Saravanan666/pypi-org huggingface dataset:
Package: metaset
This package provides a collection that is basically a “dict of sets”, named MetaSet.LinksPackage onPyPI:http://pypi.python.org/pypi/metaset/Source onGitHub:http://github.com/Polyconseil/metaset/Build onTravis CI:http://travis-ci.org/polyconseil/metaset/QuickstartInstall the package fromPyPI, using pip:pipinstallmetasetOr from GitHub:gitclonegit://github.com/Polyconseil/metaset.gitImport it in your code:>>>frommetasetimportMetaSetUsage is quite straight forward,
basic set operations are supported via the binary operators+-|^.>>>frompprintimportpprint>>>pprint(MetaSet(a={1,2},b={3})|MetaSet(b={4},c={5})){'a':{1,2},'b':{3,4},'c':{5}}Django PostgresA custom Django field is available.
It is quite straightforward:>>>frommetaset.django_fieldimportMetaSetField>>>fromdjango.dbimportmodels# doctest: +SKIP>>>classMyModel(models.Model):# doctest: +SKIPmset=MetaSetField()# doctest: +SKIPThe following versions of Python and Django are supported:Python 2.7, 3.6, 3.7 and 3.8;Django 1.11, 2.0, 2.1, 2.2, 3.0 and 3.1.Detailed considerationsThey are two ways to consider the “dict of sets” notion,
differing on how you handle the empty values for keys.The easiest idea is to consider that a key with no content is non-existent.
This is how thedictsetpackage is implemented.In this alternative implementation,
we chose to keep the empty keys as meaningful elements,
allowing for smart unions and intersections.>>>pprint(MetaSet(a={1})|MetaSet(a={2},b=set())){'a':{1,2},'b':set()}>>>MetaSet(a={1})&MetaSet(a={2},b={3}){'a':set()}So, beware of how empty-keys are handled,
and consider usingdictsetif it is a better match for your use case.
The behavior for subtraction and symmetric difference,
although sound on a mathematical point of view, may not be what you want.>>>MetaSet(a={1})-MetaSet(a={1}){'a':set()}>>>MetaSet(a={1})^MetaSet(a={1}){'a':set()}
Package: metasetup
A package for configuring settings and initializing objects.Withmetasetup, there are no configuration files, just python modules which import
and modify settings. This means, that these modules can be used as a “meta” layer on top
of normal configuration files, or to programatically configure the settings themselves.
To access settings for a particular module, one need only import it withmetasetupas a prefix (e.g.from metasetup.my_package import my_module) and use its attributes.SeeGitHubfor more info
Package: metashield-clean-up
InstallationInstall themetashield_clean_uppackage using pip:pip install metashield_clean_upUsageExample for cleaning a file.frommetashield_clean_up.apiimportMetashieldCleanUpapi=MetashieldCleanUp("REPLACE_APP_ID_HERE","REPLACE_SECRET_KEY_HERE")response=api.clean_file(stream,"my_file.pdf")response=api.get_clean_result(response.data["cleanId"])Run testsBefore run tests, replace some settings intests/settings_default.pymodule.Tests was built with Python Unittest, run the following commands:python -m unittest discover tests
Package: metashovel
MetashovelMetashovel is a Metabase utility tool to mainly import/export questions and dashboardsSetupRunning from sourceInstall Pipenv command in your system:sudo apt install pipenvInstall dependencies from the root of this project directory:pipenv installOpen shell with requirements loaded in a virtual environment:pipenv shellConfigurationDepending on subcommand, you configure the cli with:environment variables (mostly for credentials eg API keys, or access urls, eg. url to database with user, pass, hostname, db name)command line switches and argumentsEnvironment variables referenceAPI keys and Database access urlsMetashovel uses the Metabase API. Define Metabase url, username and password with these variables:METABASE_ENDPOINT- url of Metabase instance with scheme, eg:https://data.awesome.comMETABASE_AUTH_EMAIL- email for loginMETABASE_AUTH_PASSWORD- password for loginUsageMetashovel has a set of subcommands, similar to git or heroku.Exportmetashovel exportgenerates a JSON dump of all the data required to import the collections / dashboards / questions given in options.The generated JSON is printed on standard output. It contains a propertyitemswith the list of objects that got exported, as well as a propertymappingswith information to translate ids that make sense only in the context of a Metabase instance (table ids, card ids, etc).Options:-c "Some collection"- Exports all the questions and dashboards contained in the named collection and its child collections. You should ensure that the dashboards refer only to questions contained within that collection, unless you plan to import the data within the same Metabase instance. The collection must exist.Importmetashovel importreads a JSON dump generated by the export command and import the object into a Metabase instance.Options:-c "Some collection"- The name of the collection into which the objects should be imported. The collection must exist and be empty (no support for overwrite / merge at the moment).-j /path/to/file.json- The JSON file to import.Package buildingTo build the package usepython setup.py bdist_wheel.To install the package locally:pip install --upgrade dist/metashovel-0.1-py3-none-any.whlTo upload it to PyPI:Create a~/.pypircfile:[distutils] 
index-servers=pypi
[pypi] 
repository = https://upload.pypi.org/legacy/ 
username = pypi-usernameUsepython -m twine upload dist/*.ContributingTODOCode Linting and FormattingA pylint configuration is in pylintrc - configure your editor to run it automatically. Use black for formatting.
Package: metasip
MetaSIP - a GUI Development Tool for SIPSIPis a Python bindings generator for C and
C++ libraries.  It takes as its input a set of.siptext files that describes
the history of the API of the library.  A.sipfile is similar to a C/C++
header file but with addional directives, annotations and supplementary
hand-written C/C++ code.MetaSIP (specifically themsipapplication) is a GUI tool for specifying the
complete history of a library's API allowing additional directives, annotations
and hand-written code to be added.  A.mspproject file is used to store this
information and MetaSIP (specifically themsipgenapplication) can generate
an appropriate set of.sipfiles to feed to SIP.The key feature of MetaSIP is that it can scan the header files of a particular
version of a library in order to initially populate the project file.  It will
