Saravanan666/pypi-org huggingface dataset:
Package: kuut
kuutDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-nkuut--fileenv.ymlInstallpipinstall-e.# install from pypipipinstallkuutnbdev# activate conda environment$condaactivatekuut# make sure the kuut package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the kuut package$nbdev_preparePublishing# publish to pypi$nbdev_pypi# publish to conda$nbdev_conda--build_args'-c conda-forge'UsageInstallationInstall latest from the GitHubrepository:$pipinstallgit+https://github.com/dsm-72/kuut.gitor fromconda$condainstall-cdsm-72kuutor frompypi$pipinstallkuutDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find
package manager specific guidelines oncondaandpypirespectively.
Package: kuvalda
AboutValidate dict-like object against schema, using just callables.FeaturesAllows validating and sanitizing dicts using any callablesProvides several useful helpersEasy to use – no class-based boilerplate!APIvalidatefunction takes any mapping as data and another mapping as scheme and check data against scheme. It returns list of errors.sanitizefunction takes any mapping as data and another mapping as scheme and converts data according to schema definition.For more info – see tests.ExamplesSeveral schemes:schema = {
    'key1': str,
    'key2': int,
    'key3': int,
}

schema1 = {
    'key1': kuvalda.list_of(int),
    'key2': kuvalda.list_of(kuvalda.list_of(int))
}

schema2 = {
   'section1': {
       'key1': str,
       'key2': int
    },
    'section2': kuvalda.mapping(str, int),
    'key1': kuvalda.kind_of(bool)
}

schema3 = {
    'key1': int,
    'key2': kuvalda.default('oh, my'),
    'key3': kuvalda.optional(int),
    'key4': kuvalda.optional(kuvalda.list_of(int)),
    'key5': kuvalda.compose(kuvalda.default(42), int)
}Install~/yourvirtualenv/python setup.py installpip install kuvaldaLicenseThe MIT License, in LICENSE file.
Package: kuwahara-torch
kuwahara-torchKuwahara filter in PyTorch.UsageSee full code and images onexampledir.pipinstall-Ukuwahara-torchExamplesOriginally kuwahara filter was used for denoising.OriginalkuwaharaGeneralized kuwaharaBut now it is used for artistic style.OriginalkuwaharaGeneralized kuwaharaOriginalGeneralized kuwaharaTODOKuwaharaGeneralized kuwaharaAnisotropic kuwahara. Idk how to tilt the kernel in pytorch. PRs are welcome.Referenceshttps://en.wikipedia.org/wiki/Kuwahara_filterGeneralized Kuwahara paperAnisotropic Kuwahara paperAnisotropic Kuwahara but with polynomialshttps://docs.blender.org/manual/en/dev/compositing/types/filter/kuwahara.htmlhttps://www.youtube.com/watch?v=LDhN-JK3U9g
Package: kuxxx-realpython-reader
Real Python Feed ReaderThe Real Python Feed Reader is a basicweb feedreader that can download the latest Real Python tutorials from theReal Python feed.For more information see the tutorialHow to Publish an Open-Source Python Package to PyPIon Real Python.InstallationYou can install the Real Python Feed Reader fromPyPI:pip install realpython-readerThe reader is supported on Python 2.7, as well as Python 3.4 and above.How to useThe Real Python Feed Reader is a command line application, namedrealpython. To see a list of thelatest Real Python tutorialssimply call the program:$ realpython
The latest tutorials from Real Python (https://realpython.com/)
 0 How to Publish an Open-Source Python Package to PyPI
 1 Python "while" Loops (Indefinite Iteration)
 2 Writing Comments in Python (Guide)
 3 Setting Up Python for Machine Learning on Windows
 4 Python Community Interview With Michael Kennedy
 5 Practical Text Classification With Python and Keras
 6 Getting Started With Testing in Python
 7 Python, Boto3, and AWS S3: Demystified
 8 Python's range() Function (Guide)
 9 Python Community Interview With Mike Grouchy
10 How to Round Numbers in Python
11 Building and Documenting Python REST APIs With Flask and Connexion – Part 2
12 Splitting, Concatenating, and Joining Strings in Python
13 Image Segmentation Using Color Spaces in OpenCV + Python
14 Python Community Interview With Mahdi Yusuf
15 Absolute vs Relative Imports in Python
16 Top 10 Must-Watch PyCon Talks
17 Logging in Python
18 The Best Python Books
19 Conditional Statements in PythonTo read one particular tutorial, call the program with the numerical ID of the tutorial as a parameter:$ realpython 0
# How to Publish an Open-Source Python Package to PyPI

