Saravanan666/pypi-org huggingface dataset:
Package: humlab-westac
The Welfare State Analytics Text Analysis RepositoryThis repository contains various Jupyter Notebooks for exploring the curated corpus of Riksdagens Protocol.About the ProjectWelfare State Analytics. Text Mining and Modeling Swedish Politics, Media & Culture, 1945-1989 (WeStAc) is a digital humanities research project with five co-operatings partners: Umeå University, Uppsala University, Aalto University (Finland) and the National Library of Sweden.The project will digitise literature, curate already digitised collections, and perform research via probabilistic methods and text mining models. WeStAc will both digitise and curate three massive textual datasets—in all, Big Data of almost four billion tokens—from the domains of Swedish politics, news media and literary culture during the second half of the 20th century.InstallationJupyterHub installationThewestac_hubrepository contains a ready-to-use Docker setup (Dockerfileanddocker-compose.yml) for a Jupyter Hub usingnginxas reverse-proxy. The default setup usesDockerSpawnerthat spawns containers as specified inwestac_lab, and Github for autorization (OAuth2). See the Makefile on how to build the project.Single Docker containerYou can also run thewestac_labcontainer as a single Docker container if you have Docker installed on your computer.HOWTO Prepare a new version om Riksdagens Protokoll CorpusPrerequisitesThe Riksdagen Protokoll corpus XML files have been tagged usingwelfare-state-analytics/pyriksprot_taggerThewelfare-state-analytics/pyriksprothas been used to process corpus metadata and speech corpus. (make full)Important! The configuration .env files has been updated with target corpus version.Create a default DTM (document-term-matrix)The commandmake default-riksprot-dtmwill create a DTM based on the settings found in 'opts/dtm_riksprot.yml`.Runmake
Package: hummer
# lightning[![Build Status](https://travis-ci.com/Jack-Kingdom/portalutils.svg?branch=master)](https://travis-ci.com/Jack-Kingdom/portalutils)portal access utils.
![portalutils](https://raw.githubusercontent.com/wiki/Jack-Kingdom/portalutils/assets/portal.jpg)## Install`shell pip install portalutils `## Documentation
Check [wiki](https://github.com/Jack-Kingdom/portalutils/wiki) for details.## LICENSE
MIT
Package: hummingbird-dual-motor-driver
A dual motor driver for Birdbrain Technologies HummingbirdFree software: MIT licenseInstallationpip install hummingbird-dual-motor-driverYou can also install the in-development version with:pip install https://github.com/fmorton/hummingbird-dual-motor-driver/archive/main.zipDocumentationhttps://hummingbird-dual-motor-driver.readthedocs.io/DevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.5 (2022-10-10)First release on PyPI.
Package: hummingbird-joystick
Support for Birdbrain Technolgies Hummingbird joystickFree software: MIT licenseInstallationpip install hummingbird-joystickYou can also install the in-development version with:pip install https://github.com/fmorton/hummingbird-joystick/archive/main.zipDocumentationhttps://hummingbird-joystick.readthedocs.io/DevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.1 (2022-10-10)First release on PyPI.0.0.3 (2023-01-20)Change to angle/direction rather than x,y coordinates.0.0.4 (2023-01-20)Add normalized_xy support.0.0.5 (2023-01-20)Simplify sys.path management for examples.
Package: hummingbird-joystick-calculator
Calculator for the hummingbird_joystick package converting xy coordinates from the joystick to left/right motor speeds.Free software: MIT licenseInstallationpip install hummingbird-joystick-calculatorYou can also install the in-development version with:pip install https://github.com/fmorton/python-hummingbird-joystick-calculator/archive/main.zipDocumentationhttps://python-hummingbird-joystick-calculator.readthedocs.io/DevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.1 (2022-10-10)First release on PyPI.
Package: hummingbird-led-button
LED button support for Birdbrain Technologies HummingbirdFree software: MIT licenseInstallationpip install hummingbird-led-buttonYou can also install the in-development version with:pip install https://github.com/fmorton/hummingbird-led-button/archive/main.zipDocumentationhttps://hummingbird-led-button.readthedocs.io/DevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.1 (2022-10-10)First release on PyPI.
Package: hummingbird-robot
A robot using Birdbrain Technologies Hummingbird using the hummingbird_joystick and hummingbird_dual_motor_driver
packages.Free software: MIT licenseInstallationpip install hummingbird-robotYou can also install the in-development version with:pip install https://github.com/fmorton/python-hummingbird-robot/archive/main.zipDocumentationhttps://python-hummingbird-robot.readthedocs.io/DevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.1 (2022-10-10)First release on PyPI.
