Saravanan666/pypi-org huggingface dataset:
Package: ghedt
Ground Heat Exchanger Design ToolA package with the novel capability of automatically selecting ground heat
exchanger configurations based on polygonal land constraints. This package
contains advanced methods that are the first of their kind. The results are
validated against the world renownedGLHEPRO(Cook 2021).The Ground Heat Exchanger Design Tool (DT) is a Python package that can
quantify the short- and long-term thermal interaction in a ground heat exchanger
(GHE). The long-term thermal response g-functions are computed live-time withpygfunction. The DT contains a fast monthly hybrid time step
simulation for prediction of heat pump entering fluid temperatures over a design
life. The DT can vary the size (or borehole height) of a specified borehole field
to ensure the heat pump entering fluid temperature remains within specified
bounds. DT contains a novel borehole configuration selection algorithm.Novel Design AlgorithmsDT contains a novel design methodology for automated selection of borehole
fields. The advanced methodology performs optimization based on a target
drilling depth. An integer bisection routine is utilized to quickly search
over a unimodal domain of boreholes. DT can consider available drilling and
no-drilling zones defined as polygons.The selection process shown below is performed in less than half a minute on an
11th Gen Intel Core i9-11900K @ 3.50GHz. Refer toCook (2021)for more
information.Requirementsghedtrequires at least Python 3.7 and is tested with Python 3.7 and 3.8, and is dependent on the following packages:pygfunction (>=2.1)numpy (>=1.19.2)scipy (>=1.6.2)matplotlib (>=3.3.4)coolprop (>=6.4.1)pandas (>=1.3.2)openpyxl (>=3.0.8)opencv-python (==4.5.4.58)Quick StartUsers- Installghedtvia the package installer for Python (pip):pip install ghedtDevelopers- Clone the repository to via git:git clone https://github.com/j-c-cook/ghedtSeeinstallationfor more notes on installing. Seeghedt/examples/for usage.Citing the Design ToolThe Ground Heat Exchanger Design Tool and other related work is described in the following thesis:Cook, J.C. (2021). Development of Computer Programs for Fast Computation of 
    g-Functions and Automated Ground Heat Exchanger Design. Master's Thesis, 
    Oklahoma State University, Stillwater, OK.Here is an example of a BibTeX entry:@mastersthesis{Cook_2021,
school = "{Oklahoma State University, Stillwater, OK}",
author = {Cook, J C.},
language = {eng},
title = "{Development of Computer Programs for Fast Computation of g-Functions 
and Automated Ground Heat Exchanger Design}",
year = {2021},
}Questions?If there are any questions, comments or concerns pleasecreatean
issue, comment on anopenissue, comment on aclosedissue,
orstartadiscussion.AcknowledgementsThe initial release of this work (ghedt-v0.1) was financially supported by the U.S. Department of Energy contract DE‐AC05‐00OR22725 through research subcontracts from Oak Ridge National Laboratory. Dr. Jeffrey D. Spitler was integral to the successful development, mostly through advice and feedback.
Package: ghee
Ghee echoes to Google Hangouts Chat easlyHow to installSimply:pip install gheeHow to useYou should now have a command line application:ghee https://chat.googleapis.com/v1/... The message you want to send!It's extremely dumb. First argument is the Google Chat room webhook URL. Everything that follows is the message (*bold*and_italics_work).For the information about the api go to:https://developers.google.com/hangouts/chat/how-tos/webhooksCreate PyPI packageImportant:following assumes that you are using virtualenv.Install build tools:$ pip install --upgrade pip setuptools wheelBuild package:$ python setup.py sdist bdist_wheel
# [output edited out]
$ ls -l dist 
total 8
-rw-rw-r-- 1 michal_chalupczak michal_chalupczak 3032 paź  7 16:22 ghee-0.0.1-py3-none-any.whl
-rw-rw-r-- 1 michal_chalupczak michal_chalupczak 1602 paź  7 16:22 ghee-0.0.1.tar.gzUpload the package to the PyPI!Important:following assumes that you are using virtualenv.Install upload tools:$ pip install --upgrade twineFirst register at the test repo:https://test.pypi.org/account/register/and upload:$ twine upload --repository-url https://test.pypi.org/legacy/ dist/*And check if that worked:$ pip install --index-url https://test.pypi.org/simple/ --no-deps gheeIf that worked repeat with the realhttps://pypi.org/.
