Saravanan666/pypi-org huggingface dataset:
Package: manufacturing
PurposeTo provide analysis tools and metrics useful in manufacturing environments.Go to thedocumentation.Project MaturityPlots and project are reasonably mature at this point.  Calculations have been refined
and are in-line with commonly accepted standards.A major v2.0 update is coming to control charts and will be available shortly inmanufacturing.alt_vismodule.  For instance, instead of usingfrom manufacturing import x_mr_chart,
you would usefrom manufacturing.alt_vis import x_mr_chart.  The new API should
allow for a greater degree of flexibility with recalculation points and the ability
to relabel the axes.  Additionally, alternative axis labels will be able to be supplied.
These changes will eventually become "the way", but are to be considered experimental
until the v2.0 update.InstallationTo install frompypi:$>pip install manufacturingTo install from source download and install using poetry:$>poetry installBuilding$>poetry update
$>poetry buildUsageCpk VisualizationThe most useful feature of themanufacturingpackage is the visualization of Cpk.
As hinted previously, theppk_plot()function is the primary method for display of
Cpk visual information.  First, get your data into alist,numpy.array, orpandas.Series; then supply that data, along with thelower_control_limitandupper_control_limitinto theppk_plot()function.manufacturing.ppk_plot(data, lower_specification_limit=-2, upper_specification_limit=2)In this example, it appears that the manufacturing processes are not up to the task of
making consistent product within the specified limits.Zone Control VisualizationAnother useful feature is the zone control visualization.manufacturing.control_chart(data)There are X-MR charts, Xbar-R charts, and Xbar-S charts available as well.  If you call thecontrol_chart()function, the appropriate sample size will be selected and data grouped as
the dataset requires.  However, if you wish to call a specific type of control chart, usex_mr_chartxbar_r_chartxbar_s_chartp_chartContributionsContributions are welcome!RoadMapItems marked out were added most recently....Add use github actions for deploymentTransition topoetryfor releasesAddI-MR Chart(seeexamples/imr_chart.py)AddXbar-R Chart(subgroups between 2 and 10)AddXbar-S Chart(subgroups of 11 or more)Update documentation to reflect recent API changesAddp chartAddnp chartAddu chartAddc chartAdd automated testing (partially implemented)Gallery
Package: manufacturingcpkppk
PurposeTo provide analysis tools and metrics useful in manufacturing environments.I am slowly generating the documentation and, as that is maturing, I will begin to move information
from thisreadme.mdinto that location.  If you don't find something here, head over to thedocumentation.Project MaturityEvery effort is being made to ensure that the results are accurate, but the user is ultimately
responsible for any resulting analysis.The API should not be considered stable until v1.0 or greater.  Until then, breaking changes may
be released as different API options are explored.During thev0.X.Xversioning, I am using the package in my own analyses in order to find any bugs.  Once
I am reasonably satisfied that the package is feature complete, usable, and bug-free, I will break out
thev1.X.Xreleases.UsageVisualizations with Jupyter NotebooksVisualizations work approximately as expected within a jupyter notebook.data = np.random.normal(0, 1, size=30)  # generate some data
manufacturing.ppk_plot(data, lower_control_limit=-2, upper_control_limit=2)There is a sample jupyter notebook in the examples directory.Cpk VisualizationThe most useful feature of themanufacturingpackage is the visualization of Cpk.
