Saravanan666/pypi-org huggingface dataset:
Package: anton
antonantonis a Python library for auto instantiating yaml definitions to user defined dataclasses.Avoid boilerplate and get runtime type checking before the objects are created.UsageGiven ayamlfile definition in a fileindex.yamlas follows:# index.yamlinteger:23string:"Helloworld"point:x:0y:0line_segment:first_point:x:10y:10second_point:x:10y:10yaml_conflets you avoid writing the biolerplate code for loading theyamlfile and parsing the python dictionary to instantiate the Dataclass object as follows:>>>fromdataclassesimportdataclass>>>fromantonimportyaml_conf>>>>>>@dataclass...classPoint:...x:int...y:int...>>>@dataclass...classLineSegment:...first_point:Point...second_point:Point...>>>@yaml_conf(conf_path="index.yaml")...classExampleClass:...integer:int...string:str...point:Point...line_segment:LineSegment...>>>example_obj=ExampleClass()>>>example_objExampleClass(integer=23,string='Hello world',point=Point(x=0,y=0),line_segment=LineSegment(first_point=Point(x=10,y=10),second_point=Point(x=10,y=10)))RoadmapCurrently the project only supports Python3.8Runtime type checking is supported for the following types:intfloatstrbooltyping.Listtyping.Dicttyping.UnionAny user defined dataclassThe ultimate aim is to support all python versions Python3.8+ and all possible type combinations.ContributingPull requests are welcome !!! Please make sure to update tests as appropriate.For major changes, please open an issue first to discuss what you would like to change.Please do go through theContributing Guideif some help is required.Note:antoncurrently in active development. Pleaseopen an issueif you find anything that isn't working as expected.
Package: anton-cli
Collection Frameworkanton_cliis a commands-line program that takes a string and returns the number of unique characters in the string.Installpipinstallanton-cliHow to Usefromanton_cliimportsplit_letters,read_from_fileprint(split_letters('hello'))# 3also you can get a unique numbers of string from the fileprint(read_from_file('words.txt'))# SOME RESULTLaunchYou can use this program from the terminalif you want to pass a string use --string [YOUR STRING]python-manton_cli.cli--string[YOURSTRING]or if you want to pass a file use --file [YOUR FILE PATH]python-manton_cli.cli--file[YOURPATHTOFILE]See the source atLink© 2022 Anton Skazko
Package: antools
Antools - Anton's ToolsOverviewPrivate library which is also free to public use. Its purpose is to be useful code keeper.Anton's Tools package contains of following modules:loggingCustomizable logger (tested on Windows)multiprocessingMultiProcess class for logging and handling workflow when using multiprocessingMultiProcessHandler as easy multiprocessing frameworkthreadingThreadProcess class for logging and handling workflow when using threadingThreadHandler as easy multiprocessing frameworkvalidationVarValidator for validation data types and much morehelpersApproachComparator for testing effeciency of running function in main/multiprocess/threadingGetting StartedDependenciesThe antools package utilizes following libraries:*attrs==21.4.0
*numpy==1.22.1
*pandas==1.4.0
*python-dateutil==2.8.2
*pytz==2021.3
*six==1.16.0
*sqlitedict==1.7.0Package InstallationInstallable using pip. Execute:pip install antoolsAuthorsAntonín Drozda-adrozda.dev@gmail.comURLsGitHub-https://github.com/antonin-drozda/antoolsPypi-https://pypi.org/project/antools/Change Log2022.2.0 (06/02/2022)Improvements on Logger.
Added MultiprocessHandler and ThreadHandler.
Planned for the next release: TerminalApp (framework for easy apps in terminal)2022.1.0 (31/01/2022)Complete rework of previous platform.
Start package includes Logger, MultiProcess, ThreadProcess and ApproachComparator with examples.
