requested interval is daily, hourly, minute - fields is optionaltm.timeseries(currency='EURUSD',start="2021-04-20",end="2021-04-22",interval="hourly",fields=["open","high","low","close"])# returns timeseries data for the currency requested interval is daily, hourly, minute - fields is optionaltm.cfd_list()# gets list of all cfds availabletm.currency_list()# gets list of all currency codes available add two codes to get code for currencypair ex EUR + USD gets EURUSDStreaming Datafromtradermadeimportstreamdefprint_message(data):print(f"Received:{data}")api_key="api_key"# set streaming key - not the same as rest API keystream.set_ws_key(api_key)stream.set_symbols("USDJPY,EURGBP")# Set the callback for receiving messagesstream.stream_data(print_message)stream.connect()ContributingFor changes, please open an issue to discuss what you would like to
change.LicenseMIT
Package: tradernet-api
Tradernet APIPublic API client for working with the Tradernet platform.Official API documentationInstallationInstall packagepipinstall-Utradernet-apiorpoetryaddtradernet-api@latestGetting Startedfromtradernet_api.apiimportAPI# Setup clientapi_client=API(api_key="YOUR API KEY",secret_key="YOUR SECRET KEY")# Get only active orders by defaultapi_client.get_orders()# Get all ordersapi_client.get_orders(active_only=False)# Get ticker infoapi_client.get_ticker_info(ticker="AAPL")# Send order to the platformapi_client.send_order(ticker="AAPL",side="buy",margin=True,count=1,order_exp="day",market_order=True)api_client.send_order(ticker="MSFT",side="sell",margin=False,count=2,order_exp="ext",limit_price=200)api_client.send_order(ticker="TSLA",side="sell",margin=True,count=3,order_exp="gtc",stop_price=1000)# Delete/cancel active orderapi_client.delete_order(order_id=123456789)# Set stop loss and/or take profitapi_client.set_stop_order(ticker="AAPL",stop_loss=1,take_profit=2)🛡 LicenseThis project is licensed under the terms of theMITlicense. SeeLICENSEfor more details.
Package: tradernet-cli
tradernet_cliThis is a simple python client for theTraderNetAPI.
Mainly this package is purposed to ease the automation of common tasks in TraderNet.Installationpip install tradernet_cliUsagepython3 -m tradernet_cli [command] [flags]Usepython3 -m tradernet_cli --helpto get information about all available commands and flags.
Currently, the descriptions are only present inUkrainianas the package was built for personal use.
Package: traderpy
Trader-CoreTrader-Core is a Python library focused on conducting fundamental analysis of stock market data. It offers a range of functionalities and tools to perform in-depth analysis, extract insights, and aid decision-making in trading and investment strategies.FeaturesFundamental Analysis:Perform comprehensive fundamental analysis on stock market data.Data Processing:Efficiently process and clean financial data for analysis purposes.Key Metrics Calculation:Calculate essential financial metrics.Valuation Models:Implement various valuation models for stock evaluation.Financial Ratios:Compute and interpret crucial financial ratios to facilitate investment analysis.Data Visualization:Visualize data and analysis results using graphical representations.InstallationInstall Trader-Core via pip:pipinstalltrader-core
Package: tradetestlib
tradetestlib: A MetaTrader5 backtesting tooltradetestlibis a backtesting library built to integrate with MetaTrader5, with the purpose being able to provide a broad overview of a trading strategy/idea, more specifically, an evaluation of a strategy. Some of the main evaluation metrics used in this project are the sharpe ratio, and profit factor.tradetestlibalso provides the option to optimize a strategy by using a Grid Search algorithm for hyperparameter tuning.Currently, hyperparameters are limited to position sizing, and exposure.A demonstration can be foundhereInstallationtradetestlibcan be installed withpippipinstalltradetestlibUsageA simulation instances can be created by calling the Simulation class.symbolandtimeframeare only used for naming conventions, for comparing a basket of assets.train_rawandtest_raware dataframes that containOpen, High, Low, Close, signal, and true_signalcolumns.lotis the lot size used to tradestarting_balanceis the initial deposit of the simulation in USD.fromtradetestlibimportSimulationsim=Simulation(symbol=symbol,timeframe=tf,train_raw=train,test_raw=test,lot=1,starting_balance=100000)Optimization can be used by creating aparamsdictionary with the required hyperparameters.run_grid_searchreturns the optimal configuration, and overall testing set.Optimized hyperparameters may also be accessed as attributes, which can then be used to create a final simulation instance, to verify result with the test set.fromtradetestlibimportOptimizeparams={'lot':[1,2],'hold_time':[5,10],'max_loss':[0.005,0.01]}o=Optimize(symbol=symbol,timeframe=tf,train=train,test=test,metric='sharpe_ratio',how='maximize')best,df=o.run_grid_search(params)o.optimized_lot# best loto.optimized_holdtime# best holdtimeo.optimized_max_loss# best exposure
Package: tradetuya
TuyaRewritten tuya client based on pytuya. Used byhttps://github.com/TradeFace/tuyamqttTodoadd support for older devices back inwe'll seeChangelogsolved recursion problem in send_requestmoved functions back to initremoved TuyaConnection class, use send_request in try/exceptdeclassified aesciphermoved to a more functional programming styleyield and list comprehensionssetup.pyremoved code for older devices < 3.3AcknowledgementsThis module is a rewrite ofhttps://github.com/clach04/python-tuyahttps://github.com/codetheweb/tuyapias reference on commands
Package: trade-utils
algoSet of tools for algorithmic tradingContributingTo get startedinstall pipenvInstall dependenciespipenv install --devActive environmentpipenv shellTo use VSCodePyhton: Select Interpreterand choose suggested PipEnv environment.At this point version update is manual.Building And uploadingpython-mbuild
twineupload./dist/*--verboseLocal run for devdockercomposeup
pipenvshellexportCONFIG_FILE=~/config-container/config.yml
python-malgoTODO:add tests [important] way to many things are dangling on theexpectationsof valid functioning ie: caching and valid rehidrationmake config retry loading config file ie do not assign empty config on fail
Now it raises error only once on the first attempt to access config. Then it returns empty/default valuesDONE:11/07/22: makeinstall_requiresdynamic based onPipfile10/07/22: implement multiprocess caches see :synccache: mark. In order to make only one process to call the data retrieval function. to do so: donekeep the temporary cache value as a global lock aka '{cache_key}-loading' its presense mean that one process is loading the data and cache will be available soonmain: loading process should create this special value and start loading dataothers: on this cache availability should sleep before the data will become availablemain: after data is loaded set cache value and remove the locking entryothers: should poll until there is no such value in the table then read the cached data or take the role of main processto run test:python-munittestdiscover-p"*_test*"-v
Package: tradeX
TradeXThis project provides tool to download Binance trading data in the past. Use the data to develop a mini AI model for coin prediction.
Follow below step to reproduce:Install Python and required packagespipinstall-rrequirements.txtOther lacking library can be installed manually bypip install <lib_name>command.Download Binance Kline-Candlestick DatacdtradeX# ex1: install BTC data from Sep 08 2019 to now, interval is one hourPYTHONPATH=.pythonscripts/get_all_time_data.py--symbolBTCUSDT--interval1h# ex2: install other coin pairs data, .e.g SolonaPYTHONPATH=.pythonscripts/get_all_time_data.py--symbolSOLUSDT--interval3m# ex3: install data from a specified time to now, if not passed, default value is 1567962000000PYTHONPATH=.pythonscripts/get_all_time_data.py--symbolBTCUSDT--dfrom<time_in_milliseconds>--interval1hDownloaded data is saved indatadirectory as default.
Try to play with other interval values (1m 3m 5m 15m 30m 1h 2h 4h 6h 8h 12h 1d 3d 1w 1M).Split train-val datacdtradeX# replace the data path below with the newly downloaded data file.PYTHONPATH=.pythonscripts/split_train_val.py--datadata/BTCUSDT_3m_2022.10.23_14.24.54.jsonAfter running above script, there will be 2 files ending with*_train.jsonand*_val.jsongenerated.Train a simple modelcdtradeX# Without GPUpythonscripts/train.py--train_data<data/*_train.jsonfilepath>--val_data<data/*_val.jsonfilepath>
--window_size<50or100oranypositivenumber,default50>
--epochs30--bsize8# With GPUCUDA_VISIBLE_DEVICES=0,1,2,3PYTHONPATH=.pythonscripts/train.py--train_data<data/*_train.jsonfilepath>--val_data<data/*_val.jsonfilepath>
--window_size<50or100oranypositivenumber,default50>
--epochs30--bsize8--num_gpus3Trained models is saved inweightsdirectory with latest timestamp.Eval model on validation setcdtradeX

