Saravanan666/pypi-org huggingface dataset:
Package: amti-islands
AMTI IslandsObject-oriented islands in the South China Sea.InstallationInstall withpip.InterfaceIslandTheIslandclass represents an island in the South China Sea.Each instance has the following properties:url, the URL for the AMTI reference,title, the AMTI title,names, a dictionary of names for the island,occupier, optional occupying country,legal_status, the legal status of the feature,geo, aCoordinatesobject withlatandlongproperties.AMTIInstantiate theAMTIclass. This is a factory class forIslandobjects and has methodsislands(a generator forIslandinstances) andrandom_island(which returns a randomIsland).
Package: amtokenizers
Amharic Language TokenizersThis package contains set of Classes which can be used to encode Amharic language sentences into tokens that could be used by language models. The tokenizers are trained usingContemporary Amharic Corpus (CACO)datasetInstallingPip installationpipinstall-ihttps://test.pypi.org/simple/amtokenizers==0.0.5Sample CodeVariable lengthfromamtokenizersimportAmTokenizera=AmTokenizer(10000,5,"byte_bpe")encoded=a.encode("አበበ በሶ በላ።",return_tokens=False)print("encoded",encoded.tokens)# encoded ['
', 'áĬł', 'áīłáīł', 'ĠáīłáĪ¶', 'ĠáīłáĪĭ', 'áį', '¢', '
']print("decoded:",a.decode(encoded.ids))# decoded: 
አበበ በሶ በላ።
Fixed lengtha=AmTokenizer(10000,5,"byte_bpe",max_length=16)encoded=a.encode("አበበ በሶ በላ።")print("encoded",encoded.tokens())# encoded ['
', 'áĬł', 'áīłáīł', 'ĠáīłáĪ¶', 'ĠáīłáĪĭ', 'áį', '¢', '
', '<pad>', '<pad>', '<pad>', '<pad>', '<pad>', '<pad>', '<pad>', '<pad>']print(encoded.input_ids)# [0, 337, 3251, 3598, 3486, 270, 100, 2, 1, 1, 1, 1, 1, 1, 1, 1]print("decoded:",a.decode(encoded.input_ids))# decoded: 
አበበ በሶ በላ።
<pad><pad><pad><pad><pad><pad><pad><pad>DisclaimerThis package is highly inspired by Hugging Face'sHow to train a new language model from scratch using Transformers and Tokenizerstutorial.
Package: amtool
Artifact Management ToolStatement of PurposeAMT is meant to be a generic means of storing and manipulating artifact data in a human readable text format ideal for colaborative work.What AMT is:An object oriented heirarchical data management tool.Designed to be used from the command line or user interface.Intended to manage human readable files captured in a version control system.Scriptable (Written in Python with extendable API)Embeddable (C++ api to follow)What AMT is not:Specialized for any task other than the storage and manipulation of artifacts.Intended Use Cases:Distributed Issue Tracking SystemColaborative Requirements ManagementUse Case DocumentationObject ModelsSoftware Lifecycle/Project Management Documentation GenerationSimulation Input FilesWhat problem does AMT try to solve.The ability to colaboratively develop artifacts when a central server or database cannot be utilized.Case Study: Distributed Issue TrackingExamples of a use case for which there is no existing workable solution, is the requirement to use an issue tracking system for a project that will be worked by groups on multiple networks, sites, locations, and/or classification levels, where access to a central database or server cannot be maintained by all developers, all the time.  There are several excellent issue tracking systems out there, Bugzilla, Trac, Jira, but all of those solutions require access to a centralized server to interact with the issue database.  AMT provides a user definable solution to create, manage, and version control an issue database, in human readable format, within the repository the project is stored in.Command line toolsCommand line tools are executed through subcommands of the amt command.CommandUsagedumpDumps an ascii representation of the object tree.cannonicalEnforces the canonical representation of the object tree.Example Python Usageimportamt# Loadartifacts=amt.load('/path/to/artifacts')# ReadAMT_OAR_001=artifacts['Requirements']['AMT-OAR-0001']# Modifyartifacts['Requirements']['AMT-OAR-0002']['Description']='Be Cool'# Writeamt.save('/path/to/write/artifacts',artifacts)CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.9 (2019-07-02)Adding short descriptions to commands.0.1.8 (2019-07-02)Package cleanup.0.1.7 (2019-07-02)Documentation cleanup.0.1.6 (2019-06-24)Debugging automated deployment to pypi.0.1.5 (2019-06-24)Added uid command.0.1.4 (2019-06-06)Debugging build issues.0.1.3 (2019-05-12)Testing release automation.0.1.2 (2019-05-12)Adding code coverage.0.1.1 (2019-05-12)Automated deployment from travis.0.1.0 (2019-04-23)First release on PyPI.