Package: humo
humoA toolkit for non-programmer to wrangle the motion data measured by 3D motion analyzerDescriptionA toolkit for non-programmer to wrangle the motion data measured by 3D motion analyzerDEMO:FeaturesIntuitive operabilitySeamlessly from data shaping to analysisFor more information, seehumo -HP.RequirementnumpyscipypandasmatplotlibUsagequick startimporthumo# loading data and making humo objectdata=humo.dataIO.load_data()# open pkl filecfg=humo.dataIO.load_cfg()# open cfg.jsonobj=humo.motion.CoreMain(data,cfg)# make humo object# get right shoulder angleRsho=obj.getJointAngle("Rshoulder")# get multi datashoulder=obj.getJointAngle(["Rshoulder","Lshoulder"])shoulder.Lshoulder# getting Lshoulder angleshoulder.Lshoulder.x# getting Lshoulder x axis angleInstallationpipinstallhumoAnything ElseThe pickle data needed to create a humo object is created from a csv file.
By converting it to a pickle file, very fast data loading can be achieved.importhumo# Procedure to convert csv file to pkl filec2p=humo.Preprocess.convert2pkl()# opening csv filec2p.datacleansing()# cleansing csv datac2p.convert2pkl()# save csv file as pkl fileAuthorakira6LicenseMIT
Package: humon
humon-pyThis is a Python3 package for reading [Humon|https://github.com/spacemeat/humon] token streams.Installing humon-pyTo install and use in python:$pipinstallhumonUsagefromhumonimporthumont=humon.Trove.fromString('{foo:bar}')print(t.root['foo'])Developing humon-pyTo install humon-py and the tools needed to develop and run tests, run the following:$pipinstall-e.[dev]
Package: humongous
What is this?This is a pytest plugin, that enables you to test your code that relies on a
database connection to a MongoDB and expectes certain data to be present.
It allows you to specify fixtures for database collections in JSON/BSON or YAML
format. Under the hood we use themongomocklibrary, that you should
consult for documentation on how to use MongoDB mock objects. If suitable you
can also use a real MongoDb server.ConfigurationIf you don’t want to put your fixtures on the top-level directory of your package
you have to specify a directory wherehumongouslooks for your data definitions.To do so put a line like the following under thepytestsection of yourpytest.ini-file put a[pytest]humongous_basedir=tests/unit/fixtureshumongouswould then look for files ending in.yamlor.jsonin that
directory.You can also choose to use a real MongoDB server for your tests. In that case
you might also want to configure the hostname and/or the credentials if you
don’t want to stick with the default (localhost and no credentials). Use the
following configuration values in yourpytest.inito adapt the settings to
your needs:[pytest]humongous_engine=pymongohumongous_host=mongodb://user:passwd@server.tldhumongous_dbname=mydbnameBasic usageAfter you configuredhumongousso that it can find your fixtures you’re ready to
specify some data. Regardless of the markup language you choose, the data is provided
as a list of documents (dicts). The collection that these documents are being inserted
into is given by the filename of your fixutre-file. E.g.: If you had a file namedplayers.yamlwith the following content:-name:Mariosurname:Götzeposition:striker-name:Manuelsurname:Neuerposition:keeperyou’d end up with a collectionplayersthat has the above player definitions
inserted. If your fixture file is in JSON/BSON format you can also use BSON specific
types like$oid,$date, etc.You get ahold of the database in you test-function by using thehumongousfixture
like so:deftest_players(humongous):assert"players"inhumongous.collection_names()manuel=humongous.players.find_one({"name":"Manuel"})assertmanuel["surname"]=="Neuer"For further information refer to themongomockdocumentation.
Package: humor-langs
humor_langsTranslate your string to humorous text!What This Package Can Give YouSelf-WorthA Significant OtherSome Funny, Humorous Text. Haha!InstallationOperating SystemInstallation via pipWindowspip install humor-langsMacOS/Linuxpip3 install humor-langsExamplesConverting a list of sentences to owoimporthumor_langshumor_langs.owofy(["what are you doing over there?","hello there reader!","See you in the terminal!"],_print=True)This will return...Hewoooooo >w< what awe u doing ovew thewe? O·w·O
Haiiiiii 0w0 hewwo thewe weadew! ^w^
*W* See u in the tewminyaw! ;;w;;Adding a list of sentencesclapemojis on every other wordfromhumor_langsimportclap_emojifierclap_emojifier(["what are you doing over there?","hello there reader!","See you in the terminal!"],_print=True)then this would return...what 👏 are 👏 you 👏 doing 👏 over 👏 there?
hello 👏 there 👏 reader!
