Saravanan666/pypi-org huggingface dataset:
Package: yapf-isort
yapf 💌 isortScript andpre-commit hookto runyapfandisorttogether for formatting Python source files.TestsPyPIAnacondaActivityQAOtherInstallationyapf-isortcan be installed from PyPI or Anaconda.To install withpip:$python-mpipinstallyapf-isortTo install withconda:First add the required channels$condaconfig--addchannelshttps://conda.anaconda.org/conda-forge$condaconfig--addchannelshttps://conda.anaconda.org/domdfcodingThen install$condainstallyapf-isort
Package: yapf-junit
yapf-junitRun yapf and report the results in junit compatible xml.UsageUsage: yapf-junit [OPTIONS]

Options:
  --target-dir TEXT   Directory to search.  [required]
  --out-file TEXT     File to write results to.  [required]
  --yapf-config TEXT  Yapf config file to use.
  --help              Show this message and exit.
Package: yapg
Yet Another Password GeneratorThis is a password generator which aims to generate passwords that are:ReadablePronounceableSecureLongIt useszxcvbnto estimate the complexity of the passwords.This package is provided under theGNU Affero General Public License.It is provided free of charge, and if you like it, feel free to buy me a beer.
Or, as I'm not currently disclosing my contact informations, feel free toWish that I stumble upon a beer.
Package: yaphs
yaphsYet another python hook system for python 2.7/3.xUsageBasic usageImport yaphsfromyaphsimportHookRegister foo as a hook-compatible function@Hookdeffoo(*args):print(args)Register bar as a hook to be executed before calling foo@foo.before(*args):defbar(*args):print('before foo, args: '+str(args))When you call foo, bar is called beforefoo(1,2)Expected output:before foo, args: (1, 2)
(1, 2)Class usage (python 3.x only)You can use yaphs hooks inside classes:classMyClass:@Hookdeffoo(self,*args)When you register hooks, you just have to know that the first argument will be the objectc=MyClass()@c.foo.after:defbar(o,*args):print('after foo')print('object: '+str(o))print('args: '+str(args))
Package: yapi
yapi===================#### Python - Youtube Data API v3**yapi** is a simple client api for youtube.It uses [Youtube Data API v3](https://developers.google.com/youtube/v3/).Before you can use, you must a create project in [here](https://console.developers.google.com/apis/api/youtube/overview).## Installation```sudo pip install yapi```## Using```pythonimport yapiapi = yapi.YoutubeAPI('api_key')```## References```pythonvideo = api.get_video_info('video_id')results = api.general_search('keyword', max_results=10)videos = api.video_search('keyword', max_results=10, order=None)videos = api.video_search_in_channel('keyword', 'channel_id', max_results=10, order=None)channel = api.get_channel_by_name('channel_name')channel = api.get_channel_by_id('channel_id')playlist = api.get_playlist_by_id('playlist_id')playlist = api.get_playlist_by_channel_id('channel_id')playlistItems = api.get_playlist_items_by_playlist_id('playlist_id', max_results=20)# Specialapi_key = get_api_key()bool = change_api_key('api_key')```## Pagination```pythonresults = api.general_search('keyword', max_results=10, pageToken=PAGETOKEN)videos = api.video_search('keyword', max_results=10, order=None, pageToken=PAGETOKEN)videos = api.video_search_in_channel('keyword', 'channel_id', max_results=10, order=None, pageToken=PAGETOKEN)playlistItems = api.get_playlist_items_by_playlist_id('playlist_id', max_results=20, pageToken=PAGETOKEN)```## Contributing[https://github.com/ahmetkotan/yapi](https://github.com/ahmetkotan/yapi)## Youtube Data API v3[Youtube Data API v3 Doc](https://developers.google.com/youtube/v3/)
Package: yapian-haystack
Xapian-haystack is a backend ofDjango-Haystackfor theXapiansearch engine.
