Saravanan666/pypi-org huggingface dataset:
Package: markdown-vimwiki
markdown_vimwikiPython Markdown extension for useful vimwiki additionsTodo listsThe plugin supports the standard vimwiki style todo lists:* [ ]To do*[.] 0-33% complete*[o] 33-66% complete*[O] 66-99% complete* [X]100% complete*[-] rejectedleads to:<ul><liclass="done0">done0</li><liclass="done1">done1</li><liclass="done2">done2</li><liclass="done3">done3</li><liclass="done4">done4</li><liclass="rejected">rejected</li></ul>By default, it uses all the same defaults as vimwiki's syntax. That is, it uses.oOXforg:vimwiki_listsymsand-forg:vimwiki_listsym_rejected, and applies the CSS classes used by the default HTML generation tool.These are customizable. For the following markdown:*[i] yip*[a] yap*[o] yopexpecting:<ul><liclass="yip">yip</li><liclass="yap">yap</li><liclass="yop">yop</li></ul>configure as follows:markdown(source,extensions=[VimwikiExtension(list_levels='iao',list_classes=['yip','yap','yop'])])TagsThe plugin currently supports styling tags (but nothing else)::lorem:ipsum:leads to:<p><spanclass="tag">lorem</span><spanclass="tag">ipsum</span></p>The class used is customizable with thetag_classconfig option.
Package: markdown-wavedrom
Support for WaveDrom in Python MarkdownThis extension adds support forWaveDromtoPython Markdown.Installationpip install markdown-wavedromThis extension parses Markdown and replaces matching sections with HTML script elements.
To enable WaveDrom rendering, you must ensure that the proper JavaScript code is loaded into your
HTML page. Seethe WaveDrom documentationfor
details.Example# My Markdown Documentationwavedrom (
    { signal: [{ name: "Alfa", wave: "01.zx=ud.23.456789" }] }
)MkDocs IntegrationThe following minimal config is required to get markdown-wavedrom to work in MkDocs.markdown_extensions:-markdown_wavedromextra_javascript:-https://cdnjs.cloudflare.com/ajax/libs/wavedrom/2.6.8/wavedrom.min.js-https://cdnjs.cloudflare.com/ajax/libs/wavedrom/2.6.8/skins/default.js-js/wavedrom_loader.jsWheredocs/js/wavedrom_loader.jshas the following content:window.addEventListener("load",function(){WaveDrom.ProcessAll();});You can of cause also host the WaveDrom JavaScript files locally with your documentation.For a complete example with MkDocs, seethe markdown-wavedrom-mkdocs-example GitHub page.DevelopmentFeel free to open an issue or a PR if there is something that can be improved.Releases on PyPI are created automatically throughpython-semantic-release.
Therefore, this project usesAngular commit message stylefor commits.Testing$ pip install -r dev-requirements.txt
$ tox
Package: markdown-word-count
⬇ Markdown Word CountA word counter for raw Markdown files, excluding punctuation, footnotes, and special Markdown or HTML tag syntax.💻 InstallationYou will need...🐍 Python 3🐑 Acloneof this repo or asingle file downloadof the script.▶ UsageTo run this script, pass the file you want to have analyzed as the first parameter:./mwc.py myfile.mdIf that doesn't work, explicitly pass the program to Python:python mwc.py myfile.mdIf this doesn't work, trypython3instead ofpython.⛏ DevelopmentRun this to execute all tests:python -m unittest discover💬 Ports to Other Programming LanguagesA PHP port can be foundhere, with thanks to@Arcesilas!
Package: markdown-worker
Markdown WorkerThis is a simple markdown parser written in Python. It can read, write and parse markdown files. It can read a particular header, write a particular header, and parse a particular header. It can also parse the entire file.Installation# use these commands to install the package source code to your local machinegitclonehttps://github.com/mantreshkhurana/markdown-worker-python.gitcdmarkdown-worker-pythonorpipinstallmarkdown-workerorpip3installmarkdown-workerUsageI provided aexample.mdfile in the repository. You can use that to test the program, it contains all thedocumentationof the program.frommarkdown_workerimportMarkdownParserif__name__=="__main__":file_name=input("Enter the path of the Markdown file: ")parser=MarkdownParser(file_name)heading_to_search=input("Enter the heading to search: ")result=parser.search_heading(heading_to_search)print("\nContent that was under this heading:\n")print(result)AuthorMantresh Khurana
Package: markdrip
MarkdripMarkDrip is a simple HTML generator.