Planned for the next release: NONE
Package: antp
antpModule & app for processing Jinja template files with json data and environment variables.Installationpython3-mpipinstallantpUsagepython3-mantp-t|--template<templatefile>[-o|--output<outputfile>][-d|--data<json_datafile1,json_datafile2,...,json_datafileN>]Templatefileis the jinja-template. Parameter can be omitted or parameter value set to dash to read template from stdin.Outputfileis the filename where the output will be written. Parameter can be omitted or parameter value can be set to dash to write the output to stdout.Json_datafileis the json-file with the data to be accessed in the templates. The data-parameter can have multiple datafiles, use comma to separate filenames.Data from datafiles will be in thedatavariable. Variables from environment will be in theenvvariable.Examplesdata1.json{"colors":{"black":"#000000","white":"#FFFFFF","red":"#FF0000","green":"#00FF00","blue":"#0000FF"},"food":["vegetables","meat","fish"]}data2.json{"capitals":{"Finland":"Helsinki","Sweden":"Stockholm","Denmark":"Copenhagen"}}template.jinjaThe capital of Finland is{{data["capitals"]["Finland"]}}.Typical foods:{{data["food"]|join(", ")}}.Black is{{data["colors"]["black"]}}.Environment variable FOO is{{env["FOO"]}}.Run command:FOO=barpython3-mantp-ttemplate.jinja-ddata1.json,data2.json-oout.txtout.txtThe capital of Finland is Helsinki.

Typical foods: vegetables, meat, fish.

Black is #000000.

Environment variable FOO is bar.Docker containerContainerized version of antp is also available fromanttin/antp.Container usageSample template:Our message to you is: {{ env["Message"] }}Sample run:dockerrun--rm-it-v/local/path/template:/antp/template-v/local/path/output_directory:/antp/output-eMESSAGE="Hello world"antp:latestSample output:Our message to you is: Hello worldYou can useANTP_TEMPLATE,ANTP_OUTPUTandANTP_DATAenvironment variables to override the default paths. Datafiles are not used by default, so this env variable is needed if you want to use data files.Use casesThis container can be useful as a k8s init-container. Input files can be ConfigMaps. Values can be fed through ConfigMaps or env variables. Output can be set to an emptyDir volume that is shared between the containers.
Package: antplus
🐧 Welcome to antplusHuman friendly interface to ANT+.Requirements:python >= 3.9serialioInstallationFrom within your favorite python environment:$pipinstallantplusTo run the examples you'll need:$pipinstallantplus[examples]To develop, run tests, build package, lint, etc you'll need:$pipinstallantplus[dev]To run docs you'll need:$pipinstallantplus[docs]
Package: antpycv
# antpycv គឺជា Computer Vision package ដែលងាយស្រួលសរសេរកូដ python ភ្ជាប់ទៅកាន់ Arduino ដើម្បីធ្វើការបង្ហាញរូបភាពនិងកិច្ចការងារពាក់ព័ន្ធនឹងមុខងារ AI (Artificial Intelligence)។ antpycv ត្រូវបានបង្កើតឡើងដោយប្រើប្រាស់ OpenCV និង Mediapipe libraries។
## អ្នកអាចធ្វើការតំឡើង antpycv package ទៅកាន់ virtual environment (venv) project របស់អ្នកតាមរយៈ command ខាងក្រោម៖
### pip install antpycv ##### ជាការសំនូមពរអ្នកគួរតែធ្វើការ upgrade តាម command ខាងក្រោម៖
### pip install –upgrade pip setuptools wheel ###
Package: antra
BingAI (ChatGPT)Bing AI API for ChatGPTInstallationpip install bingai --upgradeImportant Feature - No Manual Intervention Required100% Programmatic Run
Edge browser opens up and automatically fetches tokens, no manual intervention whatsoeverUsagefrom bingai import BingSession
session = BingSession(email, password)
session.run()Microsoft credentials for the account which has access to the Bing Chat feature
Package: antsibull-changelog
antsibull-changelog -- Ansible Changelog ToolA changelog generator used by ansible-core and Ansible collections.Using theantsibull-changelogCLI tool for collections.Using theantsibull-changelogCLI tool for other projects.Documentation on thechangelogs/config.yamlconfiguration file forantsibull-changelog.Documentation on thechangelog.yamlformat.antsibull-changelog is covered by theAnsible Code of Conduct.InstallationIt can be installed with pip:pip install antsibull-changelogFor python projects,antsibull-changelog releasecan retrieve the current
version frompyproject.toml.
You can install the project withpip install antsibull-changelog[toml]to pull in the necessary toml parser for this feature.
