Saravanan666/pypi-org huggingface dataset:
Package: shodanpy-simeononsecurity
shodanpy_simeononsecurityA Series of Python Modules for Interacting with the Shodan APIAboutThis package provides a collection of Python modules designed to interact with the Shodan API. It simplifies the process of querying Shodan for various information, such as IP addresses, hostnames, ports, and more.InstallationYou can install this package usingpip:pipinstallshodanpy_simeononsecurityUsageOnce installed, you can import and use the modules in your Python scripts as needed. Here's an example of how to use one of the modules:fromshodanpy_simeononsecurityimportshodan_moduleresult=shodan_module.some_function()DocumentationFor detailed usage instructions, examples, and module-specific documentation, please refer to theGitHub repository.Issues and SupportIf you encounter any issues, have questions, or need support, please visit theissue trackeron GitHub.LicenseThis package is licensed under the MIT License. See theLICENSEfile for details.Explore the World of CybersecurityLinks:github.com/simeononsecuritysimeononsecurity.ch
Package: shodo
Shodo Python CLIInstallation$pip3installshodoConfigurationThese environment variables are requiredSHODO_API_ROOTRoot endpoint for API (likehttps://api.shodo.ink/@my-organization/my-project/).SHODO_API_TOKENToken to access each projects (Access to Shodo and see projects' 「API連携」 settings page)UsageLint Japanese.
This command requires authentication (API root and a token) for Lint API projects (not for writing).$shodolintfilename.md$shodolint./demo/demo.md15:18:2718:4ら抜き言葉ですてください。すぐに食べれる（→食べられる）。...3:11もしかしてAI飛行機の欠便があり、運行（→運航）状況が変わった。バ6:5もしかしてAIません。これが私で（→の）自己紹介です。こ12:11もしかしてAIなんでも問題を解決しい（→トル）ます。日本語ののよDownload filesDownload all of Markdown posts and images!$shododownload--target=docsOptions:Usage: shodo download [OPTIONS]

Options:
  --target TEXT      Target directory to save files
  --in-tree BOOLEAN  Download only files with task Folder
  --help             Show this message and exit.
Package: shoebot
Shoebot is a pure Python graphics robot: It takes a Python script as input,
which describes a drawing process, and outputs a graphic in a common open
standard format (SVG, PDF, PostScript, or PNG). It has a simple text editor
GUI, and scripts can describe their own GUIs for controlling variables
interactively. Being pure Python, it can also be used as a Python module,
a plugin for Python-scriptable tools such as Inkscape, and run from the
command line.
Package: shoebox
shoebox=======binary data archiving library - supports uploading to object storageJson payloads and string:string metadata dicts are stored in local-diskbinary files. The binary file format is versioned and tagged to allowfor easy extension.There are ArchiveReaders and ArchiveWriters which are managedby the RollManager. "Roll" comes from "roll over". It controls whenroll-over occurs from one Archive to the next. There is only oneArchiver active at a time per RollManager.The RollManager opens and closes Archivers asneeded. "As needed" is determined by which RollChecker that waspassed into the RollManager. Archive files can roll over basedon file size or elapsed time (for writing). For reading, archivefiles are only rolled over when the EOF is reached.Roll Managers also take care of filename creation, compressionof completed archives and transfer of archive files to remotestorage locations.The RollCheckers have a reference to the current Archive sothey can ask file-related questions (like "how big are you?")You can register callbacks with the RollManager for notificationson when new Archive files are opened or closed.Important Note! The Callback handlers and the RollCheckers takekwargs in the constructor since they can be dynamically loaded asplugins. So, make sure you provide named parameters to the constructors.Usage:# Make a roll checker of whatever strategy you choose.checker = roll_checker.SizeRollChecker(roll_size_mb=100)  # 100mb files# Make a roll manager for reading or writing.# Give the filename template and the checker.# (and an optional working directory for new files)# The %c in the template is per the python strptime method:# https://docs.python.org/2/library/datetime.html#strftime-strptime-behaviorx = roll_manager.WritingRollManager("test_%c.events", checker)# Write some metadata and payload ...## WritingRollManager.write(metadata, payload) where# metadata = string:string dict# payload = string of data. Most likely a json structure.# If the archive file grows beyond 100mb the old one# will automatically close and a new one created.for index in range(10):x.write({"index": str(index)}, "payload_%d" % index)x.close()For Reading:# Read from all the event data files using wildcards ...manager = roll_manager.ReadingRollManager("test_*.events")# This will keep reading across all files in the archive# until we reach the end.while True:try:metadata, json_payload = manager.read()except roll_manager.NoMoreFiles:breakLook at `test/integration/test_rolling.py` for a more complete example.
Package: shoedog
shoedog (WIP)A flexible, efficient plug-and-play query engine built on top of SQLAlchemy, inspired by GraphQL
This library is a work in progress!Setting upfrom shoedog import shoedoggify
from flask import Flask
from flask_sqlalchemy import SQLAlchemy

