Saravanan666/pypi-org huggingface dataset:
Package: package-versions
Package versionsImplements version numbers, e.g. for use in your custom package/module/extension/addon system.Version ranges are stored as VersionRange and can be created using syntax similar to pip:VersionRange('==3')# >=3.0,<4.0VersionRange('<=2.5,>1')# >=2.0,<=2.5VersionRange('==2.*')# >=2.0,<3.0The main functionality is the combination of version ranges as best as possible, which is needed in case two packages rely on the same third package, but with different version limitations:VersionRange('<=2.5,>1')&VersionRange('==2.*')#>=2.0,<=2.5VersionRange('<4.4')&VersionRange('>0,<=7')#>=1.0,<4.4VersionRange('<4.4')&VersionRange('>5.3')#==5.3 and an optional warning or error (due to the mismatch in range)It can also choose the most appropriate version among a list of options:options=['0.0.0','2.8.','2.1.unordered','1.0.dev1','2.2.words','2.9.9','999.999.0']VersionRange('>=2.2,<2.9').choose(options)# 2.8VersionRange('>2.2,<2.8').choose(options)# 2.8. and an optional warning or error (due to no match in range)VersionRange('>2.2').choose(options)# 999.999.0And parse package dependencies:parse_dependency('package>=3')# ('package', VersionRange(>=3.0))parse_dependency('specialname123>2.0,<3')# ('specialname123', VersionRange(>=2.1,<3.0))parse_dependencies('packA>1.3,<6\n#packskip==*\n\npackB<3.4#,>1.2')# OrderedDict([('packa', VersionRange(>=1.4,<6.0)), ('packb', VersionRange(<=3.3))])For a lot more examples, see the unit tests.InstallationInstall using:pip install package-versionsImport using:from package_versions import VersionRange, parse_dependenciesYou’re ready to go!RestrictionsA restriction this package imposes is that it assumed that feature versions are pairs of at most two integers, like11.7but not11.7.3or1.7dev.Version11.7.3is assumed to contain only bug-fixes compared to11.7, and as such will always be preferred. Personally I like this unambiguous interpretation, but it’s up to you if you accept it.Due to internal representation, there is a maximum for major and minor versions of 46340.Package names roughly follow Python module naming guide (start with a letter, lowercase, not too long). Note that some systems treat upper and lower case as the same, so it’s probably wise to keep this restriction.TestsThere are a lot of py.test unit tests that you can run using:python3-mpytestLicenseBSD 3-clause “Revised” License. Keep the license file and understand that I’m not to be held liable, and then you’re free to do pretty much whatever.
Package: package-viacep
package_viacepDescription.
The package package_viacep is used to:
- Utility for Brazil zip code query
- Utility for Brazil zip code validationInstallationUse the package managerpipto install package_viaceppipinstallpackage_viacepUsagefrompackage_viacepimportviacepinstance=viacep.ViaCep()''' Return of Dict Object'''data=instance.GetData('Zip Code')AuthorAntonio OliveiraLicenseMIT
Package: package-Ygor
Projeto: Pacote de Processamento de ImagensAula: Coding Lab PRO - Digital Innovation One(clique aqui para ver o meu perfil na plataforma)Tecnologia: PythonData: 04/10/2022DescriÃ§Ã£oO pacote "image_processing-test" Ã© usado para:MÃ³dulo "Processing":CorrespondÃªncia de histograma;Similaridade estrutural;Redimensionar imagem;MÃ³dulo "Utils":Ler imagem;Salvar imagem;Plotar imagem;Resultado do grÃ¡fico;Plotar histograma;Passo a passo da configuraÃ§Ã£o para hospedar um pacote em Python no ambiente de testes Test PypiInstalaÃ§Ã£o das Ãºltimas versÃµes de "setuptools" e "wheel"py -m pip install --user --upgrade setuptools wheelTenha certeza que o diretÃ³rio no terminal seja