Thetomlextra is always available, but it is noop on Python >= 3.11,
astomllibis part of the standard library.For more information, see thedocumentation.DevelopmentInstall and runnoxto run all tests. That's it for simple contributions!noxwill create virtual environments in.noxinside the checked out project
and install the requirements needed to run the tests there.To run specific tests:nox -e testto only run unit tests;nox -e integrationto only run integration tests; this runsantsibull-changelog lintagainst antsibull-changelog and community.general
(after cloning its repository) and records coverage data.nox -e coverageto display combined coverage results after runningnox -e test integration;nox -e lintto run all linters and formatters at once;nox -e formattersto runisortandblack;nox -e codeqato runflake8,pylint,reuse lint, andantsibull-changelog lint;nox -e typingto runmypyandpyreCreating a new release:Runnox -e bump -- <version> <release_summary_message>. This:Bumps the package version inpyproject.toml.Createschangelogs/fragments/<version>.ymlwith arelease_summarysection.Runsantsibull-changelog releaseand adds the changed files to git.Commits with messageRelease <version>.and runsgit tag -a -m 'antsibull-changelog <version>' <version>.Runshatch build --clean.Rungit pushto the appropriate remotes.Once CI passes on GitHub, runnox -e publish. This:Runshatch publish;Bumps the version to<version>.post0;Adds the changed file to git and rungit commit -m 'Post-release version bump.';Rungit push --follow-tagsto the appropriate remotes and create a GitHub release.LicenseUnless otherwise noted in the code, it is licensed under the terms of the GNU
General Public License v3 or, at your option, later. SeeLICENSES/GPL-3.0-or-later.txtfor a copy of the license.The repository follows theREUSE Specificationfor declaring copyright and
licensing information. The only exception are changelog fragments inchangelog/fragments/.
Package: antsibull-docs-parser
antsibull-docs-parser - Python library for processing Ansible documentation markupThis is a Python library for processing Ansible documentation markup. It is named afterantsibull-docswhere this code originates from. It was moved out to make it easier to reuse the markup code in other projects without having to depend on all of antsibull-docs's dependencies.DevelopmentInstall and runnoxto run all tests.noxwill create virtual environments in.noxinside the checked out project and install the requirements needed to run the tests there.To run specific tests:nox -e testto only run unit tests;nox -e lintto run all linters and formatters at once;nox -e formattersto runisortandblack;nox -e codeqato runflake8,pylint,reuse lint, andantsibull-changelog lint;nox -e typingto runmypyandpyre;nox -e create_vectorsto update thetest-vectors.ymlfile. Please note that this file should be synchronized with the corresponding file inthe antsibull-docs-ts project.Releasing a new versionRunnox -e bump -- <version> <release_summary_message>. This:Bumps the package version inpyproject.toml.Createschangelogs/fragments/<version>.ymlwith arelease_summarysection.Runsantsibull-changelog releaseand adds the changed files to git.Commits with messageRelease <version>.and runsgit tag -a -m 'antsibull-docs-parser <version>' <version>.Runshatch build --clean.Rungit pushto the appropriate remotes.Once CI passes on GitHub, runnox -e publish. This:Runshatch publish;Bumps the version to<version>.post0;Adds the changed file to git and rungit commit -m 'Post-release version bump.';Rungit push --follow-tagsto the appropriate remotes and create a GitHub release.
Package: antsichaut
AntsichautAntsichaut automates the filling of achangelog.yamlused by antsibull-changelog.You define a Github repository and a Github release. Then the script
searches all pull requests since the release and adds them to thechangelog.yaml.The PR's get categorized into the changelog-sections based on these default labels:group_config = [
  {"title": "major_changes", "labels": ["major", "breaking"]},
  {"title": "minor_changes", "labels": ["minor", "enhancement"]},
  {"title": "breaking_changes", "labels": ["major", "breaking"]},
  {"title": "deprecated_features", "labels": ["deprecated"]},
  {"title": "removed_features", "labels": ["removed"]},
  {"title": "security_fixes", "labels": ["security"]},
  {"title": "bugfixes", "labels": ["bug", "bugfix"]},
  {"title": "skip_changelog", "labels": ["skip_changelog"]},
]This means for example that PR's with the labelmajorget categorized
into themajor_changessection of the changelog.PR's that have askip_changelogdo not get added to the changelog at all.PR's that do not have one of the above labels get categorized into thetrivialsection.Installationpip install antsichautManual UsageYou need a minimalchangelog.ymlcreated by antsibull-changelog:antsibull-changelog release --version 1.17.0Then define the version and the github repository you want to fetch the PRs from.