app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:////tmp/test.db'
db = SQLAlchemy(app)

shoedoggify(app, db)The above code will set up a/shoedogendpoint on your application that takes aPOSTrequest. The payload on thePOSTrequest is a shoedog payload, with the following syntax:query Company {
    name
    year_founded [(* > 1994 and * < 2017) or * == 2019]
    investors {
        name [any in ['gv', a16z']]
        amount_invested [all > 2000000]
    }
    contact_details (SingaporeContact) {
        address
        singapore_contact_number
    }
}The above query will return a json response containing all instances of Company where:The year founded is between 1994 and 2017, or is exactly 2019The investors have all invested over 2,000,000 dollarsThe investors include at least one investor with a name that is either 'gv' or 'a16z'Furthermore, the json response has a predictable structure, returning only the fields that were requested.{'companies': [{
    'name': 'XYZ Company',
    'year_founded': 1995,
    'investors': [{
        'name': 'gv',
        'amount_invested': 2000001 
    }],
    'contact_details': {
        'address': '123 Foobar Road',
        'singapore_contact_number': '+65 9635 9999'
    }
}, ...]}Notice thatThecontact_detailswas returned as a dictionary, since it is a different model.Thecontact_detailsfield was cast as aSingaporeContact, which allows us to query for thesingapore_contact_numberfield which is only on that particular subclass. This query would have failed without the cast!
Package: shogen
InstallationYou can install shogen by running:$ pip install --user shogenOn Linux the executable script can then be found in~/.local/binand on MacOS the script is under/Users/YOURUSERNAME/Library/Python/2.7/bin.UsageTypical usage is:$ shogen.py [options] genomefile metabolismfile catalysationfile queries

Options:
  -h, --help   show this help message and exit
  -k K, --k=K  Number of ranked  shortest genome segments (Default to 5)
  -l L, --l=L  maximum length of a genome segment (Default to 200)SamplesSample files for finding functional gene units in e. coli are available here:genome.txtmetabolism.txtcatalyze.txtqueries.txt
Package: shogen2
InstallationYou can install shogen2 by running:$ pip install shogen2UsageTypical usage is:$ shogen2.py [options] genomefile metabolismfile.sbml catalysationfile queries