As hinted previously, theppk_plot()function is the primary method for display of
Cpk visual information.  First, get your data into alist,numpy.array, orpandas.Series; then supply that data, along with thelower_control_limitandupper_control_limitinto theppk_plot()function.manufacturing.ppk_plot(data, lower_control_limit=-2, upper_control_limit=2)In this example, it appears that the manufacturing processes are not up to the task of
making consistent product within the specified limits.Zone Control VisualizationAnother useful feature is the zone control visualization.manufacturing.control_plot(data, lower_control_limit=-7.0, upper_control_limit=7.0)Features MapAnalysisPpk analysisPpk plots/histogramsCpk analysis/plot/histogram by subgroupIn-control/out-of-control analysis (do Ppk and Cpk converge to approximately the same value)Control chart plot(seeControl Chart Rules)Beyond limits violations highlighted(one or more points beyond the control limits)Zone A violations highlighted(2 out of 3 consecutive points in zone A or beyond)Zone B violations highlighted(4 out of 5 consecutive points in zone B or beyond)Zone C violations highlighted(7 or more consecutive points on one side of the average - in zone C or beyond)Trend violations highlighted(7 consecutive points trending up or down)Mixture violations highlighted(8 consecutive points with none in zone C)Stratification violations highlighted(15 consecutive points in zone C)Over-control violations highlighted(14 consecutive points alternating up and down)Gage R&R analysisUsabilityImport from CSVImport from MS ExcelCreate documentation usingsphinxGenerate reportsGalleryCurrently, no distinction is made between Ppk and Cpk, so the entire chart shows the Cpk.Some of the data for the zone control chard was manipulated in order to display the results.
Note that, if a phenomenon is not present within the data, then it will not be plotted at
all.
Package: manuscript
Manuscript helps you manage your python scripts and their dependenciesPython still is a scripting language, and it is awesome for
this. Moreover, we now have some great libraries that make writing
scripts even easier, like requests, docopt or pathlib. However, having
to install them system-wide, or start worrying about virtualenv for
just one script is annoying. Manuscript is here to help you handle that.Just add a line of the form#deps: requests docopt pathlibto your script,
and manuscript will install them in a virtualenv and create a wrapper for you.InstallYou can get it onpypiwith the usualpip install manuscript.You can also install manuscript using manuscript! For this, use this line get manuscript and its dependencies, and use manuscript to install itself:cd /tmp && wget https://bitbucket.org/pitrou/pathlib/raw/e39c980b59a9705fe60f24e36cb202771af88256/pathlib.py https://raw.github.com/docopt/docopt/0.6.1/docopt.py https://raw.github.com/madjar/manuscript/master/manuscript.py && python3 manuscript.py install -c manuscript.pyOnce it’s done, I recommend you add~/.manuscript/bin/to your path, to make it easier to access installed scripts.Manuscript requires python 3.UsageYou just wrotesome_awesome_script.pythat usesrequestsanddocopt, and you want to use it on your system without worrying about the dependencies. Just add this line somewhere in your script:#deps requests docoptThen run manuscript:manuscript install some_awesome_script.pyThis will install all the dependencies in a virtualenv and create a wrapper around the script as~/.manuscript/bin/some_awesome_script.The virtualenv will use the interpreter mentioned in the script’s shebang, falling back topythonif none is found. You can force an interpreter with the-ioption, like so:manuscript install some_awesome_script.py -i pypyIf you don’t want a script to share the default virtualenv with other scripts, you can specify a virtualenv name in which to install the script’s dependencies (it will be created if needed):manuscript install some_awesome_script.py -e awesome-venvIf you want to reuse an env created by virtualenv-wrapper, you can passworkon:NAMEas the environment name. Manuscript will use theWORKON_HOMEenvironment variable to find it. If it does not exist, manuscript will not create it.If you edit you script to add more dependencies, just run:manuscript check-depsThis will install all missing dependencies for all the scripts.Finally, if you want to use manuscript on a script that won’t last (something downloaded from the internet that sits on your/tmpfor example), just add the-cargument: manuscript will first copy the script to a safe place, then do the whole dance.ContributeThe source code is available ongithub.Bug reports and pull requests welcomed !AuthorThis project is made by Georges Dubus <georges.dubus@gmail.com>.
You can find me on twitter:@georgesdubus.History0.2.0 (201-01-08)Added an option to choose the name of the env. If it begins with “workon:”, use a virtualenv-wrapper env.0.1.0 (2013-11-11)First release on PyPI.