pythonscripts/eval.py--val_datadata/BTCUSDT_3m_2022.10.23_14.24.54_val.json
--window_size<50oranypositivenumber,shouldbesamewithtrainedwindow_size>
--weightweights/2022.10.23_15.50.09/epoch=19-val_loss=3.94.pth.ckptAuto futures-trading on Binance with your own strategypythonrun_testnet.py--interval3m--symbolbtcusdt
Package: tradfricoap
tradfricoapA module and command line utility for working with the Ikea Tradfri Gateway.InstallationRequirementstradfricoap uses py3coap for communicating with the gateway. Py3coap is available on PyPi and should be installed automaticly when installing tradfricoap. If no prebuild wheel of py3coap is available on PyPy, py3coap can be installed fromsource.From PyPi$ pip3 install tradfricoapFrom source$ git clone https://github.com/moroen/tradfricoap.git
$ cd tradfricoap
$ python3 setup.py installConfiguration$ tradfri config gw IP KEYBasic usage./tradfri.py--helpList all devices./tradfrilistControll a light./tradfrion<ID>
./tradfrioff<ID>
./tradfrilevel<ID><LEVEL>(Level:0-254)
Package: tradier-python
Tradier-PythonTradier-python is a python client for interacting with the Tradier API.Getting StartedYou will need a Tradier account token which you can download from your account after logging in.The client also takes an optional default_account_id which can make it easier to get information if you only have one account.The default endpoint points to the sandbox. You will need to set the endpoint to the brokerage endpoint for live use.Reference documentation for the API can be found here:https://documentation.tradier.com/brokerage-api/overview/market-dataInstallingpip install tradier-pythonExmpleimport os