o mesmo do arquivo "setup.py"C:\User\Henrique\image-processing-package> py setup.py sdist bdist_wheelApÃ³s completar a instalaÃ§Ã£o, verifique se as pastas abaixo foram adicionadas ao projeto:build;dist;image_processing_test.egg-info.Basta subir os arquivos, usando o Twine, para o Test Pypi:py -m twine upload --repository testpypi dist/*ApÃ³s rodar o comando acima no terminal, serÃ¡ pedido para inserir o usuÃ¡rio e senha. Feito isso, o projeto estarÃ¡ hospedado no Test Pypi.hospedÃ¡-lo no Pypi diretamente.Aqui o objetivo nÃ£o Ã© utilizar o projeto da Karina para postar em meu perfil do Pypi pessoal, visto que o projeto Ã© dela. Ainda nÃ£o tenho nenhum projeto que possa ser utilizado como pacote.No entanto, tenha em mente que o Test Pypi, como o prÃ³prio nome diz, Ã© apenas um ambiente de testes. Para que o projeto esteja disponÃ­vel como um pacote para ser usado publicamente, Ã© necessÃ¡rio hospedÃ¡-lo no site oficial do Pypi.InstalaÃ§Ã£o local, apÃ³s hospedagem no Test PypiInstalaÃ§Ã£o de dependÃªnciaspip install -r requirements.txtInstalÃ§Ã£o do PacoteUse o gerenciador de pacotespip install -i https://test.pypi.org/simple/ image-processing-testpara instalar image_processing-testpipinstallimage-processing-testComo usar em qualquer projetofromimage-processing-test.processingimportcombinationcombination.find_difference(image1,image2)Autor (quem hospedou o projeto no Test Pypi)Ygor Silva Lino TeixeiraLicenÃ§aMIT
Package: packagify
PackagifyA packaging utility to access folders that aren't suitable to be used as packages, as python packages.How to usefrompackagifyimportPackagifypackage=Packagify("/home/workspace/my_package")object=package.import_module("module",["object"])object1,object2=package.import_module("module",["object1","object2"])How this worksThis class overrides the import functionality of python while importing the module.When the package tries to import certain modules from it's directory assuming the script ran from there, we change the level of import from absolute to relative.If a module adds a system path (using sys.path.append) we change the path to reflect the location of the module relative to the location from where we are loading the entire pacakage.After importing we revert back the functions to originals so that rest of the importing can work as is
Package: packaging
Reusable core utilities for various Python Packaginginteroperability specifications.This library provides utilities that implement the interoperability
specifications which have clearly one correct behaviour (eg:PEP 440)
or benefit greatly from having a single shared implementation (eg:PEP 425).Thepackagingproject includes the following: version handling, specifiers,
markers, requirements, tags, utilities.DocumentationThedocumentationprovides information and the API for the following:Version HandlingSpecifiersMarkersRequirementsTagsUtilitiesInstallationUsepipto install these utilities:pip install packagingThepackaginglibrary uses calendar-based versioning (YY.N).DiscussionIf you run into bugs, you can file them in ourissue tracker.You can also join#pypaon Freenode to ask questions or get involved.Code of ConductEveryone interacting in the packaging project’s codebases, issue trackers, chat
rooms, and mailing lists is expected to follow thePSF Code of Conduct.ContributingTheCONTRIBUTING.rstfile outlines how to contribute to this project as
well as how to report a potential security issue. The documentation for this
project also covers information aboutproject developmentandsecurity.Project HistoryPlease review theCHANGELOG.rstfile or theChangelog documentationfor
recent changes and project history.
