Saravanan666/pypi-org huggingface dataset:
Package: tractus
tractusTrace HTTP requests and gather performance metrics.Installpip install tractusUsagefromtractusimportTracerresult=Tracer('https://google.com').trace()print(f'Host IP:{result.ip}')print(f'Status code:{result.status_code}')print(f'DNS time:{result.dns}ms')print(f'Handshake time:{result.handshake}ms')print(f'First byte time:{result.first_byte}ms')print(f'Full body time:{result.full_data}ms')print(f'Body length:{result.data_length}bytes')print(f'Headers length:{result.headers_length}bytes')Helpers:# Get result as jsonresult.as_json()# Get result as dictresult.as_dict()LicenseMITNamehttps://en.wiktionary.org/wiki/tractus
Package: tracuni
trac_uniConvenient library to plug in tracer to incoming and outgoing points and extract data from thereFeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.Historyv0.0.2 (2018-12-24)Bump version: 0.0.1 → 0.0.2   - finally tox works with all versions in
PyCharm environment   - starter tests for type and constants.Bump version: 0.0.1 → 0.0.2.Refab:   - entry point rename.Feat:   - python 3.4 compatible named tuples for library options   -
starter constant   - tested.Refab:   - some basic test to make 100% coverage.Chore:   - move interpreter version requirements from Pipfile into
setup.py   - turn on live log for py.test   - return standard
environment names in tox setup   - set interpreter location for ‘py-
charm’ in tox setup   - fix python path passed in tox setup   - edit
doc according to 2 previous items.Wip:v0.0.1 (2018-12-21)Bump version: 0.0.0 → 0.0.1   Project prepared for coding the tests.Chore:   - put into project current source to refab and test.Chore:   - changelog by git commits generation tool. [Konstantin
Goncharov]Docs:   - short list what have been done to provide tooling.Chore:   - add make scripts for devpi   - setup docs generation with
browser refresh on changes   - all make commands works. [Konstantin
Goncharov]Feat:   - add primitive test   - satisfy flake8. [Konstantin
Goncharov]Chore:   - return template dev deps.Chore:   - install bumpversion dep   - move pipfile loca index example
in main file   - add make script to generate requirements(_dev).txt.Chore:   - add devpi to make local repo builds   - describe how to add
devpi   - provide files for run test in devpi environment. [Konstantin
Goncharov]v0.0.0 (2018-12-20)Chore:   - add description how to create this scaffolding   - zeroed
version.Chore:   - initialize python envs and deps.Chore:   - start from template.
Package: trac-UserPicturesPlugin
Adds user picture icons (avatars) to Trac.Screenshots of the plugin in action can be found athttps://github.com/boldprogressives/trac-UserPicturesPlugin/wiki/ScreenshotsCredit goes to Michael Bayer for the idea – and most of the code – inhttps://bitbucket.org/zzzeek/tracvatarA mirror is also available on Bitbucket:https://bitbucket.org/boldprogressives/trac-userpictures-pluginThe avatar engine is configurable, and two are provided in this
package: a GravatarProvider that looks up the user’s email address at
Gravatar, and a UserManagerProvider that uses internally hosted images
provided by the Trac UserManager Plugin if it is installed:http://trac-hacks.org/wiki/UserManagerPluginThe approach of the plugin is to filter specific Trac views, gather
all the authors found in the “data” hash being passed to Genshi, then
using Genshi filters to insert additional avatar nodes with the proper
img tags.Currently supported views are:TimelineTicket details: reporter, owner, comments, comment diffsAttachment views (on tickets, wiki pages, etc)Source control views (directory listings, file contents, changesets)Report and custom query viewsWiki history, diffs and individual versionsSearch resultsThis is, more or less, all the places where users show up in a
standard Trac instance.  If you find any other places where icons
should also be inserted, whether in a standard Trac installation or in
a view provided by your favorite plugin, please submit an issue or a
patch.Patches implementing additional avatar engines are also welcome.InstallationInstall the plugin in your favorite way (python setup.py develop,
uploading an egg, etc) and then enable its components in trac.ini like
so:[components]
userpictures.* = enabledYou should then choose your preferred avatar engine.  For Gravatar:[userpictures]
pictures_provider = UserPicturesGravatarProviderFor UserManager, ensure that the UserManager plugin is installed, and
then:[userpictures]
pictures_provider = UserPicturesUserManagerProviderIf you do not explicitly select either engine, a default provider is
used which displays a blank silhouette for every user.There are a number of optional “size” settings for each view; these
are set to sensible defaults that are designed to look good with a
standard Trac install and the stylesheet provided by this plugin, but
look at the source in userpictures/__init__.py (and the CSS in
userpictures/htdocs/userpictures.css) if you really want to change the
way the icons are displayed.Changes0.1.1 (20 Aug 2012)Fixed typo in code that caused Python error when navigating to browser views0.1 (19 Aug 2012)Initial release.