from tradier_python import TradierAPI

token = os.environ["TRADIER_TOKEN"]
account_id = os.environ["TRADIER_ACCOUNT_ID"]
t = TradierAPI(token=token, default_account_id=account_id)

profile = t.get_profile()
print(profile)Version History0.1.3Include tags by default when getting orders0.1.2Export models from the package0.1.1Bug fixes0.1.0Initial releaseLicenseThis project is licensed under the MIT License - see the LICENSE.md file for details
Package: trading212api
trading212apiAn unofficial API library for Trading212 based on SeleniumDescriptionThis library allows you to interface withTrading212throughSelenium.
Once you log in, the only operation requiring a human interation, you can buy and sell stocks, in both real and practice modes.Installationpip install trading212apiInstall aSeleniumweb driver, e.g., theChrome WebDriverAvailable methodsenable_real_mode(): this method is used to enable real/live modeenable_practice_mode(): this method is used to enable practice/demo modeinitiate_connection(webdriverfile, loginusername=None, loginpassword=None, headless=False): initializes the connection toTrading212throughSelenium, optionally asking for username and password to login; in such case, an automatic login will be performed; otherwise, user interaction will be required, for a manual login to occur; ifheadlessisTrue, the browser will be executed in headless modeget_stocks_list(brw, navigationpath=None): returns all the list of stocks available, optionally selecting a specific>separated list identifying the navigation path, in terms of content, to followget_stock_info(brw, ticker, backtohome_begin=True, backtohome_end=True): starting from aselenium.webdriver.chrome.webdriver.WebDriverobjectbrw, this method retrieves information from a stock identified by a giventicker, optionally, returning home at the begin/end of the methodget_portfolio(brw): starting from aselenium.webdriver.chrome.webdriver.WebDriverobjectbrw, this method returns information on the current portfoliobuy(brw, ticker, amount, max_price=None): starting from aselenium.webdriver.chrome.webdriver.WebDriverobjectbrw, this method buys a stock identified by its ownticket, specifying theamountin terms of money to invest in the current valuta, plus an optional maximum pricemax_price; returns a boolean value indicating the success of the operationsell(brw, ticker, amount=None, min_price=None): starting from aselenium.webdriver.chrome.webdriver.WebDriverobjectbrw, this method sells a stock identified by its ownticket, specifying theamountin terms of number of stocks to sell and an optional minimum pricemin_price; returns a boolean value indicating the success of the operationSample usage# import the library
import trading212api

# enable practice mode
trading212api.enable_practice_mode()

# initiate the connection
brw = trading212api.initiate_connection('./chromedriver')

# get and print portfolio information
portfolio = trading212api.get_portfolio(brw)
print(portfolio)

# get and print information on a given stock
stock_info = trading212api.get_stock_info(brw, 'AAPL')
print(stock_info)

# get all most popular stocks
popular_stocks = trading212api.get_stocks_list(brw, navigationpath='Stocks>Most Popular')

# get and print information on all most popular stocks
for s in popular_stocks:
	stock_info = trading212api.get_stock_info(brw, s.get('ticker'))
	print(stock_info)