Thanks for checking it out.You can find more information about Xapianhere.FeaturesXapian-Haystack provides all the standard features of Haystack:WeightingFaceted search (date, query, etc.)SortingSpelling suggestionsEdgeNGram and Ngram (for autocomplete)LimitationsTheendswithsearch operation is not supported by Xapian-Haystack.RequirementsPython 3+Django 2.2+Django-Haystack 2.8.0Xapian 1.4+InstallationFirst, install Xapian in your machine e.g. with the script provided,install_xapian.sh. Call it after activating the virtual environment to install:source <path>/bin/activate
./install_xapian.sh <version><version>must be >=1.4.0. This takes around 10 minutes.Finally, install Xapian-Haystack by running:pip install xapian-haystackConfigurationXapian is configured as other backends of Haystack.
You have to define the connection to the database,
which is done to a path to a directory, e.g:HAYSTACK_CONNECTIONS = {
    'default': {
        'ENGINE': 'xapian_backend.XapianEngine',
        'PATH': os.path.join(os.path.dirname(__file__), 'xapian_index')
    },
}The backend has the following optional settings:HAYSTACK_XAPIAN_LANGUAGE: the stemming language; the default isenglishand the list of available languages
can be foundhere.HAYSTACK_XAPIAN_WEIGHTING_SCHEME: a tuple with parameters to be passed to the weighting schemeBM25.
By default, it uses the same parameters as Xapian recommends; this setting allows you to change them.HAYSTACK_XAPIAN_FLAGS: the options used to parseAutoQueries;
the default isFLAG_PHRASE | FLAG_BOOLEAN | FLAG_LOVEHATE | FLAG_WILDCARD | FLAG_PURE_NOTSeeherefor more information
on what they mean.HAYSTACK_XAPIAN_STEMMING_STRATEGY: This option lets you chose the stemming strategy used by Xapian. Possible
values areSTEM_NONE,STEM_SOME,STEM_ALL,STEM_ALL_Z, whereSTEM_SOMEis the default.
Seeherefor
more information about the different strategies.XAPIAN_NGRAM_MIN_LENGTH,XAPIAN_NGRAM_MAX_LENGTH: options for custom configuration of ngrams (phrases) length.HAYSTACK_XAPIAN_USE_LOCKFILE: Use a lockfile to prevent database locking errors when running management commands with multiple workers.
Defaults toTrue.TestingXapian-Haystack has a test suite in continuous deployment with GitHub Actions. The file.github/workflows/test.ymlcontains the steps required to run the test suite.SourceThe source code can be found ingithub.CreditsXapian-Haystack is maintained byJorge C. Leitão;David Sauvewas the main contributor of Xapian-Haystack and
Xapian-Haystack was originally funded byTrapeze.Claude Parozis a frequent contributor.ANtlordimplemented support for EdgeNgram and Ngram.LicenseXapian-haystack is free software licenced under GNU General Public Licence v2 and
Copyright (c) 2009, 2010, 2011, 2012 David Sauve, 2009, 2010 Trapeze, 2014 Jorge C. Leitão.
It may be redistributed under the terms specified in the LICENSE file.Questions, Comments, Concerns:Feel free to open an issuehereor pull request your work.You can ask questions on the django-haystackmailing list:
or in the irc#haystack.
Package: yapic
YAPiC is developed byImage and Data Analysis Facility,Core Reseach Facilities,DZNE(German Center for Neurodegenerative Diseases).YAPiC - Yet Another Pixel Classifier (based on deep learning)Check theYAPiC Websitefor documentation,
examples and installation instructions.What is YAPiC for?With YAPiC you can make your own customzied filter (we call itmodelorclassifier) to enhance a certain structure of your choice.We can, e.g train a model for detection of oak leafs in color images, and use this oak leaf model to filter out all image regions that are not covered by oak leaves:Pixels that belong to other leaf types
or to no leafs at all are mostly suppressed, they appear dark in the output image.Pixels that belong to oak leafs are enhanced, they appear bright in the output image.The output image is also called aprobability map, because the intensity of each pixel corresponds to the probability of the pixel belonging to an oak leave region.You can train a model for almost any structure you are interested in, for example to detect a certain cell type in histological micrographs (here: purkinje cells of the human brain):Histology data provided by Oliver Kaut (University Clinic Bonn, Dept. of Neurology)We have used YAPiC for analyzing various microscopy image data. Our experiments are mainly related to neurobiology, cell biology, histopathology  and drug discovery (high content screening).
