Saravanan666/pypi-org huggingface dataset:
Package: gada-pyrunner
gada-pyrunnerPython runner forgada.InstallUsing pip:$pip3installgada-pyrunnerDocumentationBuild the doc with:$makehtmlYou can find the latest documentation ongada-pyrunner.readthedocs.io.Basic exampleCreate a Python package with the following structure and add it to yourPYTHONPATH:├──mycomponent
│├──__init__.py
│├──mynode.py
│└──config.ymlContent ofmynode.py:defmain():print("hello world")if__name__=="__main__":main()Content ofconfig.yml:nodes:mynode:runner:pythonfile:${comp_dir}/mynode.pyUsage:$gadamycomponent.mynode
helloworldTestingThetestdirectory contains many tests that you can run with:$tox.LicenseLicensed under theMITLicense.
Package: gadd
gaddVery opinionated formatting python files after git addIntentI needed a small tool to reformat and lint all the staged.pyfiles according to the specific rules. I wanted it to be able topipinstall it and available in thePATH. Also, I wanted to clearly see what changes are made by the formatter and be able to reverse it. It is calledgaddbecause you run it aftergit addcommand.
It will do:Remove unused importsSort importsReformat withBlackRunflake8andpylintlintersSearch for deadcode withvultureObeys.flake8,.pylintrcandwhitelist.pyconfig files in the current directory.It meant be be executed in the root of the project.Usageinstallpipx:python3-mpipinstall--userpipx
python3-mpipxensurepathInstallgaddwithpipx:pipxinstallgaddStage file to test:gitaddsome_file.py
gaddPublish topipwithpoetryMake it pip installable with CLI command.Make and publishpippackage withpoetry:Installpoetry. I would highly recommend to install it withpipxcd gadd
pipx install poetry
poetry initModifypyproject.tomlfile:[tool.poetry]name="gadd"version="0.1.0"description="Sort imports, remove unused imports, run Black, flake8, pylint, vulture in one go for al staged .py files"authors=["Almaz Kunpeissov <hello@akun.dev>"]keywords=["Black","Sort imports","analysis","automation","autopep8","code","flake8","formatter","gofmt","lint","linter","pyfmt","pylint","python","remove unused imports","rustfmt","static","vulture","yapf"]readme="README.md"license="MIT"homepage="https://github.com/almazkun/gadd"repository="https://github.com/almazkun/gadd"documentation="https://github.com/almazkun/gadd"include=["LICENSE",]classifiers=["Topic :: Software Development :: Libraries :: Python Modules","Topic :: Software Development :: Quality Assurance","Topic :: Software Development :: Debuggers",][tool.poetry.dependencies]python="^3.6"autoflake="^1.4"black="^21"flake8="^4.0"gitpython="^3.1"isort="^5.10"pylint="^2.11"vulture="^2.3"[tool.poetry.dev-dependencies][tool.poetry.scripts]gadd='gadd:main'[build-system]requires=["poetry-core>=1.0.0"]build-backend="poetry.core.masonry.api"Poetry build wheels:poetrybuildPoetry publish:poetrypublishTODOload from.conffile for vulturemake itasyncremove python warnings (PYLINTHOME is now '.cache/pylint' but obsolescent '.pylint.d' is found; you can safely remove the latter)Fixisorts output
Package: gadgetfinder
GadgetFinderA tool with interactive shell for finding gadgets in executable files.
Support ELF and PE file format, multiple architectures and modes: x86, ARM, 32bit, 64 bit.
