Saravanan666/pypi-org huggingface dataset:
Package: gatered
GateRedA library to fetch Reddit data using Reddit WebAPI (gateway), w/ pushshift historical submissions support.Documentation·Replit PlaygroundWhy this library?Although there are existing libraries (e.g. praw) to interact with Reddit developer's API,
there are still several drawbacks when we trying to collect vast amount of data.gateredtries to counter these problems to provide these features:No authentication (API key) is needed to access the data.Extra attributes is presented using the Reddit webAPI compared to the public devAPI.Fully Async based.Proxy support viahttpx.InstallYou can install this library easily from pypi:# with pippipinstallgatered# with poetrypoetryaddgateredUsingThe library provides easy functions to get start fast:gatered.func.get_post_commentsgatered.func.get_posts_with_subreddit_infogatered.func.get_postsgatered.func.get_commentsgatered.func.get_pushshift_postsAlternatively you can directly usegatered.client.Clientandgatered.pushshift.PushShiftAPIclasses as your base to implement your own logics.Errors can be handled by importing eithergatered.RequestErrororgatered.HTTPStatusError,
seehttpx exceptionsto learn more.Seeexamples/for more examples.
Alternately, you canfork the example repo on Replitand play around online.LicenseCopyright 2022 CounterTekLicensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: gatetools
Tools forGATEsimulations.Install with :pip install gatetoolsClone the repository withgit clone --recursive https://github.com/OpenGATE/GateTools.git(orgit submodule update --initto update)
thencd GateTools, thenpip install -e .Example of usage:gt_gate_info
gt_image_convert input.dcm -o output.mhd
gt_image_convert input.mhd -o output_float.mhd -p float
gt_image_arithm *.mhd -o output.mhd -O sum
gt_gamma_index dose.mhd gate-DoseToWater.mhd -o gamma.mhd --dd 2 --dta 2.5 -u "%" -T 0.2Use the flag-hto get print the help of each tool. Here is the current list of command line tools.ToolCommentgt_affine_transformResample (resize, rotate) an imagegt_dicom_infoPrint tag values of a dicom filegt_dicom_rt_pbs2gateConvert Dicom RT proton plan for Gategt_dicom_rt_struct_to_imageTurn Dicom RT Struct contours into mask imagegt_dvhCreate Dose Volume Histogramgt_gamma_indexCompute gamma index between imagesgt_gate_infoDisplay info about current Gate/G4 versiongt_hausdorffCompute Hausdorff distancegt_image_arithmPixel- or voxel-wise arithmetic operationsgt_image_convertConvert image file format (dicom, mhd, hdr, nii ... )gt_image_cropCrop an imagegt_image_gaussBlur an image using gaussian filtergt_image_resizeResize an imagegt_image_statisticsStatistics of an imagegt_image_to_dicom_rt_structConvert mask image to Dicom RTStructgt_image_uncertaintyCompute statistical uncertaintygt_merge_rootMerge root filesgt_morpho_mathCompute morphological operationgt_phsp_convertConvert a phase space file from root to npygt_phsp_infoDisplay information about a phase space filegt_phsp_mergeMerge two phase space files (output in npy only)gt_phps_peaksTry to detect photopeaks (experimental)gt_phsp_plotPlot marginal distributions form a phase space filegt_write_dicomConvert image (mhd, nii, ...) to dicomgt_digi_mac_converterConvert old digitizer macros to the new commands (Gate9.3)All tools are also available to be use within your own Python script with, for example:import gatetools as gt
gt.image_convert(inputImage, pixeltype)Tests: runpython -m unittest gatetools -v
python -m unittest gatetools.phsp -vClasses and function documentation. Use the following command to open a browser for documentation (it is still not very convenient ; will be improved later).pydoc -bFor developers, please have a look at thereadme_dev.mdfile.
