Saravanan666/pypi-org huggingface dataset:
Package: measurements
What is this?This is a collection of Python modules containing functions to handel measurements.InstallationThis package can be installed using pip (recommended way):pip3 install measurementsor by downloading and running:python3 setup.py installWeb sitesThe source code of this package is hosted on:https://github.com/jor-/measurementsA Python wheel is available on:https://pypi.python.org/pypi/measurementsAuthorJoscha Reimerjor@informatik.uni-kiel.deCopyrightCopyright (C) 2011-2016  Joscha Reimerjor@informatik.uni-kiel.deThis 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 3 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, see <http://www.gnu.org/licenses/>.
Package: measurement-stats
A statistical package for measurement and population statistics that
incorporate measurement uncertainties and error propagation.Installation:pip install measurement_statsError PropagationSay, for example, that we have measured a rectangle to be 11 +/- 0.4 centimeters
wide and 8 +/- 0.3 centimeters long. We can then calculate the area with
uncertainty as follows:from measurement_stats import ValueUncertainty

width = ValueUncertainty(11, 0.4)
length = ValueUncertainty(8, 0.3)

area = length * width

print('AREA:', area.label)
# $ AREA: 88 +/- 5For a more complicated example, consider the canonical physics 101 experiment
of trying to calculate the acceleration due to gravity using a pendulum. If a
student has setup a pendulum with a measured length of 92.95 centimeters and an
uncertainty of 0.1 centimeters and measured a period of that pendulum to be
1.936 seconds with an uncertainty of 0.004 seconds, the acceleration due to
gravity, with propagated uncertainty, can be determined as follows:from measurement_stats import ValueUncertainty

l = ValueUncertainty(92.95, 0.1)
T = ValueUncertainty(1.936, 0.004)

g = 4.0 * (math.pi ** 2) * l / (T ** 2)

print('Acceleration Due To Gravity:', g.label)
# $ Acceleration Due To Gravity: 979 +/- 4
Package: measurenary
MeasurenaryMeasurenary is a Python library for computing your suitable similarity matrix from your binary data.InstallationTo use Measurenary, first install it using pip:(.venv) $ pip install measurenaryGet startedTo get started, you can import the library and use theAgglomerativeBestMeasureorPairBestMeasureclass:importmeasurenary# Instatntiate a Measurenary objectaggbs=measurenary.AgglomerativeBestMeasure()# Call the fit functionaggbs.fit(X)# Print out the resultprint(aggbs.get_result())
Package: measure-noise
measure-noiseMeasure how our data deviates from normal distributionBranchStatusCoveragemasterdevInstallpip install measure-noiseUsageThedeviance()method will return a(description, score)pair describing how the samples deviate from a normal distribution, and by how much.  This is intended to screen samples for use in the t-test, and other statistics, that assume a normal distribution.SKEWED- samples are heavily to one side of the meanOUTLIERS- there are more outliers than would be expected from normal distributionMODAL- few samples are near the mean (probably bimodal)OK- no egregious deviation from normalN/A- not enough data to make a conclusion (akaOK)Examplefrom measure_noise import deviance