Can also assemble and disassemble instructions.RequirementscapstonekeystonepyelftoolspefileGetting startedcreate a virtualenv:virtualenvenvsourceenv/bin/activate# activate the Python virtualenvInstall development dependencies:pipinstall-rrequirements.txtRun the interactive shell:cdsrc/gadgetfinder
python3shell.pyExamplesIn the interactive shell, run:asminceax;addeax,ecx--archx86--mode64disas['0xff','0xc0','0x1','0xc8']--mode64asmpopebp;ret
disas['0x5d','0xc3']load../../data/prog.fileinfo
dumpsearchpopebpBuild your own packageYou can edit configuration in setup.config.To build:python3-mpipinstall--upgradepip
python3-mpipinstall--upgradebuild
python3-mbuildPackage usageInstallation$ pip install gadgetfinder==0.0.1Usage
Package: gadgethiServerUtils
gadgethiServerUtilsThis is the utility helper functions that can support the gadgethi server development.New in 0.3.0GadgethiServer.pyRemove test keyword argument. Testing uses another structure so this parameter is not needed anymore.NEED IMMEDIATE ACTIONtable_list now only accept full name and does not assume "_table" suffix.NEED IMMEDIATE ACTIONcredential_path now needs to be provided to the server instance.authentication.pyNEED IMMEDIATE ACTIONClass Renamed to GadgethiHMAC256Verification, GadgethiHMAC256Encryption. Doday Util client needs to refer to the new clients. (However, we recommend to use GadgethiClient instead of DodayHttpClient)GadgethiClient.pyNEED IMMEDIATE ACTIONFor future HTTP client. Refer to the spec of this new file.
Package: gadgetpie
GadgetA wide variety of tools in the software development.1 Gadget Abstract List1.1 dict2classConvert a parameter from "dict" type to simple User-defined class type.Such as:# Import required packagesfromgadgetimportDict2Classimportdatetime# Defines a dictionarytest_dict={'now':datetime.datetime.now(),'num':77,'txt':'Hello!','dct':{'t_num':667,'t_txt':'hello!'},'lst':[1,2,3,'abc'],'set':{1,3,3,4,'abc'},'tpl':(1,2,3,5,'abc')}# Converts to user-defined class hereud_class=Dict2Class().convert(test_dict)
Package: gadget-python
gadget-pythonPython utilities for emitting and processing Gadget log entriesFree software: MIT licenseDocumentation:https://gadget-python.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2016-08-16)First release on PyPI.
Package: gadgetron-dataflow-monitor
A Gadgetron Dataflow MonitorA Gadgetron debugger tools by Python with QT plus matplotlib, with love by Cong Zhang你好Quick StartServer side## --begin-- step just need when developing in loop, no need for end user after installcdsrc## --end-- step just need when developing in loop, no need for end user after installgadgetron1. Tester side(gadget start by gadgetron)## --begin-- step just need when developing in loop, no need for end user after installcdsrc## --end-- step just need when developing in loop, no need for end user after installgadgetron_ismrmrd_client-fgadm/test_datas/testdata.h5-Cgadm/use_in_gadgetron_sample/python_monitor_start_automate.xml2. Tester side(gadget start by hand)## --begin-- step just need when developing in loop, no need for end user after installcdsrcexportPYTHONPATH=$PWD## --end-- step just need when developing in loop, no need for end user after installpython-mgadm.gadgetron_dataflow_monitor## --begin-- step just need when developing in loop, no need for end user after installcdsrc## --end-- step just need when developing in loop, no need for end user after installgadgetron_ismrmrd_client-fgadm/test_datas/testdata.h5-Cgadm/use_in_gadgetron_sample/python_monitor_start_automate.xmlInternal[Core]A QT+Matplotlib UI application to show dataData Producer run in a standalone Thread to produce data and send to UI by trigger signalThe core Application can be use under three ways:As a start by hand external application which listen to gadgetron stream dataUse as data process gadget which start by gadgetronUse as normal Python UI application which read data from ismrmrd fileTODOfix the speed problem of realtime updatefix the initial focus problem(can not receive key event unless user click on canvas)?add a sample to read data from testdata and show directly? [done]rename and publish to pypi, project structure may need to adjust [wip]add a screen gif to demo how to use ( use peek software )CD by github actionReferenceshttps://matplotlib.org/stable/gallery/user_interfaces/embedding_in_qt_sgskip.htmlhttps://github.com/gadgetron/GadgetronOnlineClass/blob/master/Courses/Day1/Lecture2/visualization/visualization.pyhttps://github.com/matplotlib/matplotlib/pull/19255https://github.com/anntzer/matplotlib/tree/qt6WarningThis depend on new released Python with Qt 6, and unpublished mathplotlib with QT6 support!