However, YAPiC is a very generally applicable tool and can be applied to very different domains. It could be used for detecting e.g. forest regions in satellite images, clouds in landscape photographs or fried eggs in food photography.
Package: yapic.di
Very fastDependency Injectionfor Python, which is highly uses typing features. Sometimes faster
then similar call in Python.RequirementsOnly works with Python 3.7 or greaterc++ 11 comaptible compiler.(only if u want to build from source)Wheels provided for windows x86/x64 and linux x86/x64UsagefromtypingimportGeneric,TypeVarfromyapic.diimport*T=TypeVar("T")classCar(Generic[T]):engine:Tdef__init__(self,engine:T):self.engine=engine# simplified Car classclassCar(Generic[T]):engine:Inject[T]classGasoline:passclassDiesel:passclassElectronic:passclassDieselCar(Car[Diesel]):passELECTRONIC_CAR=Token("ELECTRONIC_CAR")injector=Injector()injector.provide(Gasoline)injector.provide(Diesel)injector.provide(Electronic)injector.provide(DieselCar)injector.provide(ELECTRONIC_CAR,Car[Electronic])diesel=injector[DieselCar]assertisinstance(diesel,DieselCar)assertisinstance(diesel.engine,Diesel)electronic=injector[ELECTRONIC_CAR]assertisinstance(electronic,Car)assertisinstance(electronic.engine,Electronic)defdrive_diesel(car:DieselCar):assertisinstance(car,DieselCar)assertisinstance(car.engine,Diesel)injector.exec(drive_diesel)# you can set constant values, like a dictMEANING_OF_LIFE=Token("MEANING_OF_LIFE")injector[MEANING_OF_LIFE]=42assertinjector[MEANING_OF_LIFE]==42defquestion(q:MEANING_OF_LIFE):assertq==42injector.exec(question)# cached injectablelife_q=Injectable(question)# this is same as with injector.exec(question), but injectable is precachedlife_q(injector)Keyword Only ArgumentsclassConfig(dict):def__init__(self):super().__init__(some_key=42)defget_kwarg(config:Config,*,name,type):ifname=="some_key":returnconfig[name]else:raiseNoKwOnly()deffn(*,some_key:str):assertsome_key==42injector=Injector()injector.provide(Config)injector.provide(fn,provide=[KwOnly(get_kwarg)])For more info seePython Stub fileortest filesRelease ProcesschangeVERSIONinsetup.pygit add setup.pygit commit-m"chore(bump): VERSION"git checkout releasegit merge mastergit tag-aVERSION-m"chore(bump): VERSION"git push && git push--tagsgit checkout mastergit merge release
Package: ya_pickledb
Yet another PickleDB (thread-safe!)Features•Usage•Installation•License•ya-pickledb(Yet Another PickleDB) is a an open-source key-value store forPythonusing themsgpackmodule. It is heavily inspired bypickledb, but also provides new features (like thread-safety usingsafer).The new feature additions are inspired byelara; but since it cannot serialize complex data structure to filesystem I decided to take the best of both worlds and create a new package.⚡ FeaturesManipulate different data structures (strings, lists, dictionaries and so on)Fast and flexibleThread-safe!Choose between manual and auto commitsCache simple data structures📚 Usageimportya_pickledbdb=ya_pickledb.load('kvstore.db',True)db.set('foo','bar')value=db.get('foo')print(value)This is the full list of all functions available to the user:commit(): manually save the data to file storage.set(key, value, max_age=None): set the value of a key.get(key): get the value of a key.getall(): get a list of all keys.exists(key): get wheter a key exists or not.rem(key): remove a key.totalkeys(): get a total number of keys inside the db.lcreate(key): create a list.lpush(key, value): add a value to a list.lgetall(key): return all values in a list.lget(key, value, pos): return the value in a specific position of a list.lremlist(key): remove a list.lremvalue(key, value): remove a value from a list.lpop(key, pos): remove ne value in a list.llen(key): return the length of a list.lexists(key, value): determine if a value exists in a list.hcreate(key): create a dict.hset(key, dict_key, value): add a key-value pair to a dict.hget(key, dict_key): get the value for a key in a dict.hgetall(key): get all the key-value pairs from a dict.hrem(key): remove a dict.hpop(key, dict_key): remove one key-value pair fro a dict.hkeys(key): get all the keys for a dict.hvals(key): get all the values for a dict.hexists(key, dict_key): determine if a key exists in a dict.All the functions should returnNoneif something goes wrong (e.g. thekeyaccessed is missing). Errors are raised when the input type is wrong (e.g. setting aboolas key).🚀 InstallationRun the following command to install the latest version:pip install ya_pickledb🪪 Licenseya_pickledbis made with 🖤 by thethelicatoand released under theMIT LICENSE.