Either via arguments or via environment variables:> cd /path/to/your/ansible/collection
> antsichaut \
  --github_token 123456789012345678901234567890abcdefabcd \
  --since_version 1.17.0 \
  --to_version 1.18.0 \
  --major_changes_labels=foo
  --major_changes_labels=bar
  --minor_changes_labels=baz
  --repository=T-Systems-MMS/ansible-collection-icinga-director> cd /path/to/your/ansible/collection
> export SINCE_VERSION=1.17.0  # (or `latest`)
> export TO_VERSION=1.18.0     # optional. if unset, defaults to current date
> export REPOSITORY=T-Systems-MMS/ansible-collection-icinga-director
> export MAJOR_CHANGES_LABELS=["foo","bar"]
> export MINOR_CHANGES_LABELS=["baz"]
> antsichautThis will fill thechangelog.yamlwith Pull Requests.
Then runantsibull-changelog generateto create the final changelog.Usage with Github ActionsInputssince_versionRequiredthe version to fetch PRs sinceto_versionthe version to fetch PRs toUsage----name:"GetPrevioustag"id:previoustaguses:"WyriHaximus/github-action-get-previous-tag@master"env:GITHUB_TOKEN:"${{secrets.GITHUB_TOKEN}}"-name:"Runantsichaut"uses:ansible-community/antsichaut@mainwith:GITHUB_TOKEN:"${{secrets.GITHUB_TOKEN}}"since_version:"${{steps.previoustag.outputs.tag}}"ExamplesCheck these examples out:telekom_mms.icinga_directorprometheus.prometheusAcknowledgements and KudosThis script was initially forked fromhttps://github.com/saadmk11/changelog-ci/and modified by @rndmh3ro. Thank you, @saadmk11!From May 2021 through May 2023, this project was maintained by @rndmh3ro and then graciously transferred to the ansible community organization. Thank you @rndmh3ro!LicenseThe code in this project is released under the MIT License.
Package: ants-pi
Welcome to ANTS👋!ANTSis a toolbox for analyzing time-series data.
You can recruit your own workers and order some
analyzing jobs! Here, we call the workers as'ants'!
Here after, you don't have to work alone.Work with your ants!InstallationYou can startANTSwith typing a simple command in your terminal.pipinstallants-piDocumentationThis documentation will help your ants!
Package: antspyt1w
ANTsPyT1wreference processing for t1-weighted neuroimages (human)the outputs of these processes can be used for data inspection/cleaning/triage
as well for interrogating neuroscientific hypotheses.this package also keeps track of the latest preferred algorithm variations for
production environments.install by calling (within the source directory):python setup.py installor install viapip install antspyt1wwhat this will doprovide example databrain extractiondenoisingn4 bias correctionbrain parcellation into tissues, hemispheres, lobes and regionshippocampus specific segmentationt1 hypointensity segmentation and classificationexploratorydeformable registration with robust and repeatable parametersregistration-based labeling of major white matter tractshelpers that organize and annotate segmentation variables into data frameshypothalamus segmentationFIXME/TODOthe two most time-consuming processes are hippocampus-specific segentation
(because it uses augmentation) and registration.  both take 10-20 minutes
depending on your available computational resources and the data.  both
could be made computationally cheaper at the cost of accuracy/reliability.first time setupimportantspyt1wantspyt1w.get_data()NOTE:get_datahas aforce_downloadoption to make sure the latest