>>> desc, score = deviance([1,2,3,4,5,6,7,8])
>>> desc
'OK'Developmentgit clone https://github.com/mozilla/measure-noise.git
cd measure-noise
pip install -r requirements.txt
pip install or tests/requirements.txt
python -m unittest discover testsWindowsYou must download thescipyandnumpybinary packages.
Package: measurer
MeasurerEasily measure Python function performanceInstall$ pip install measurerUsageimportmeasure@measure.time(repeats=100,copy=False,gc_off=True)defa():pass# Your logic hereprint(a())# 6.700000000005313e-06defb():pass# Your logic hereprint(measure.time(b,repeats=100,copy=False,gc_off=True)())# 6.199999999997874e-06GoalCurrently, this module contains only one decorator measuring function execution time. The goal was to make performance evaluation extremely easy for non-experienced programmers, who wants to check how much resources their programs/solutions take.
As a subject for future development, other types of measurers could be implemented (e.g. memory, recursive function calls etc.)DetailsWhy not"timeit"?Timeit is not suitable for function calls with arguments. Thus, one has to wrap a tested function with another function (without arguments) and evaluate redundant function calls (which sometimes causes big overhead).We still perform redundant calls...Yes. Ideally, we have to analyze syntactic tree and create some sort of "inline" method call. However, this is a hobby module, so we don't push towards ideal implementation.Why do  we dump parameters with Pickle?Packages like "msgpack" or "marshal" show comparable performance (and time to time they are faster), but the difference is not significant. So we use pickle, cause it's a built-in package (we try to leave the module simple).
Package: measures
A python library to send application metrics using UDP.InstallationpipinstallmeasuresUsagecountfrommeasuresimportMeasuremeasure=Measure('myclient',('localhost',1984))measure.count('mymetric',dimensions={'name':'john'})time (measure time spent on a given block)importtimefrommeasuresimportMeasuremeasure=Measure('myclient',('localhost',1984))withmeasure.time('mymetric'):# do some slow operation:time.sleep(3.14159)importtimefrommeasuresimportMeasuremeasure=Measure('myclient',('localhost',1984))withmeasure.time('mymetric')asdimensions:# do some slow operation:time.sleep(1.61803)# add any relevant information, if necessary:dimensions['relevant_info']='pertinent_info'sendfrommeasuresimportMeasuremeasure=Measure('myclient',('localhost',1984))dimensions={'time':10.1,'relevant_info':pertinent_info}measure.send('mymetric',dimensions)multiple destinationsMetrics can be sent to more than one backendfrommeasuresimportMeasuremeasure=Measure('myclient',[('backend.host.1',1984),('backend.host.2',1984)]ContributingSet up your environmentgitclonehttps://github.com/globocom/measures.gitcdmeasuresmkvirtualenvmeasurespipinstall-rtest_requirements.txtRun the testsmaketestsWrite tests for your new feature or bug fixWrite needed code changesIterate, have fun :)Make a pull request with your changesWho do I talk to?File an issue athttps://github.com/globocom/measuresor contact us atbusca@corp.globo.com
Package: measuring-tools
Measuring ToolsA Python Module to help deal with measurments in an object oriented way.An Object can be converted from one measurment to another.frommeasuring_tools.lengthimportLength# Convert From One Length To Anotherlength1=Length(value=1,measurement='yard')length2=length1.to_meter()print(length2)# OutputLength(value=0.9144,measurement='meter')Two objects are designed to interact with one another even if measurments are different.Example:frommeasuring_tools.lengthimportLength# Two Lengths - One In Meters, One In Yardslength1=Length(value=1,measurement='meter')length2=Length(value=1,measurement='yard')print(length1+length2)# OutputLength(value=1.9144,measurement='meter')In the example above, length two is converted from yard to meter and then added to length1. The output is a new object separate from length1 and length2.Inplace operations are also available.frommeasuring_tools.lengthimportLength# Inplace Subtractionfootball_field=Length(value=100,measurement='yard')football_field-=25print(football_field)# OutputLength(value=75,measurement='yard')In the example above, the value of football_field is modified directly. The output is the same as object.
Package: meatgen
Meatspace Password GeneratorGenerate passwords from real world phenomenaUsageusage: meatgen [-h] [-d DELIMITER] [--wordlist WORDLIST] key [key ...]

Generate passwords from real world phenomena

positional arguments:
  key                   A sequence of keys from the wordlist

optional arguments:
  -h, --help            show this help message and exit
  -d DELIMITER, --delimiter DELIMITER
                        The string that separates keys and values in the
                        wordlist
  --wordlist WORDLIST   Path to a file container a wordlistThe wordlist is also accepted overSTDIN.WordlistA wordlist is simple a textfile containing lines in the form of "{KEY}{DELIMITER}{VALUE}\n", this list is parsed at the beginning of execution and used to generate the output.
Any lines not matching this format will simply be ignored.Typically each password generation technique comes with it's own wordlists. The most well known isdiceware, but alternative techniques exist as well, such aspokerware.Examples$ meatgen --wordlist /home/example-user/Documents/pokerware-formal.txt ACADD ACTCC 3C4CH 5STHS
abide anemia fake peace
$ cat /home/example-user/Documents/pokerware-formal.txt | meatgen ACADD ACTCC 3C4CH 5STHS
abide anemia fake peace
$ meatgen --wordlist /home/example-user/Documents/diceware.wordlist.asc 11136
abbot
Package: meatoo
ContentsSummaryInstallationRequirementsChangelogSummaryMeatoois a website which shows which packages in Gentoo Linux need a version bump. The database queries Freshmeat, The Cheese Shop and other sources for its information. The meatoo command-line client
uses an XML-RPC interface.Usage Examples:$ meatoo -m python
     List all packages owned by the Python herd needing a version bump.

$ meatoo -l
     List latest 20 packages needing a version bump.