Package: manuscriptify
manuscriptifyCompile Google docs into a manuscriptInstallation and Setup1. Install manuscriptify$ python3 -m venv .venv
$ source .venv/bin/activate
$ pip install manuscriptify2. Setup your project$ cat << EOF >> ~/.zshrc

# manuscriptify project config
export MSFY_PROJECT_FOLDER='my awesome novel'
export MSFY_PSEUDONYM='John Smith'
export MSFY_CATEGORY='YA' # Adult/Middle School/etc
export MSFY_GENRE='Adventure Fantasy'
export MSFY_TITLE='My Awesome Novel'
EOF

$ source ~/.zshrcNotes:If using ubuntu you should use ~/.profile instead of ~/.zshrcIf using windows you must use WSL/ubuntu at present3. Organise your writing folderManuscriptify inspects the 'writing' folder inside your
project folder. That's where you need to put your writing.
You can have as many levels of structure as you want, but
you need to place an integer value (to be used as the sort
key) in the description field of each object in the folder
tree.Usage$ manuscriptify
My Awesome Novel compiled successfully

# The contents of the writing folder inside
# your project folder was assembled and
# placed in a new doc in the manuscripts
# folder.
Package: manuscripts
GrimoireLab ManuscriptsThe aim of this project is the automatic generation of reports from the enriched indexes with items from perceval data sources (git commits, github pull requests, bugzilla bugs ...) enriched using GrimoireELK.To follow the basic step you need the enriched indexes in the Elastic Search provided as param to the report tool.The basic steps creating a report for git, gerrit, its and mls data sources from April 2015 to April 2017 by quarters is:bin/manuscripts-g--data-sourcesgitgerrititsmls-u<elastic_url>-s2015-04-01-e2017-04-01-dproject_data-iquarterand the PDF is generated in project_data/report.pdf_UsageUse-hflag to show usage as follows:$ > bin/manuscripts -h
-d DATA_DIR, --data-dir DATA_DIR
                        Directory to store the data resultsParams:-d, --data-dir: directory to store data files that will be used to create the report PDF file (csv and eps files containing metrics results).
Package: manven
manven (0.5.1)Welcome to manven's README.manvenis a small CLI wrapping the functionality ofvirtualenvto makemanagingvirtualenvironments easier.
Functionalities include creating, activating, removing and listing virtual environments, together with simply ways to quickly create and prune temporary environments.
Follow the documentation below for how to install and how to get started.Happy venv-ing!InstallationSeeinstallation.Getting startedSeegetting started.CompletionsIf you're usingzshyou can copy (or symlink) the filecompletions/_manvento a folder in your$fpathto enable completions of commands and virtual environments to activate. This requirescompinitto have been activated in your.zshrc.Choose virtual environment with fzfAdditionally you can add the following functions to your.zshrcto trigger fuzzy finding of virtual environments with a trigger sequence (default**)._fzf_complete_manven() {
  _fzf_complete --reverse --prompt="venv> " -- "$@" < <(
    manven list
  )
}

_fzf_complete_smanven() {
    _fzf_complete_manven
}With these functions and if you typesmanven activate **<TAB>you can choose the virtual environment usingfzf.
Package: manwe
Warning:This is a work in progress, probably not yet ready for use!Manwë is a Python client library for working with theVardadatabase for
genomic variation frequencies. It also provides a command line interface to
some of its functionality.The main goal of Manwë is to offer the complete Varda API, but on an
abstraction level that is nice to work with from Python code.>>>importmanwe>>>session=manwe.Session()>>>user=session.create_user('testlogin','password')>>>user.dirtyFalse>>>user.name='Test User'>>>user.dirtyTrue>>>user.save()>>>user.dirtyFalse>>>forsampleinsession.samples():...printsample.user.name...Rob Userman
Barry Robsfriend
Rob UsermanTo install the latest release via PyPI using pip:pip install manweDocumentationThelatest documentationwith user guide
and API reference is hosted at Read The Docs.You can also compile the documentation directly from the source code by
runningmake htmlfrom thedoc/subdirectory. This requiresSphinxto be installed.CopyrightManwë is licensed under the MIT License, see the LICENSE file for details. See
the AUTHORS file for a list of authors.
