Saravanan666/pypi-org huggingface dataset:
Package: pure-pyawabi
pure-pyawabipure-pyawabiis a pure python implementation of awabi(https://github.com/nakagami/awabi).If you have Rust development environment, see alsohttps://github.com/nakagami/pyawabi.RequirementsPython 3.8+MeCab dictionaryex) Ubuntu$ sudo apt install mecab mecab-ipadic-utf8Install python package$ pip install pure-pyawabiHow to usepyawabi command$ echo 'すもももももももものうち'  | pyawabi
すもも  名詞,一般,*,*,*,*,すもも,スモモ,スモモ
も      助詞,係助詞,*,*,*,*,も,モ,モ
もも    名詞,一般,*,*,*,*,もも,モモ,モモ
も      助詞,係助詞,*,*,*,*,も,モ,モ
もも    名詞,一般,*,*,*,*,もも,モモ,モモ
の      助詞,連体化,*,*,*,*,の,ノ,ノ
うち    名詞,非自立,副詞可能,*,*,*,うち,ウチ,ウチ
EOS$ echo 'すもももももももものうち'  | pyawabi -N 2
すもも  名詞,一般,*,*,*,*,すもも,スモモ,スモモ
も      助詞,係助詞,*,*,*,*,も,モ,モ
もも    名詞,一般,*,*,*,*,もも,モモ,モモ
も      助詞,係助詞,*,*,*,*,も,モ,モ
もも    名詞,一般,*,*,*,*,もも,モモ,モモ
の      助詞,連体化,*,*,*,*,の,ノ,ノ
うち    名詞,非自立,副詞可能,*,*,*,うち,ウチ,ウチ
EOS
すもも  名詞,一般,*,*,*,*,すもも,スモモ,スモモ
も      助詞,係助詞,*,*,*,*,も,モ,モ
もも    名詞,一般,*,*,*,*,もも,モモ,モモ
もも    名詞,一般,*,*,*,*,もも,モモ,モモ
も      助詞,係助詞,*,*,*,*,も,モ,モ
の      助詞,連体化,*,*,*,*,の,ノ,ノ
うち    名詞,非自立,副詞可能,*,*,*,うち,ウチ,ウチ
EOSuse as packageuse function>>> import pyawabi
>>> import pprint
>>> pp = pprint.PrettyPrinter()
>>> pp.pprint(pyawabi.tokenize("すもももももももものうち"))
[('すもも', '名詞,一般,*,*,*,*,すもも,スモモ,スモモ'),
 ('も', '助詞,係助詞,*,*,*,*,も,モ,モ'),
 ('もも', '名詞,一般,*,*,*,*,もも,モモ,モモ'),
 ('も', '助詞,係助詞,*,*,*,*,も,モ,モ'),
 ('もも', '名詞,一般,*,*,*,*,もも,モモ,モモ'),
 ('の', '助詞,連体化,*,*,*,*,の,ノ,ノ'),
 ('うち', '名詞,非自立,副詞可能,*,*,*,うち,ウチ,ウチ')]
>>> pp.pprint(pyawabi.tokenize_n_best("すもももももももものうち", 2))
[[('すもも', '名詞,一般,*,*,*,*,すもも,スモモ,スモモ'),
  ('も', '助詞,係助詞,*,*,*,*,も,モ,モ'),
  ('もも', '名詞,一般,*,*,*,*,もも,モモ,モモ'),
  ('も', '助詞,係助詞,*,*,*,*,も,モ,モ'),
  ('もも', '名詞,一般,*,*,*,*,もも,モモ,モモ'),
  ('の', '助詞,連体化,*,*,*,*,の,ノ,ノ'),
  ('うち', '名詞,非自立,副詞可能,*,*,*,うち,ウチ,ウチ')],
 [('すもも', '名詞,一般,*,*,*,*,すもも,スモモ,スモモ'),
  ('も', '助詞,係助詞,*,*,*,*,も,モ,モ'),
  ('もも', '名詞,一般,*,*,*,*,もも,モモ,モモ'),
  ('もも', '名詞,一般,*,*,*,*,もも,モモ,モモ'),
  ('も', '助詞,係助詞,*,*,*,*,も,モ,モ'),
  ('の', '助詞,連体化,*,*,*,*,の,ノ,ノ'),
  ('うち', '名詞,非自立,副詞可能,*,*,*,うち,ウチ,ウチ')]]
>>>use tokenizer object>>> tok = pyawabi.Tokenizer()
>>> pp.pprint(tok.tokenize("すもももももももものうち"))
[('すもも', '名詞,一般,*,*,*,*,すもも,スモモ,スモモ'),
 ('も', '助詞,係助詞,*,*,*,*,も,モ,モ'),
 ('もも', '名詞,一般,*,*,*,*,もも,モモ,モモ'),
 ('も', '助詞,係助詞,*,*,*,*,も,モ,モ'),
 ('もも', '名詞,一般,*,*,*,*,もも,モモ,モモ'),
 ('の', '助詞,連体化,*,*,*,*,の,ノ,ノ'),
 ('うち', '名詞,非自立,副詞可能,*,*,*,うち,ウチ,ウチ')]
>>>
Package: purepyodbc