Package: tracvatar
Adds avatar icons provided by eitherGravatarorLibravatarto Trac.Credit goes to theHackergotchiPluginfor
some general ideas.Ideally, Trac itself would just include support for author avatars
as a built in, since this is an extremely common and desirable feature.For now, the approach of the plugin is to filter specific Trac views,
gather all the authors found in the “data” hash being passed to
Genshi, then using Genshi filters to insert additional avatar nodes.Currently supported views are:TimelineIssue displayIssue change display (i.e. comments, attachments)Source browser listing (tested for svn and hg so far)Individual changeset page (tested for svn and hg so far)User prefs page (includes link to “change your avatar” at
gravatar.com/libravatar.org)InstallationTo install, just usepython setup.py bdist_eggto create an egg file which
then goes into the Tracplugins/folder, or justpython setup.py installto plug it in entirely.ConfigurationTo enable the plugin in trac.ini:[components]
tracvatar.* = enabledThere are then available optional “size” settings for each view, shown
below are defaults:[tracvatar]
ticket_reporter_size = 60
ticket_comment_size = = 40
timeline_size = 30
browser_lineitem_size = 20
browser_changeset_size = 40
prefs_form_size = 40
avatar_default = default
backend = gravatar
metanav_size = 30
Package: trac-WorkflowActionButtons
This plugin adds a row of “action buttons” to the top of every ticket detail page. These buttons allow you to quickly act on a ticket (with a workflow action like “reassign”, “resolve”, “reopen”, etc) without scrolling down to the Actions section. When a button is pressed, a modal dialog opens up with a small form prompting the user for any additional information (e.g. resolution when resolving the ticket, or new owner when reassigning) and an optional comment.The plugin does nothing if Javascript is disabled.
Package: trac-WorkflowNotificationPlugin
0.6 (2017-??-??)Configuring notifications through Trac’s web admin system now requires
TICKET_ADMIN only, not full TRAC_ADMIN.  This permission check is also
FineGrainedPermissions-aware.Notification templates can now access achange_historyvariable to email
all commenters on a ticket, display a full history of ticket changes in
the email body, and other use cases.0.5 (2013-11-21)Notifications can now be configured through Trac’s web admin system.0.4 (2012-12-12)Support for Trac 0.11.70.3 (2012-12-11)Allow configuration of conditional notifications.Provideactionstring in templates.0.2 (2012-12-10)Provideold_valuesdict in templates.‘*’-notifications are no longer triggered for @created actions.0.1 (2012-12-09)Everything is new!
Package: tracy
Tracy provides a simple but informative and configurable view at live, running
Python programs. The basic functionality is to render the source of each line
traversed, complete with graphical call stack level depth indication and
sourceline reference. Using magic comments, users can choose to print out
variable values at interesting points or hide lines for minimized clutter. More
features planned. Sorry, no distutils as yet, just drop the folder into a place
on your path. Snazzy epydocs provided. Pls have a try and do feed back, if you
like.