Package: manwrapper
manwrapperA simple command-line tool to view man pages.Descriptionmanwrapperis a Python-based utility that provides an easy way to view man pages. It's designed to be straightforward and user-friendly, making it easier for users to access manual pages without diving deep into themancommand intricacies.InstallationTo installmanwrapper, you can use pip:pipinstallmanwrapperOr, if you want to install from the source:gitclonehttps://github.com/bet0x/manwrapper.gitcdmanwrapper
pipinstall.UsageAfter installation, you can use themanwrappercommand followed by the topic you want to view:manwrapperlsThis will display the man page for thelscommand.ContributingContributions are welcome! Please check out theissueson GitHub to see what's needed, or open a new one if you have a feature request or found a bug.LicenseThis project is licensed under the MIT License. See theLICENSEfile for details.ContactAlberto FerrerEmail:albertof@barrahome.orgGitHub:@bet0x
Package: manx
Manx: Migrations for elasticsearchManx is a migration utility for elasticsearch.  It's likeFlywayorAlembic, but for elasticsearch.The migration also appears to be quite complex, containing many stopovers and foraging zones--Manx shearwater - WikipediaFeaturesPure Python implementationAutomatic index migration and aliaisingDynamic migration script executionManx officially supports Python 3.8+.InstallationTo install Manx, simply:$ pip install manxDevelopmentManx usespoetryfor dependency management and packaging. To install:$ poetry installTo build the distributable:$ poetry buildTo publish the package toPyPI:$ poetry publishStandardsManx uses several tools to ensure code standards:flake8: lintingblack: formattingmypy: type hintingisort: import sortingResourcesPoetrypytestpytest-covpytest-asynciopytest-mockImage CreditManx ShearwaterPuffinus puffinus© Kirk ZufeltJuan Fernández, Valparaíso, Chile | 1 Mar 2020Macaulay Library ML216800971|eBird S66021223|The Cornelle Lab
Package: many
manyThis package provides a general-use toolkit for frequently-implemented statistical and visual methods. See theblog postfor an explanation of the purpose of this package and the methods used.Full documentationInstallationpipinstallmanyNote: if you want to use CUDA-accelerated statistical methods (i.e.many.stats.mat_mwu_gpu), you must also independently install the corresponding version ofcupy.ComponentsStatistical methodsThe statistical methods comprise several functions for association mining between variable pairs. These methods are optimized forpandasDataFrames and are inspired by thecorrcoeffunction provided bynumpy.Because these functions rely on native matrix-level operations provided bynumpy, many are orders of magnitude faster than naive looping-based alternatives. This makes them useful for constructing large association networks or for feature extraction, which have important uses in areas such as biomarker discovery. All methods also return estimates of statistical significance.In certain cases such as the computation of correlation coefficients,these vectorized methods come with the caveat ofnumerical instability. As a compromise, "naive" loop-based implementations are also provided for testing and comparison. It is recommended that any significant results obtained with the vectorized methods be verified with these base methods.The current functions available are listed below by variable comparison