Python is famous for coming with batteries included. Sophisticated
capabilities are available in the standard library. You can find modules for
working with sockets, parsing CSV, JSON, and XML files, and working with
files and file paths.

However great the packages included with Python are, there are many
fantastic projects available outside the standard library. These are most
often hosted at the Python Packaging Index (PyPI), historically known as the
Cheese Shop. At PyPI, you can find everything from Hello World to advanced
deep learning libraries.

[... The full text of the article ...]You can also call the Real Python Feed Reader in your own Python code, by importing from thereaderpackage:>>> from reader import feed
>>> feed.get_titles()
['How to Publish an Open-Source Python Package to PyPI', ...]
Package: kuzu
KùzuKùzu is an embedded graph database built for query speed and scalability. Kùzu is optimized for handling complex join-heavy analytical workloads on very large databases, with the following core feature set:Flexible Property Graph Data Model and Cypher query languageEmbeddable, serverless integration into applicationsColumnar disk-based storageColumnar sparse row-based (CSR) adjacency list/join indicesVectorized and factorized query processorNovel and very fast join algorithmsMulti-core query parallelismSerializable ACID transactionsKùzu started as a research project at University of Waterloo and is now being
developed primarily byKùzu Inc., a spinoff company from University of Waterloo.
Kùzu is available under a permissible license. So try it out and help us make it better! We welcome your feedback and feature requests.InstallationLanguageInstallationPythonpip install kuzuNodeJSnpm install kuzuRustcargo add kuzuJavajar fileC/C++precompiled binariesCLIprecompiled binariesTo learn more about installation, see ourInstallationpage.Getting StartedRefer to ourGetting Startedpage for your first example.More information can be found atData ImportCypher ReferenceClient APIsBuild from SourceInstructions can be found atBuild Kùzu from Source.ContributingWe welcome contributions to Kùzu. If you are interested in contributing to Kùzu, please read ourContributing Guide.LicenseBy contributing to Kùzu, you agree that your contributions will be licensed under theMIT License.Citing KùzuIf you are a researcher and use Kùzu in your work, we encourage you to cite our work.
You can use the following BibTeX citation:@inproceedings{kuzu:cidr,
  author =  {Xiyang Feng and
             Guodong Jin and
             Ziyi Chen and
             Chang Liu and
             Semih Saliho\u{g}lu},
  title={K\`uzu Graph Database Management System},
  booktitle={CIDR},
  year={2023}
}
@misc{kuzu-github,
  author =  {Xiyang Feng and
             Guodong Jin and
             Ziyi Chen and
             Chang Liu and
             Semih Saliho\u{g}lu},
  title = {{K\`uzu Database Management System Source Code}},
  howpublished = {\url{https://github.com/kuzudb/kuzu}},
  month        = nov,
  year         = 2022
}Contact UsYou can contact us atcontact@kuzudb.comorjoin our Discord community.
Package: kuzukiri
日本語kuzukiriA simple text segmenterWhat's this?This is a python library for text segmentation of Japanese text.FeaturesText segmentation by simple rules,rule-based, no machine learning,so you can assume results.comparably fast. It's written in rust-lang.Installfrom PyPIpipinstallkuzukirifrom source codepipinstallsetuptools-rust
pythonsetup.pyinstallUsageimportkuzukirisegmenter=kuzukiri.Segmenter()text="これはテストです。文分割します。"sentences=segmenter.split(text)print(sentences)# => ['これはテストです。', '文分割します。']For details, seeexamplesandtestsdirectories.LicenseMITDependenciesPyO3: to compile rust code for python.unicode_normalization crate: for NFKC normalization
Package: kv
KV provides a dictionary-like interface on top of SQLite. Keys can be
unicode strings, numbers or None. Values are stored as JSON.>>> from kv import KV
>>> db = KV('/tmp/demo.kv')
>>> db['hello'] = 'world'