Options:
  -h, --help   show this help message and exit
  -k K, --k=K  Number of ranked  shortest genome segments (Default to 5)
  -l L, --l=L  maximum length of a genome segment (Default to 200)SamplesSample files for finding functional gene units in e. coli are available here:genome.txtmetabolism.sbmlcatalyze.txtqueries.txt
Package: shoki
shoki (書記)shoki is a secretary in Japanese. This python program is here to help take a text-only file of meeting minutes and convert it into structured data. This structured data can then be converted into other formats.InstallpipinstallshokiUsageshokicreate--location[uri]whereuriis the location of the content served with aContent-Type: text/markdownorContent-Type: text/plainencoded as utf-8.Exampleshokicreate--locationhttps://webcompat-meet.herokuapp.com/0CMnUyYMSBaQJQ97Yxc8Ww/downloadHistoryIt was initially defined for addressing the needs ofMozilla webcompat team. It's strongly inspired by W3C meetings style. We aretaking minuteof our meetings on CodiMD. Once the meeting has been done. We generate the minutes with a mediawiki format that we add to thelist of our meetings.Example:Web Compatibility team minutes - September 11, 2018(raw source)ContributingIf you wish to contribute to this project, read thecontributing guidelines.Features - ToDoThe required features are:Parses meeting date and timeParses agenda items and agenda ownersParses agenda item descriptionParses action itemsStarts parsing after a dedicated stringStops parsing after a dedicated stringHandles the output in different formats (can be extended)Includes Mediawiki markup output formatHandles an URI for the text minutes inputHandles a file for the text minutes inputSome constraints:Avoid using regexTests Driven
Package: shongololo
ShongololoCO2 and Imet sensor ground atation snapThis is the README for the shongololos portion of the VTAgmonitoring applicationspython shongololo.py --settings=run_settingsInstall:Install for testing with web frontend$gitclone--recurse-submodulesgit@gitlab.com:r4space/VTAgMonitoring.git
$cdVTAgMonitoring/apps/sensor-logger
$virtualenv--python=python3.venv
$source.venv/bin/activate
$pipinstall-rrequirements.txt
$pythonserver.pyVisit localhost:5000 in a browser
ctrl-c to cancle server.py when doneInstall for deployment.. code-block::bash
sudo aptitude install python3-dev python3-pip virtualenv
virtualenv --python=python3 .venv
source .venv/bin/activate
pip install -r requirements.txt
pip install setuptools wheel twineFollow this gist for installin flask on ubuntuOperationAs a stand alone application:Follow install stepscd VTAgMonitoring/apps/python3 -m shongololo.shongololoData will output to screen and write to fileIn conjuntction with the python flask web interfaceAssFollow install stepsOn webpage:
a) Press "Setup Logger" and wait for log to indicated it has concluded testing sensors (it can take a few seconds)
b) When ready to log data for storage press "Start data capture" (This will also take a few seconds to start as it connects to all sensors"
c) When ready to stop capturing press "Stop Data Capture"
d) Repeat if you wish to sample data again
d) When ready to shutdown system press "Shutdown App"Maintenance for developers$python3-mpipinstall--user--upgradesetuptoolswheeltwine
$python3setup.pysdistbdist_wheel
$twineupload--repository-urlhttps://upload.pypi.org/legacy/dist/*DocsGenerate docs:$cddocs/
$makehtml
Package: shoobx.flowview
XPDL File viewer and browserCHANGES1.0.0 (2017-05-23)Move to public repository.Use community tools: tox, Travis CI, and Coveralls.ioAdd support for Python 3.5, 3.6, and PyPy.0.9.7 (2017-05-16)Make sure that CHANGES.rst and README.rst are included in release.0.9.6 (2017-01-23)Make sure flowview.css is also included.0.9.5 (2017-01-23)Make sure all files are included in source distro.
Package: shoobx.junitxml
IntroductionThis package provides azope.testrunnerfeature that stores the test
results in a JUnit-compatible XML file. This file can be consumed by
Jenkins and other tools to generate test reports.This is achieved by implementing a custom output formatter that
collects and then writes out the XML file. The formatter then
delegates further test result tracking to the oriignal output formatter.The core code of this package is based on the excellent work by Martin
Aspelli and the Plone Foundation. Thus the code is released under ZPL
2.1, the original license ofcollective.xmltestreport.UsageIn order to install your own features, you have to customize the mainRunnerclass a bit. Here is what we do at Shoobx:from shoobx.junitxml import feature
import zope.testrunner.runner

feature.JUnitXMLSupport.install_options()

class Runner(zope.testrunner.runner.Runner):

    def configure(self):
        super(Runner, self).configure()
        self.features.append(feature.JUnitXMLSupport(self))