package data is installed.example processingimportosos.environ["TF_NUM_INTEROP_THREADS"]="8"os.environ["TF_NUM_INTRAOP_THREADS"]="8"os.environ["ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS"]="8"importantspyt1wimportantspynetimportants##### get example data + reference templates# NOTE:  PPMI-3803-20120814-MRI_T1-I340756 is a good example of our naming style# Study-SubjectID-Date-Modality-UniqueID# where Modality could also be measurement or something elsefn=antspyt1w.get_data('PPMI-3803-20120814-MRI_T1-I340756',target_extension='.nii.gz')img=ants.image_read(fn)# generalized default processingmyresults=antspyt1w.hierarchical(img,output_prefix='/tmp/XXX')##### organize summary data into data frames - user should pivot these to columns# and attach to unique IDs when accumulating for large-scale studies# see below for how to easily pivot into wide format# https://stackoverflow.com/questions/28337117/how-to-pivot-a-dataframe-in-pandasAn example "full study" (at small scale) is illustrated in~/.antspyt1w/run_dlbs.pywhich demonstrates/comments on:how to aggregate dataframeshow to pivot to wide formathow to join with a demographic/metadata filevisualizing basic outcomes.ssl errorif you get an odd certificate error when callingforce_download, try:importsslssl._create_default_https_context=ssl._create_unverified_contextto publish a releasepython3 -m build
python -m twine upload -u username -p password  dist/*
Package: antsys
antsysA general purpose ant colony optimization system.OverviewThe Ant Colony Optimization (ACO) is a technique, inspired by the foraging behavior of ants, to find good solutions for discrete optimization problems. Its central metaphor resides in the indirect communication mechanism through chemical signals (pheromones) used by many species of social ants in their search for food sources.The same inspiration was build in theantsyspackage, wich takes advantage ofpythonflexibility to be easily applied to different optimization problems.InstallationInstallation viapippip3 install antsysUsage Example:Travelling Salesman ProblemThe Travelling Salesman Problem (TSP) is the challenge of finding the shortest yet most efficient route for a person to take given a list of specific destinations. It is a well-known optimization problem and commonly solved by ACO algorithm.Import necessary packages and modulesfromantsysimportAntWorldfromantsysimportAntSystemimportnumpyasnpimportrandomGenerate a travelling salesman problem instance# generate citiesprint('cities:')print('| id |    x    |    y    |')cities=[]forcityinrange(10):x=random.uniform(-100,100)y=random.uniform(-100,100)cities.append((city,x,y))print('|%4i|%9.4f|%9.4f|'%cities[city])The functionsalesman_ruleswill append the euclidean distance between cities to the edges.defsalesman_rules(start,end):return[((start[1]-end[1])**2+(start[2]-end[2])**2)**0.5]The functionsalesman_costwill be used to calculate the cost of any possible solution (path).defsalesman_cost(path):cost=0foredgeinpath:cost+=edge.inforeturncostThesalesman_heuristicis a simple heuristic that will help the ants to make better choices. Edges with small distances have a slightly higher probability of selection.defsalesman_heuristic(path,candidate):returncandidate.infoThis function shows the details of a possible solution (sys_resp).defprint_solution(sys_resp):print('total cost =%g'%sys_resp[0])print('path:')print('| id |    x    |    y    |--distance-->| id |    x    |    y    |')foredgeinsys_resp[2]:print('|%4i|%9.4f|%9.4f|--%8.4f-->|%4i|%9.4f|%9.4f|'%(edge.start[0],edge.start[1],edge.start[2],edge.info,edge.end[0],edge.end[1],edge.end[2]))The world (new_world) is created from the nodes (cities) as a complete graph. In this point,salesman_rules,salesman_costandsalesman_heuristicare defined as respectivelyr_func,c_funcandh_func. These functions are bound to the world and the first one has an important role in its structure.new_world=AntWorld(cities,salesman_rules,salesman_cost,salesman_heuristic)Configureant_optas anAntSystem.ant_opt=AntSystem(world=new_world,n_ants=50)Execute the optimization loop.ant_opt.optimize(50,20)Show details about the best solution found.print_solution(ant_opt.g_best)Examples can be foundhereas jupyter notebooks.