Package: gateway-4d-viewer
gateway_4d_viewerThis repository hosts a simple flask app that serves data from various sources to Earthwave's 4d viewer client.The package is typically run via gunicorn inside a container with the likes of google cloud run but can be downloaded
and run independently - such as within a juptyhub environemnt.For core API definition, see gateway_4d_viewer/routes*.py.For help with this package please e-mailsupport@earthwave.co.uk
Package: gateway-provisioners
Gateway ProvisionersGateway Provisioners provideskernel provisionersthat interact with kernels launched into resource-managed clusters or otherwise run remotely from the launching server.
This functionality derives fromJupyter Enterprise Gateway'sprocess proxyarchitecture. However, unlikeprocess proxies,
you do not need to use a gateway server to use these provisioners - although, in certain cases,
it is recommended (for example when the launching server does not reside within the same network as the launched kernel).Here is the current set of provisioners provided by this package, many of which have their requirements conditionally
installed:KubernetesProvisioner- Kernels (residing in images) are launched as pods within a Kubernetes clusterpip install gateway_provisioners[k8s]DockerSwarmProvisioner- Kernels (residing in images) are launched as containers within a DockerSwarm clusterDockerProvisioner- Kernels (residing in images) are launched as containers on the local serverpip install gateway_provisioners[docker]YarnProvisioner- Kernels are launched into a Hadoop YARN cluster (primarily Spark)pip install gateway_provisioners[yarn]DistributedProvisioner- Kernels are launched across a set of hosts using SSH, round-robinpip install gateway_provisionersThis package also includes command-line utilities that can be used to create kernel specifications or inject bootstrap
files into docker images relative to the desired provisioner:jupyter-k8s-spec- for building kernel specifications relative to theKubernetesProvisionerjupyter-docker-spec- for building kernel specifications relative toDockerProvisionerandDockerSwarmProvisionerjupyter-yarn-spec- for building kernel specifications relative to theYarnProvisionerjupyter-ssh-spec- for building kernel specifications relative to theDistributedProvisionerjupyter-image-bootstrap- for injecting bootstrap support when building kernel-based imagesNote:The container-based provisioners (KubernetesProvisioner,DockerSwarmProvisioner, andDockerProvisioner)
require that the hosting server also be running within the same environment/network. As a result, these provisioners
may be better suited for use by a Gateway Server (e.g.,Jupyter Kernel Gateway)
so as to not require the Notebook/Lab server also be deployed in a container.InstallationDetailed deployment instructions are located in theOperators Guideof the project docs. Here's a quick start usingpip:# install from pypipipinstall--upgradegateway-provisioners# options for the command-line utilities can be viewed using '--help-all'jupyteryarn-specinstall--help-all# run it with default options to install a Python-based kernelspec for Hadoop Yarnjupyteryarn-specinstallContributingTheContribution pageincludes
information about how to contribute to Gateway Provisioners. We encourage you to explore the other topics in ourContributors Guidelike how toset up a development environment,
or gaining an understanding of thesystem architecture,
among other things.
Package: gatf
Genetic Algorithms with Tensorflow (GATF)Gitlab|PyPI|ReadTheDocsGenetic algorithms built with Tensorflow for optimizing objective functions built with TensorflowInstallationInstallation should be in acondaorvirtualenvenvironment. Install dependencies into the environment first then install GATF using pip:pip install gatfDependencies:Python >=3.7Numpy 1.21Tensorflow 2.9Other versions are expected to work but have not been tested.UsageSee theReadTheDocsfor documentation and example usageContributorsContributions are welcome! If you want something new,fork the repositoryand then make a merge request to have it implemented.BugsCreate an issue on Gitlaband I'll do my best to address it quickly.
Package: gather
Gather – gather all plugins into a dictionaryContributingWe welcome all issues, and PRs.
We are committed to a positive environment:
see our code of conduct at the root of the tree.Running:$ noxShould DTRT – if it passes, it means
unit tests are passing, and 100% coverage.
Pull requests can be submitted without passingnox,
but will have to be fixed before merging.