Package: ghenv
GitHub Env (GHENV)Copy your .env into GitHub Secrets within secondsFlow:Checks if a .env exists at your current workdir, errors out if it doesn't.Loads all the environment variables from the .env file.Asks for the name of the repository you'd like to use.Creates KV pairs of the environment variables and their values on GitHub secrets on your chosen repo.Optional environment variables:GH_TOKEN- GitHub token to use for authentication. If not provided, it will ask for a token.GH_REPO- GitHub repository to use. If not provided, it will ask for a repository.
Package: gherkindb
gherkindb--------gherkindb is lightweight, fast, and simple database based on pickledb```````````````::import gherkindbdb = gherkindb.load('test1.db', True)db.set('key', 'value')# Outputs: valueprint(db.get('key'))# Added serialization functionalitydef my_func():print("Much better!")db.sset('func', my_func)# Outputs: Much better!db.sget('func')()# Also :# Outputs: Much better!reborn = db.sget('func')reborn()And Easy to Install```````````````````::$ pip3 install gherkindb
Package: gherkin-translator
Gherkin translatorТранслятор ключевых слов пользовательского сценария, написанного наgherkin, из русского языка в английскийСкрипт переводит ключевые слова gherkin с русского на английский для удобства переноса тест-кейсов в TMS Zephyr.До:@positiveСтруктура сценария:Успешная авторизация по логину и паролюДано есть логин и пароль пользователя, который предварительно зарегистрирован в ЕЛК| name     | value      || email    | <email>    || phone    | <phone>    || password | <password> |Когда вызываем метод авторизации по логину и паролюТогда получаем ответ с кодом статуса "200"Иполучаем тело ответа в формате jsonИв теле ответа есть токен авторизацииПримеры:|email|phone|password||odeto@rover.info|null|Test123456||null|+79999999123|Test123456||ukkosu@rover.info|+79999999567|Test123456|После:@positiveScenario:Успешная авторизация по логину и паролюGivenесть логин и пароль пользователя, который предварительно зарегистрирован в ЕЛК|name|value||email|<email>||phone|<phone>||password|<password>|Whenвызываем метод авторизации по логину и паролюThenполучаем ответ с кодом статуса "200"Andполучаем тело ответа в формате jsonAndв теле ответа есть токен авторизацииExamples:|email|phone|password||odeto@rover.info|null|Test123456||null|+79999999123|Test123456||ukkosu@rover.info|+79999999567|Test123456|ЗависимостиДля реализации CLI интерфейса используетсяtyperУстановка модуляpipinstallgherkin-translatorИспользованиеpython-mgherkin_translatorpath/to/test.featureМожно также указывать путь до директории. В таком случае скрипт будет искать все файлы фич, заканчивающиеся на.featureи будет пытаться перевести их.
Package: gherlint
gherlintLinter for Gherkin feature files, written in PythonInstallSimply runpip install gherlint.Linting Feature Filesgherlintcomes with a command line interface.
To recursively lint all feature files in a directory, rungherlint lint.Computing Metricsgherlintcan also create some metrics for you if you want to know how many features, scenarios and steps you have
in your test suite. To do so, rungherlint stats.Disclaimergherlintis still in an early development phase. New checks will be added over time.
If you want to contribute, feel free to open issues suggesting useful checkers, or open a pull request if you want
to!RoadmapThe following work items are planned for the upcoming releases:V0.0.x - V0.1.0:Parser and object model for feature filesBasic checkers to demonstrate workflowBasic text based reporterV0.1.x - V1.0:<-- we are hereAdd more checkersAdd more output formatsExtend object model as necessary for checkersReach a stable interface for object model, checkers and reportersV1.x - V2.0:Support configuration to enable/disable individual messagesImplement plugin architecture to allow users to add custom checkersCHANGELOGV0.4.0New checks:unused-parameterempty-backgroundoutline-could-be-a-scenarioconsider-using-backgroundexamples-outside-scenario-outlineduplicated-tagOther changes:unparseable-fileis now issued for all nodes that offend thegherkinparser together with more error information provided by itmissing-parameternow clearly states what parameter is not defined in the examplesIfgherlintpatches the file contents with a forgotten# languagetag the line numbers for messages