See 👏 you 👏 in 👏 the 👏 terminal!NOTE:When testing it out, if the outputs look like some random question marks,then your console probably doesn't support emojis.Converting a list of sentences to a kind-of strong british accentfromhumor_langsimportstrong_british_accentstrong_british_accent(["what are you doing over there?","hello there reader!","See you in the terminal!"],_print=True)then this'll return...whaht -ahe you doing ov-ah th-ahe?
helloh th-ahe reahd-ah!
Seah you in the t-ahminahl!(yea, it's kind of bad~)Converting a sentence to emojisfromhumor_langsimporttext_to_emojitext_to_emoji("hello world! <3",_print=True)then this'll return...🇭️ 🇪️ 🇱️ 🇱️ 🇴️  🇼️ 🇴️ 🇷️ 🇱️ 🇩️ ❗️  ❤️LicenseThis package iscurrently under the MIT License.Click hereto learn more about the license.
Package: humpday
humpday derivative-free optimizers (docsandElo ratings)Deriv-free optimizers from many packages in a common syntax, with evaluationThere's acolab notebookthat recommends a black-box derivative-free optimizer for your objective function.About fifty strategies drawn from various open source packages are assignedElo ratingsdepending on dimension of the problem and number of function evaluations allowed.Hello and welcome to HumpDay, a package that helps you choose a Python global optimizer package, and strategy therein, fromAx-Platform,bayesian-optimization,DLib,HyperOpt,NeverGrad,Optuna,Platypus,PyMoo,PySOT, Scipyclassicandshgo,Skopt,nlopt,Py-Bobyaq,UltraOptand maybe others by the time you read this. It also presentssomeof their functionality in a common calling syntax.Cite or be citedPull requests atCITE.mdare welcome. If your package is benchmarked here I'd like to get this bit right.InstallSeeINSTALL.mdShort version:pip install humpday
pip install humpday[full]RecommendationsPass the dimensions of the problem, function evaluation budget and
time budget to receivesuggestionsthat are independent of your problem set,from pprint import pprint 
    from humpday import suggest
    pprint(suggest(n_dim=5, n_trials=130,n_seconds=5*60))wheren_secondsis the total computation budget for the optimizer (not the objective function) over all 130 function evaluations. Or simply pass your objective function, and it will time it and do something sensible:from humpday import recommend

    def my_objective(u):
        time.sleep(0.01)
        return u[0]*math.sin(u[1])

    recommendations = recommend(my_objective, n_dim=21, n_trials=130)Points raceIf you have more time, callpoints_raceon a list of your own objective functions:from humpday import points_race
    points_race(objectives=[my_objective]*2,n_dim=5, n_trials=100)See thecolab notebook.How it worksIn the background, 50+ strategies are assignedElo ratingsby sister repooptimizer-elo-ratings. Oh I said that already. Never mind.ContributeBy all means contribute more tooptimizers.Articles(most recent)HumpDay: A Package to Take the Pain Out of Choosing a Python Optimizer.Comparing Python Global Optimizers.
Package: humps
Convert any string to camelCase.DescriptioncamelCase starts with a lower case alphabetic character, the rest of the string contains alphanumeric characters. Any character case in the input is ignored. Any spaces in the input capitalise the following character if alphabetic, except for the first character. Any non-alphanumeric characters are ignored.InstallationShell:pipinstallhumpsPython:fromhumps.camelimportcaseprint(case('Hello, World!'))# Output: helloWorld
Package: humpty
For when you need an.eggbut all you have is a.whl.DescriptionHumpty is a command-line utility to convert Python binary wheel
packages to eggs.Currently, the tool is in a “works for me” state.  (It is not
guaranteed to work for you.)Development takes place ongithub.
The package is installable fromPyPIObsolescenceNote that recent developments may have made this utility unnecessary.
As ofsetuptools38.2.0,easy_installsupport installing
wheels as unzipped eggs. Also,zc.buildout, as of 2.10.0 takes
advantage of this to support installation from wheels.SynopsisThe humpty “man page”:$ humpty --help
Usage: humpty [OPTIONS] WHEELS...

  Convert wheels to eggs.

Options:
  -d, --dist-dir DIR  Build eggs into <dir>.  Default is <cwd>/dist.
  --help              Show this message and exit.Suppose you need an egg of a distribution which has only been uploaded
to PyPI as a wheel:$ pip install --download . publicsuffixlist
[...]