Package: yaplon
yaplonConvert between JSON, YAML and PLIST (binary and XML) in the commandline.
Can be used in piping. Written in Python 3.9 (not 2.7 compatible).Copyright (c) 2021 Adam Twardochadam+github@twardoch.comCopyright (c) 2012-2015 Isaac Museisaacmuse@gmail.comMIT licenseBased onSerialized Data Converter for Sublime TextInstallationInstall therelease version:pip3 install --user --upgrade yaplonInstall thedevelopment version:pip3 install --user --upgrade git+https://github.com/twardoch/yaplonUsageyaplon [c|j|p|x|y]2[j|p|x|y] -i input -o output [options]Commands:c2j  -i CSV -o JSON [-d DIALECT] [-k KEY] [-m] (minify)
c2p  -i CSV -o PLIST [-d DIALECT] [-k KEY] [-m] (minify)
c2x  -i CSV -o XML [-d DIALECT] [-k KEY] [-m] (minify) [-S] (simple XML)
c2y  -i CSV -o YAML [-d DIALECT] [-k KEY] [-m] (minify)
j2p  -i JSON -o PLIST [-b] (make binary PLIST)
j2x  -i JSON -o XML [-m] (minify) [-S] (simple XML)
j2y  -i JSON -o YAML [-m] (minify YAML)
p2j  -i PLIST -o JSON [-m] (minify) [-b] (keep binary)
p2x  -i PLIST -o XML [-m] (minify) [-S] (simple XML)
p2y  -i PLIST -o YAML [-m] (minify YAML)
x2j  -i XML -o JSON [-m] (minify) [-b] (keep binary)
x2p  -i XML -o PLIST [-b] (make binary PLIST)
x2y  -i XML -o YAML [-m] (minify YAML)
y2j  -i YAML -o JSON [-m] (minify) [-b] (keep binary)
y2p  -i YAML -o PLIST [-b] (make binary PLIST)
y2x  -i YAML -o XML [-m] (minify) [-S] (simple XML)Also installs direct CLI tools that correspond to the commands:csv22json,csv22plist,csv22xml,csv22yaml,json22plist,json22xml,json22yaml,plist22json,plist22xml,plist22yaml,xml22json,xml22plist,xml22yaml,yaml22json,yaml22plist,yaml22xmlNote that they have22rather than2in the filenames, so they don’t conflict with other similar (often single-purpose) tools that you may have.ExamplesJSON to YAMLFile to file via the dedicated CLI tool:$ json22yaml -i input.json -o output.yamlUsing pipe redirects, via the yaplon tool with j2y command:$ yaplon j2y < input.json > output.yamlRead file, output minified to stdout, via the Python 3 module$ python3 -m yaplon j2y -m -i input.jsonPLIST to JSONRead PLIST file, output minified JSON file, via the dedicated CLI tool.$ plist22json -m -i input.plist > output.jsonRead plist file, output minified JSON to stdout, via the yaplon tool with p2j command.$ yaplon p2j -m -i input.plistChangelog1.5.7: switched to Unicode output in JSON, refactoring1.5.3: added CSV reading and limited XML read/write1.2.7: removed obsolete plistlib.Data reference1.2.3: bugfix1.2.1: added support for orderedattrdict.AttrDict1.1.0: added -s for sorting data1.0.8: initial public releaseLinksProject homepage:https://twardoch.github.io/yaplon/Python package on PyPi:https://pypi.org/project/yaplon/Source on Github:https://github.com/twardoch/yaplonDonate viahttps://www.paypal.me/adamtwar
Package: yapocis
Yapocis is “Yet another Python OpenCL interface specification”.Memorable. Easy to pronounce and spell. Clearly related to the semantics of the project.Or not, all the good names are used and I am not in marketingIt includes easy-to-call-from-Python, reasonably performing implementations of the Mandelbrot kernel, 3x3 median filters, image gradients, and HSI <-> RGB image conversions. I use it to develop much less generally useful implementations of bizarre image processing ideas.