>>> db[42] = ['answer', 2, {'ultimate': 'question'}]
>>> dict(db)
{42: [u'answer', 2, {u'ultimate': u'question'}], u'hello': u'world'}There is a locking facility that uses SQLite’s transaction API:>>> with kv.lock():
...   l = db[42]
...   l += ['or is it?']
...   db[42] = lAnd that’s about it. Thecodeis really simple.
Package: kvakk-git-tools
kvakk-git-toolsRepo for sharing recommended git config and git scripts in Statistics Norway.This repo should cover git config files for the production zone, Linux
and Windows (Citrix and VDI), JupyterLab (Dapla and production zone),
administrative zone and stand alone.Initially the repo will contain a collection of git configurations for the different
environments. But the aim is to make a common script, setting up the recommended
git config for all SSB platforms, based on the detected environment.StatusThessb_gitconfig.pyscript works and is tested on the following platforms:DaplaProduction zone, Linux (including Jupyter)Production zone, Windows (Citrix)DirectoriesTheexistingdirectory contains configurations collected from existing environments
before any recommendations are implemented. Therecommendeddirectory contains the
recommended config files for the different environments.Thessb_gitconfigdirectory is the root directory for the script that should
set the ssb recommended git config based on the detected environment. It is a
work in progress and not finished yet.UsageLinux and Mac OS:gitclonehttps://github.com/statisticsnorway/kvakk-git-tools.git
kvakk-git-tools/kvakk_git_tools/ssb_gitconfig.pyWindows:gitclonehttps://github.com/statisticsnorway/kvakk-git-tools.git
pythonkvakk-git-tools\kvakk_git_tools\ssb_gitconfig.pyDeveloper guideInitial setupThe Poetry tool is used for dependency management. Install poetry as described on thePoetry installation page, if not
already installed. Then run the following commands in the cloned repo:poetryinstall
poetryrunpre-commitinstallSource code requirementsThe source code must support python version 3.6, because one of the supported platforms
is based on RHEL 7.It shall be possible to run the script from a plain python installation. That is:
Don't use external libraries.The source code shall run on these platforms: Linux, Windows and macOS.LintingYou can do local linting with the following commands:poetryrunflake8
poetryrunmypy.
poetryrunpylintkvakk_git_tools/*.pyBumping versionUsemaketo bump thepatch,minorversion ormajorversion before creating a pull request to themainGIT
branch.You can use eitherbump-version-patch,bump-version-minor, orbump-version-major.
Bumping must be done with a clean git working space, and automatically commits with the new version number.Then just rungit push origin --tagsto push the changes and trigger the release process.Building and releasingBefore merging your changes into themainbranch, make sure you have bumped the version like outlined above.An automatic release process will buildkvakk-git-toolsand release a new version of the package topypi.orgautomatically.
Package: kvault
kvaultkvaultis a simple Miniature Key-Value Datastore in Python with aRedis-like interface.RequirementsPython 3.10+Python is the programming language of choice for this project, therefore, will be required to be available in
the system. One can download and setup Python in their local development environment following the steps provided in
the link.PoetryPoetry is the dependency manager & packaging tool used for this project and can be installed following the setup
provided in the link as well.virtualenvUsed to create virtual environments for installing & setting up Python dependencies.SetupRunning locally, will require avirtualenvsetup and that can be done by following the
instructions:virtualenv.venvThis will create a virtual environment in the current root directory of the project.Next, install the required dependencies:poetryinstallThis installs the dependencies for the project.Runningby default, thekvaultserver runs on localhost:31337.The following options are supported:Usage: kvault.py [options]