type. Benchmarks are also provided with comparisons to the equivalent looping-based method. In all methods, ameltoption is provided to return the outputs as a set of row-column variable-variable pair statistic matrices or as a singleDataFramewith each statistic melted to a column.Visual methodsSeveral visual methods are also included for interpretation of results from the statistical methods. Like the statistical methods, these are also grouped by variable types plotted.DevelopmentInstall dependencies withpoetry installInitialize environment withpoetry shellInitialize pre-commit hooks withpre-commit install
Package: many-abis
Many AbisGet different DEX abis easily for blockchain developers.Now we support dex:arbitrum:[1]SushiSwapavalanche:[1]traderjoexyzbsc:[1]ApeSwap Finance[2]BiSwap[3]MDEX (BSC)[4]PancakeSwap v2[5]PancakeSwap v3[6]Uniswapbsc-test:[1]PancakeSwap v2 (TEST)[2]PancakeSwap v3 (TEST)cronos:[1]Mad Meerkat Financeeth:[1]Uniswap V2[2]Uniswap V3fantom:[1]SpiritSwap[2]SpookySwapheco:[1]MDEX (HECO)kcc:[1]KoffeeSwapmoonriver:[1]Solarbeamokx:[1]CherrySwappolygon:[1]QuickSwapoptimism:[1]Uniswap V3[2]Velodrome V1InstallationDownloadpipinstallmany-abis# pypipipinstall-ihttps://pypi.org/simplemany-abis# updatepipinstall-Umany-abis# orpipinstall-U-ihttps://pypi.org/simplemany-abisUsageimportmany_abisasma# ======================================================================# get all abi namesprint(ma.ALL_ABIS_NAME)# get all abisprint(ma.ABIS)# you can access ABI by dot nameprint(ma.ABIS.ERC20)# ======================================================================# get abi from address using etherscan apima.get_abi_from_address("0x0841BD0B734E4F5853f0dD8d7Ea041c241fb0Da6","YOUR API KEY",ma.CHAIN_CONTRACT_API.BSC)# ======================================================================# chainschains=ma.all_chains()print(chains)# ['arbitrum', 'avalanche', 'bsc', 'bsc-test', 'cronos', 'eth', 'fantom', 'heco', 'kcc', 'moonriver', 'okx', 'polygon', 'optimism']# different methods to get chainbsc=ma.get_chain_by_id(chain_id=56)bsc=ma.get_chain_by_name(name="bsc")bsc=ma.get_chain(name="bsc")bsc=ma.get_chain(chain_id=56)bsc=ma.chain(name="bsc")bsc=ma.chain(chain_id=56)print(bsc)# use ['key'] or dot key name to access chain infoprint(bsc['chain_id'])# 56print(bsc.name)# Binance Smart Chain Mainnetprint(bsc.dex.pancake_v2.router_address)# 0x10ED43C718714eb63d5aA57B78B54704E256024E# to get some items from chaineth_weth=ma.get('eth','weth')print(eth_weth)# {'address': '0xC02aaA39b223FE8D0A0e5C4F27eAD9083C756Cc2', 'name': 'Wrapped ETH', 'symbol': 'WETH'}ds=ma.get('bsc','dex','pancake_v2')print(ds)# {'factory_address': '0xcA143Ce32Fe78f1f7019d7d551a6402fC5350c73', 'name': 'PancakeSwap v2', 'router_address': '0x10ED43C718714eb63d5aA57B78B54704E256024E', 'website': 'https://pancakeswap.finance/swap'}# print all dexma.print_all_dex()
Package: manyapi
ManyAPIAll in one API wrapper written in Python.API list & ExamplesAPI List :api_list.mdExamples :examplesdirectoryContributionCan I add more API wrapper/fix some code?Totally Allowed :)Licence & CopyrightCopyright 2022-present EterNommGNU General Public License 3.0

A permissive license whose main conditions require preservation of copyright and license notices.
Contributors provide an express grant of patent rights.
Licensed works, modifications, and larger works may be distributed under different terms and without source code.