are no longer shiftedTypes ofAndandButsteps are now inferred correctlyNew commandfix-language-tagsto automatically add or fix missing or incorrect language tagsRename some message codes to have a defined structure: each checker has its own hundreds digit.V0.3.0New checks:missing-language-tagwrong-language-tagunparseable-fileOther changes:gherlintcan now automatically detect the language used and make sure that it can parse the files
even without a# languagetoken present.V0.2.0New checks:missing-given-stepmissing-when-stepmissing-then-stepempty-scenarioempty-featurefile-has-no-featuremissing-parameterOther changes:Support forBackgroundDetermination of step type independent of languageDistinction betweenScenarioandScenario Outlineindependent of languageV0.1.0First package in alpha status:Parser and object model for feature filesBasic checkers to demonstrate workflowBasic text based reporter
Package: ghetto
ghetto======A tool for (automatized) torrent files downloading from RSS feeds to usewith torrent clients which don't have built-in RSS functionality.Requirements------------Python 2.7 with `pip` package manager.Tested under MacOS X and Debian Linux.Installation------------pip install ghettoorgit clone https://github.com/infinite-library/ghetto.git ghettocd ghettopython setup.py installUsage-----All available options can be shown using ``ghetto`` command without anyparameters. After creation of a new configuration it is automatically added tocrontab of the current user to fetch feed time to time.Only those torrent files which titles are passing filters and aren't passingblacklist are downloaded. Comments started from ``#`` character and empty linesallowed.Example of filters list:```# Some ongoings by HorribleSubsHorribleSubs*Heavy*Object*720pHorribleSubs*Ushio*Tora*720p# All Doki BD releasesDoki*x1080*BD```Example of blacklist:```# E.g. we hate .mp4 containers*.mp4```License-------MIT
Package: ghettobird
ghettobirdA Python framework/tool designed for web scraping.
(This readme and the tool itself are still under construction.)InstallationUse the package managerpipto install foobar.pipinstallghettobirdGoalsThe primary goal of this project is to simplify scraping applications into a single dictionary/JSON object (with a few auxilary functions sprinkled in).This allows us to:Reduce boilerplate codeIncrease code readabilityGroup fragile pieces of code for easy maintenanceReduce inconsistancies in error handlingUsageUsage examples feature thiswebsite. It is a static HTML page, but a JS-heavy sample will be added soon.fromghettobirdimportflyExample One: Grabbing a single elementIf we wanted to grab a page header from our sample page and we expect only one element to be returned, we could use the following "flightpath":itinerary={"url":"http://ghettobird.sample.s3-website.us-east-2.amazonaws.com","flightpath":{"header":"//*[@class='page-header']",},}We would be returned with dictionary that follows the blueprint we laid out, but with the data being populated with:{'header':'Jobs in St. Louis, Missouri'}Example Two: Grabbing a listIf we wanted to grab every single job title from our sample page, the following flightpath would be appropriate. Notice the brackets that surround our xpath. This allows us to return multiple values from elements.itinerary={"url":"http://ghettobird.sample.s3-website.us-east-2.amazonaws.com","flightpath":{"titles":["//h4[@class='title']"],},}The result:{'titles':['Senior Software Dev','Agile Coach','Software Engineer','Junior Software Dev','Ping Pong Player']}Example Three: Transformer functionsBy default, elements that are found with a given xpath have their text values returned unless specified otherwise. However, if we need to perform some sort of transformation on the element or get an HREF rather than text, "transformer" functions will be necessary.fromghettobirdimportfly,transformer
Package: ghettoq
Version:0.4.5Introductionghettoq is a ghetto queue framework, used to implement Redis, MongoDB,
Beanstalk, CouchDB, and Django database support forcarrotInstallationYou can installghettoqeither via the Python Package Index (PyPI)
or from source.To install usingpip,:$ pip install ghettoqTo install usingeasy_install,:$ easy_install ghettoqIf you have downloaded a source tarball you can install it
by doing the following,:$ python setup.py build
# python setup.py install # as rootExamples>>> from ghettoq.simple import Connection
>>> import simplejson>>> conn = Connection("redis", host="localhost", database=1)>>> # Publishing messages
>>> q = conn.Queue("tasks")
>>> payload = {"name": "George Constanza"}
>>> q.put(simplejson.dumps(payload))>>> # Consuming messages
>>> message = q.get()
>>> simplejson.loads(message)
{"name": "George Constanza"}# Empty raises ghettoq.messaging.Empty