Mistletoe is used for rendering.The site ishereeven in the rendered result.InstallRecommend usingpipx.pip install markdripHow to usemarkdrip filenameOptionsRunmarkdrip --help.Usage: main.py [OPTIONS] TARGET

Options:
  --output TEXT  Output destination file path
  --theme TEXT   Applicable CSS file name. Does not include extension.
  --help         Show this message and exit.Custom CSSCSS is stored under~ / .markdrip.
Note that when writing CSS, specify the tag name directly in the selector.Ex.)h1, h2, h3, h4, h5 {
	color: black
}
Package: marked
Introductionmarkedis a library and CLI utility for transforming HTML-ish (HTML, XHTML, HTML5 etc.)
documents and fragments intomakrdownformatted content.It is inspired by Aaron Swartz’html2text, but
with a more permissivelicense, and using the excellentBeautifulSouplibrary for extremely flexible markup parsing.InstallationUsage (CLI utility)Usage (library)License
Package: marker
MarkerA marking utility to help automate code testing, and interfacing with the submission platform. Currently, the following platforms are supported:CanvasMarkUsThis package installs the programmarker. It can either be run as an interactive REPL or through the command line directly. It supports the following commands:download: Downloads files from the given LMS.prepare: Copies needed files into student directories, compiles code.run: Runs all the test cases, creates logs and compiles marks.upload-marks: Uploads the student marks to the LMS.upload-reports: Uploads the testing logs to the LMS for the student.delete-reports: Deletes the testing logs from the LMS for the student.set-status: Sets the marking state of the submission (MarkUs only).stats: Gives you some basic statistics of the results.Each of the commands can be run either for individual students or for everyone. Runmarker helpormarker help commandfor more information.How to installThere are 2 ways to install this marker.(1) Using PIPThis is by far the recommended way of installing this utility. Simply run:pipinstallmarker(2) Build from sourceAlternatively, if you want to develop, you will need to build from source. First, clone this repository to your machine:gitclonehttps://github.com/mustafaquraish/markerThen, go into the cloned repo and useflitto installcdmarker
pipinstallflit
flitinstallHow to useSome examples on how to use this marker with Python and C code are provided
in thetemplatesdirectory, however it is designed to work with any programming
language as long as you can run tests from the command line. Even if you're not
using C, the template will be helpful in showing you how to set it up to work
with your environment.Full Documentation
Package: markerlib
markerlibCompile or interpret PEP 345 environment markers.Usage:>>> import markerlib
>>> marker = markerlib.compile("os.name == 'posix'")
>>> marker(environment=markerlib.default_environment(),
           override={'os.name':'posix'})
True
>>> marker(environment=markerlib.default_environment(),
           override={'os.name':'nt'})
FalseThe implementation uses the ast to compile environment markers as Python
statements with a limited set of allowed node types.0.6.0Allow _ where . was previously used (‘os.name’ -> ‘os_name’)0.5.2Restore ‘as_function’ bw/compat synonym for ‘compile’0.5.1Include ‘empty marker’ heuristic in markerlib itself0.5One final release until it’s just a part of distribute0.4Cache compiled marker functions with weakref.WeakValueDictionaryRename markerlib.as_function to markerlib.compile0.3Might work on Python 2.5 (includes needed parts of the ast module from
Python 2.6+)Include 100% test coverage, tox config file0.1Initial version
Package: marker-web
Marker-WebThis is a Flask-backend and Vue.js frontend for themarkerlibrary. TheTry it out with dummy data!(Mobile friendly too)Runningmarker-webspins up a local server and hosts the frontend so you can use the marking utilities with a GUI. The layout makes it trivial to package this as a standalone app if needed.Disclaimer: This is still in development. There most definitely are UI quirks and missing features. If you find any, please open an Issue on GitHub and let me know!How to installThere are 2 ways to install this marker.Using PIPThis is by far the recommended way of installing this utility. Simply run:pipinstallmarker-webBuild from sourceAlternatively, if you want to develop, you will need to build from source:gitclonehttps://github.com/mustafaquraish/marker-webcdmarker-web