purepyodbcWhat is this?This is a project which aims to provide a "pure Python" implementation of ODBC.It will eventually implement theDB API 2.0specification.It may or may not end up adopting a similar public API to the well-knownpyodbc.Why would you do a foolish thing like that?I'll give you two reasons:I could use something like this myself, but it would need to be compatible with PyPy3.x and with recent editions of SQL Server (and the features thereof).I could learn something by doing this project.Why not just use {{package}}?I refer you tomy previous answer.Can I use this?I wouldn't do that if I were you.I mean, if you actually did, ho-ho, bwahaha!Ahem.I mean, if you actuallydid, then... it would beentirely at your own risk.Can I contribute to it?We both know you've got nothing better to do, so... why not give it a shot? The worst I can do is say no.In all sincerity, there are bound to be people who are better-qualified than I am to do something like this. You might just be one of those people!What platforms does it support?The good news is that everything that works so far works wonderfully (more or less) on my machine, for my specific use case.The bad news? Oh... you don'treallywant to hear the bad news, do you?
Package: purepy-remctl
purepy-remctlThis is a pure Python implementation of aremctlprotocol version 3 client. The interface mostly follows thePython C bindingwhich is
packaged with the original remctl software distribution, with a few exceptions:There is noRemctl.set_ccache(ccache)method, there is aRemctl.set_credential(credential)method instead.set_credential()accepts an (initiator)gssapi.Credentialobject from thepython-gssapipackage, which will be used as a
credential to initiate the GSSAPI security context with the remctl server. This allows using, for
example, a delegated credential to perform remctl operations without needing to store the
delegated credential in a credential cache.There is no_remctlmodule providing a low-level wrapper of the C API.There is no support for the remctl protocol version 1. Only version >= 2 servers are supported.The motivation for writing this module instead of using the existing Python bindings to the remctl
C client library was:To be able to use delegated credentials obtained from the python-gssapi package in an
application to perform remctl operations.To avoid performing blocking socket operations in the C library, so that remctl operations can be
performed in an application usinggeventwithout blocking (if thesocketmodule is patched by gevent)This project is licensed under the terms of the MIT license (see LICENSE.txt).
Package: purepyvmware
<!– wp:heading –>
<h2>Pure Storage VMware Python SDK</h2>
<!– /wp:heading –><!– wp:paragraph –>
<p>In an effort to bring more options for VMware and Pure Storage end-users this SDK will implement common tasks and workflows used between the two vendors.</p>
<!– wp:paragraph –>_To report issues or request new features, please enter them here:_https://github.com/PureStorage-OpenConnect/PureStorageVMwarePythonSDK/issuesFor questions, <a href=”https://codeinvite.purestorage.com/”>join our Pure Storage Code Slack</a> team! Check out the #python channel!