Package: tradecalc
TradecalcCLI tool to calculate trading positions for risk management on different
markets.Free software: MIT licenseDocumentation:http://tradecalc.readthedocs.io/en/latest/Source:http://github.com/toirl/tradecalcFeaturesCalculate max position size you can buy/sell at a given price, with a
limited risk.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.2 (2017-07-21)Bugfix release.Fixed:Wrong calculation of volume and position size in case of sell orders.0.1.1 (2017-07-21)Maintainance release.Fixed:Support for Python 2.70.1.0 (2017-07-21)First release on PyPI.Features:Calc max position on buyCalc max position on sell
Package: tradedangerous
TradeDangerousCopyright (C) Oliver "kfsone" Smith, July 2014Copyright (C) Bernd 'Gazelle' Gollesch 2016, 2017Copyright (C) Jonathan 'eyeonus' Jones 2018 - 2021REQUIRES PYTHON 3.4 OR HIGHER.What is Trade Dangerous?TradeDangerous is a set of powerful trading tools for Elite Dangerous, organized around one of the most powerful trade run optimizers available.The TRO is a heavy hitter that can calculate complex routes with multiple stops while taking into account the profits you make along the routeThe price data in TradeDangerous is either manually entered or crowd sourced from a website such asTromador's Trading Dangerously, often using a plugin such as the included eddblink.What can it do for me?You're in a ship with 8 cargo spaces that can make 8.56 ly per jump; you're willing to make upto 2 jumps between stations, and we want to see how much money we can make if in 2 trade stops (hops).trade.py run --credits 5000 --capacity 8 --ly-per 8.56 --jumps 2 --hops 2If we ran this, TD would search the galaxy for trade runs. But it could take us days to reach some of them. So lets say we're currently at Kummer City in the Andere system.trade.py run --from "andere/kummer city"
    --credits 5000 --capacity 8 --ly-per 8.56 --jumps 2 --hops 2(The above represents a single line)That's a lot to type. TD is designed to support laziness when it comes to typing, so it allows for all kinds of short-cuts.trade.py ru
    --fr and/kumm     find a station matching 'kumm' in a
                      system matching 'and'
    --cr 5k           'k', 'm' and 'b' are recognized suffixes
    --cap 8           8 units of cargo
    --ly 8.56         maximum distance *per jump*
    --ju 2            maximum 2 jumpsThe default for hops is 2, so I didn't have to include it.You can also use "=" to connect an option with its values:trade.py ru --fr=and/kumm --cr=5k --cap=8 --ly=8.56 --ju=2With the data at the time I write this, this produces:ANDERE/Kummer City -> ANDERE/Malzberg Vision
  ANDERE/Kummer City: 6 x Titanium, 2 x Polymers,
  G 224-46/Lorrah Dock: 7 x Coltan, 1 x Lepidolite,
  ANDERE/Malzberg Vision +8,032cr (502/ton)This tells us our overall route (line #1), what load to pick up from the first station, what to sell it for and pick up at the second stop and where to finish and unload for our final profit.Note that it could have just told us to pick up 6 Titanium (the max we could afford) or 8 Copper (the highest profit we could fill up with), Instead, TD crunched hard numbers and maximized the earnings of every cargo space AND credit.If you want to give Trade Dangerous a try, look no further than theSetup Guideand theUser Guide.Curious about programming with Trade Dangerous/Python? Take thePython Quick Peek.
Package: trade-database-manager
*** IMPORTANT NOTICE ***This package isnotin a usable stage. It is only uploaded for convenience of developing and testing.Postgreslq InitializationCREATEDATABASEtrade_data;CREATEUSERtradedbadminWITHPASSWORD'trade_password';GRANTALLPRIVILEGESONDATABASEtrade_dataTOtradedbadmin;\connecttrade_data;GRANTALLONSCHEMApublicTOtradedbadmin;Add the following lines in thepg_hba.conffile to allow password authentication for thetradedbadminrole.# trade database
host    all            tradedbadmin     0.0.0.0/0               scram-sha-256
host    all            tradedbadmin     ::/0                    scram-sha-256
Package: tradedoubler-api-client
tradedoubler_api_clientUnofficial simple python wrapper for Tradedoubler APIinstalationpip install tradedoubler-api-clientexample of usagefromtradedoubler_api_clientimportTradedoublertd=Tradedoubler('relative_path_to_credentials.json')pending_sales=td.pending_sales()list_pendint_sales=td.pending_sales().get_all()list_pendint_sales.csv(path='csv')list_pendint_sales.json(path='json')more examples...credentials.json schema:{"td_secret":"[secret]","td_id":"[id of application]","td_user_name":"[email@domain.com]","td_userpassword":"[passToAcount]"}visitsolutions.tradedoubler.com/tools/api-client/index.phpto get app id and secret.List of reasons to deny transactioncodereason6Application/Credit Check Denied7Fraudulent Order/Application8Duplication / Sale Accredited to Another Source9Order Yet To Be Fulfilled10Returned goods13Invalid Lead14Order Cancelled16Insuffient Information (Applicable only for untracked sales)17Order not found (Applicable only for untracked sales)18Sale Already Accredited to Publisher (Applicable only for untracked sales)19Voucher incorrectly used
Package: trade-engine
Trade Enginea library for demo trading | backtest and forward test simulationFeaturesRequirementsGetting startContributingContributions are very welcome. There are a number of requirements:See Issues tab, and feel free to submit your own issuesAdd PRs if you discover a solution to an existing issueThe code should be Pep8 compliant.Comments are required for every class and function and they should be a clear description.At least one broad test case and a set of unit tests must be provided for every function.Avoid very pythonic constructionLicensetrade-engineis freely available under the MITlicense.