pythonsetup.pyinstallHow to useLocallyIn it's simplest form, you can start up the server with:$marker-webYou can also pass in thesame arguments asmarkerCLI.Currently, if either:Your configuration file is not is notassgn_dir/config.yml, orYoursrc_diris not the same asassgn_dirThen youmustpass in the correct arguments when runningmarker-web. Otherwise, the interface provides a little file explorer which lets you pickassgn_dir(and can infer the other two arguments)By default, anyone else logged in on the machine can access the endpoints. To prevent this, you can run inauthenticated modewith:$marker-web--authThis will print out a random token which needs to be entered in the frontend to be able to access any information. A link is also print out with the token embedded in it, so you can just open that URL in your browser.By default, the server runs on port6275. You can specify an alternate port using:$marker-web--portPORTRemote (Experimental)Note: This requires the remote machine to havemarker-webinstalled, and for you to have SSH access to it.If you want to run the marker on a remote machine, but show the frontend on your local browser, this can be done via port-forwarding over SSH. For full flexibility, you want todo this manually. However, if you are fine with some defaults, you can run:$marker-web--remoteHOSTwhich is approximately the same as running:$ssh-LPORT:localhost:PORTHOSTmarker-web--authFor the features available to you in the GUI, you should read through thedocumentation for the marker CLI. Most things should be self-explanatory.Development notes:Thefrontenddirectory contains the Vue frontendThemarker_webdirectory contains the marker_serverTheextradirectory contains some files to build a standalone app (on MacOS at least)
Package: market-api
market-apiПолучение токенаmarket.csgo.comИспользованиеimportdatetimeimportpprintfrommarket_apiimportMarketConfig,MarketClient,MarketException,modelsconfig=MarketConfig(api_key="...")client=MarketClient(config)pprint.pprint(awaitclient.account.get_my_steam_id())pprint.pprint(awaitclient.account.change_currency(models.Currency.EUR))pprint.pprint(awaitclient.trades.history(datetime.datetime.now()-datetime.timedelta(days=1),datetime.datetime.now()))asyncformessageinclient.wss.listen_raw([models.WSSChannel.HISTORY_GO],need_auth=True):pprint.pprint(message)
Package: market-break
market-breakA set of tools to help create algorithmic trading strategies and test them, in a vectorized way.first of allspecifics:writen and owned by: Shahaf Frank-Shapirall the rights are saved for: Shahaf Frank-Shapirprogramming languages: python 3.9.12 (100%)before we startdescription:visit the docs to learn more about this project and how to develop with it.dependencies:opening:
For this is a complex program, which uses a lot of modules, there are required dependencies needed
in order to run the program. keep in mined the program was writen in python 3.9, so any python version lower
than 3.9 might not work properly.install app dependencies by writing the "-r" option to install the requirements
writen in a file, and write the following line in the project directory:pip install -r requirements.txtrun a testrun from windows command line (inside the project directory)run with python by writing to the command line in the project directory:python test.py
Package: marketdataproviders
Market Data ProvidersMiscellaneous APIs around Market Data providers.APIsCurrently only basic access to:https://eodhistoricaldata.com/is implemented.BuildThis is built usingPoetry.# after checkout, within top-level checkout directorypoetryinstall# To update dependencies, or after `poetry add ...`poetryupdate# to make sure we are using our virtual env's tooling (created# automatically by poetry, much like conda env)# We can, for example add ipython as a dev dependency, then shell into our# env, only then will we get this install. Use `which ipython` to verify.poetryshell# To build distributable packagespoetrybuildPublishingTo PyPiCreate PyPI account with a new token.Add this to poetry's config:poetry config pypi-token.pypi <my-token>Simply publish:poetry publishTo Local RepositoryOnce off only: Prepare Local RepositorySee:https://pypi.org/project/pypiserver/: Install this.https://python-poetry.org/docs/master/repositories/# Create locationLOCAL_REPO_FS=$HOME/.local/home-pypi
mkdir-p$LOCAL_REPO_FScd$LOCAL_REPO_FS# Run pypi-server in local repo fs, unauthorised mode.pypi-server-i127.0.0.1-v-P.-a.-p9292.Add repository name topoetryconfig:poetryconfigrepositories.home-pypihttp://localhost:9292/Updatepipconfiguration to use this extra index.# ~/.pip/pip.conf -> https://pypi.org/project/pypiserver/#configuring-pip
# Add the following config

[global]
extra-index-url = http://localhost:9292/simple/To publish to local repo:# Publish distributable packages to local repo set-up with name above.