Package: manychat
ManyChat Python PackageThis is an unofficial Python package for an easy use of theManyChat API.Installationpip install manychatUsagefrommanychatimportManyChatmc=ManyChat('YOUR_MANYCHAT_API_KEY')# Pagepage_info=mc.fb.page.get_info()# Sendingsend_flow=mc.fb.sending.send_flow(subscriber_id='SUBSCRIBER_ID',flow_ns='content20210489114753_47763'# this is just an example)# Subscribersubscriber_info=mc.fb.subscriber.get_info(subscriber_id='SUBSCRIBER_ID')To see more examples, please go to:tests/manychat_tests.pyGitHub Repo:https://github.com/daiangan/manychat-pythonSome Notes:All methods are named using the Python function naming rules: lowercase with words separated by underscores as necessary to improve readability.So, for example, the ManyChat endpoint/fb/sending/sendFlowis translated to:fb.sending.send_flow()More info aboutStyle Guide for Python Code.Please read the official ManyChat API Documentation for more details:https://api.manychat.com/About this projectThis project is created and maintained by:Daian GanGithub:daianganE-mail:daian@ganmedia.comWebsite:https://daiangan.com
Package: manychat-api-python
ManyChat API Python libraryInstallationUsing pip (recommended):python3 -m pip install manychat-api-pythonManually:python3 setup.py installUsageAfter installing the library, you need to get the ManyChat API token in the API tab of the settings of your page at manychat.com.
Here are some examples of the library usage with1234567890123456:1234567890ABCDEFGHIJKLMNOPQRSTUVAPI token:As an instance (recommended):import ManyChat

api = ManyChat.API('1234567890123456:1234567890ABCDEFGHIJKLMNOPQRSTUV')
page_info = api.fb.page.getInfo()As a singleton:import ManyChat

ManyChat.API.init('1234567890123456:1234567890ABCDEFGHIJKLMNOPQRSTUV')
page_info = ManyChat.API.fb.page.getInfo()DocumentationList of available ManyChat API methods you can get at theManyChat API homepage.
Package: manychat-python
manychat-pythonThis is an unofficial Python package for an easy use of theManyChat API.Installationpip install manychat-pythonUsagefrommanychatimportManyChatmc=ManyChat('YOUR_MANYCHAT_API_KEY')# Pagepage_info=mc.fb.page.get_info()# Sendingsend_flow=mc.fb.sending.send_flow(subscriber_id='SUBSCRIBER_ID',flow_ns='content20210489114753_47763'# this is just an example)# Subscribersubscriber_info=mc.fb.subscriber.get_info(subscriber_id='SUBSCRIBER_ID')To see more examples, please go to:tests/manychat_tests.pyGitHub Repo:https://github.com/daiangan/manychat-pythonSome Notes:All methods are named using the Python function naming rules: lowercase with words separated by underscores as necessary to improve readability.So, for example, the ManyChat endpoint/fb/sending/sendFlowis translated to:fb.sending.send_flow()More info aboutStyle Guide for Python Code.Please read the official ManyChat API Documentation for more details:https://api.manychat.com/About this projectThis project is acloneof the project created and maintained by:Daian GanGithub:daianganE-mail:daian@ganmedia.comWebsite:https://daiangan.com
Package: manyconfig
An easy-to-use declarative loader of configurationWhat does it do?Manyconfig lets you describe your configuration using simple blocks. You can
then load this configuration in a simple statement, even if it is scattered
across various file and environment variables.We call these descriptions a MetaConfig not to confuse them with the
configuration itself, which is the result of loading a MetaConfig.I can’t leverage Manyconfig for my use case!If that’s the case, please tell me. Manyconfig is still in its early days, so
this is bound to happen. I’ll happily add building blocks if it enables more
use cases.
Package: manydo
manydoDead-simple parallel execution with a loading bar sprinkled on top.Installationpip install manydo. Or, better for you, usePoetry:poetry add manydo.Usagemanydois simple. All you need ismap:frommanydoimportmapmap(lambdax:x+3,[1,2,3])# [4, 5, 6]map(function,iterable,num_jobs=16)# try not to burn your CPUmap(function,iterable,loading_bar=False)map(function,iterable,desc='Passes arguments to tqdm')Related projectspqdmis very similar, but didn't work for me ¯\_(ツ)_/¯