Package: tradeentry
CompatibL Trade Entry AI (Community Edition)SummaryTrade entry from natural language for the capital markets using LLMsCopyrightEach individual contributor holds copyright over their contributions to the
project. The project versioning is the sole means of recording all such
contributions and copyright details. Specifying corporate affiliation or
work email along with the commit shall have no bearing on copyright ownership
and does not constitute copyright assignment to the employer. Submitting a
contribution to this project constitutes your acceptance of these terms.Because individual contributions are often changes to the existing code,
copyright notices in project files must specify The Project Contributors and
never an individual copyright holder.
Package: trade-executor
Trade Executor: Algorithmic Trading Engine for DeFitrade-executoris a Python framework for backtesting and live execution of algorithmic trading strategies on decentralised exchanges.Note: This is early beta software.Please pop in to the Discord for any questions.FeaturesOnly trading framework that has been built grounds up fordecentralised financeHigh quality documentationSupportdecentralised markets like Uniswap, PancakeSwapBacktesting enginerLive tradingWebhook web serverfor JavaScript frontend and monitoring system integrationDeploy asDocker containerPrerequisitesYou need to knowBasics of PythonBasics of tradingWe have collected learning material for developers new to algorithmic tradingGetting startedFirst study the example codeCode examplesTrading strategy examplesSee TradingView PineScript porting exampleMore informationRead documentation on running and backtesting strategiesVisitTrading Strategy website to learn about algorithmic trading on decentralised exchangesJoin the Discord for any questionsInstallationNote: The project is under active development. We recommend any developers to use Github master branch
for installations.gitclonegit@github.com:tradingstrategy-ai/trade-executor.gitcdtrade-executor
gitsubmoduleupdate--init--recursive# Extra dependencies# - execution: infrastructure to run live strategies# - web-server: support webhook server of live strategy executors# - qstrader: still needed to run legacy unit testspoetryinstall-Eweb-server-Eexecution-Eqstrader-EquantstatsOr with pip:pipinstall-e".[web-server,execution,qstrader,quantstats]"Architecture overviewHere is an example of a live trading deployment of atrade-executorpackage.Running testsSeeinternal development documentation.CommunityTrading Strategy websiteCommunity Discord serverBlogTwitterTelegram channelNewsletterLicenseAGPLContact for the commercial dual licensing
Package: tradeforce
-------Docker-------Get bash shell in containerdocker exec -it tradeforce bashGet requirments.txtcd /to/path/tradeforce/root
docker build -t tradeforce:build --target build .
docker create --name tradeforce_build tradeforce:build
docker cp tradeforce_build:/opt/tradeforce/requirements.txt ./requirements.txt------------------Window Powershell------------------Run dedicated market server$env:RUN_MARKET_SERVER="True"; docker-compose up; Remove-Item Env:\RUN_MARKET_SERVERRun JupyterLab$env:RUN_JUPYTERLAB="True"; docker-compose up; Remove-Item Env:\RUN_JUPYTERLAB-----------Linux Bash-----------Run dedicated market serverRUN_MARKET_SERVER="True" docker-compose upRun JupyterLabRUN_JUPYTERLAB="True" docker-compose up
Package: tradehub
Tradehub Python APIThis repository is designed to easily integrate your Python code or application with the Switcheo Tradehub Blockchain. This API is designed to interact with the decentralized network of Validators designed to keep the blockchain running and secure. This allows you to choose trusted endpoints or select random endpoints to interact with.This project has been submitted on the Switcheo Foundation forums as part of the wider Switcheo community and you can follow official progress in this thread:https://forum.switcheo.foundation/topic/49/python-sdk-for-tradehubNOTE:This repository and underlying blockchain is under active development and may change drastically from each update.If you have ideas or contributions we are accepting Pull Requests.Getting Startedpip install tradehubOr Using Poetry -https://python-poetry.org/poetry add tradehubDocumentationThe documentation site can be found at:https://mai-te-pora.github.io/tradehub-python/Examples and TestsWe have provided examples and tests (unittests) for the majority of the functions available across this project. We are always looking for help with this because having tests pass has proven to be the most difficult part of this project.UsageThere are many clients to choose from and depending on your needs there are only one or two you should mainly interact with because most of these inheret from the building blocks.Traders should use theDemex ClientValidators could use theDemex Clientbut combining theWalletClient andAuthenticated Clienttogether is effectively the same.The way these classes inheret from each other is as follows (top level first):Demex Client:arrow_up:Authenticated Client     +     Wallet:arrow_up:Transactions Client:arrow_up:Public Client:arrow_up:Public Blockchain Client:arrow_up:Network Crawler ClientDemex ClientThis client utilizes all the other clients and can call wallet, authenticated, and public endpoints.from tradehub.demex_client import DemexClient