then indicate all of the tasks that might need to be performed in order to
complete the implementation of the bindings.  It will also scan a new version
of the library, compare it with the previous version, update the project file
appropriately, and indicate any new tasks that now might need to be performed
in order to keep the bindings up to date.  These features make it relatively
easy to maintain the bindings for a large library.Currently the scanning of a library's header files is done usingCastXMLand this must also be installed.MetaSIP is implemented with Python andPyQt6.It should be noted that MetaSIP was developed a number of years ago by the
author as a personal productivity tool.  As a result it is fairly feature
complete.  However because it has not been used by a significant number of
people, its behavour may seem quirky in places.  It is certainly poorly
documented with no online help.LicenseMetaSIP is licensed under the BSD 2 clause license.InstallationTo installmsipgen, run:pip install metasipTo install the additional dependencies required by themsipGUI development
tool, run:pip install 'metasip[gui]'Creating Packages for DistributionPython sdists and wheels can be created with any standard Python build
frontend.For example, usingbuildan sdist and wheel
will be created from a checkout in the current directory by running:python -m build --outdir .Building the DocumentationThe documentation is built usingSphinx,myst_parserand thesphinx-rtd-themetheme.Change to thedocsdirectory of a checkout and run:make htmlThe HTML documentation can then be found in the_build/htmlsubdirectory.
Package: metasort
# MetasortA Digital Health Hack Weekend Project using OneCodex API.Filter reads based on taxonomy assignment from OneCodex.Upload a Fast(a/q) file and download individual files sorted by species.## CLIset your OneCodex API keyexport ONE_CODEX_API_KEY=f8xxxxxxxxxxx78source venv/bin/activatepip install metasortmetasort seq.fq /path/to/outdirexample output:wc -l /path/to/outdir/*.fq | sort -n -k1 | tail19648 /path/to/outdir/Cellular organisms.fq30016 /path/to/outdir/Staphylococcus aureus subsp. aureus.fq81680 /path/to/outdir/Bacteria.fq126364 /path/to/outdir/Staphylococcus epidermidis.fq398684 /path/to/outdir/Staphylococcus.fq2030880 /path/to/outdir/Firmicutes.fq3195432 /path/to/outdir/Staphylococcus aureus.fq## WebUsage:pip install -r requirementspython webapp.pyLive demo here:[https://genome-sort.herokuapp.com/](https://genome-sort.herokuapp.com/)
Package: metaspace2020
METASPACE Python clientPython package that provides programmatic access toMETASPACE.ApplicationsRunning batch jobsExploratory analysis of submitted dataQuick access to things hidden from web interface (such as location of files on S3 and other metadata)InstallationYou need to havePython 3.6 or higherto use this library.pip install metaspace2020DocumentationThe package documentation is available atmetaspace2020.readthedocs.ioAcknowledgements and licenseSee the top-level README
Package: meta-sparse
Strain Prediction and Analysis using Representative SEquences (SPARSE)SPARSE indexes >100,000 reference genomes in public databases in to hierarchical clusters and uses it to predict origins of metagenomic reads.InstallationSPARSE runs on Unix and requires Python version 2.7 (Python 3.x supports are under development)System modules (Ubuntu 16.04) :pipgfortranllvmlibncurses5-devcmakexvfb-run (for malt, optional)3rd-party software:samtools (>=1.2)mash (>=1.1.1)bowtie2 (>=2.3.2)malt (>=0.4.0) (optional)Seerequirements.txtfor python module dependencies.Installation via PIP [Suggested]pip install meta-sparseInstallation from source codes (Ubuntu)sudo apt-get update
sudo apt-get install gfortran llvm libncurses5-dev cmake python-pip samtools bowtie2
git clone https://github.com/zheminzhou/SPARSE
cd SPARSE/EM && make
pip install -r requirements.txtUpdating SPARSEYou can update to latest version using PIP:pip install --upgrade meta-sparseIf you installed SPARSE from github, move to installation directory and pull the latest version:cd SPARSE
git pullQuick StartSeehttp://sparse.readthedocs.io/en/latest/for full documentation.Download reference databaseWe provide a pre-compiled database based on RefSeq (dated 19.05.2018) to download athttp://enterobase.warwick.ac.uk/sparse/refseq_20180519.tar.gz. The database can be downloaded and unpacked by running:curl -o refseq_20180519.tar.gz http://enterobase.warwick.ac.uk/sparse/refseq_20180519.tar.gz
 tar -vxzf refseq_20180519.tar.gzThis pre-compiled database is about 350GB and contains four default mapping databases, which can be specified in the next step: representative, subpopulation, Virus, Eukaryota.To update the database or build a costum database, please refer to the full documentation.Predict read originsThis following command will map and evaluate all reads in both fastq-files against the specified mapping databases.sparse predict --dbname refseq_20180519 --mapDB representative,subpopulation,Virus,Eukaryota --r1 read1.fq.gz --r2 read2.fq.gz --workspace <workspace_name>For single-end reads, only --r1 needs to be specified. All output files are stored in the respective workspace.Create a reportsparse report <workspace_name>The report will be stored in <workspace_name>/profile.txtExtract reference specific readsThe following command extracts all reads specific to the provided reference ids, which can be found in the output of step 2.sparse extract --dbname refseq_20171014 --workspace <workspace_name> --ref_id <comma delimited indices>CitationSPARSE is published as a conference proceeding in "Research in Computational Molecular Biology".Zhemin Zhou, Nina Luhmann, Nabil-Fareed Alikhan, Christopher Quince, Mark Achtman, 'Accurate Reconstruction of Microbial Strains from Metagenomic Sequencing Using Representative Reference Genomes' RECOMB 2018: Research in Computational Molecular Biology pp 225-240. doi:https://doi.org/10.1007/978-3-319-89929-9_15A preprint version of the manuscript is also accessible in bioRxiv:https://doi.org/10.1101/215707
Package: metaspore