>>> q.get()
EmptyUsing Django database supportIf settings is already configured you don’t have to specify any
connection options.>>> from ghettoq.simple import Connection>>> conn = Connection("database")
>>> queue = conn.Queue(name="tasks")
>>> queue.put("To whom it may concern")
>>> queue.get()
"To whom it may concern"Using MongoDB supportIf settings is already configured you don’t have to specify any
connection options. The settings attrs used are:BROKER_HOST: ‘127.0.0.1’ if not setBROKER_PORT: 27017 if not setBROKER_VHOST (Database Name): ‘ghettoq’ if not setCollection name: “messages”… should be added support for BROKER_COL settings var?>>> from ghettoq.simple import Connection>>> conn = Connection("mongodb")
>>> queue = conn.Queue(name="tasks")
>>> queue.put("To whom it may concern")
>>> queue.get()
"To whom it may concern"Using Beanstalk supportRequires the beanstalkc python library. If settings is already configured you
don’t have to specify any connection options. The settings attrs used are:BROKER_HOST: ‘localhost’ if not setBROKER_PORT: 11300 if not setBROKER_VHOST: ‘ghettoq’ if not set>>> from ghettoq.simple import Connection>>> conn = Connection("beanstalk")
>>> queue = conn.Queue(name="tasks")
>>> queue.put("To whom it may concern")
>>> queue.get()
"To whom it may concern"Beanstalk also supports priorities. Jobs with lower priory numbers are
executed before jobs with higher numbers. This number defaults to 0
and ranges from 0 to 2**32 - 1.>>> queue.put("spam", priority=3)
>>> queue.get()
"spam"Using CouchDB supportIf settings is already configured you don’t have to specify any
connection options. The settings attrs used are:BROKER_HOST: ‘127.0.0.1’ if not setBROKER_PORT: 5984 if not setBROKER_VHOST (Database Name): ‘ghettoq’ if not setView name: “ghettoq/messages”>>> from ghettoq.simple import Connection>>> conn = Connection("couchdb")
>>> queue = conn.Queue(name="tasks")
>>> queue.put("To whom it may concern")
>>> queue.get()
"To whom it may concern"The couchdb backend requires the couchdb python module.LicenseThis software is licensed under theNew BSD License. See theLICENSEfile in the top distribution directory for the full license text.
Package: ghevaluator
Galaxy History EvaluatorGalaxy History Evaluator orghevaluatoris a command-line Python tool to compare Galaxy histories to a template workflow and generate a JSON and HTML report files.ContextGalaxyis anopen, web-based platform for data-intensive computational research.When running their data analysis, Galaxy users create histories storing their data, but also the steps of the data analysis, i.e. the tools used, their versions and parameters.Galaxy is also used for training where participants follow step-by-step tutorials, stored in Galaxy histories. At the end, participants might want to know if they followed correctly the tutorial and instructors might need to evaluate histories to give feedback and deliver certificates.Evaluating histories manually can be painful and error prone.Galaxy History Evaluator aims to solve this by providing a command-line tool to compare a Galaxy history to a templare workflow and generate a report in JSON and HTML with difference between the provided history and the expected workflow.UsageGalaxy History Evaluator can be used via command-line$ghevaluator--help
usage:ghevaluator[-h]-uHISTORY_URL-wWORKFLOW_URL-aAPIKEY[-oOUTPUT]CompareaGalaxyhistorytoatemplateworkflowandgeneratetheJSONandHTMLreportfiles

options:-h,--helpshowthishelpmessageandexit-uHISTORY_URL,--history_urlHISTORY_URLURLtoGalaxyhistory-wWORKFLOW_URL,--workflow_urlWORKFLOW_URLURLtotemplateworkflow-aAPIKEY,--apikeyAPIKEYGalaxyAPIkey-oOUTPUT,--outputOUTPUTPathtooutputdirectoryInstallationGalaxy History Evaluator can be installed with pip:$pipinstallghevaluatorTestsExport the Galaxy API key as environment variable$exportGALAXY_API_KEY=<REPLACE_WITH_GALAXY_API_KEY>Run the unit tests$maketestDocumentationDocumentation could be found athttps://streetscience.community/ghevaluator/To update it:Make the changes insrc/docsGenerate the doc with$makehtml
Package: ghexplorer
Github-Agent (GHAgent)TODOCreate a LICENSEUsageTo install:pip install ghagentTo initialize:gha initTo config time window:gha config timewindowTo config GitHub API Token:gha config tokenTo run:gha run <repo-name>

# e.g. gha run litanlitudan/skyagiDevelopment SetupInstallpipxInstallpoetryInstall dependenciescd ghagent
poetry installRun# poetry run gha <supported commands, e.g. init, config, run...>

# config
poetry run gha config ...