Package: pure-radix
pure_radixRadix treelibrary but in pure clean Python. Run it on PyPy or IronPython or wherever.DependenciesWe try to keep dependencies light:attrsdataclass library (2881 LoC)To run the tests, you'll needpytestand optionallyhypothesis.Examples>>>frompure_radiximportSetNode>>>>>># Create a tree where each node holds a set. You are free to>>># customize what information is held inside each node.>>>t=SetNode()>>>>>>node1=t.node_get((10,11,12),create=True)>>>node2=t.node_force((10,11,30))# equivalent>>>>>>node1.add("cat")>>>node2.add("dog")>>>>>>print(t.node_debug_string())[][10,11][12]{'cat'}[30]{'dog'}>>>>>># This node exists because it's a common prefix between node1 and node2.>>>t.node_get((10,11))SetNode(node_prefix=(10,11),raw_data=None)>>>>>># This node doesn't exist.>>>print(t.node_get((10,)))NoneThe library works with any kind of sequence, including strings!>>># It also works with strings!>>>t=SetNode()>>>>>>t.node_force("catalogue").add(1)>>>t.node_force("category").add(2)>>>t.node_force("categorization").add(3)>>>t.node_force("cart").add(4)>>>t.node_force("carpet")# leaf node without actual data!SetNode(raw_data=None)>>>t.node_force("car").add(5)>>>t.node_force("star").add(6)>>>>>>print(t.node_debug_string())[]['c','a']['r']{5}['p','e','t']['t']{4}['t']['a','l','o','g','u','e']{1}['e','g','o','r']['i','z','a','t','i','o','n']{3}['y']{2}['s','t','a','r']{6}Are you looking for the longest common prefix? Here is how you can get the nodes that have the longest common prefix with a sequence:>>>forn,nodeint.node_find_closest_nodes("catenary"):...print(n,node)...4SetNode(raw_data=None)3SetNode(raw_data={1})2SetNode(raw_data={5})0SetNode(raw_data={6})Do you need to recursively get all non-empty nodes under a node?>>>list(t.node_get("cat").node_find())[SetNode(raw_data={2}),SetNode(raw_data={3}),SetNode(raw_data={1})]Let's empty some nodes now!>>>t.node_get("category").clear()>>>t.node_get("catalogue").clear()>>>t.node_get("star").clear()>>>print(t.node_debug_string())[]['c','a']['r']{5}['p','e','t']['t']{4}['t']['a','l','o','g','u','e']['e','g','o','r']['i','z','a','t','i','o','n']{3}['y']['s','t','a','r']Empty nodes do not get removed automatically! You must remove them yourself:>>>t.node_prune()>>>print(t.node_debug_string())[]['c','a']['r']{5}['t']{4}['t','e','g','o','r','i','z','a','t','i','o','n']{3}Use a powerful method of traversal:>>>def_enter(stack,frame):>>>yield("enter",frame.node,frame.node.node_sequence)>>>>>>def_exit(stack,frame):>>>yield("exit",frame.node,frame.node.node_sequence)>>>>>>foraction,node,seqint.node_visit(enter=_enter,exit=_exit):>>>print(action,node,seq)enterSetNode(raw_data=None)()enterSetNode(raw_data=None)('c','a')enterSetNode(raw_data={5})('c','a','r')enterSetNode(raw_data={4})('c','a','r','t')exitSetNode(raw_data={4})('c','a','r','t')exitSetNode(raw_data={5})('c','a','r')enterSetNode(raw_data={3})('c','a','t','e','g','o','r','i','z','a','t','i','o','n')exitSetNode(raw_data={3})('c','a','t','e','g','o','r','i','z','a','t','i','o','n')exitSetNode(raw_data=None)('c','a')exitSetNode(raw_data=None)()
Package: purerpc
purerpcpurerpcis a native, async Python gRPC client and server implementation supportingasyncio,uvloop, andtrio(achieved withanyiocompatibility layer).This project is in maintenance mode.  Updates will primarily be limited to fixing
severe bugs, keeping the package usable for actively developed projects, and
easing maintenance.For use cases limited to asyncio, consider the Python package published by the
maingrpcproject instead.RequirementsCPython >= 3.7PyPy >= 3.7InstallationLatest PyPI version:pipinstallpurerpc[grpc]NOTE: for PyPy, replace "grpc" with "grpc-pypy".  Support is tentative, asgrpc does not officially support PyPy.Latest development version:pipinstallgit+https://github.com/python-trio/purerpc.git[grpc]These invocations will include dependencies for the grpc runtime and