Options:
  -h, --help            show this help message and exit
  -d, --debug           Log debug messages.
  -e, --errors          Log error messages only.
  -t, --use-threads     Use threads instead of gevent.
  -H HOST, --host=HOST  Host to listen on.
  -m MAX_CLIENTS, --max-clients=MAX_CLIENTS
                        Maximum number of clients.
  -p PORT, --port=PORT  Port to listen on.
  -l LOG_FILE, --log-file=LOG_FILE
                        Log file.
  -x EXTENSIONS, --extension=EXTENSIONS
                        Import path for Python extension module(s).Note that the above output can be obtained from the below command:pythoncli.py-hTo run with debug logging on port 31339, for example:pythonkvault.py-d-p31339This will result in an output like below:.--.
 /( @ >    ,-.  KVault 127.0.0.1:31339
/ ' .'--._/  /
:   ,    , .'
'. (___.'_/
 ((-((-''This indicates that the server is running and awaiting client connectionsClient setup should be simple, in another terminal, open a new Python console to interact with the kvault server:fromclientimportClientclient=Client()client.set('key',{'name':'Charlie','pets':['mickey','huey']})print(client.get('key'))# {'name': 'Charlie', 'pets': ['mickey', 'huey']}A sample of the expected interaction of a client andkvaultserver
Package: kv-cache
Installation$[sudo]pipinstallkv-cacheHow it works$KV_CACHE/<key>$XDG_CACHE_HOME/kv-value/<key>by defaultExamples>>>importkv_cache>>>kv_cache.update("key",'value')>>>kv_cache.get("key")'value'>>>kv_cache.exists("key")True>>>kv_cache.rm("key")>>>kv_cache.clear()# clear all keysreadme42.com
Package: kvcheetah
kvcheetahA lightweight 2D game engine based on Kivy.Installation Instructions (pip)on Windows, executepip install kvcheetahon Linux, executesudo pip3 install kvcheetahto test your installation on Windows, executepython -m kvcheetahon Linux, executepython3 -m kvcheetahInstallation Instructions (GitHub)download the latest wheel from the release section that matches your OSopen a terminal or command prompt window and use pip to install the downloaded
wheel fileto test your installation on Windows, executepython -m kvcheetahon Linux, executepython3 -m kvcheetahBuilding Instructionsclone this repoopen a terminal or command prompt window and switch to the "kvcheetah" folderon Windows, executepython setup.py bdist_wheelon Linux, executepython3 setup.py bdist_wheelFeaturesspriteshardware-acceleratedsupports basic collision detectionsupports rotationsupports color adjustmenttilemapshardware-acceleratedsupports adjustable viewportsupports scrollingimplements viewport cullingsupports collision detectionTested OnPython 3.8.7 and Kivy 2.0.0 for Windows 10 (64-bit)Python 3.6.8 and Kivy 1.11.0 for Windows Vista (32-bit)Python 3.8.5 and Kivy 2.0.0 for Lubuntu 20.04 (64-bit)MacOS X CatalinaAndroid 10 (experimental)Status
Package: kvcomcon
kvcomcon: key-value-comment configExample:::# My cool configfoo = barsentence = This is my cool sentence.The config format is line-based. Each line must be one of these:1. A comment line (the first non-whitespace character is '#'2. An empty line (whitespace is allowed)3. somekey = somevalueLeading and trailing whitespace is stripped from each line, as well asaround each key and value. For example, these two lines are equivalent:::"key=val 123""  key  = val 123     "
Package: kv-deta
Key-Value Model for DetabaseAPIconstructorclass KVModel(dict)example:from kv_deta import KVModel 

class Example(KVModel):
  class Config(KVModel.Config):
    deta_key = DETA_BASE_KEY
    # or
    deta = Deta(DETA_BASE_KEY)

    table_name = "my_kv_table"	# optional

    time_to_live = None  #   int seconds from now(). takes precedence over expire!
    expire = None  #   ISO string or int unix timestamp