中文介绍MetaSpore: One-stop machine learning development platformMetaSpore is a one-stop end-to-end machine learning development platform that provides a full-cycle framework and development interface for from data preprocessing, model training, offline experiments, online predictions to online experiment traffic bucketization and ab-testing.MetaSpore is developed and opensourced byDMetaSoulteam. You could also join ourslack user discussion space.Core FeaturesMetaSpore has the following features:One-stop end-to-end development, from offline model training to online prediction and bucketing experiments, with a unified development experience across the entire process;Deep learning training framework, compatible with PyTorch ecology, supports distributed large-scale sparse feature learning;The training framework is connected with PySpark to seamlessly read the training data from the data lake and data warehouse;High-performance online prediction service, supports fast inference for neural network, decision tree, Spark ML, SKLearn and other models; supports heterogeneous hardware inference acceleration;In the offline unified feature extraction framework, the online feature reading logic is automatically generated, and the feature extraction logic is unified cross offline and online;Online algorithm application framework, providing model prediction, experiment bucketing and traffic splitting, dynamic hot loading of parameters and rich debug functions;Rich industry algorithm examples and end-to-end solutions.Documentation and examplesOffline Training Getting Started TutorialOnline Algorithm Application (Java implementation)Online Model ServingOnline Feature ExtractionOnline Experiment PipelineA MovieLens end-to-end recommender system demo, includingOffline modelsOnline algorithm application (Java implementation)Installation package downloadTraining packageWe provide precompiled offline training wheel package on pypi, install it via pip:pipinstallmetasporeThe minimum Python version required is 3.8.After installation, also install pytorch and pyspark (they are not included as depenencies of metaspore wheel so you could choose pyspark and pytorch versions as needed):pipinstallpyspark
pipinstalltorch==1.11.0+cpu-fhttps://download.pytorch.org/whl/cpu/torch_stable.htmlServing packageWe provide prebuilt docker images for MetaSpore Serving Service:CPU only imagedocker pull dmetasoul/metaspore-serving-release:cpu-v1.0.1GPU imagedocker pull dmetasoul/metaspore-serving-release:gpu-v1.0.1SeeRun Serving Service in Dockerfor details.Compile the codeOffline training framework compilationCommunity guidelinesCommunity guidelinesFeedbackFor questions about usage, you can post questions inGitHub Discussion, or throughGitHub Issue.MailEmail us atopensource@dmetasoul.com.SlackJoin our user discussion slack channel:MetaSpore User DiscussionOpen source projectsMetaSpore is a completely open source project released under the Apache License 2.0. Participation, feedback, and code contributions are welcome.
Package: metasporecli
metasporecli: Command-line Interface for MetaSpore Flow Managementmetasporecli implements themetasporecommand, which can be used to manage MetaSpore flows.With metasporecli installed and the configuration filemetaspore-flow.ymlin the current
directory, we can use the follwing command to start a MetaSpore flow:metasporeflowupand the following command to stop a MetaSpore flow:metasporeflowdownUse the following commands to see help of themetasporecommand:metaspore-h
metasporeflow-hInstallmetasporecli can be installed using pip. We recommend the user to create a virtualenv to install metasporecli.python-mpipinstallmetasporecliThe latest release of metasporecli can be found on PyPImetasporecli: Command-line Interface for MetaSpore Flow Management.Buildpython-mpipwheel.metasporecli depends onmetasporeflow, to build metasporecli with locally built metasporeflow, use the following command:python-mpipwheel.../metasporeflow/metasporeflow-*-py3-none-any.whl
Package: metasrc
Metasrc (pronouced “meta source”) is a Python library for gathering metadata about LSST’s software and documentation projects and synthesizing it into JSON-LD (linked data) resources.This project is related to LSST DocHub, an experimental project to gather LSST information artifacts from across the web, and make them discoverable through a single API.
DocHub adapters can use this library to create LSST DocHub JSON-LD resources.Metasrc is developed byLSST, the Large Synoptic Survey Telescope.
Learn more atwww.lsst.org.LicenseMetasrc is MIT licensed. SeeLICENSE.
Package: metastock
MetastockEnvironmentSincepoetryhelps us manage environments, we no longer need to use Python virtualenv.When creating a new project and using it with PyCharm, it will be fully integrated with the default mechanism. This will
create a new isolated environment in the/.cache/pypoetry/folder.Lúc đó, chỉ còn trường hợp xảy ra là mình muốn thay đổi version của python. For more info,
visitlinkpyenvinstall3.9.8
pyenvlocal3.9.8# Activate Python 3.9 for the current projectpoetryinstallDevelopmentPM2In local development, we can use pm2 with commandpm2startmetastock/bin/start_consumer.py--log-date-format''--interpreter=/home/wsl/.cache/pypoetry/virtualenvs/metastock-bq6tFdVW-py3.11/bin/python--instances4--max-memory-restart1G----name=test_consumerProductionSo far, the significant way is run by pm2. This is the best method that will not consume much time and resources
compared to building a Docker file or Kubernetes.But, we need create a python file to call metastock moduleEx:pm2startmetastock/start_consumer.py--log-date-format''--interpreter=/home/wsl/.cache/pypoetry/virtualenvs/metastock-bq6tFdVW-py3.11/bin/python--instances4--max-memory-restart1G----name=test_consumerPublish appIncrease version inpyproject.tomlRun publish commandpoetrypublish--buildRefer:Create a packagehttps://typer.tiangolo.com/tutorial/package/
Package: metastock2pd
metastock2pdA simple utility to convert metastock data to pandas dataframe.You can conda install it fromhttps://anaconda.org/yoavgit/metastock2pdThis is a simpler version ofhttps://github.com/themech/ms2txtand themech should get all the credit for the heavy lifting in parsing the bytes.There are two functions you care about:metastock_read_master('c:/directory') will read metastock master, emaster and xmaster files as a table of available files. We can then read these files directly using...metastock_read('c:/directory/F1.dat') will read metastock datafiles: either dat or mwd extensions.
Package: metas-unclib
METAS UncLibTo use METAS UncLib, simply do:>>> from metas_unclib import *
>>> use_linprop()