$ meatoo -c dev-python/cherrypy
     Check if an exact category/package needs a version bump.InstallationYou can install the meatoo client withemergeapp-portage/meatooor install from thesubversion repositorywitheasy_installmeatoo==dev.As of 0.0.8 the meatoo client is in Gentoo’s Portage tree.RequirementsPython>=2.3Changelog0.1.1 - April 29, 2007
CherryPy 3.0 compatability (server)
Package: meatpy
Project DescriptionThe goal of this project is to provide a standard framework for processing and
analysing high-frequency financial data.MeatPy currently supports Nasdaq ITCH 5.0. It can easily be adapted to process event-time data from multiple financial exchanges
and formats.TeamMeatPy was created by Vincent Grégoire (HEC Montréal)
and Charles Martineau (University of Toronto). Javad YaAli (Polytechnique Montréal) provided valuable research assistance on the project.
Package: me-backup
me-backupInstallBaixar o pacote do PIP.$sudopython-mpipinstallme-backupPara testar a instalação, rode o comando de help:$ sudo python -m me_backup --help   
    Usage: python -m me_backup [OPTIONS] COMMAND [ARGS]...

    Options:
    --help  Show this message and exit.

    Commands:
    install  Create needed files (run with sudo).Caso não exista nenhuma instalação anterior em/etc/me-backup, simplesmente chame o módulo dentro da instalação de python do sistema usando sudo. Isso irá abrir um formulário para instação dos recursos.Neste caso, é exigido uso de privilégio, porque o pacote irá realizar alterações na pasta/etc/me-backupe no cron do usuário informado na instalação em/var/spool/cron/.$sudopython-mme_backupinstallMe-backupneverrunned,thisfollowstepswillcreatethetoolfolderandconfigfileinto/etc/me-backup!(needsudo)DefaultUser:[lucas]Usersshellrc:[/home/lucas/.zshrc]Taskfile:[/etc/me-backup/tasks.yaml]Logpath:[/etc/me-backup/mebk.log]Loglevel:[INFO]Defaulthost:[127.0.0.1]Defaultcrontabpath:[/var/spool/lucas]Pronto! Rodando o help novamente, outros comandos para uso serão listados.$sudopython-mme_backup--helpUsage:python-mme_backup[OPTIONS]COMMAND[ARGS]...Options:--helpShowthismessageandexit.Commands:generate_yamlCreateatasks.yamlmodelfile.print_rsyncReturnthersynccommandrun_nowRunthebackuptasksrightnow.scheduleSchedulethetaskstorunusingyourtimeconfigurations.Dentro da pasta/etc/me-backupo arquivotasks.yamlserá criado. Nele existe uma tarefa de modelo pré-configurada:tasks:-name:backup homeslug:bkp_homesrc:/home/lucas/Arduinoremote_src:Falsedst:/mnt/storage/backup/TESTE/dst1/Arduinoremote_dst:Falsecopy_config:type:syncwake_on_lan:enabled:Falsemac_address:'d8:9c:67:07:87:e3'frequency:shortcut:dailyexclude:extensions:-txtfolder:-.ssh
Package: mebo
meboMebo is a python package to control theMebo Robotwith Python. It is currently in active development, so there might be breaking changes. Some basic usage is defined below, but more extensivedocumentation is available at ReadTheDocs.NoteThis project is not associated with the official Mebo project or its owners, Skyrocket LLC.NoteThis package and the associated modules have been tested on Mebo version 1only.Installationpip install meboQuickstartSome basic usage is below. The API will change and limited documentation exists, but it works for getting started.frommeboimportMebom=Mebo(auto_connect=True)# discover and connect automatically!m.move('n',speed=255,dur=1000)# move forward at max speed for 1 secondm.arm.up(dur=1000)# move the arm up for one secondm.claw.open(dur=1000)# open the claw for one secondDevelopmentRequirements:python >= 3.6To get started with the project:git clone https://github.com/crlane/python-mebo.git
python -m venv mebo-venv
. mebo-venv/bin/actvate
pip install -r requirements.txt
pip install -e .To run the tests:pip install -r test_requirements.txt
py.testTodo[ ] Cleaner API (better subclasses, kwargs for component methods, no metaprogramming)[ ] Clean up kwargs inconsistency[ ] Better documentation[ ] Better tests[ ] Media stream (multithreading or asyncio, http with <video> tag)
Package: mebuex