    hash = my_hash_function	# default lambda x: hashlib.sha256(str(x).encode('utf8')).hexdigest()kv = Example({"key":"value"})updatekv.update({"k2":42})as in dictionarysavekv.save()commitalldata to detabasegetmixed dict.get(key) & deta.get(key) & dict.setdefault(key, default)kv.get(key="some key"[, default="default"])returns value fromdeta.get(key)or set it bydefaultif deta.get() returnedNonedeletekv.delete(key) -> selfdeletekeyfrom self & basekeyskv.keys(param=None) -> Listreturn list(key)incr, decrbased on Deta.Base.Util.incremental()kv.incr(key="counter"[, quantity=1])returns incremented value forkey.
if detabase have not specifickey, creates it and setvalue=quantityquery@classmethod
kv.query(param=criteria, limit=1000, last=None) -> Dictreturn dict(key:value)query param see alsohttps://deta.space/docs/en/build/reference/deta-base/queriesreadkv.read(param=criteria, limit=1000, last=None) -> selfcall query() and replacesalldata incurrentmodel objectTable Structfielddescriptionkeyhash(key)pathorigin key, hidden fieldvaluedataNewsv0.2.1, v0.2.2 method delete(), refactorv0.1.23 TTL addedv0.1.22bigintbug isnot a bugBase currently supportsmaximum 16 digitnumbers (integers and floating points),
pleasestore larger numbers as a string.@classmethod query() -> dictbyrules.
you can search key(s) like an other ordinary fieldsread()uses query() and replaces all data in current model without creating new dictionary objectv0.1.20 methods implementation exchangedincr2 <--> incrbug detected: Deta.Base.Util.incremental() doesn't work withbigintv0.1.18 setup repairedv0.1.17 hotfixv0.1.16query(), keys()v0.1.15rename()v0.1.13 backward compatibility brokenv0.1.12incr()rewritten with Deta.Base.Util.incremental()v0.1.11incr(key: str, quantity=1),decr(key: str, quantity=1): return incr(key, -quantity)v0.1.8get()fixget(key, default)save()LicenseIt's opensource and free software, see theLICENSEfor more detailssimilar projectscsv-detasql-detaTODOsave() refactordelset()TTLincr(),decr()query()return dictrename(key, new_key)keys()get keys listget(key)
Package: kvdiff
KVDiffCompare two text files by key columnsGetting StartedLet's say we have two text files maintaining a list of systems with versions.$ cat a.txt
MacOS 10.12
Windows 10
Ubuntu 16$ cat b.txt
MacOS 10.14
Windows 10
Manjaro 17To see which systems are new inb.txt, deleted inb.txt, and version changed inb.txt, runkvdiff -k1 a.txt b.txtin the terminal:$ kvdiff -k1 a.txt b.txt
* MacOS 10.12
> MacOS 10.14
+ Manjaro 17
- Ubuntu 16KVDiff reports that MacOS has a version change, new system Manjaro with version 17 is added, and Ubuntu is deleted.RequirementsPython >=3.5sort(1)Installation$ pip install kvdiffUsageRunkvdiff --helpfor more infomationLicenseMIT licensedHow It WorksKVDiff: Compare Two Large Text Files by Key Columns
Package: kvdl
Keyvault-Cert-DownloaderYet another Azure keyvault cert downloader.UsageAt the moment, this will:Read all of the certificate bundles from a configured instance of Azure Key VaultConvert them to PEM encodingOutput them to a configured location on diskThe tool satisfies a very specific need we have @faithlife. More functionality and flexibility coming soon (maybe)!Example configkeyvaults:my-vault:output:dir:/tmp/crtext:.pemDevelopmentVenv SetupUse Python 3.8:/usr/local/opt/python@3.8/bin/python3-mvenv.venvBootstrapsource.venv/bin/activate
pipinstall-rrequirements.txt
Package: kvdr
kvdrKey/Value Dump and Restore (KVDR)Simple tool to dump and restore data from Key/Value (Redis like) databases.Requirementsredis-pydocoptInstallationQuick (Linux)Assuming you have pip3 already installed (CentOS:yum install python3installs python3-pip too):pip3 install --user kvdr
kvdr --help
# or, in the case .local/bin is not in your $PATH:
# .local/bin/kvdr --helpQuick (Linux, Git)You may want to install a version that has not been published to PyPI.
In this case please do the following:# Create virtual environment
python3 -m venv $HOME/.kvdr
# Activate it
. $HOME/.kvdr/bin/activate
# Install kvdr, version 0.9.8
pip3 install git+https://gitlab.com/dejan/kvdr.git@0.9.8#egg=kvdrIn theory every useful change I made in kvdr is tagged with a new (semantic) version, so it may be that
at the time you read this there were some newer releases, so please check the GitLab page.Installation on Windows/ReactOSshould be as straightforward. I suggest you
tryMSYS2. In MSYS2, with Python3 packages installed, the installation steps
should be the same as above.How to useUsekvdrorkvdr --helpto see the list of available options. It should look something like:KVDR - Key/Value Dump and Restore