>>> a = ufloat(3.0, 0.3, desc='a')
>>> b = ufloat(4.0, 0.4, desc='b')

>>> c = umath.sqrt(a**2 + b**2)
>>> print(c)
5.0 ± 0.3671511950137164RequirementsnumpypythonnetonLinuxandmacOS:Mono .NET frameworkOptional RequirementsscipymatplotlibjupyterLinuxTheLD_LIBRARY_PATHenvironment variable has to be set to:export LD_LIBRARY_PATH=~/.local/lib/python3.6/site-packages/metas_unclib/mkl_custom/linux/intel64macOSTheDYLD_LIBRARY_PATHenvironment variable has to be set to:export DYLD_LIBRARY_PATH=~/.local/lib/python3.6/site-packages/metas_unclib/mkl_custom/macos/intel64
Package: metasyntactic
Version:1.0.14SynopsisThis is a port of the excellent Perl moduleAcme::MetaSyntactic,
written by Phillipe (BooK) Bruhat.In fact it is automatically generated from Acme::MetaSynctacic.
And this particular version was generated from version 0.99.The original CONTRIBUTORS file is shipped with this distribution.UsageGeneralGet a list of all themes:>>> import metasyntactic
>>> metasyntactic.all_themes
set(...)Get random theme:>>> metasyntactic.random()
<module 'metasyntactic.themes.stars' from 'metasyntactic/themes/stars.py'>Get random metavariable from random theme:>>> metasyntactic.random().random()
['Barbouille']Get 4 random metavariables from random theme:>>> metasyntactic.random().random(4)
['eve', 'irene', 'frank', 'ellen']Get random metavariables from 4 random themes:>>> [theme.random() for theme in metasyntactic.random(4)]
['Barbouille', 'Fragarach', 'Grumpy', 'the_Lord_of_the_Rings']Get 2 random metavariables from 4 random themes:>>> [theme.random(2) for theme in metasyntactic.random(4)]
[['Lupa', 'Civetta'],
 ['spigot', 'physique'],
 ['Patrice_Petit', 'Yvette_Chauvire'],
 ['GiNG_GiNG', 'DOINK_DOINK_DOINK_DOINK']]Themes# Get theme by theme name
>>> foo = metasyntactic.get("foo")
>>> foo
<module 'metasyntactic.themes.foo' from 'metasyntactic/themes/foo.py'>