demex_crawl = DemexClient(mnemonic=mnemonic, network="mainnet", trusted_ips=None, trusted_uris=None)
demex_ips = DemexClient(mnemonic=mnemonic, network="mainnet", trusted_ips=["54.255.5.46", "175.41.151.35"], trusted_uris=None)
demex_uris = DemexClient(mnemonic=mnemonic, network="mainnet", trusted_ips=None, trusted_uris=["http://54.255.5.46:5001", "http://175.41.151.35:5001"])demex_crawlwill crawl the Tradehub network for active validators to interact with. There is ~5 second startup time to perform this but if you are running a long running process this should be acceptable.demex_ipswill respond very quickly as we are assuming trust and only checking that they have their persistence service turned on, can be used for quick interaction or lookups.demex_urissimilar todemex_ips, can be used for quick interaction or lookups.Walletdemex_ips.wallet.addressAuthenticated Clientdemex_ips.tradehub.send_tokens()Public Clientdemex_ips.tradehub.get_all_validators()
Package: trade-lib
trade-lib自己的交易常用库pip install trade-lib使用importtrade_lib# load exchange config from ~/.config/exchange.yamlconfig=trade_lib.get_exchange_config(exname)# set_dingdingdingding_config={'robot_id':'','secret':''}trade_lib.set_dingding(dingding_config)trade_lib.dinding_send('ding...')upload to pypipython3 setup.py sdist bdist_wheel

twine upload dist/*
Package: tradelocker
TradeLocker Python API WrapperThis project provides a Python wrapper for TradeLocker's public API. It simplifies the process of making requests to the API by providing Pythonic interfaces.A full description of the TradeLocker's public API can be found atTradeLocker API DocumentationTable of ContentsGetting StartedInstallationUsageContributingLicenseGetting StartedTo use this Python wrapper, you'll need the username, password and the id of the server that you use to access TradeLocker.
If you don't already have access, you need to find a broker that supports TradeLocker and create an account.InstallationThis package requires Python 3.11 or later.
The easiest way to install this package is using pip:pipinstalltradelockerUsageHere's a simple example on how to use the TradeLocker Python API wrapper.
The code below initializes a TLAPI object with authentication data.
It then: fetches price history and latest price, creates an order that converts into a position, waits for 2 seconds, and finally closes the same position.fromtradelockerimportTLAPIimporttime,random# Initialize the API client with the information you use to logintl=TLAPI(environment="https://demo.tradelocker.com",username="user@email.com",password="YOUR_PASS",server="SERVER_NAME")symbol_name="BTCUSD"# "RANDOM"all_instruments=tl.get_all_instruments()ifsymbol_name=="RANDOM":instrument_id=int(random.choice(all_instruments['tradableInstrumentId']))else:instrument_id=tl.get_instrument_id_from_symbol_name(symbol_name)price_history=tl.get_price_history(instrument_id,resolution="1D",start_timestamp=0,end_timestamp=0,lookback_period="5D")latest_price=tl.get_latest_asking_price(instrument_id)order_id=tl.create_order(instrument_id,quantity=0.01,side="buy",type_="market")iforder_id:print(f"Placed order with id{order_id}, sleeping for 2 seconds.")time.sleep(2)tl.close_position(order_id)print(f"Closed order with id{order_id}.")else:print("Failed to place order.")For more detailed examples, see theexamplesdirectory.ContributingTo contribute to the development of this project, please create an issue, or a pull request.Steps to create a pull request:Clone the project.Create your feature branch (git checkout -b feature/YourFeature).Commit your changes (git commit -am 'Add some feature').Push to the branch (git push origin feature/YourFeature).Create a new Merge Request.LicenseThis project is licensed under the terms of the MIT license. SeeLICENSEfor more details.
Package: trademac-marker
Class for use https://markerapi.com/=======Install=======.. code-block:: bashpip install trademac-marker=======Example=======.. code-block:: pythonfrom trademark.marker import APIparams = {'username': 'username','password': 'password','search': 'search'}marker = API(params)print marker.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