Package: antu
# AntU
Universal data IO and neural network modules in NLP tasks.data IOis an universal module in Natural Language Processing system and not based on any framework (like TensorFlow, PyTorch, MXNet, Dynet…).neural networkmodule contains the neural network structures commonly used in NLP tasks. We want to design commonly used structures for each neural network framework. We will continue to develop this module.# RequirementsPython>=3.6bidict==0.17.5numpy==1.15.4numpydoc==0.8.0overrides==1.9pytest==4.0.2##### If you need dynet neural network:dynet>=2.0# Installing via pip`bash pip install antu `# Resources[Documentation](https://antu.readthedocs.io/en/latest/index.html)[Source Code](https://github.com/AntNLP/antu)
Package: antx
antx - Annotation TransferTransfer annotations from source text to destination using diff match patch.UsageInstall using pip.$ pip install antxImportfrom antx import transferTransfernew_target = transfer(source_text, annotations, target_text, output="txt")source_text:= contains source textannotations:= contains list of annotations in source text that you want to transfer to target texttarget_text:= contains target textoutput:= Flag to indicate type of output. It can be txt or yaml.Examplesource_text="""༄༅། །ཕྱག་ཆེན་སྔོན་འགྲོ་བཞི་སྦྱོར་དང་དངོས་གཞིའི་ཁྲིད་རིམ་མདོར་བསྡུས་ངེས་དོན་སྒྲོན་མེ་ཞེས་བྱ་བ་བཞུགས་སོ། །<𰵀auམཛད་པ་པོ། འཇམ་མགོན་ཀོང་སྤྲུལ་བློ་གྲོས་མཐའ་ཡས། །>༄༅། །ཕྱག་ཆེན་སྔོན་འགྲོ་བཞི་སྦྱོར་དང་དངོས་གཞིའི་ཁྲིད་རིམ་མདོར་བསྡུས་ངེས་དོན་སྒྲོན་མེ་ཞེས་བྱ་བ་བཞུགས་སོ། །""target_text="""༄༅། །ཕྱག་ཆེན་སྔོན་འགྲོ་བཞི་སྦྱོར་དང་དངོས་གཞིའི་ཁྲིད་རིམ་མདོར་བསྡུས་ངེས་དོན་སྒྲོན་མེ་ཞེས་བྱ་བ་བཞུགས་སོ། །མཛད་པ་པོ། འཇམ་མགོན་ཀོང་སྤྲུལ་བློ་གྲོས་མཐའ་ཡས། །༄༅། །ཕྱག་ཆེན་སྔོན་འགྲོ་བཞི་སྦྱོར་དང་དངོས་གཞིའི་ཁྲིད་རིམ་མདོར་བསྡུས་ངེས་དོན་སྒྲོན་མེ་ཞེས་བྱ་བ་བཞུགས་སོ། །༄༅། །གྲུབ་བརྒྱའི་སྤྱི་མེས་མར་མི་དྭགས་གསུམ་ནས། །དཔལ་ལྡན་དུས་གསུམ་མཁྱེན་པའི་བཀའ་བརྒྱུད་ནི།"""annotations=[['author_start',r"(\<[𰵀-󴉱]?au)"],['author_end',r"(\>)"]]result=transfer(src,annotations,trg,output="txt")Annotationtransferstarted...Mappingannotationstotofu-IDs[INFO]Computingdiffs...[INFO]Diffcomputed!Transferingannotations...print(result)༄༅།།ཕྱག་ཆེན་སྔོན་འགྲོ་བཞི་སྦྱོར་དང་དངོས་གཞིའི་ཁྲིད་རིམ་མདོར་བསྡུས་ངེས་དོན་སྒྲོན་མེ་ཞེས་བྱ་བ་བཞུགས་སོ།།<𰵀auམཛད་པ་པོ།འཇམ་མགོན་ཀོང་སྤྲུལ་བློ་གྲོས་མཐའ་ཡས།།>༄༅།།ཕྱག་ཆེན་སྔོན་འགྲོ་བཞི་སྦྱོར་དང་དངོས་གཞིའི་ཁྲིད་རིམ་མདོར་བསྡུས་ངེས་དོན་སྒྲོན་མེ་ཞེས་བྱ་བ་བཞུགས་སོ།།༄༅།།གྲུབ་བརྒྱའི་སྤྱི་མེས་མར་མི་དྭགས་གསུམ་ནས།།དཔལ་ལྡན་དུས་གསུམ་མཁྱེན་པའི་བཀའ་བརྒྱུད་ནི།