Usage:
  kvdr dump [--file=<file_name> | --screen] <redis_url>
  kvdr load (--file=<file_name>) [--dry-run] <redis_url>
  kvdr --dry-run
  kvdr (-h | --help)
  kvdr --version

Options:
  -h --help           Show this screen.
  --version           Show version.
  --screen            Dump to the console instead of file.
  --file=<file_name>  A file where we store dumped Redis records. Default: "redis.dump"
  --dry-run           A trial run. Works only for the loading operation.

Examples:
  kvdr dump --file=redis13.backup redis://admin:BABADEDAuikxWx0oPZYfPE3IXJ9BVlSC@localhost:6379/13
  kvdr load --file=redis13.backup redis://:BABADEDAuikxWx0oPZYfPE3IXJ9BVlSC@localhost:6379/3Data dumpredis-cli -h localhost -a BABADEDAuikxWx0oPZYfPE3IXJ9BVlSC -n 13 < var/test-data.redis
kvdr dump --file=redis-dump.txt redis://admin:BABADEDAuikxWx0oPZYfPE3IXJ9BVlSC@localhost:6379/13If you have just cloned the kvdr repository, but not installed anything, you can run it inside the working
directory:cd <path to the working directory>
python3 -m venv $HOME/.kvdr
# Activate it
. $HOME/.kvdr/bin/activate
PYTHONPATH=. python3 -m kvdr.kvdr dump --file=redis-dump.txt redis://admin:BABADEDAuikxWx0oPZYfPE3IXJ9BVlSC@localhost:6379/13Data loadLoad theredis.dumpfile data into the redis://localhost/3 database# Let's first delete all the data in the existing database:
redis-cli -h localhost -a BABADEDAuikxWx0oPZYfPE3IXJ9BVlSC -n 3 | echo "flushdb\nquit"
# Load the data    
kvdr load --file=redis.dump redis://localhost/3This does not work (yet):kvdr load --dry-run --file=redis.dump file:///blah.datCreditsAndy McCurdy- for writing fantastic Python library for Redis.FutureAdd support for memcachedAdd support for DynamoDBCheck whether kvdr works out-of-box withKeyDBDesign an API so users can write Dumper/Loader implementations of their own.Bug reports and feature requestsPlease file anissue on GitLab.
Package: kvector2
#vector2.pyModule to handle vectors in a 2D space.vector2.Vector :Represent a 2D vector. It can be interpreted as a tuple of length 2 like (x, y).You can declare a vector by passing :Vector()-> null vectorVector( (x, y) )-> vector of coordinates (x,y)Vector( angle, length )-> vector of lengthlengthpointing towardsanglein radiansVector( angle=a, len=l )-> same asVector(a, l)Vector( coords=t )-> same asVector(t)Vector( x=x, y=y )-> same asVector((x, y))Positional arguments, if they’re given correctly, will override keyword arguments.Thexandywill overridecoords, wich will overrideangleandlen.You can add/substact two vectors together, or multiply/divide them by a scalar.vector.length()-> return the distance from the origin to the extremity of the vector.You can compare a vector to another or to a number(the length of the vector(s) will be used).vector.xint()-> return the integer part of the x-coordinate.vector.yint()-> same, but with the y-coordinate.vector.as_tuple()-> convert to a tuple.vector.as_int_tuple()-> shortcut for(vector.xint(), vector.yint()).vector.is_equal_to(other)-> with the==or the!=operators, two vectors will be compared by their length. useis_equal_toto test if they’reexactlythe same.