zope.testrunner.runner.Runner = RunnerCall the test runner with the argument–xml=junit.xmlto specify the name
of the generated JUnit file.Code repositoryhttps://github.com/shoobx/shoobx.junitxmlChangelog0.2.2 (2021-01-13)Fixed documentation.0.2.1 (2020-12-03)Support for latest zope.testrunner and other latest dependenciesAdded missing stderr and stdout params to test_failure and test_error
methods of XMLOutputFormattingWrapper
(prevented xml report file generation in zope.testrunner >= 5.1)dropped support for python 2, updated support for 3.X0.2.0 (2018-10-10)Add support for Python 3.7Add support for the latestzope.testrunner, which switches fromoptparsetoargparse.0.1.4 (2018-03-30)Record doctest cases in modules where test cases are defined,
instead of putting them all in ‘doctest’ module.0.1.3 (2018-02-09)Bugfix: When test failure has binary data, record a Base64 representation of
the failure0.1.2 (2018-02-07)Python 3 bugfix0.1.1 (2017-10-03)Added some basic tests.Official Python 3.6 support.0.1.0 (2017-10-03)Initial release
Package: shooju-ts
shooju-tscontains loads/dumps functionality for sjts, a json-ish format for time series data designed for use withShoojuand compatible with loads() and dumps() commands based on the json package.  Currently, it is intended to be used only with the shooju package from pip to speed up retrieval of Shooju data.  We do plan on documenting the format to enable uses beyond Shooju.  The serializer is based onUltraJSON.InstallationInstall using pip:pip install shooju-tsBasic UsageMay be used as a drop in replacement for most other JSON parsers for Python:>>> import sjts
>>> sjts_string = sjts.dumps({'success':True,'series':[{'points':[(13242323324,2)]}]})
>>> print sjts.dumps(sjts_string)
{'success':True,'series':[{'points':[(1,2)]}Sourcehttps://bitbucket.org/shooju/sjts(restricted access for now)Changelist0.1Initial public release not intended for standalone use without the shooju package.DevelopmentTo compile for windows set environment variable (for VS2015):$ SET VS90COMNTOOLS=%VS140COMNTOOLS%
Package: shooker
ShookerTool for C-code injections in already compiled bins.UsageWrite hook config as described in theinstruction.shooker --xml config.xml target_dir/ output_dir/Installpip install shookerPlease read aboutcommon errorsTestsFollow the instruction to check the functionalitygitclonehttps://github.com/ReKreker/shookercdshooker/tests
cmake-S.-Bbuildpushdbuild
make
maketestpopdTo improveAdd ability to inject to .exe/.dllTry to avoid sub-instruction patching mechanism in the hook(s)Add support of arm architectureAdd support hooking raw binariesDevelop true hook(not replace)Plug in IDA/Ghidra
Package: shoonya
shoonyaUnofficial Trading APIs for Finvasia Shoonya Web Platform.Finvasiaoffers Zero Brokerage trading and is doing good recently with it's new Shoonya platform.Please checkshoonyaweb platform.Open account withFinvasiaWORK IS STILL IN PROGRESSUSE AT YOUR OWN RISKInstallationPython version>3.9is needed for this module to workGit is required for below command to workpip install git+https://gitlab.com/algo2t/shoonya.gitAlternate wayDownload the.whlfile from releases sectionUsing pip to install =>python -m pip install shoonya-0.1.0-py3-none-any.whlHow to setup a good environmentInstall latest Python version 3.9.x, download it fromhereLinux comes with python upgrade it to latest version 3.9.xUsescoopfor Windows as package manager.Use your favorite editor likeVSCodiumorVSCodedownload it fromhereVScode is available for Windows, Linux and MacPython extension for vscode ishereMagicPython is also good extensionWonderful documentation for working with python and vscode ishereUse virtualenv to create a virtual python env so that your system is not affectedSteps for virtualenv creation -python -m pip install virtualenvand then virtualenv venvActivate thevenv=>.\venv\Scripts\activate(this is an example for Windows OS)Install and upgrade modules(venv) PS D:\trading\algo2trade\shoonya> python -m pip install -U pip wheel setuptools pylint rope autopep8Usage# Check config.py example FIRSTfromconfigimportusername,password,pannofromshoonyaimportShoonyaaccess_params=Shoonya.login_and_get_authorizations(username=username,password=password,panno=panno)print(access_params)withopen('params.json','w')aswrl:json.dump(access_params,wrl)config.pyexampleusername='FA12345'password='FinvAsia@P123'panno='ABCDE1234Z'Usage existingparams.jsonimportjsonfromconfigimportusername,password,pannofromshoonyaimportShoonya,TransactionType,ProductType,OrderType,InstrumentType# NOTE: The params.json is created using the above login exampleACCESS_FILE=f'params.json'withopen(ACCESS_FILE,"r")asaccess:credentials=json.load(access)access_token=credentials["access_token"]key=credentials['key']token=credentials["token_id"]username=credentials['user_id']usercode=credentials["usercode"]usertype=credentials["usertype"]panno=credentials['panno']shn=Shoonya(username,access_token,panno,key,token,usercode,usertype,master_contracts_to_download=['NSE','NFO'])bal=shn.get_limits()print(bal)df=pd.DataFrame(bal,index=None)df['MTM']=df['REALISED_PROFITS']+df['MTM_COMBINED']print(df[['MTM','REALISED_PROFITS','AMOUNT_UTILIZED','CLEAR_BALANCE','AVAILABLE_BALANCE','MTM_COMBINED']])scrip=shn.get_instrument_by_symbol('NSE','SBIN')print(scrip)Check complete example in examples folderHereusing_existing_access_tokens.pyis present for help