# Just press Enter when username asked, we don't have authentication on.
poetry publish --repository home-pypi
Package: marketdesign
Market DesignThis project is a python implementation of the market mechanism described in the paper"Shapley value based pricing for auctions and exchanges" (Lindsay 2018).  The project uses abidding languagethat extends the version in the
paper to allow bidders to express their preferences more concisely.Installing on WindowsInstallgitandPython 3.xif not already installed.# Get a copy of the project. 
git clone https://github.com/luke777/marketdesign.git
# Set up and activate the virtual environment 
cd marketdesign
py -m venv env
env\Scripts\activate
py -m pip install -r requirements.txt
# Verify that the command-line solver runs
py solver.py examples\Lindsay2018_t1_seller_and_2_buyers.txtIf Windows PowerShell gives the error message "running scripts is disabled on this system", try executing the followingSet-ExecutionPolicy Unrestricted -Scope ProcessOn Linux/macOS try usingpython3instead ofpyto run python
andsource env/bin/activateinstead of.\env\Scripts\activateto activate the virtual environment.Command-line solverThe programsolver.pyreads in bids from a file and outputs the
winning bids and payments.  If the python virtual environment is not already activated, activate is as follows.env\Scripts\activateThe solver can then be run.py solver.py examples\Lindsay2018_t1_seller_and_2_buyers.txtThree file formats are supported.
The directoryexamplescontains examples of each of the formats.  The cases are taken from Lindsay 2018.TextThis format is the most concise.  Bids are specified in a text file
with one line per bidder.CSVThis format is convenient if bids are prepared in a spreadsheet.JSONThis format is relatively more verbose but allows bids
to be easily prepared and analyzed using most programming languages.By default, the results of solving the market are shown onscreen.  The output can
be directed to a file as follows.py solver.py examples\Lindsay2018_t2.1_two_demand_types.csv -o output.jsonThe format of the output is determined by the filename extension.  As with inputs,
the supported formats are text (.txt), csv, and json.Web solverThe programweb-solver.pystarts a micro web service that allows the
market solver to be accessed online.If the python virtual environment is not already activated, activate it withenv\Scripts\activateThen start the service withpy web-solver.pyOpeninghttp://localhost:5000in a browser should display links to the following.A form for submitting bids in text format.A form for uploading a file with bids in cvs format.A form for submitting bids in json format.An example of a graphical interface that lets users experiment
with different bids.  The bids are captured using javascript
and sent to the server in json format.
Package: marketfeed-multi-broker-sdk
Multi-Broker SDKMulti-Broker SDK is a Python library that allows you to seamlessly integrate multiple brokerage services in your application. This package simplifies interaction with different brokers, providing a unified way to implement and manage your trades.InstallationUse the package manager pip to install BrokerSDK. Run the following command in your terminal:pip install marketfeed-multi-broker-sdk
pip install git+https://github.com/tradeclone/multi-broker-sdk.gitUsageTo utilize the functionality of BrokerSDK, import it into your Python script:from marketfeed_multi_broker_sdk import BrokerSDK
from marketfeed_multi_broker_sdk import Broker, Login, LoginResponseInitialize the SDK with the specific broker's name and user details:sdk_xts = BrokerSDK(Broker.XTS, client_code='CLIENT_CODE')
sdk_fyers = BrokerSDK(Broker.FYERS, client_code='CLIENT_CODE')
sdk_shoonya = BrokerSDK(Broker.SHOONYA, client_code='CLIENT_CODE')
sdk_kotak_neo = BrokerSDK(Broker.KOTAK_NEO, client_code='CLIENT_CODE')Use the BrokerSDK to log in. The BrokerSDK handles communication with the specific broker based on the provided broker name.For FYERS:loginResponse: LoginResponse = sdk_fyers.login(
    Login(
        totp_key="TOTP_KEY",
        pin="0000"
    )
)
if loginResponse.token == "":
    print(loginResponse.message)
else:
    print("TOKEN GENERATED", loginResponse.token)For XTS:loginResponse: LoginResponse = sdk_xts.login(
        Login(
            api_key="API_KEY",
            api_secret="API_SECRET"
        )
    )
if loginResponse.token == "":
    print(loginResponse.message)
else:
    print("TOKEN GENERATED", loginResponse.token)For SHOONYA:loginResponse: LoginResponse = sdk_shoonya.login(
        Login(
            password="PASSWORD",
            totp_key="TOTP_KEY",
            app_vendor="APP_VENDOR",
            app_imei="APP_IMEI",
            app_key="APP_KEY"
        )
    )
if loginResponse.token == "":
    print(loginResponse.message)
else:
    print("TOKEN GENERATED", loginResponse.token)For KOTAK_NEO:loginResponse: LoginResponse = sdk_kotak_neo.login(
        Login(
            mobile="MOBILE",
            password="PASSWORD",
            mpin="MPIN",
            consumer_key="CONSUMER_KEY",
            consumer_secret="CONSUMER_SECRET"
        )
    )
if loginResponse.token == "":
    print(loginResponse.message)
else:
    print("TOKEN GENERATED", loginResponse.token)ContributingWe welcome contributions from the community. If you'd like to contribute to BrokerSDK, feel free to submit a pull request or open an issue on our GitHub page.Please make sure to update tests as appropriate.For further details and updates about this project, please read through the documentation on our GitHub page.Remember, your contributions enhance the capabilities of our project. Happy coding!