# run
poetry run gha run litanlitudan/skyagi

# build
poetry build

# publish to PyPI
poetry publish
Package: gh-folder-download
GitHub Folder DownloaderA command line application (CLI) to download only a specific folder without downloading the full repository implemented with Python using Typer and GitHub API.Usage:gh-folder-download[OPTIONS]Options:--urlTEXTRepositoryURL[required]--outputDIRECTORYOutputfolder[default:.]--tokenTEXTGitHubtoken--force/--no-forceRemoveexistingoutputfolderifitexists[default:no-force]--install-completion[bash|zsh|fish|powershell|pwsh]Installcompletionforthespecifiedshell.--show-completion[bash|zsh|fish|powershell|pwsh]Showcompletionforthespecifiedshell,tocopyitorcustomizetheinstallation.--helpShowthismessageandexit.
Package: gh-frames-depot
OverviewTheFramesDepotclass is designed to store and manage video frames
in shared memory, allowing for controlled access and efficient frame
management in asynchronous environments. It’s particularly useful in
scenarios where frames need to be shared between different processes or
handled at different rates.FeaturesFixed-size Queue: Holds a specified maximum number of frames.Shared Memory: Utilizes shared memory for efficient inter-process
communication.Backpressure Management: Provides a callback mechanism to handle
situations where the frame queue is full.Asynchronous Support: Designed to work in an asynchronous
environment, ensuring safe and efficient operations.UsageInitializationframe_size=(width,height,channels)# Dimensions of the framesmemory_name="frame_depot"# Name for the shared memory blockmax_size=10# Maximum number of frames in the queueframes_depot=FramesDepot(frame_size,memory_name,max_size)Adding Frames# Assume frame is a NumPy array representing a video frame and current_frame is an integer frame numberframe_dict={"frame_number":current_frame,"frame":frame}awaitframes_depot.enqueue(frame_dict)Retrieving Framesframe_number=5# The specific frame number you want to retrieveframes_depot.get_frame(frame_number)Handling Full QueueImplement a backpressure_callback function that will be called when the
queue is full.defbackpressure_callback():print("The queue is full. Consider slowing down frame production or handling the surplus.")frames_depot=FramesDepot(frame_size,memory_name,max_size,backpressure_callback)Clearing the Queueawaitframes_depot.clear_queue()Closing and Releasing Resourcesawaitframes_depot.close()Methods__init__(frame_size, memory_name, max_size, backpressure_callback):
Initializes the FramesDepot.enqueue(frame_dict): Asynchronously adds a frame to the queue and
shared memory.get_frame(frame_number): Retrieves a specific frame by number.clear_queue(): Asynchronously clears the frame queue and index.close(): Asynchronously closes and releases all resources,
including shared memory.Propertiesqueue_is_full: Indicates whether the queue is full.RequirementsPython 3.7+NumPyasyncioNoteEnsure proper synchronization and error handling in your production
environment, especially when dealing with shared resources and
asynchronous operations.
Package: ghga-event-schemas
GHGA Event SchemasA package that collects schemas used for events published from and subscribed by GHGA service.Quick StartInstallationThis package is available at PyPI:https://pypi.org/project/ghga-event-schemasYou can install it from there using:pip install ghga-event-schemasThereby, you may specify following extra(s):dev: dependencies needed for development and testingDevelopmentFor setting up the development environment, we rely on thedevcontainer featureof vscode
in combination with Docker Compose.To use it, you have to have Docker Compose as well as vscode with its "Remote - Containers" extension (ms-vscode-remote.remote-containers) installed.
Then open this repository in vscode and run the commandRemote-Containers: Reopen in Containerfrom the vscode "Command Palette".This will give you a full-fledged, pre-configured development environment including:infrastructural dependencies (databases, etc.)all relevant vscode extensions pre-installedpre-configured linting and auto-formatinga pre-configured debuggerautomatic license-header insertionMoreover, inside the devcontainer, there if following convenience commands available
(please type it in the integrated terminal of vscode):dev_install- installs the package with all development dependencies and installs pre-commit
(please run that if you are starting the devcontainer for the first time
or if you added any python dependencies to the./pyproject.toml)If you prefer not to use vscode, you could get a similar setup (without the editor specific features)
by running the following commands:# Execute in the repo's root dir:cd./.devcontainer# build and run the environment with docker-composedocker-composeup# attach to the main container:# (you can open multiple shell sessions like this)dockerexec-itdevcontainer_app_1/bin/bashLicenseThis repository is free to use and modify according to theApache 2.0 License.