We are happy to give guidance as to fixing.ContributorsMoshe Zadka <zadka.moshe@gmail.com>Mark R. Williams <mrw@enotuniq.org>LicenseMIT License
Package: gather2gether
Gather2getherHelps remote people to accomplish tasks together.Gather2gether is composed of aREST api (Flask server)CLI (full documentation)Installpip install gather2getherAlternatives using docker:I prefer start gather2gether inside a docker containerI prefer start gather2gether with already configured docker compose servicesConfigureStart mysql databasedocker run --rm --name g2gdb -p3307:3306 -e MYSQL_ROOT_PASSWORD=root -e MYSQL_DATABASE=gather2gether -e MYSQL_USER=g2g -e MYSQL_PASSWORD=g2g -d mysql:5.7Setup gather2gether.propertiesCreate anywhere configuration filegather2gether.properties[database]
host = 127.0.0.1
port = 3307
db_name = gather2gether
user = g2g
password = g2gStart serverConfiguration filegather2gether.propertiesis created in current directory, run:gather2getherConfiguration filegather2gether.propertiesis created in another directory (suppose /srv/g2g/conf/), run:G2G_CONF_PATH=/srv/g2g/conf gather2getherUse clig2g --helpContributeInstall from sourcegit clone git@github.com:witrdotnet/gather2gether.git
cd gather2gether/
virtualenv .venv (add "-p /usr/bin/pythonX.Y" to specify python version)
source .venv/bin/activate
pip install Jinja2
python setup.py installRun TestsWith unittestpython -m unittest discover test/With nosetestsnosetests -v --with-coverage --cover-package=gather2gether --cover-inclusiveStart servergather2gether
Package: gatherer
GathererCollects data from multiple MySQL Databases in a multi-tenant architecture. Gatherer helps to gather the scattered data across different databases which share the same schema. It outputs the whole collected data into a single CSV file.PipYou can install this package from pip by running the following command :pip install gathererProsCuts out the need of performing a manual job by executing your query on each database and then merging them.No wait for huge response which may fail or exceed different limits.Specific databases may be excluded.Huge and complex queries can be read from a file.Catalog can be loaded from three different sources (manual list, the same instance as tenant, the remote instance).Eliminates the need of advanced knowledge in cross-database queries.The process can be terminated at any time, and it can be restarted later.ParametersName | Description | Type | Default--- | --- | --- | ---host | The MySQL Instance IP/Identifier of Tenant Database/s (or all-with Catalog). | string | localhostuser | The MySQL Instance User of Tenant Databases (or all-with-Catalog). | string | rootpassword | The MySQL Instance Password of Tenant Databases (or all-with-Catalog). | string | Emptyport | The MySQL Instance Port of Tenant Databases (or all-with-Catalog). | integer | 3306output_dir |  Each tenant file will be stored here before the final merge. Consider it as a temporary database. | string | output_dirtenant_query | The SELECT query to be performed. | string | Nonetenant_query_source | The SELECT query to be performed from file. | string | Nonetenant_dbs | Databases given manually. If this is set then Catalog parameters will not be taken into consideration. | array | Noneskip_tenant_dbs | Tenant Databases to be skipped. | string | Nonecatalog_db | The Catalog Database. The Catalog Query will be executed here. | string | Nonecatalog_query | The Query to SELECT Tenants Database names. | string | Nonecatalog_host | The MySQL Instance IP/Identifier of Catalog.  | string | Nonecatalog_user | Catalog host User. | string | Nonecatalog_password | Catalog host Password | string | Noneoutput_file_name | The name of the file which contains the final result. | string | outputskip_processed_tenants | Tenant Databases to be skipped. | string | Nonefile_encoding | The File Encoding to be used in final CSV. | string | latin-1file_headers | The Headers in final CSV file. | string | latin-1debug | Debug the process on console. | boolean | FalseHow it worksCollector runs a given query in each tenant database which is present in its {list}, this list is either given manually (filled with Database names) or fetched automatically by a given Catalog query.Each of these runs yields a result which is outputted into a CSV file in {output_dir}. At the end of this, all files are merged into a single one.Simple usageimportgatherergatherer.gather(host='localhost',user='root',password='',port=3306,tenant_query='SELECT my_column_1,my_column_2,my_column_3 FROM my_table;',skip_tenant_dbs=['My_Tenant1_DB','My_Tenant2_DB'],catalog_db='CATALOG_DB',catalog_query='SELECT my_tenant_database_name FROM my_tenants;',output_dir='temp_output')
Package: gatherstockdata
Gather Stock DataThis project is primarily for personal use and education and can be used to gather simple stock data from yahoo finance. It
provides a simple way of gathering stock data without all the hard work.AuthorsLucas RimfrostInstallationInstall gatherstockdata with pip
Use the following command in cmd:pipinstallgatherstockdataUsagefromgatherstockdataimport*defmain():# Ticker of stock as parameterdata=gather_funda_info("AAPL")returndata['pps']show_data=main()print(show_data)
Package: gatherunique
Gather UniqueSimple, unique list gatherer, with *args for passable blacklist check and optional list_in for
automated sorting against blacklist/sInstallationpip install gather_uniqueUsagefromgatheruniqueimportGatherUniquegather=GatherUnique()head="Header to display"# Unique list from stdin, no headeruniq1=gather.run()# Unique list from stdin, with provided blacklist and headeruniq2=gather.run(['1','2','3','4','5'],header=head)# Unique list from list_in= against provided blacklistuniq3=gather.run(['1','2','3','4','5'],list_in=['6','6','1','2'])Note that args are considered blacklists by default. Use 'header=' and 'list_in=' to differentiate
Package: gaticos
GaticosGaticos ("Little Cats"? "Cutey Cats"?) it's a simple package to print "miau" in your console or print an ascii
draw of a cat in your shell with quotes ¯_(ツ)_/¯pipinstallgaticosPrint miaus:gaticos-c2>>Miau!
>>Miau!Print motivation frase in spanish:gaticosanimame
Miau!████Alloraralallorería██░░████░░████░░▒▒████████▒▒░░████████▒▒░░░░▒▒▒▒░░▒▒░░░░▒▒████░░░░████░░░░░░░░░░░░░░░░░░░░████░░██
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Package: gating
GatingGating is an simple application to plot data from a csv and create and allow users to gate the data.Getting StartedInstallationYou can pip intall the package by typing any of the following:pipinstallgatingpipinstallhttps://github.com/Luiza-Cp/Gating(back to top)Usagegating-path-path_to_save-x-yWhere:path is the path to the csv fle containig data to be plot;path_to_save is the path where gated data will be saved;x is the nameof the column to be plotted in the X axis;y is the nameof the column to be plotted in the Y axis.ContributingContributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make aregreatly appreciated.If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!Fork the ProjectCreate your Feature Branch (git checkout -b feature/AmazingFeature)Commit your Changes (git commit -m 'Add some AmazingFeature')Push to the Branch (git push origin feature/AmazingFeature)Open a Pull Request(back to top)LicenseDistributed under the MIT License. SeeLICENSE.txtfor more information.(back to top)ContactLuiza Cherobini Pereira  -luiza.cp1998@gmail.comProject Link:https://github.com/Luiza-Cp/Gating(back to top)
Package: gatoniel-utils
gatoniel-utilsLibrary with utils and helpers for myself.FeaturesFully typed with annotations and checked with mypy,PEP561 compatibleAdd yours!Installationpipinstallgatoniel-utilsExampleShowcase how your project can be used:fromgatoniel_utils.exampleimportsome_functionprint(some_function(3,4))# => 7LicenseMITCreditsThis project was generated withwemake-python-package. Current template version is:0c5619079cb74e7dc72e1f18e9176b3b3a1a843f. See what isupdatedsince then.