  Saved ./publicsuffixlist-0.2.8-py2.py3-none-any.whl
Successfully downloaded publicsuffixlist

$ humpty -dist-dir . publicsuffixlist-0.2.8-py2.py3-none-any.whl
Converting publicsuffixlist-0.2.8-py2.py3-none-any.whl to publicsuffixlist-0.2.8-py2.6.egg

$ easy_install publicsuffixlist-0.2.8-py2.7.eggReferencesPEP 427- The Wheel Binary Package Format 1.0PEP 491- The Wheel Binary Package Format 1.9PEP 241- Metadata for Python Software PackagesPEP 314- Metadata for Python Software Packages v1.1PEP 345- Metadata for Python Software Packages 1.2PEP 426- Metadata for Python Software Packages 2.0PEP 459- Standard Metadata Extensions for Python Software PackagesSetuptools:The Internal Structure of Python EggsAuthorsJeff DairikiHistoryRelease 0.2.1 (2017-12-18)CompatibilityDrop support for python 3.3.PackagingInclude tests in sdist.TestingTest with wheel version 0.18 (among others.)Increase test coverageRelease 0.2 (2017-11-08)Python 2.6 is no longer supported.  We now test under cpython 2.7
and cpython 3.3 through 3.6.Changed BehaviorThe strict check for wheel binary compatibility with the current platform
has been removed.  Now a warning is printed in this case.
When running under py35 or py36, distlib sometimes falsely reports
that some wheels are not binary compatible. See distlib ticket#93.Bugs FixedFixEggInfo_Legacy.requiresto work with recent versions ofdistlib.  Withdistlib<=0.2.4,distlib.wheel.Wheel.metadata.run_requiresis a list of strings,
taken from lines of the RFC822 style metadata.  With recent versions
ofdistlib,run_requiresis a list of dicts in the “JSON”
format described inPEP 426.  This addresses#1.Always create eggs withzip_safe=False.  There currently seems
to be no robust way to determine whether a package is zip_safe from
its wheel. See#3for further discussion.
(Thank you to immerrr.)Fix parsing of markers inEggInfo_Legacy.requires.  Apparently,
asofdistlib==0.2.6,distlib.markers.interpretno longer
handles leading whitespace in the marker string well.Fix failing testtest_humpty:TestScriptCopyer.test_copies_script.
Apparently,distlib.markers.interpret==0.2.6now just prepends
the new hashbang line to the copied script, but does not remove
the original hashbang.Release 0.1 (2015-07-16)Initial release.
Package: humu1us-cipher
Encryption and decryption tools. Cipher mix AES encryption with base64 encode generating plain text encrypted files.Usagevariables:>>>importcipher>>>cipher.encrypt("encryption_password","something to encrypt!")'WDJoMWJYVXhkWE5mWlc1algxOGNSc2hFT1o2ZGRBOGhoWnByQjYzZnZBYlp3N2ZKZmVDTEw2V1ZEMWlhZ0ZyZDVpSnpVZDll'>>>importcipher>>>encrypted=cipher.encrypt("encryption_password","something to encrypt!")>>>cipher.decrypt("encryption_password",encrypted)'something to encrypt!'files:>>>importcipher>>>txt="file content to encrypt!">>>cipher.write("/tmp/file.encrypted","encryption_password",txt)>>>importcipher>>>cipher.read("/tmp/file.encrypted","encryption_password")'file content to encrypt!'ACredentialsclass can be used to handle secrets stored inJSONformats:>>>importjson>>>secrets={..."db_dsn":"mysql://user:pass@host:port/dbname",..."api_token":"some token"...}>>>cipher.write("/tmp/secrets","encryption_password",json.dumps(secrets))>>>>>># so, in your app you can do something like this:>>>importcipher>>>cred=cipher.Credentials("/tmp/secrets","encryption_password")>>>cred.db_dsn'mysql://user:pass@host:port/dbname'>>>cred.api_token'some token'Generating keysThere are a lot of ways to create keys but a good easy to use way to create non-easy to remember keys is using/dev/urandom, almost on Unix systems. For example:dd if=/dev/urandom bs=16 count=1 | base64 > /path/to/key_fileThecountparameter is the number of blocks to read and write, while thebsparameter is the size of each block.CLIThere is also available a nice command line. Just installcipherand start using it!$ ciphercmd-vwill let you know it is ready to be used.InstallationPyPi:$ pip install humu1us-cipherDevelopment version:$ git clone git@github.com:humu1us/cipher.git
$ cd cipher
$ pip install -e .ContributionContributions are welcome! Feel free to report bugs or open an issue if you feel a new feature is needed. Pull requests are welcome!