Package: gadgit
GADGITGenetic Algorithm for Disease Gene Identification ToolboxFree software: MIT licenseDocumentation:https://gadgit.readthedocs.io.InstallationViapip:pip install gadgitFor more information, see the specific installation instructions in thedocumentation.Basic Usageimportgadgitga_info=gadgit.GAInfo()fixed_genes=['BRCA1','AR','ATM','CHEK2','BRCA2','STK11','RAD51','PTEN','BARD1','TP53','RB1CC1','NCOA3','PIK3CA','PPM1D','CASP8']gene_info=gadgit.GeneInfo('brca.csv',['Betweenness'],fixed_list=fixed_genes)pop,stats,hof=gadgit.ga_multi(gene_info,ga_info)gadgit.post_run(gene_info,ga_info,pop,stats,hof)Customization of parameters can be found in the class documentation of theGAInfoandGeneInfoclasses locatedon the module docs.FeaturesMulti objective supportEvolutionary algorithm parameter selectionDynamic bioinformatics settingsVariable community sizeGenerational statisticsPost processing helpersCentrality buildersHPC readyCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.6.0 (2022-08-15)Add multiprocessing support0.5.0 (2021-08-19)Update to stricter elitismOptimize breeding pipelineAdd better within generation loggingFix SoR implementation bug0.4.0 (2021-05-27)Change frontier to be calculated only based on eliteAdd elite gene ranker to post run script0.3.0 (2021-05-20)Restructured moduleSoR supportError checkingREADME updatesLinting fixes0.2.1 (2021-03-02)Reformatting of documentation and help page text to pass checks0.2.0 (2021-03-02)Added documentation on readthedocsAbstracted self correctionsSingle point crossover addedCrossover selectionRandom seed controlUpdate requirements0.1.3 (2021-02-17)Fix more build bugsExpose post processing functionClean up string representation of parameter classesAdd fixed genes supportAdd more assertions for debuggingMade mutation respect fixed genes structureUpdated test dataframe0.1.2 (2021-02-17)Include more packages to build step0.1.1 (2021-02-17)Fixes to package building0.1.0 (2021-02-17)First release on PyPI.
Package: gadm
📝 GADMThis library provides all countries's national and prefectural boundaries in the form ofgeopandasdataframe, by dynamically fetching fromGADM dataset.:gear: Installationpipinstallgadm:running: How to RunBasic usageimportgeopandasasgpdfromgadmimportGADMDownloaderdownloader=GADMDownloader(version="4.0")country_name="Vietnam"ad_level=0gdf=downloader.get_shape_data_by_country_name(country_name=country_name,ad_level=ad_level)assertisinstance(gdf,gpd.GeoDataFrame)gdf.plot()Use with visualization libraryGADM's data frame can be interactively visualized on a jupyter notebook withfoliumimportfoliumasflimportgeopandasasgpdfromgadmimportGADMDownloaderdownloader=GADMDownloader(version="4.0")country_name="Vietnam"ad_level=1gdf=downloader.get_shape_data_by_country_name(country_name=country_name,ad_level=ad_level)m=fl.Map(zoom_start=10,tiles="OpenStreetMap")for_,ringdf.iterrows():sim_geo=gpd.GeoSeries(r["geometry"]).simplify(tolerance=0.001)geo_j=sim_geo.to_json()geo_j=fl.GeoJson(data=geo_j,style_function=lambdax:{"fillColor":"orange"})fl.Popup(r["VARNAME_1"]).add_to(geo_j)geo_j.add_to(m)mDownload satellite images based on boundaries from gadmCheckthe following example🎛  Development Environmentcondaenvcreate--fileenvironment.yml
condaactivategadm
Package: gadma
GADMAWelcome to GADMA v2!GADMA implements methods for automatic inference of the joint demographic history of multiple populations from the genetic data.GADMA is a command-line tool. Basic pipeline presents a series of launches of the global search algorithm folowed by the local search optimization.GADMA provides two types of demograpic inference: 1) for user-specified model of demographic history or a custom model, 2) automatic inference for the model with specified structure (up to three populations, see morehere).GADMA provides choice of several engines of demographic inference. This list will be extended in the future. Available engines and maximum number of supported populations for custom model:∂a∂i(up to 5 populations)moments(up to 5 populations)momi2(up to ∞ populations)momentsLD- extenstion ofmoments(up to 5 populations)More information about engines seehere.GADMA features variuos optimization methods (globalandlocalsearch algorithms) which may be used forany general optimization problem.Two global search algorithms are supported in GADMA:Genetic algorithm — the most common choice of optimization,Bayesian optimization — for demographic inference with time-consuming evaluations, e.g. for four and five populations usingmomentsor ∂a∂i.GADMA is developed in Computer Technologies laboratory at ITMO University under the supervision ofVladimir Ulyantsevand Pavel Dobrynin. The principal maintainer isEkaterina Noskova(ekaterina.e.noskova@gmail.com)GADMA is now of version 2!SeeChangelog.DocumentationPlease seedocumentationfor more information including installation instructions, usage, examples and API.Getting helpF.A.Q.Please don't be afraid to contact me for different problems and offers via emailekaterina.e.noskova@gmail.com. I will be glad to answer all questions.Also you are always welcome tocreate an issueon the GitHub page of GADMA with your question.CitationsPlease see full list of citations indocumentation.If you use GADMA in your research please cite:Ekaterina Noskova, Vladimir Ulyantsev, Klaus-Peter Koepfli, Stephen J O’Brien, Pavel Dobrynin, GADMA: Genetic algorithm for inferring demographic history of multiple populations from allele frequency spectrum data,GigaScience, Volume 9, Issue 3, March 2020, giaa005,https://doi.org/10.1093/gigascience/giaa005If you use GADMA2 in your research please cite:Ekaterina Noskova, Nikita Abramov, Stanislav Iliutkin, Anton Sidorin, Pavel Dobrynin, and Vladimir Ulyantsev, GADMA2: more efficient and flexible demographic inference from genetic data,GigaScience, Volume 12, August 2023, giad059,https://doi.org/10.1093/gigascience/giad059If you use Bayesian optimization please cite:Ekaterina Noskova and Viacheslav Borovitskiy, Bayesian optimization for demographic inference,G3 Genes|Genomes|Genetics, Volume 13, Issue 7, July 2023, jkad080,https://doi.org/10.1093/g3journal/jkad080
Package: gadm-connector
Gadm-connectorSimple donwloader for gadm border data.importgadmNetherlands=gadm.Country("NLD",0,"4.1")InstallingGadm-connector is available on PyPI:python -m pip install gadm-connectorGadm-connector is build for python 3.8+.Featuresget geopandas dataframe of country bordersget list of coordinates of country borders
Package: gado
gadogenerate poetry with gcc diagnostics🚧 In development - Testing is appreciated! 🚧🖋️ Aboutgado(gccawesomediagnosticsorchestrator) is a wrapper of gcc that outputs its errors and warnings in a more poetic format.It currently takes rhymes from a database of all Shakespeare's works.🔎 UsageAfter installing, you will be able to callgadoandgado++. You can use them just likegcc/g++!Typegado --helpfor more info.Examples:gado source.c -o executable
gado++ source.cpp -o executable💡 Tip:There areC/C++source files in theexamplesfolder. Why don't you try to compile them (withgado errors.corgado++ errors.cpp)?📝 RequirementsYou need gcc>=9, python3 and pip in order to install gado.⬇️ InstallingPyPIAs gado is written in python, installation by pip is recommended.sudo pip install gadoManualYou can manually install gado by cloning this repository and running the install script.git clone https://github.com/diksown/gado
cd gado
sudo python setup.py install🤝 Contributinggadois open source. You are more than welcome tohelp on it!
Package: gadopt
G-ADOPTThis repository contains material and examples relating to the G-ADOPT
Platform, a computational platform for inverse geodynamics, being
developed and maintained by researchers from the Research School of
Earth Sciences at the Australian National University. It builds on a
recent surge in accessible observational datasets and advances in
inversion methods using sophisticated adjoint techniques that provide
a mechanism for fusing these observations with dynamics, physics and
chemistry.G-ADOPT is supported and funded by the Australian Research Data
Commons (ARDC), with additional partner contributions from AuScope,
the NCI and Geosciences Australia.InstallationG-ADOPT is available on PyPI asgadopt, and requires a workingFiredrakeinstallation. To bring
in the optional nonlinear optimisation dependencies, install thegadopt[optimisation]variant.