Package: packaging-classifiers
Cannonical source for classifiers on PyPI (pypi.org).UsageCheck if a classifier is valid:>>> from packaging_classifiers import classifiers
>>> 'License :: OSI Approved' in classifiers
True
>>> 'Fuzzy :: Wuzzy :: Was :: A :: Bear' in classifiers
False
>>>Determine if a classifier is deprecated:>>> from packaging_classifiers import deprecated_classifiers
>>> 'License :: OSI Approved' in deprecated_classifiers
False
>>> 'Natural Language :: Ukranian' in deprecated_classifiers
True
>>> deprecated_classifiers["Natural Language :: Ukranian"].deprecated_by
['Natural Language :: Ukrainian']Get a pre-sorted list of classifiers:>>> from packaging_classifiers import sorted_classifiers
>>> sorted_classifiers[0]
'Development Status :: 1 - Planning'
>>> sorted_classifiers[-1]
'Typing :: Typed'
Package: packaging-dists
packaging-distsParse distribution file names for project information. This library is not
particularly useful on its own, but can be used to make sense of distribution
information from package indexes. For example:>>>frompackaging_distsimportInvalidDistribution,parse>>>frompypi_simpleimportPyPISimple>>>client=PyPISimple()>>>fordistinclient.get_project_files("numpy"):...try:...print(parse(dist.filename))...exceptInvalidDistributionase:...print(e)(skipped)Wheel(project='numpy', version=<Version('1.19.2')>, build='', python='cp38', abi='cp38', platform='macosx_10_9_x86_64')Wheel(project='numpy', version=<Version('1.19.2')>, build='', python='cp38', abi='cp38', platform='manylinux1_i686')Wheel(project='numpy', version=<Version('1.19.2')>, build='', python='cp38', abi='cp38', platform='manylinux1_x86_64')Wheel(project='numpy', version=<Version('1.19.2')>, build='', python='cp38', abi='cp38', platform='manylinux2010_i686')Wheel(project='numpy', version=<Version('1.19.2')>, build='', python='cp38', abi='cp38', platform='manylinux2010_x86_64')Wheel(project='numpy', version=<Version('1.19.2')>, build='', python='cp38', abi='cp38', platform='manylinux2014_aarch64')Wheel(project='numpy', version=<Version('1.19.2')>, build='', python='cp38', abi='cp38', platform='win32')Wheel(project='numpy', version=<Version('1.19.2')>, build='', python='cp38', abi='cp38', platform='win_amd64')Wheel(project='numpy', version=<Version('1.19.2')>, build='', python='pp36', abi='pypy36_pp73', platform='manylinux2010_x86_64')Sdist(project='numpy', version=<Version('1.19.2')>)
Package: packaging-legacy
Legacy PackagingThis library provides support for "legacy" Python Packaging functionality
removed fromhttps://github.com/pypa/packaging.Supported APIsThis library includes support for the following deprecated/removed APIs:LegacyVersionRemoved inhttps://github.com/pypa/packaging/pull/407, this includes apackaging_legacy.version.parsefunction that handles legacy versions.- from packaging.version import parse, LegacyVersion+ from packaging_legacy.version import parse, LegacyVersion
Package: packaging-utils
A bunch of scripts I use for keeping track of packages I maintain and for work with rpm dependency trees.Some of them are focused on openSUSE, but feel free to adapt them to you OS or even open pull requests!Toolscheck_anitya: Checks latest version on anitya and compares it with locally available version.license_rewriter: Rewrites RPM specfiles to use %license macro (not needed anymore).branch-and-fix-license: Branches a package at the OpenBuildService, fixes %license and submits the packages (not needed anymore).changelog_extractor: Extracts the changelog from a file in an archive, shows the changes sinnce the last version found in the changes file and converts it to the RPM changelog format.librariesio-latest-version: Retrieves the latest version from libraries.io (currently only PyPI is supported) for the given software. The name of the software can be detected from the current working directory.specfile-version-updater: Updates the version in the spec file, remove the old tarball and add the new one.update-packages: If called with the name of a package, it searches for it in$PACKAGING_DIR(defaults to~/packaging/), excludinghome:*-directories, callsspecfile-version-updater, tries to build it, callschangelog-extractor, applies it, and commits the updated package.ConfigurationSome scripts require a configuration. The file used is.config/packaging_utils.ini.### Forlibrariesio-latest-version/specfile-version-updaterYou can get your API key here:https://libraries.io/account`ini [libraries.io] api_key = INSERT API KEY HERE `
Package: packagit
packagitIncrement version, create and push tag for release on github and pypiInstallation# Set up a virtualenv.python3-mvenvvenvsourcevenv/bin/activate# Install from PyPIpipinstallpackagitSetupWrite your first version number inside the setup.py of your project in the form:VERSION="0.2101.0"# major.YYMM.minorCopy the workflow file (release.yml) to the .github/workflows folder of your project repository.