generation of service stubs.To install extra dependencies for running tests or examples, using thetest_utilsmodule, etc., apply the[dev]suffix (e.g.pip install purerpc[dev]).protoc pluginpurerpc addsprotoc-gen-purerpcplugin forprotocto yourPATHenvironment variable
so you can use it to generate service definition and stubs:protoc--purerpc_out=.--python_out=.-I.greeter.protoor, if you installed thegrpcio-toolsPython package:python-mgrpc_tools.protoc--purerpc_out=.--python_out=.-I.greeter.protoUsageNOTE:greeter_grpcmodule is generated by purerpc'sprotoc-gen-purerpcplugin.ServerfrompurerpcimportServerfromgreeter_pb2importHelloRequest,HelloReplyfromgreeter_grpcimportGreeterServicerclassGreeter(GreeterServicer):asyncdefSayHello(self,message):returnHelloReply(message="Hello, "+message.name)asyncdefSayHelloToMany(self,input_messages):asyncformessageininput_messages:yieldHelloReply(message=f"Hello,{message.name}")if__name__=='__main__':server=Server(50055)server.add_service(Greeter().service)# NOTE: if you already have an async loop running, use "await server.serve_async()"importanyioanyio.run(server.serve_async)# or set explicit backend="asyncio" or "trio"Clientimportpurerpcfromgreeter_pb2importHelloRequest,HelloReplyfromgreeter_grpcimportGreeterStubasyncdefgen():foriinrange(5):yieldHelloRequest(name=str(i))asyncdeflisten():asyncwithpurerpc.insecure_channel("localhost",50055)aschannel:stub=GreeterStub(channel)reply=awaitstub.SayHello(HelloRequest(name="World"))print(reply.message)asyncforreplyinstub.SayHelloToMany(gen()):print(reply.message)if__name__=='__main__':# NOTE: if you already have an async loop running, use "await listen()"importanyioanyio.run(listen)# or set explicit backend="asyncio" or "trio"You can mix server and client code, for example make a server that requests something using purerpc from another gRPC server, etc.More examples inmisc/folderProject historypurerpc was originally written byAndrew Stepanovand used the curio async event loop.  Later it
was migrated to theanyioAPI, supporting
asyncio, curio, uvloop, and trio (though curio support has since been dropped
from the API).After going a few years unmaintained, the project was adopted by thepython-trio
organizationwith the intent of ensuring a
continued gRPC solution for Trio users.
Package: pure-safetensors
pure_safetensorsSafetensorslibrary but in pure clean Python. Run it on PyPy or IronPython or wherever.DependenciesWe try to keep dependencies light:attrsdataclass library (2881 LoC)marshmallowserialization and validation library (2647 LoC)sortedcollectionstiny sorted collections library (339 LoC) built on top ofsortedcontainers(1493 LoC)(optional)sparsefilesparse file library (191 LoC)(optional)ficklewhitelist-based firewall for safe pickle loading, used for PyTorch model conversion (926 LoC)Optionally, this library integrates with NumPy (if available). PyTorch integration is planned, someday.To run the tests, you'll needpytest,numpy, and optionallyhypothesis.Examplesfrompure_safetensorsimportSafeTensorswithSafeTensors("/path/to/example.safetensors","r+")assf:arrays=sf.as_numpy()arrays["hello"][3,:]+=420.69arrays["world"]=arrays["hello"][0:2]*10# assign multiple arrays! much faster!arrays.update({"q":my_array_1,"k":my_array_2,"v":my_array_3,})# delete arrays! such wonders!delarrays["v"]ConversionDo you have an existing PyTorch checkpoint model that you would like to convert to safetensors? Then try running:python3-mpure_safetensorsimport-pytorch/path/to/model.ckpt/path/to/model.safetensorsYou may also be able to convert the modelin-placewithout making an additional copy! Use this facility at your own risk (or make a zero-costcopy-on-writebackupcopyof your checkpoint file usingcp --reflink=always ...if your filesystemsupports it).# convert itpython3-mpure_safetensorsimport-pytorch-inplace/data/model.ckpt# renamemv/data/model.ckpt/data/model.safetensorsBugsThe space allocator is a greedy algorithm based on first-fit-decreasing bin packing. So if you add/remove tensors to an existing file, it may leave too much empty space behind.PyTorch support isn't implemented yet.AlternativessafetensorsNarsil/pure_torch.pyNarsil/safetensors.cpppure_safetensorssafetensorspure_torch.pysafetensors.cppWritten in pure Python?✅❌✅—Supports NumPy (without PyTorch)?✅✅❌—Supports PyTorch?❌✅✅—Can work without numpy or pytorch?✅✅❌—Can write safetensors files?✅✅❌❌Can modify file in-place to add/remove tensors?✅❌❌❌Has test suite?✅✅❌❌Stable API?🤷✅❔❔Automatically makes files sparse to save space?✅❌❌❌Works on platforms without mmap?✅❌❌❌