MebuexA setuptoolsExtensionandbuild_extwrapper for builds based on Meson.UsageMebuex assumes that the structure of a package is as follows:root
 | - builddir
 | ... some source layout to be compiled with Meson ...
 | - *packagename*
 |    | ... Python package layout handled by setup.py ...
 | - setup.py
 | - meson.buildThat is, the root directory of the package contains thesetup.pyfile,
themeson.buildfile, a Meson build directory (herebuilddir, but can be
configured), directories covering the sources to be built by Meson, and the
Python package source tree.The relevant part of this layout is thatsetup.pyandmeson.buildare
contained in the root directory, and that a designated build directory is
specified (need not exist before building). The Meson build file should contain
all relevant configuration to build a Python extension within the build
directory (herebuilddir). Thesetup.pyfile should be based on setuptools
and contain all relevant configuration for the Python part of the package.Within thesetup.pyfile, the Python extension built by Meson can then be
included using theMesonExtensionandbuild_extcommands supplied by Mebuex.
An example code would look like this (suppose that the Meson build would yield
an extensionmypackage.backend):fromsetuptoolsimportsetupfrommebueximportMesonExtension,build_extext=MesonExtension('mypackage.backend',builddir='builddir')setup(name='mypackage',version='1.0.0',author='Me',description='Or is it yours?',ext_modules=[ext],cmdclass={'build_ext':build_ext})Finding the NumPy include directoryMebuex ships with a Python script to discover the system NumPy includes when
building in the isolated build environment. Thegravelspooncommand that
helps break out of the build prison can be used in ameson.buildfile as
follows:incpath_np=run_command(gravelspoon)incdir_np=include_directories([incpath_np])InstallMebuex can be installed with Pip locallypipinstall.or from PyPI:pipinstallmebuexLicenseMebuex is licensed under the MIT license (see the LICENSE file).ChangelogThe format is based onKeep a Changelog,
and this project adheres toSemantic Versioning.[1.2.0] - 2023-12-29AddedAdd thegravelspooncommand to break out of the setuptools build isolation
and find the system NumPy includes.[1.1.7] - 2023-08-20AddedPrint error message stderr when re-raising assumed compilation error.[1.1.6] - 2023-08-20AddedPrint error message when re-raising assumed compilation error.[1.1.5] - 2023-06-02ChangedTry wiping the build directory if compilation within a previously setup
build directory fails.[1.1.4] - 2023-05-04ChangedBe more verbose ondestpatherror inbuild_ext.build_extension.[1.1.3] - 2023-04-14AddedAdd example project inexample/subfolder.[1.1.2] - 2023-04-13ChangedChange topyproject.tomlinstall workflow.[1.1.1] - 2022-10-05ChangedAdd a more informative error message if the directory to copy the built
extension to does not exist.[1.1.0] - 2022-07-13ChangedFixed empty lib being copied to wheel directory instead of Meson-compiled
lib.Fix handling of dots in compiled names (likely irrelevant).[1.0.0] - 2022-07-13AddedFirst version
Package: mebula
Mebula is a framework which you can use in your testing code to mock your calls to cloud providers’ APIs.
At the moment, Oracle’s OCI, Google Cloud and Microsoft Azure are supported.InstallationFor Microsoft Azure, install themebula[azure]package.For Google Cloud, install themebula[google]package.For Oracle’s OCI, install themebula[oracle]package.UsageAzureYou can use themock_azurecontext manager and then use the Azure functions as normal:fromazure.common.client_factoryimportget_client_from_json_dictfromazure.mgmt.computeimportComputeManagementClientfrommebula.azureimportmock_azuredeftest_azure():withmock_azure():credential=DefaultAzureCredential()client=ComputeManagementClient(credential=credential,subscription_id="foo")assertlist(client.virtual_machines.list("group"))==[]GoogleYou can use themock_googlecontext manager and then use the Google API functions as normal:importgoogleapiclient.discoveryfrommebulaimportmock_googledeftest_google(client):withmock_google():client=googleapiclient.discovery.build("compute","v1")assertclient.instances().list(project="foo",zone="bar").execute()=={}OracleYou can use themock_oraclecontext manager and then use the Oracleocifunctions as normal:importocifrommebula.oracleimportmock_oracledeftest_oracle():withmock_oracle():compute=oci.core.ComputeClient(config={})assertcompute.list_instances("foo").data==[]CoverageCoverage is very minimal at the moment. Only launching and listing instances is supported.