Copy an (empty?) changelog.txt to the root of your project repository.UsageRun at the shell promptpackagit0# 0 is the major version number, the minor number will be automatically incremented.
Package: packaide-client
OverviewThis is a simple API wrapper that allows interaction with aPackaideServerinstance.The API allows for passing multiple SVG files to the server, which are then nested into one or more SVG files. The
resulting SVG files are then returned to the client.Installationpipinstallpackaide_clientUsageThe main class is aPackaideClientwhich exposes a single methodpack. This method takes a list of SVG strings,
height and width (in inches) and returns a list of SVG strings. The resulting SVG strings will have the nested shapes.As a side note, the original size (ie:viewBox) of the input SVG files has no influence on the size of the output SVG
files. The output SVG will always conform to the height and width parameters. However, if any shape or path in the input
SVG files is too large to fit in the output SVG, aValueErrorwill be always be raised.Examplefrompackaide_clientimportPackaideClient# URL is the address of the server instance, usually operating on port 8000URL="http://localhost:8000"client=PackaideClient(URL)svg1="<svg>...</svg>"svg2="<svg>...</svg>"results=client.pack([svg1,svg2],height=60,width=40,tolerance=.1,offset=5,rotations=4)# Returns a list of SVGs# results can be passed to other functionsforsheetinresults:print(sheet)# Or written to a filesfori,sheetinenumerate(results):withopen(f"sheet_{i}.svg","w")asf:f.write(sheet)ParametersThepackmethod takes the following parameters:svgs: A list of SVG strings to be nestedheight: The height of the output SVG in incheswidth: The width of the output SVG in inchestolerance: The tolerance used when quantizing curves (Discretization tolerance)offset: The offset distance around each shape (dilation)rotations: The number of rotations to attempt when nesting shapes.
Package: packbits
This module implements a PackBits encoder/decoder for Python 2.x and 3.x.PackBits encoding is used in PSD and TIFF files.Installationpip install packbitsUsageImportpackbitsmodule; then usepackbits.encode(data)andpackbits.decode(data)functions.ContributingDevelopment happens at github and bitbucket:https://github.com/kmike/packbitshttps://bitbucket.org/kmike/packbitsThe main issue tracker is at github:https://github.com/kmike/packbits/issuesFeel free to submit ideas, bugs, pull requests (git or hg) or regular patches.In order to run tests, installtoxand typetoxfrom the source checkout.The license is MIT.
Package: packcircles
packcirclesA pure Python implementation of the circle packing algorithm detailed in Wang et al. (2006). Visualization of large hierarchical data by circle packing.Proc of the SIGCHI, 517-520.InstallationUsingpip:pip install packcirclesor directly usingsetup.py:git clone https://github.com/mhtchan/packcircles.git
cd packcircles
python setup.py installUsageThe functionpacktakes an iterable of the radii of the circles to pack and returns a generator that yields the layout of each circle as tuples in the form(x_coordinate, y_coordinate, radius).Exampleimportpackcirclesaspccircles=pc.pack([15,5,7,12])print(list(circles))## [(-15.579319782711305, 4.287939798231928, 15), (4.4206802172886945, 4.287939798231928, 5), (2.9206802172886945, -7.6179411015587295, 7), (20.647637933172685, -0.7801804930509242, 12)]The layout in the gif at the top of the page can be generated by the following code:importpackcirclesaspcimportmatplotlib.pyplotaspltfrommatplotlib.cmimportget_cmapradii=[28,12,51,26,10,16,24,25,59,11,29,40,16,11,10,26,39,16,48,36,28]fig,ax=plt.subplots()cmap=get_cmap('coolwarm_r')circles=pc.pack(radii)for(x,y,radius)incircles:patch=plt.Circle((x,y),radius,color=cmap(radius/max(radii)),alpha=0.65)ax.add_patch(patch)fig.set_figheight(15)fig.set_figwidth(15)ax.set(xlim=(-150,140),ylim=(-180,170))plt.axis('off')