Package: gator
About GatorGator is short for "change propagator", and can be used to make changes across multiple Github repositories at once.The entrypoint will be a dockerized CLI and a python package.You will give Gator an imperative yaml spec file, and some repos to process. Gator will create PRs or Issues in Github according to the spec. The CLI will allow you to test your specs locally, making sure that the code changes look as you expect before PRs are created.If the reusable code modifications do not suffice, you will be able to make changes to code programatically, and use Gator to automate the git aspects, and assist you with testing. An exampleChangesetspecification will look like this:kind:Changesetversion:v1alphaspec:name:Docker image registry migrationissue_title:Replace all usages of outdated Docker image registry URL with new URLissue_body:|# Artifactory Has Moved... Some text to be included in the PR or issue body.filters:-kind:RegexFilterversion:v1alphaspec:regex:'registry.company.com'paths:-definitions/application_spec.ymlcode_changes:-kind:RegexReplaceCodeChangeversion:v1alphaspec:replacement_details:-regex:'registry.company.com'replace_term:"registry.parent-company.com"paths:-definitions/application_spec.ymlDevelopment StatusGator has not reached Minimum Viable Product status yet, but is actively in development as of early 2022.ContributingIf you're interested in contributing, please check out the CONTRIBUTING.md file at repo root.
Package: gator-client
Gator ClientA web client for theGatorAPI.Package managergator-client uses thepoetrypackage manager to manage its dependencies. To install the dependencies, run the following command:poetry installSee thepoetrydocumentation for more information and
installation instructions.ToolsThere are a number of tools available to help you with the development of sqrl. These tools ensure that your code is well-formed, follows the best practices, and
is consistent with the rest of the project.Linting the codebaseFor detecting code quality and style issues, runflake8For checking compliance with Python docstring conventions, runpydocstyleNOTE: these tools will not fix any issues, but they can help you identify potential problems.Formatting the codebaseFor automatically formatting the codebase, runautopep8 --in-place --recursive .. For more information on this command, see theautopep8documentation.For automatically sorting imports, runisort .Running testsFor running tests, runpytest.
Package: gatorconfig
GatorConfigA simple Python tool utilizing both a CLI and GUI approach
to automate the generation of configuration files forGatorGrader.
This tool is designed to assist educators in grading
GitHub-based assignments for their computer science courses.RequirementsPythonPipxPoetryUsageInstall with pip or pipxTo install the tool and its dependencies using pip, run the following command:pipinstallgatorconfigAlternatively, you can install using pipx by running:pipxinstallgatorconfigRunning GatorConfigGatorConfig is a tool that can utilize the command line interface, which
was built to accommodate the users. To run the GatorConfig program
in CLI, type the command:gatorconfigOnce you run this command, the program will output:Wrote file to: C:\Users\<YOUR PATH>\config\gatorgrader.ymlThis command will auto-generate a default configuration file for GatorGradle
namedgatorgrader.ymllocated in theconfigfolder.Additionally, you can run thegatorconfig --helpfor more
information about the configuration. This command will list the variables
in the file as well as the defaults it outputs.ContributingTechnical detailsThe GitHub Actions
workflow executespytest(withcoverage) andpylintusing the Poetry configuration, and checks
markdown withmarkdownlintand
spelling withcspell.Installing Python dependenciesAfter cloning this project, you will likely want to instruct Poetry to create a
virtual environment and install the Python packages (such as pytest and pylint)
listed inpyproject.toml.To install Python dependencies:poetryinstall-EguiTo install without the extra GUI feature, install with:poetryinstallRunning tasksThis project uses thetaskipytask runner
to simplify testing and linting. You can see the actual commands run when tasks
are executed under the[tool.taskipy.tasks]header inpyproject.toml.Testyour code withpoetry run task testLintyour code withpoetry run task lintAuthorsWesley Long, @WesleyL30 -Lead CLI developerDanny Ullrich, @ullrichd21 -Lead GUI developerKobe Coleman, @ColemanKobePaige Downey, @PaigeCDFavour Ojo, @favourojo
Package: gator-core
gator-coreA dataset aggregation framework for Sqrl Planner.ToolsLinting the codebaseFor detecting code quality and style issues, runflake8For checking compliance with Python docstring conventions, runpydocstyleNOTE: these tools will not fix any issues, but they can help you identify potential problems.Formatting the codebaseFor automatically formatting the codebase, runautopep8 --in-place --recursive .For more information on this command, see theautopep8documentation.For automatically sorting imports, runisort .