Package: yaposib
OVERVIEWYaposib is a python binding to OSI, the Open Solver Interface from
COIN-OR. It intends to give access to various solvers through python.
Yaposib was created in order to be integrated in pulp-or
(http://code.google.com/p/pulp-or).YAPOSIB PROJECT PAGEThe official project page has yet to move to coin-or.DOCUMENTATIONThe documentation can be built with sphinx from the source. For your
convenience, it is also hosted onhttp://yaposib.readthedocs.orgDEPENDENCIESyaposib depends on
- boost pythonhttp://www.boost.org- coin osihttps://projects.coin-or.org/OsiINSTALLATIONTo build and install this package, just use pip or easy_install. You need
gcc and boost::python.Advanced configuration is possible: see the documentation for that.TESTINGRun the executable that comes installed in the package$ yaposib-configADDING TESTSYaposib uses the unittest package. Adding tests is encouraged: To do so,
edit the file yaposib/test/test_yaposib.py. Anything bug filed on the
bugtracker should result (if possible) in a new test.BUGSReport them onhttp://code.google.com/p/yaposib/issues/list
Package: yapot
yapot=====Yet Another PDF OCR ToolThis is a library (tool) that makes PDF -> Text as easy as possble by doing a lot of the hard stuff for you!You will need ImageMagick, Tesseract, and QPDF to use yapot.Ubuntu------> sudo apt-get install imagemagick libmagickcore-dev> sudo apt-get install tesseract-ocr> sudo apt-get install qpdfTo use yapot, do the following:> pip install yapotThen some code:from yapot import convert_documentsuccess, pdf_text = convert_document('file.pdf')if success == True:with open('file.txt', 'w') as f:f.write(pdf_text)else:print "Unable to convert PDF!"It's that simple!Some more advanced things you can do are set the resolution, page delineation, and tell yapot not to delete temporary files (this can be useful when debugging nasty pdf's).success, pdf_text = yapot.convert_document(pdf_filename = pdf_filename,       # The name of the pdf fileresolution = 200,                  # Image DPI resolutiondelete_files = True,               # delete temporary filespage_delineation = '\n--------\n', # page deination textverbose = False,                   # output verbositytemp_dir = str(uuid.uuid4()),      # location of temp directory to usepassword = '',                     # password for PDF filemake_thumbs = True,                # create thrumbnails for each pagethumb_size = 512,                  # width of thumbnail imagethumb_dir = './thumbs',            # directory to place thumbnailsthumb_prefix = 'thumb_page_',      # prefix for thumbnail images)
Package: yapowf
(YAPOWF) Yet Another Power Factory APIThis project contains a new python - power factory API.It is still in progress…How to install$ pip install yapowfConnect Power FactoryfromyapowfimportNetwork## Connect to PFcredentials={"path":r"pathon_module_path","username":"your_username","password":"your_password_if_needed",}pf=Network(**credentials)## Activate a projectpf.activate_project("project_name_here")## Activate a study casepf.activate_study_case("studycase_name_here")## Get grid paramsbus_df=pf.get_bus_params()line_df=pf.get_line_params()gen_df=pf.get_gen_params()trafo3_df=pf.get_3wtrafo_params()trafo2_df=pf.get_2wtrafo_params()shunt_df=pf.get_shunt_params()## Search for an element name## Allowed types: "line", "gen", "load", "trafo3w", "trafo2w", "shunt"elems=pf.search_element_name("elem_name_here","line")## Want to run a power flow ??res=pf.run_load_flow()## Gettting results in dataframeld_gen_df=res.genld_gen_pu_df=res.gen_pu## Want to run a dynamic simulation ??res=pf.run_dynamic_sim()## Gettting results in dataframeres_gen_df=res.genres_bus_df=res.bus## All methods have associated DocStringshelp(pf.run_dynamic_sim)LicenseGNU GNU GPLv3
Package: yapper