Package: mecab
Unofficial MeCab binding Python module for many OSs (Windows, macOS, and Linux)Official Japanese document about MeCab is available:https://taku910.github.io/mecab/Japanese document about this Python wrapper is available:https://qiita.com/yukinoi/items/990b6933d9f21ba0fb43Installation$ pip install mecabor$ python -m pip install mecabNOTE: If you use Python 64-bit on Windows,MeCab 64-bit binaryis required.If you encountered the error such asMeCab_wrap.cxx:178:11: fatal error: ‘Python.h’ file not found, please try the following command:$ CPLUS_INCLUDE_PATH=`python-config –prefix`/Headers:$CPLUS_INCLUDE_PATH pip install mecabUsage>>>importMeCab>>>t=MeCab.Tagger()>>>sentence="太郎はこの本を女性に渡した。">>>print(t.parse(sentence))太郎名詞,固有名詞,人名,名,*,*,太郎,タロウ,タローは助詞,係助詞,*,*,*,*,は,ハ,ワこの連体詞,*,*,*,*,*,この,コノ,コノ本名詞,一般,*,*,*,*,本,ホン,ホンを助詞,格助詞,一般,*,*,*,を,ヲ,ヲ女性名詞,一般,*,*,*,*,女性,ジョセイ,ジョセイに助詞,格助詞,一般,*,*,*,に,ニ,ニ渡し動詞,自立,*,*,五段・サ行,連用形,渡す,ワタシ,ワタシた助動詞,*,*,*,特殊・タ,基本形,た,タ,タ。記号,句点,*,*,*,*,。,。,。EOS>>>n=t.parseToNode(sentence)>>>whilen:>>>print(n.surface,"\t",n.feature)>>>m=m.nextBOS/EOS,*,*,*,*,*,*,*,*太郎名詞,固有名詞,人名,名,*,*,太郎,タロウ,タローは助詞,係助詞,*,*,*,*,は,ハ,ワこの連体詞,*,*,*,*,*,この,コノ,コノ本名詞,一般,*,*,*,*,本,ホン,ホンを助詞,格助詞,一般,*,*,*,を,ヲ,ヲ女性名詞,一般,*,*,*,*,女性,ジョセイ,ジョセイに助詞,格助詞,一般,*,*,*,に,ニ,ニ渡し動詞,自立,*,*,五段・サ行,連用形,渡す,ワタシ,ワタシた助動詞,*,*,*,特殊・タ,基本形,た,タ,タ。記号,句点,*,*,*,*,。,。,。BOS/EOS,*,*,*,*,*,*,*,*LicenseMeCab is copyrighted free software by Taku Kudo <taku@chasen.org> and Nippon Telegraph and Telephone Corporation, and is released under any of the GPL (see the file GPL), the LGPL (see the file LGPL), or the BSD License (see the file BSD).Also, this Python binding is under any of the GPL, the LGPL, or the BSD License.Changes0.996.2 (2020/02/11)Bugfix: memory leak for MeCab.Tagger().parseToNode()ContributingSeehttps://github.com/ikegami-yukino/mecab/blob/master/mecab/python/CONTRIBUTING.md
Package: mecab-cygwin
mecab-cygwinMeCabPython wrapper forCygwinbymecab-python3withmecab-cygwin64ormecab-cygwin32.UsageSeemecab-python3 page. UTF-8 only.InstallationOnly for Cygwin withgcc-g++python37-pippython37-devel:pip3.7installmecab-cygwin
Package: mecab-ko-dic
mecab-ko-dicThis is a Korean dictionary for the MeCab tokenizer, packaged for use in Python
withmecab-python3orfugashi.Should you use this?We (at Luminoso) think this is probably a better way to find tokens in Korean
words than just splitting the text on spaces would be. We also know that MeCab
wasn't designed for Korean. But it gives us the kind of tokens we need better
than other things we've tried.One reason we're packaging this is to use it inwordfreq, which needs to
have a reasonable set of consistent tokens so it can look up their frequencies,
and already uses MeCab for Japanese.If interoperability with things that already use MeCab is not your goal, you
probably have better options for Korean NLP than this.CreditsThe dictionary data was created by Yongwoon Lee and Yungho Yu. We've included it
as part of this package under the terms of the Apache License 2.0. The original
dictionary can be foundhere.The idea to package a MeCab dictionary as a Python repository, as well as the
code structure for doing so, come fromPaul McCann's ipadic package.UsageTo install:pip install mecab-ko-dicTo initialize with mecab-python3:import MeCab
import mecab_ko_dic
tagger = MeCab.Tagger(mecab_ko_dic.MECAB_ARGS)
print(tagger.parse("안녕하세요세계."))LicenseThe data we use, and this code repository itself, are released under the Apache
License 2.0. See the LICENSE.txt file included in this distribution.