Package: pack-dataset
Project description:This project contains a loader of a special data set, as well as a connection to the database using pymssql.Prepare for projectFirst you need to create a settings.json in which the fields are specified:"prefix_login" - If you need a prefix for login (if not required, add a field and pass an empty string),
"url" - Url for connection by token,
"cert_vault_tls" - The path to the security certificate,
"cert_vault_key" - The path to the security key,
"cert_vault_verify" - The path to the security verifyYou can create such a file manually, then placing it in the library location directory. Or use
the existing library function to write configuration files (write_settings), but first you need to import
the package and create an instance of the library class (at the first launch, a message about the absence of a configuration
file should be displayed, but after its creation, such a message will not be displayed):import pack_dataset
datasets_loader = pack_dataset.create_connect()
datasets_loader.write_settings(prefix_login, url, cert_vault_tls, cert_vault_key, cert_vault_verify)Get start:First you need to import the package:import pack_datasetNow create an instance of the connection class:datasets_loader = pack_dataset.create_connect()And the data for connecting to the database is contained in the permanent environment, then they are automatically initialized. Connection to databases is carried out in 2 ways. The first is the connection via login and password:datasets_loader.connect_to_db_with_login(login, password)Or through a special token using thehvaclibrary:datasets_loader.connect_to_db_with_token(vault_token, vault_secret_engine, vault_path)Now you just want to get a data set indicating how many rows you need to get (don’t specify lines if you want to unload everything):dataset = datasets_loader.get_data_weather(row=15)Manual connection to the database:If, when creating a class, a message is displayed stating that it was not possible to get connection data to the database, you must specify them manually:datasets_loader.connect_data['server'] = server:port
datasets_loader.connect_data['database'] = database_name
datasets_loader.connect_data['schema'] = schema_name
datasets_loader.connect_data['table'] = table_nameNext, you can connecting to the database (in any convenient way) and get a dataset:datasets_loader.connect_to_db_with_login(login, password)
dataset = datasets_loader.get_data_weather(row=15)
Package: packed
packedInstallationpip3installpackedUsagefrompackedimportpackable@packable# 1) register classclassEqualMatcher:def__init__(self,expected):self._expected=expecteddefmatch(self,actual):returnactual==self._expecteddef__packed__(self):# 2) pick fieldsreturn{"expected":self._expected}clientfrompackedimportpackmatcher=EqualMatcher("banana")packed=pack(matcher)# -> send «packed» over networkserverfrompackedimportunpack# <- recieve «packed» as binarymatcher=unpack(packed)assertmatcher.match("banana")isTrue
Package: packege-name
image_processingDescription
The package image_processing is used to:
Processing:
- Histrogram matching
- Structural similarity
- Resize image
Utils:
- Read image
- Save image
- Plot image
- Plot result
- Plot histogramInstallationUse the package managerpipto install package_name'''bash
pip install package_name
'''Usage'''python
from package_name.module1_name import file1_name
file1_name.my_function()
'''AuthorCaio CesarLicenseMIT
Package: packelf
packelfApackelfpacks ELF files by relocating linked shared objects.