Package: purescripto
PurescriptoPureScript, Python, support since Python 3.5.pspyis provided to meet the interface ofspago.This requires the installation ofPureScript Python.Basic Usagesh>pspy--init# initialize PSPY configure. PLEASE do this after `spago init`.sh>pspy# build a projectsh>pspy--run# run built python packagesh>pspy--update# build and update Python FFI dependenciesDefault output python package is the name of your PureScript project, i.e.,
projectxxxproduces a python packagexxxin in directoryxxx/xxx,
and you can add axxx/setup.pyto package Python modules and publish it to PyPI.pure-py.jsonThis is the default configuration.{"corefn-dir":"output","entry-module":"Main","index-mirror":"default","pspy-blueprint":"pspy-blueprint","spago":"spago"}It's designed for cases of making very complex extensions and very rare corner cases,
in most cases you're not expected to change it.The details ofpure-py.jsonwill be added here when I have bandwidth.
Package: puresec-cli
RequirementsPython 3.4+UsageSee Serverless plugin:serverless-puresec-cli.DevelopmentInstall dependencies, run the tests, and run the CLI (withoutpipinstalling)../setup.pyinstall./setup.pytestpython3-mpuresec_cli--helpThen fork and pull request!ReleaseSet__version__inpuresec_cli/__init__.pyCommit, and rungit tag vX.X.XreplacingX.X.Xwith the new versionSetanalytics.write_keyinpuresec_cli/stats.pyDON’T COMMIT ITRun./setup.py sdist uploadUpdate version ofhttps://github.com/puresec/serverless-puresec-cliUpdate backend latest versionAnonymous statisticsIn order to continue improving this tool, the CLI will be sending anonymous statistics about your usage.
All reported information contains non-personal predictable information from your execution, along with a
random unique identifier that is attach to you. Predictable means that it won’t send any local paths, function names, etc.To opt out of anonymous statistics simply run:puresec--statsdisable# or 'enable' if it's a wonderful dayOne final report will be transmitted about your unsubscription, with no further details.
Package: pureskillgg-assistant-coach
Shared Python modules to assist coaching services.DescriptionModels to generate assessments.InstallationThis package is registered on thePython Package Index (PyPI)aspureskillgg-assistant-coach.Install it with$ poetry add pureskillgg-assistant-coachDevelopment and TestingQuickstart$ git clone https://github.com/pureskillgg/assistant-coach.git
$ cd assistant-coach
$ poetry installRun each command below in a separate terminal window:$ make watchPrimary development tasks are defined in theMakefile.Source CodeThesource codeis hosted on GitHub.
Clone the project with$ git clone https://github.com/pureskillgg/assistant-coach.gitRequirementsYou will needPython 3andPoetry.Install the development dependencies with$ poetry installTestsLint code with$ make lintRun tests with$ make testRun tests on changes with$ make watchPublishingUse thepoetry versioncommand to release a new version.
Then runmake versionto commit and push a new git tag
which will trigger a GitHub action.Publishing may be triggered using on the web
using aworkflow_dispatch on GitHub Actions.GitHub ActionsGitHub Actions should already be configured: this section is for reference only.The following repository secrets must be set on GitHub Actions.PYPI_API_TOKEN: API token for publishing on PyPI.These must be set manually.Secrets for Optional GitHub ActionsThe version and format GitHub actions
require a user with write access to the repository
including access to read and write packages.