Package: hund
hundImplement Hund's rules in Python.Copyright noticeCopyright (C) 2013-2023 Daniel Jung.
Contact:proggy-contact@mailbox.orgThis program is free software; you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by the Free
Software Foundation; either version 2 of the License, or (at your option)
any later version.This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for
more details.You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
Package: hun-date-parser-nsoma97
Hungarian Date ParserA tool for extracting datetime intervals from Hungarian sentences and turning datetime objects into Hungarian text.Install and try the package withpip install hun-date-parser.:fire: UsageIf not specified otherwise, relative dates (eg.: tomorrow, next week, etc.) are calculated relative to the current datetime, at the time when the DatetimeExtractor is instanciated.fromhun_date_parserimportDatetimeExtractordatetime_extractor=DatetimeExtractor()datetime_extractor.parse_datetime('találkozzunk jövő kedd délután!')# {'start_date': datetime.datetime(2020, 12, 29, 12, 0), 'end_date': datetime.datetime(2020, 12, 29, 17, 59, 59)}datetime_extractor.parse_datetime('találkozzunk szombaton háromnegyed nyolc előtt két perccel')# {'start_date': datetime.datetime(2020, 12, 26, 7, 43), 'end_date': datetime.datetime(2020, 12, 26, 7, 43, 59)}The date parser is also capable of parsing explicit intervals from the text even when only one side of the interval is specified.datetime_extractor.parse_datetime('2020 decemberétől 2021 januárig')# {'start_date': datetime.datetime(2020, 12, 1, 0, 0), 'end_date': datetime.datetime(2021, 1, 31, 23, 59, 59)}datetime_extractor.parse_datetime('2020 decemberéig')# {'start_date': None, 'end_date': datetime.datetime(2020, 12, 31, 23, 59, 59)}The library is also capable of turning datetime objects into their Hungarian text representation.fromdatetimeimportdatetimefromhun_date_parserimportDatetimeTextualizerdatetime_textualizer=DatetimeTextualizer()datetime_textualizer.generate_candidates()datetime_textualizer.generate_candidates(datetime(2020,12,20,18,34),time_precision=2)# {'date': ['ezen a héten vasárnap', '2020 december 20'],#  'times': ['tizennyolc óra harmincnégy perc', '18:34', 'este hat óra harmincnégy perc', 'este fél 7 után 4 perccel']}:pencil: LicenseThis project is licensed underApache-2.0license. Feel free to use it in your own projects.:wrench: ContributeAny help or feedback in further developing the library is welcome!
Package: hundlab-MAT
Macrophage Anlaysis Toolkit (MAT)This tool was documented inour paperon marcophage and fibrosis quantificationHundlab Website:hundlab.orgPyPI:pypi.org/project/hundlab-MATGithub:github.com/hundlab/MATSetupWindowsPython 3 will need to be installed prior to setting up MAT, preferably any python
greater than 3.7. Python 3 can be downloaded from thepython website.
The x86-64 executable installer is reccommended, as the default install configuration
will set python to open .py files by double clicking. If it is installed correctly opening
cmd or powershell window and typingpy --versionwill print the installed python
version.Install MAT by opening a cmd or powershell window and runningpy -m pip install hundlab-MAT, this should install MAT and all of its dependancies.Once MAT has been installed it can be run via cmd, powershell or the start menu. To run
typeMacrophageAnalysisToolkit.py. To create a desktop shortcut typeMacrophageAnalysisToolkit.pyinto the start menu selectCopy full path, then on the
Desktopright-click->new->new shortcutand paste the path when it askes for a
path.If MAT does not run above as described this means that the python scipts directory has
not been added to the windows path. To find the install location of python typepy -0pthis will give the location of the python executable. In the same directory
as python.exe is a Scripts directory and theMacrophageAnalysisToolkit.pywill be in
there. Once the MAT script has been found, a shortcut can be made to it directly and
placed on the desktop.Note that it may take some time for MAT to start and it may be slow with larger images.
On some machines the calibration widgets are especially slowMac/LinuxPython 3 will need to be installed prior to setting up MAT. Python 3 can be
installed via your package manager in linux. If it is installed correctly
opening a terminal and typingpython --version(in some distributions such as Ubuntu
the command is python3) should print the python version. It may also be necessary
to install Qt5. On unbuntu the package isqt5-default.Install MAT using pip:python -m pip install hundlab-MATTo run MAT use the commandMacrophageAnalysisToolkit.py.UsageTODO!! For now see the paper.