Package: gadwall
gadwall - Command Line Client to duckdbgadwallis a pure Python based command line toduckdbimage fromwikimediaUsage$ python -m gadwall stocks.ddb 
Welcome to the gadwall, a duckdb shell. Type help or ? to list commands.

duckdb> ?

Documented commands (type help <topic>):
========================================
db  help  quit  schema

Undocumented commands:
======================
EOF

duckdb> db
stocks.ddb
duckdb> schema
stocks
duckdb> schema stocks
0 date TIMESTAMP False None False
1 symbol VARCHAR False None False
2 open FLOAT False None False
3 high FLOAT False None False
4 low FLOAT False None False
5 close FLOAT False None False
6 adj_close FLOAT False None False
7 volume INTEGER False None False
duckdb> SELECT symbol, MAX(close) FROM stocks GROUP BY symbol;
GOOG 1827.989990234375
MSFT 231.64999389648438
ORCL 65.30000305175781
duckdb> quit
Package: gae-app-settings
# Google AppEngine App SettingsThis package provies a straightforward way to store and access environment-specific and secret/private variables in the Google App Engine Datastore.## Quick startInstall `gae_app_settings`:```bash$ pip install gae_app_settings```In your settings module or some other module that loads at startup:```pythonfrom gae_app_settings import AppSettingvalue = AppSetting.get('MY_SETTING_KEY', DEFAULT_VALUE)```## Full documentationAppSetting is a class that is used to persist/store sensitive values in your environment. It is designed to work just like a dictionary, but it is limited to just string values.Settings cannot be set programmatically, they are only retrievable:```pythonvalue = AppSetting.get('MY_SETTING_KEY', DEFAULT_VALUE)```**NOTE:** regardless of the type of `DEFAULT_VALUE `, `value` will always be a string. This is to ensure that the return value is of the same type whether the setting is set or unset, as a set value will be a string.You can also retrieve values without passing a default:```pythonvalue = AppSetting.get('MY_SETTING_KEY')```**Note:** If no default value is provided and the key has not been given a value in the datastore, the `get()` call will raise a `KeyError` and a placeholder entry will be created in the datastore. Once the placeholder has been replaced with a value future calls to `get()` will succeed.## Best practicesThe following best practices are recommended:1. Settings should be loaded at program start and stored locally in a `settings.py` or similar module1. Default values should be provided for every setting:1. these should be the values that make sense when running/testing locally1. placeholders will be inserted into the Datastore, and these only need to be overwritten if there are environment-specific settings that need to be set (in production, all values should be set)1. Do not change the type of the `value` property in the datastore; coersion should happen on the result of the call to `get()`
Package: gae-catnado
gae-catnadoThis is a work in progress subject to sudden change.A collection of useful properties and helpers for use with Google App Engine.Install with pip:pip install gae-catnado.See thedocs on GitHub.Changelog0.0.1dev29Revampedcatnado.utils.validatorsto write clean data toself.request.registryAdded some more unit tests around validators0.0.1dev28Addedcatnado.handlers.csrf_protected_handleras a handler whose POST/PUT/DELETE requests are protected automatically.0.0.1dev27Addedcatnado.handlers.simple_public_handlerfor rendering simple pages.Addedcatnado.utils.csrffor easily adding CSRF protection to apps.0.0.1dev14Unit tests forcatnado.utils.validators0.0.1dev13Updates tocatnado.utils.validators0.0.1dev12Addedcatnado.utils.apiandcatnado.handlers.service_api_handler; helpers
for making secure API calls and building API handlers that validate requests are