YapperYapper converts Python docstrings toastrofiles for use by theAstrostatic site generator.It usesgriffeto parse python modules and extracts numpy style docstrings.Docstrings and parameter descriptions will be passed through as raw markdown wrapped in Astro<Markdown is:raw></Markdown>components.Class and function elements are wrapped withhtmlwithcssclasses that can be styled from Astro.See thecityseer.benchmarkurbanism.comdocumentation site and associateddocs repofor a working example.Conversion of markdown formatting, code blocks, admonitions, etc., is all handled downstream by Astro's remark and rehype plugins. Styling is likewise handled downstream viacsstargeting the associated element classes.ConfigurationConfiguration is provided inpyproject.tomlfile placed in the current directory, else a--configparameter can be provided with a relative or absolute filepath to atomlconfig file.yapper--config./custom_config.tomlThetomlfile must include a[tool.yapper]section, with keys corresponding to the default configuration options:[tool.yapper]package_root_relative_path='./'intro_template="""---\nimport { Markdown } from 'astro/components';\n---\n"""outro_template=""module_map=[{module="test.mock_file",astro="./tests/mock_default.astro"},]If you want to wrap the.astrooutput in a particular layout, then set theintro_templateandoutro_templateaccordingly, for example, the following will import thePageLayoutlayout and will wrap the generated content accordingly:[tool.yapper]package_root_relative_path='./'intro_template="""---\nimport { Markdown } from 'astro/components';\nimport PageLayout from '../layouts/PageLayout.astro'\n---\n\n<PageLayout>"""outro_template="""</PageLayout>\n"""module_map=[{module="test.mock_file",py="./tests/mock_file.py",astro="./tests/mock_default.astro"},]Themodule_mapis mandatory and specifies the names of the python modules to be processed via themodulekey and anastrokey corresponding to the output file:Developmentyapperuses apyproject.tomlfile to specify project dependencies and scripts related to project development and publishing.Seepyproject.tomlfor available scripts.
Package: yappgen
yapp : Yet Another Phasing Programyapp is a program that includes a set of utilities to work on high
density genetic data in pedigrees. It is similar to other existing
softwares such as LINKPHASE, FIMPUTE, AlphaPhase ... . I
developed it for my own research to have a tool that is opensource and
that I can tweak to my own needs.If you find it useful for you, drop me a note (e.g.on twitter
@BertrandServin). If you want to contribute ideas or code, you are
welcome if you know python :)yapp and its utilities implement some models and methods that have been
invented by other people. If you use yapp it is important that you
acknowledge their work by citing the appropriate
references. These will depend on the way you use the software, see thedocumentation.
Package: yapp-pipelines
yapp— Yet Another Python (data) Pipelineyapp is a simple python data pipeline framework, inspired byploomber.yapp allows you to quickly define pipelines to pack together your messy Python experiments and make better
use of them.Development is still in early stages, many things may change in the future.If you are looking for a similar tool to use right away in something resembling a production environment, just
use Ploomber.yapp strives to be as simple as possible and make you focus on the correctness of your algorithms.
It's developed with specific requirements in mind and built according to those: it may be the best choice for you once completed, or may be not.
Basic functionality is there but there are some very rough edges to be smoothed. There are no tests and not even a proper example yet.Installpip install yapp-pipelinesUsageSeedocumentation.