It copies linked shared objects into.libdirectory of the given path and rewriterpathof ELF files bypatchelfto make them relocatable.RequirementspatchelfLimitationIt may break ELF files which already userpathto change reference of shared objectsSee alsorefreeze-scripts- Make EXE files inScriptsdirectory relocatable
Package: packer
A new type of package managerStill under developmentGoalsPackage management works but it is far from ideal. There is no simple,
free, platform agnostic way to distribute software. I want to fix this.EnterPacker, a package manager built from scratch to support simple
multiplatform software installation.It should be:SimpleExtendableMultiplatform (Starting with Windows, OSX, Ubuntu)InstallaionInstall using the following command:pip install packerDependencies:Python (must be on PATH)pippywin32 (Windows)
Package: packerlicious
Aboutpackerlicious - a python library to createpackertemplates.This project leverages the logic engine oftroposphere.Installationpackerlicious can be installed via pip:$pipinstallpackerliciousExamplesBelow is the packerlicious equivalent ofpacker’s example template>>>frompackerliciousimportbuilder,provisioner,Template>>>template=Template()>>>template.add_builder(builder.AmazonEbs(access_key="...",secret_key="...",region="us-east-1",source_ami="ami-fce3c696",instance_type="t2.micro",ssh_username="ubuntu",ami_name="packer {{timestamp}}"))<packerlicious.builder.AmazonEbsobjectat0x104e87ad0>>>>template.add_provisioner(provisioner.Shell(script="setup_things.sh"))<packerlicious.provisioner.Shellobjectat0x1048c08d0>>>>print(template.to_json()){"builders":[{"access_key":"...","ami_name":"packer {{timestamp}}","instance_type":"t2.micro","region":"us-east-1","secret_key":"...","source_ami":"ami-fce3c696","ssh_username":"ubuntu","type":"amazon-ebs"}],"provisioners":[{"script":"setup_things.sh","type":"shell"}]}Currently supported Packer resourcesBuilders:alicloud-ecsamazon-chrootamazon-ebsamazon-ebssurrogateamazon-ebsvolumeamazon-instanceazure-armcloudstackdigitaloceandockerfilegooglecomputehcloudhetznercloudhyperonehyperv-isohyperv-vmcxlinodelxclxdncloudnulloneandoneopenstackoracle-classicparallels-isoparallels-pvmprofitbricksproxmoxqemuscalewaytencentcloud-cvmtritonvagrantvirtualbox-isovirtualbox-ovfvmware-isovmware-vmxyandexPost Processors:alicloud-importamazon-importartificeatlaschecksumcompressdigitalocean-importdocker-importdocker-pushdocker-savedocker-taggooglecompute-importgooglecompute-exportmanifestshell-localvagrantvagrant-cloudvspherevsphere-templateProvisioners:ansible-localansiblebreakpointchef-clientchef-soloconvergefileinspecpowershellpuppet-masterlesspuppet-serversalt-masterlessshellshell-localwindows-shellwindows-restartCommunity Plugins:Builders:jetbrains-infra/packer-builder-vsphere (vsphere-iso, vsphere-clone)solo-io/packer-builder-arm-imageProvisioners:jrbeilke/packer-provisioner-inspecLicensingpackerlicious is licensed under theApache license 2.0.
SeeLICENSEfor the full license text.packerlicious contains source code fromtropospherewhich is licensed under theBSD 2-Clause license
Package: packermate
Generate and runPackerbuild configurations from a simple YAML definition.Currently supported features:-Ubuntu on VirtualBox preseed build from installation ISO image.VirtualBox build from existing OVF file.VirtualBox build from Vagrant box file.VirtualBox build from installed Vagrant box.VirtualBox build from Atlas Vagrant box name.VirtualBox build from Vagrant box URL.AWS AMI build from existing AMI.AWS AMI from Vagrant box file.AWS AMI from installed Vagrant box.AWS AMI build from Atlas Vagrant box name.AWS AMI build from Vagrant box URL.File, shell and Ansible provisioners.Export to Vagrant box file.Export Vagrant box version metadata to file.Specify command to run after Vagrant export.To DoDocumentation.Tests.LicenseCopyright (c) 2016 Warren MooreThis software may be redistributed under the terms of the MIT License.
See the file LICENSE for details.Contact@wamonite     - twitter
       \_______.com - web
warren____________/ - email
Package: packet
The packet module is a front-end to the struct module.  It allows the
user to define a packet format, and to create a Python class to represent
those packets with named attributes for each packet field:# demo: make an IP packet packer/unpacker

# IP Prototype
ipp = Prototype()
ipp.add_uint8('vhl')
ipp.add_uint8('tos')
ipp.add_uint16('len')
ipp.add_uint16('id')
ipp.add_uint16('off')
ipp.add_uint8('ttl')
ipp.add_uint8('p')
ipp.add_uint16('sum')
ipp.add_uint32('src')
ipp.add_uint32('dst')
IP = ipp.klass('IP', NETWORK)
del ipp

# ....

# create an IP packet instance from bytes
packet = IP(bytes)

# create an empty packet
packet = IP()

# access fields
print(packet.len)

# pack fields into bytes
bytes = packet.pack()