coming from another service within the same application.Addedcatnado.utils.validatorsAddedflake8-docstrings-catnadoand related bits and pieces"we've traced the call... it's coming from inside the house!"0.0.1dev11AddedJSONPropertyand basic unit testsA way to store JSON data validated by aJSON Schema(draft 3 or 4)This new property adds the new pip requirementjsonschema
Package: gaecl
GAE Collerated LoggerCollerated request logger for GAE python3 flexible|standard environmentInstallfrom PyPIpip install gaeclfrom githubpip install --user git+https://github.com/takashi8/gaeclUse as WSGI MiddlewarefromgaeclimportRequestLoggerMiddleware# app: WSGI app instanceapp=Flask(__name__)app=RequestLoggerMiddleware(app,loglevel='INFO',project=os.getenv('GOOGLE_CLOUD_PROJECT'),module=os.getenv('GAE_SERVICE'),version=os.getenv('GAE_VERSION'),)@app.route('/')deflog():logging.info('info log')logging.warn('warn log')logging.error('error log')logging.critical('critical log')return'ok'
Package: gaeconf
GaeconfCLI utility to generate .yaml GAE configurationsFree software: MIT licenseDocumentation:https://gaeconf.readthedocs.io.FeaturesCLI interface that receives a yaml config module and a GAE service name and outputs a valid GAE app-yaml fileCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2019-06-26)First release on PyPI.0.1.1 (2019-06-27)Minor changes in setup.py0.1.2 (2019-06-27)Adds-eoption in CLI to expose host environment variables0.1.3 (2020-08-26)Updates requirement version for ruamel.yaml package
Package: gaedriver
gaedriver is a tool to automate end-to-end test for App Engine apps.MOTIVATIONBefore you can run an end-to-end test, you need to bring up your test
environment. For App Engine apps, this means starting dev_appserver or
deploying an application. The gaedriver package allows you to do those
things with an API.Current statusalpha - We understand what’s needed and know how to solve it. Looking for more
testers to provide feedback on the APIs and usage in general.A Python Tutorial can be found athttp://code.google.com/p/gaedriver/wiki/PythonTutorial.
Package: gaeenv
Google App Engine virtual environment===========================``gaeenv`` (Google App Engine virtual environment) is a tool to integrateGoogle App Engine SDK into existing environments built by virtualenv_Install-------Global installation^^^^^^^^^^^^^^^^^^^You can install gaeenv globally with `easy_install`_::$ sudo easy_install gaeenvor `pip`_::$ sudo pip install gaeenvLocal installation^^^^^^^^^^^^^^^^^^Using virtualenv_ you can install gaeenv via pip_/easy_install_ inside anyvirtual environment built with virtualenv_ or virtualenv_wrapper_::$ virtualenv --no-site-packages env$ . env/bin/activate(env) $ pip install gaeenv(env) $ gaeenv --version0.1.0If you want to work with the latest version of the gaeenv you caninstall it from the github `repository`_::$ git clone https://github.com/llinder/gaeenv.git$ ./gaeenv/gaeenv/main.py --help.. _repository: https://github.com/llinder/gaeenv.. _pip: http://pypi.python.org/pypi/pip.. _easy_install: http://pypi.python.org/pypi/setuptoolsDependency----------For gaeenv^^^^^^^^^^^* python* requestsUsage-----Basic^^^^^Activate existing environment::$ . env/bin/activateOr activate existing environment with virtualenvwrapper::$ workon envInstall latest Google App Engine SDK into environment::(env) $ gaeenv install sdkCheck location of main utilities::(env) $ which dev_appserver.pyVIRTUAL_ENV/lib/google_appengine/dev_appserver.py(env) $ which appcfg.pyVIRTUAL_ENV/lib/google_appengine/appcfg.pyDeactivate environment::(env) $ deactivate_gaeAdvanced^^^^^^^^Get available SDK versions::$ gaeenv list sdk1.8.81.8.71.8.61.8.51.8.41.8.31.8.21.8.11.8.01.7.71.7.61.7.51.7.4Install App Engine SDK "1.8.1"::$ gaeenv install sdk --version=1.8.1Link all packages in requirements.txt into src/lib::$ . env/bin/activate(env)$ pip install -r requirements.txt(env)$ gaeenv install requirements -r requirements.txtGaeenv changelog=================Version 0.1.0-------------- Initial release