Package: marketmaker
Market MakerMarket Maker is a suite of tools for managing threat simulation plans and test cases. Market Maker consists of three components: 1) Python library, 2) CLI scripts, and 3) extensions.Thedocumentation directorycovers the core concepts and how to use the tool. A quickstart guide is also included in the docs here:Quickstart.For an example of Market Maker generated content, see the SRAindexesrepo:https://github.com/SecurityRiskAdvisors/indexesInstalltionpip install marketmaker
Package: marketo-monkey
marketo-monkeyCLI tool to facilitate Marketo integration.InstallingUsesnap:$ snap install marketo-monkey [--edge] [--classic]--classicwould allow you to edit the configuration file
(credentials) from the tool, otherwise it's not necessary.$ marketo-monkey -v
2018-06-08 14:26:12,793 DEBUG Added a stderr logging handler to logger: urllib3
Could not access the configuration file ...
Please edit /home/ubuntu/snap/marketo-monkey/common/marketo-monkey.yaml manuallyUsage$ marketo-monkey lead
'Lead' object available fields:
    firstName, lastName, email, company

$ marketo-monkey lead email=foo.bar@example.com
Lead object updated!
{'createdAt': '2018-06-08T12:19:00Z',
 'email': 'foo.bar@example.com',
 'firstName': 'Foo',
 'id': 33374563,
 'lastName': 'Bar',
 'updatedAt': '2018-06-08T17:57:07Z'}

$ marketo-monkey snap
'Snap' object available fields:
    createdAt, marketoGUID, updatedAt, Confinement, channel, emailAddress, revision, snapName

$ marketo-monkey snap emailAddress=foo.bar@example.com,snapNamexx=testing-snap5
Failed to create or modify snap!
    Field 'snapNamexx' not found
    Value for requried field 'snapname' not specified

$ marketo-monkey snap emailAddress=foo.bar@example.com,snapName=testing-snap5
Snap object created!
{'Confinement': None,
 'channel': None,
 'createdAt': '2018-06-08T18:34:21Z',
 'emailAddress': 'foo.bar@example.com',
 'marketoGUID': 'e1361ee9-7f9e-4a2c-acb4-b7e988ac8c55',
 'revision': None,
 'seq': 0,
 'snapName': 'testing-snap5',
 'updatedAt': '2018-06-08T18:34:21Z'}
Package: marketools
marketools: tools for stock market analysisAboutmarketools is a Python package for web scraping and analysis of stock market data. Project is under development. At the moment, analysis functionality is limited. You are welcomed to contribute to the project.Source of dataData are scraped fromStooqservice.SupportYou may report issues and functionality requestshere.Installationpipinstallmarketoolsorgitclonehttps://github.com/AlbertRtk/marketools.gitDocumentationDocumentationanalysisstockstqscraperExampleImport Stock classfrommarketoolsimportStockCreate Stock instance for selected ticker, herePKNpkn=Stock('PKN')For not Polish stocks, you need to append country code to the ticker (after a dot), e.g.,apple=Stock('AAPL.US')Get and print OHLC (open-high-low-close) data from the last 5 dayspkn_ohlc=pkn.ohlc# returns pandas.DataFrameprint(pkn_ohlc.tail(5))Print available fundamental informationprint(pkn.fundamentals)
Package: marketpanda
Market PandaThis project offers a interface marketvault, a database that serves a securities database for investment research and algorithmic trading. It can either work with an offline marketvault instance or the online service.TechnologiesThe project utilizes python 3.10 along with the following packages:pandas- Python software library for data manipulation.requests- Python library that makes HTTP requests simpler.Other technologies that were utilized within this project are listed here:Docker- Platform that offers virtual software packages within unique containers.Installation GuideClone the repository to your desired location, and confirm that python 3.7 or greater and the packages listed in the Technologies section are installed. The offline version is intended for educational and personal purposes.pipinstallmarketpandaGetting Startedcoming soon ...ContributorsFayssal El Mofatiche:fayssal.elmofatiche@dnbf.tech//LinkedInLicenseMIT LicenseCopyright (c) [2023] [Fayssal El Mofatiche]Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.