# Get random name
>>> foo.random()
'fubar'

# Get several random names.
>>> foo.random(8)
['bar', 'xyzzy', 'foobar', 'thud', 'foo', 'fred', 'garply', 'quux']

# Get all names
>>> foo.all()
set(....)Categories# Get random name in specific category
>>> foo.random(8, category="fr")
['truc', 'test1', 'machin', 'titi', 'tutu', 'pipo', 'test2', 'tata']

# get default category
>>> foo.default()
'en'

# get all available categories
>>> foo.categories()
set(['en', 'fr', 'nl'])

# get all names in specific category
>>> foo.all(category="fr")
set(...)

>>> yapc = metasyntactic.get("yapc")

>>> yapc.random(4, section="america north")
['Buffalo', 'Pittsburgh', 'Boca_Raton', 'Saint_Louis']

>>> yapc.sections()
set(['america north',
     'america south',
     'asia',
     'australia',
     'brazil',
     'canada',
     'europe',
     'israel',
     'taipei'])InstallationYou can installmetasyntacticeither via the Python Package Index (PyPI)
or from source.To install usingpip,:$ pip install metasyntacticTo install usingeasy_install,:$ easy_install metasyntacticIf you have downloaded a source tarball you can install it
by doing the following,:$ python setup.py build
# python setup.py install # as rootBug trackerIf you have any suggestions, bug reports or annoyances please report them
to our issue tracker athttp://github.com/ask/metasyntactic/issues/LicenseThis software is licensed under theArtistic License.
And I don’t reserve any copyright for this work, as all the hard work
should be credited to the original authors.