Set these additional secrets to enable the action:GH_USER: The GitHub user’s username.GH_TOKEN: A personal access token for the user.GIT_USER_NAME: The name to set for Git commits.GIT_USER_EMAIL: The email to set for Git commits.GPG_PRIVATE_KEY: TheGPG private key.GPG_PASSPHRASE: The GPG key passphrase.ContributingPlease submit and comment on bug reports and feature requests.To submit a patch:Fork it (https://github.com/pureskillgg/assistant-coach/fork).Create your feature branch (git checkout -b my-new-feature).Make changes.Commit your changes (git commit -am ‘Add some feature’).Push to the branch (git push origin my-new-feature).Create a new Pull Request.LicenseThis Python package is Copyright (c) 2019-2021 FPS Critic, Inc.WarrantyThis software is provided by the copyright holders and contributors “as is” and
any express or implied warranties, including, but not limited to, the implied
warranties of merchantability and fitness for a particular purpose are
disclaimed. In no event shall the copyright holder or contributors be liable for
any direct, indirect, incidental, special, exemplary, or consequential damages
(including, but not limited to, procurement of substitute goods or services;
loss of use, data, or profits; or business interruption) however caused and on
any theory of liability, whether in contract, strict liability, or tort
(including negligence or otherwise) arising in any way out of the use of this
software, even if advised of the possibility of such damage.
Package: pureskillgg-csgo-dsdk
Python Data Science Development Kit for CS:GO.DescriptionDo data science with CS:GO.InstallationThis package is registered on thePython Package Index (PyPI)aspureskillgg-csgo-dsdk.Install it with$ poetry add pureskillgg-csgo-dsdkDevelopment and TestingQuickstart$ git clone https://github.com/pureskillgg/csgo-dsdk.git
$ git lfs install
$ git lfs pull
$ cd csgo-dsdk
$ poetry installRun each command below in a separate terminal window:$ make watchPrimary development tasks are defined in theMakefile.Source CodeThesource codeis hosted on GitHub.
Clone the project with$ git clone https://github.com/pureskillgg/csgo-dsdk.git
$ git lfs install
$ git lfs pullRequirementsYou will needPython 3andPoetry.Install the development dependencies with$ poetry installTestsLint code with$ make lintRun tests with$ make testRun tests on changes with$ make watchPublishingUse thepoetry versioncommand to release a new version.
Then runmake versionto commit and push a new git tag
which will trigger a GitHub action.Publishing may be triggered using on the web
using aworkflow_dispatch on GitHub Actions.GitHub ActionsGitHub Actions should already be configured: this section is for reference only.The following repository secrets must be set on GitHub Actions.PYPI_API_TOKEN: API token for publishing on PyPI.These must be set manually.Secrets for Optional GitHub ActionsThe version and format GitHub actions
require a user with write access to the repository
including access to read and write packages.
Set these additional secrets to enable the action:GH_USER: The GitHub user’s username.GH_TOKEN: A personal access token for the user.GIT_USER_NAME: The name to set for Git commits.GIT_USER_EMAIL: The email to set for Git commits.GPG_PRIVATE_KEY: TheGPG private key.GPG_PASSPHRASE: The GPG key passphrase.ContributingPlease submit and comment on bug reports and feature requests.To submit a patch:Fork it (https://github.com/pureskillgg/csgo-dsdk/fork).Create your feature branch (git checkout -b my-new-feature).Make changes.Commit your changes (git commit -am ‘Add some feature’).Push to the branch (git push origin my-new-feature).Create a new Pull Request.LicenseThis Python package is licensed under the MIT license.WarrantyThis software is provided by the copyright holders and contributors “as is” and
any express or implied warranties, including, but not limited to, the implied
warranties of merchantability and fitness for a particular purpose are
disclaimed. In no event shall the copyright holder or contributors be liable for
any direct, indirect, incidental, special, exemplary, or consequential damages
(including, but not limited to, procurement of substitute goods or services;
loss of use, data, or profits; or business interruption) however caused and on
any theory of liability, whether in contract, strict liability, or tort
(including negligence or otherwise) arising in any way out of the use of this
software, even if advised of the possibility of such damage.