# buy 10 USD of AAPL
trading212api.buy(brw, 'AAPL', 10)

# sell 1 stock of AAPL
trading212api.sell(brw, 'AAPL', 1)TODOImprove code readabilityContactsYou can find me onTwitteras@auino.
Package: tradingalgorithm
Hello, welcome to tradingalgorithm, a Python package for easy algorithmic trading on AlpacaThis package allows one to check account status, make long orders, make short orders, run a custom momentum-based algorithm, and automatically calculate the best tickers to trade in the S&P500 based off of probability of returns and betas.To run this package, you will need an IEX Finance key, as well as an Alpaca API keyTo install the algorithm:$ pip install tradingalgorithmTo pick a stock ticker:import tradingalgorithm

ticker = tradingalgorithm.tickerpicker()To create a stock class:import tradingalgorithm

ticker = 'AAPL'

aapl = tradingalgorithm.stock(alpacaKey, alpacaSecretKey, iexKey, ticker)Methods in the class:aapl.position()
# output: Number of shares:  
#         Market Value: 
#         Profit/Loss: 

aapl.checkhours()
# output: The market is (open or close)Returns maximum amount of shares that you can trade of the ticker based on market value of cash portfolioaapl.max_shares()Takes AAPL (or chosen ticker) long at the current market price and specified share amountaapl.longmarket(shares)Takes AAPL (or chosen ticker) long at the current close of the stockaapl.longlimit(shares)Takes AAPL (or chosen ticker) short at the current market priceaapl.short(shares)Closes entire short or long position in AAPL (or chosen ticker) based on whether you specify "long" or "short" as the typetocloseaapl.closeposition(typetoclose)Runs a momentum algorithm ONE TIME based on volume and time&sales, will take a stock short, long, close position, re-position, and employs a custom stop-lossaapl.algo()Runs the same momentum algorithm CONTINUOUSLY for the set amount of minutesaapl.trade(minutes)
Package: trading-api-wrappers
Trading API WrappersPython 3.6+ clients for popularCrypto Exchangesand other useful services.Disclaimer:Still at an early stage of development. Rapidly evolving APIs.Supported APIs:BudaBitfinexBitstampCoinDeskCoinMarketCapCryptoMKTKrakenOpenExchangeRatesInstallationRequirementsPython 3.6+To install, simply usepoetry(orpip, of course):$poetryaddtrading-api-wrappersDev setup$poetryinstallRename.env.exampleto.envand configure your credentials (for tests)UsageBudaPublic API:fromtrading_api_wrappersimportBudaclient=Buda.Public()Authenticated API:fromtrading_api_wrappersimportBudaclient=Buda.Auth(API_KEY,API_SECRET)Buda API Doc:https://api.buda.comBitfinexPublic API:fromtrading_api_wrappersimportBitfinexclient=Bitfinex.Public()Authenticated API:fromtrading_api_wrappersimportBitfinexclient=Bitfinex.Auth(API_KEY,API_SECRET)Bitfinex API Doc:https://bitfinex.readme.io/v1/docsBitstampPublic API:fromtrading_api_wrappersimportBitstampclient=Bitstamp.Public()Authenticated API:fromtrading_api_wrappersimportBitstampclient=Bitstamp.Auth(API_KEY,API_SECRET,CUSTOMER_ID)Bitstamp API Doc:https://www.bitstamp.net/apiKrakenPublic API:fromtrading_api_wrappersimportKrakenclient=Kraken.Public()Authenticated API:fromtrading_api_wrappersimportKrakenclient=Kraken.Auth(API_KEY,API_SECRET)Kraken API Doc:https://www.kraken.com/help/apiCoinDeskfromtrading_api_wrappersimportCoinDeskclient=CoinDesk()CoinDesk API Doc:https://www.coindesk.com/apiCoinMarketCapfromtrading_api_wrappersimportCoinMarketCapclient=CoinMarketCap()CoinMarketCap API Doc:https://coinmarketcap.com/apiCryptoMKTPublic API:fromtrading_api_wrappersimportCryptoMKTclient=CryptoMKT.Public()Authenticated API:fromtrading_api_wrappersimportCryptoMKTclient=CryptoMKT.Auth(API_KEY,API_SECRET)CryptoMKT API Doc:https://developers.cryptomkt.comOpenExchangeRatesfromtrading_api_wrappersimportOXRclient=OXR(APP_ID)OpenExchangeRates API Doc:https://docs.openexchangerates.orgCurrencyLayerfromtrading_api_wrappersimportCurrencyLayerclient=CurrencyLayer(ACCESS_KEY)CurrencyLayer API Doc:https://currencylayer.com/documentationLicenceThe MIT LicenseCopyright © 2017Felipe Aránguiz|Sebastián AránguizSeeLICENSEDonationsBitcoin:186kDw9LFcPvup17YSrWZbFqdZzELUFad3Ether:0xeF38fA6c0a37A1BdB60CADd7f6e71F351F6d2583