Package: shootout-opt
SHOOTOUT toolboxWhy I wrote this packageComparing numerical optimization algorithms is always a pain for me. Things I hate to do:writing lots of loops for testing various hyperparameters.writing the code to store the results, painfully changing details all the time.comparing algorithms in a fair manner though lengthy plotting scripts.comming back to old codes for review updates a year after the simulations, and finding I did not store all the hyperpameters by mistake.looking up plotly syntax when updating plots, every single time.reading papers that compare algorithms in one run/one set of parameters.Plus I am a very chaotic person, changing workflow every single paper. So I needed some tools to balance this entropy and make my life easier.What this doesUsing a decorator function @run_and_track(), one may run a script many times with user-defined hyperparameters grid; store all the results in clearly formatted pandas dataframe usable by plotly express.provide a few helpful functions for processing this dataframe, to produce interesting comparison plots (convergence plots, who is fastest at given threshold plots)InstallationThe package can be pip installed usingpipinstallshootout-optor by cloning the repo and runningpipinstall-e.with root in the root folder of this package.TODOSTODO: auto-tests on push on githubTODO: sphynx doc, onlineTODO: pipelinesTODO: examplesFeedbackI wrote this for myself, but if you have some ideas for improvements or new features, feel free to drop an issue or a pull request.
Package: shopant-sdk
ShopAnt SDK for PythonInstallpip install shopant-sdkServer IntegrationfromflaskimportFlask,request,jsonifyfromshopan_sdkimportShopAntServerserver=ShopAntServer(PRODUCT_ID,PRODUCT_SECRET)app=Flask(__name__)@app.route('/api/v1/shopant/integration',methods=['POST'])defshopant_integration():returnjsonify(server.inetgration(request.json()))
Package: shopcloud-datalake
Datalake CLIThis project develops a of Command Line Interface (CLI) tool designed to facilitate the migration of data from Sage ERP systems into a structured datalake and data-warehouse architecture on Google Cloud. Aimed at enhancing data management and analytics capabilities, these tools support project-specific datalake environments identified by unique tags.Getting StartedConfiguration Creation:Install the toolpip3installshopcloud-datalakeSet up your configuration directory:mkdirconfig-dirCreate a new Datalake configuration:datalake--project="your-google-cloud-project-id"--base-dir="config-dir"configcreateConfiguration Synchronization:Sync your configuration files to the project bucket:datalake--project="your-google-cloud-project-id"--base-dir="config-dir"configsyncData Migration Execution:Run the data migration process with or without specifying a table:datalake--project="your-google-cloud-project-id"--base-dir="config-dir"run--partition-date=YYYY-MM-DD
datalake--project="your-google-cloud-project-id"--base-dir="config-dir"run<table>--partition-date=YYYY-MM-DDArchitekturflowchart LR
    subgraph Data-Lake
    Sage[(Sage)] --> datalake-cli
    GCS_SCHEMA[(Storage)] --> |gs://shopcloud-datalake-sage-schema| datalake-cli
    datalake-cli --> |gs://shopcloud-datalake-sage-data| GCS_DATA[(Storage)]
    end
    subgraph Data-Warehouse
    GCS_DATA[(Storage)] --> SCDS[(BigQuery)]
    endFAQsWhere are the configurations stored?Configurations are stored in a Google Cloud Storage bucket associated with each project.What is the structure of the Datalake?Each project has a dedicated Google Cloud Project for data storage.What file format is used?Data is stored in Parquet format for efficiency and performance.
How is data partitioned? Data is partitioned using BigQuery's TimePartitioning feature.Development# run unit tests$python3-munittest# run unit tests with coverage$python3-mcoveragerun--source=tests,shopcloud_datalake-munittestdiscover&&python3-mcoveragehtml-dcoverage_report
$python3-mcoveragerun--source=tests,shopcloud_datalake-munittestdiscover&&python3-mcoveragexml
Package: shopcloud-django-authenticator
Shopcloud-Django-AuthenticatorSingle Sign In from ShopcloudQuickstartpip3 istall shopcloud-django-authenticatorAdd "authenticator" to your INSTALLED_APPS setting like this::INSTALLED_APPS=[...'authenticator',]AUTHENTICATOR_KEY=os.environ.get('AUTHENTICATOR_KEY','DEV-KEY')To generate a key usepwgen -s $1 64Include the polls URLconf in your project urls.py like this::path('authenticator/', include('authenticator.urls')),Runpython manage.py migrateto create the polls models.Install custom Tags for Login Button{% load tower_tags %}
{% tower_login request 'QYG69GK' %}Release$rm-rfbuilddist
$pip3installwheeltwine
$python3setup.pysdistbdist_wheel
$twineuploaddist/*