Package: amt-tools
Automatic Music Transcription (AMT) ToolsImplements a customizable machine learning pipeline for AMT in PyTorch.
This framework abstracts various components of the AMT task, such as the dataset(s), data formatting, feature extraction, model usage, output formatting, training, evaluation, and inference.
This makes for easy modification and extension through inheritance.The framework is a work-in-progress. Its development is ongoing to meet my evolving research needs.InstallationStandard (PyPI)Recommended for standard/quick usage:pip install amt-toolsCloning RepositoryRecommended for running example scripts or making experimental changes:git clone https://github.com/cwitkowitz/amt-tools
pip install -e amt-toolsUsageThis repository can be used for many different purposes.
Please see theREADME.mdwithin each subpackage for more information.Additionally, several papers are implemented under theexamples/paperssubdirectory in standalone scripts which utilize the framework.
These examples demonstrate the versatility of the framework and serve as guides for how one might use it.
Package: amtui
Artifact Management Tool User InterfaceStatement of PurposeA user interface to the Artifact Management ToolFree software: MIT licenseDocumentation:https://amtui.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.2 (2019-07-04)Debugging PyPi deployment from travis.0.1.1 (2019-07-04)Debugging PyPi deployment from travis.0.1.0 (2019-07-04)First release on PyPI.
Package: amulet-core
Amulet CoreA Python 3 library to read and write data from Minecraft's various save formats.This library provides the main world editing functionality for Amulet Map EditorIf you are looking for the actual editor it can be found atAmulet Map EditorDocumentationOur online documentation can be found here:https://amulet-core.readthedocs.ioInstallingInstall Python 3.7We recommend setting up apython virtual environmentso you don't run into issues with dependency conflicts.runpip install amulet-coreto install the library and all its dependencies.DependenciesThis library uses a number of other libraries. These will be automatically installed when running the command above.NumpyAmulet_NBTPyMCTranslateContributingFor DevelopmentDownload the code to your computer, install python and run the following command from the root directory.
runpip install -e .[dev]This command will install the library in development mode with the libraries required for development.Black(Required for formatting)Must be run before pushing a Pull RequestFor information about contributing to this project, please see the contribution sectionbelowCode FormattingFor code formatting, we use the formatting utilityblack.
To run it, run the following command from your favorite terminal after installing:black amulet testsIn order for your pull request to be accepted, this command must be run to format every file.Building the DocumentationTo build the documentation locally, run the following command:make htmland then navigate to the
generated directorydocs_build/htmlin your favorite web browserBranch NamingBranches should be created when a certain bug or feature may take multiple attempts to fix. Naming
them should follow the following convention (even for forked repositories when a pull request is being made):For features, use:impl-<feature name>For bug fixes, use:bug-<bug tracker ID>For improvements/rewrites, use:improv-<feature name>For prototyping, use:proto-<feature name>Pull RequestsWe ask that submitted Pull Requests give moderately detailed notes about the changes and explain
any changes that were made to the program outside of those directly related to the feature/bug-fix.
Make sure to run all tests and formatting otherwise we cannot accept your pull request.Note: We will also re-run all tests before reviewing, this is to mitigate additional changes/commits
needed to pass all tests.Once a Pull Request is submitted, we will mark the request for review, once that is done, we will
review the changes and provide any notes/things to change. Once all additional changes have been made,
we will merge the request.
Package: amulet-editor
Amulet-EditorA Minecraft world editor and converter that supports all versions since Java 1.12 and Bedrock 1.7.Running compiled buildsDownload the installer for your operating system from the list ofcompiled builds.Double click on the installer when downloaded and follow the installation steps. It can then be run and uninstalled like a normal program.Running from SourceIf you are running a compiled build you do NOT need to do this.InstallPython 3.9+We recommend setting up apython virtual environmentso you don't run into issues with dependency conflicts.Clone or download the repository source code.In the source code directory runpython -m pip install .to install the library and all its dependencies. Linux and MacOS users will need to usepython3runamulet_editorto run the program
Package: amulet-leveldb
Amulet LevelDBA Cython wrapper for Mojang's modified LevelDB library.Installpip install amulet-leveldbUsefromleveldbimportLevelDBcreate_if_missing=True# optional input. Default False.db=LevelDB("path/to/db",create_if_missing)db.put(b"key",b"value")print(db.get(b"key"))# b"value"See thesource codefor full documentation.
Package: amulet-map-editor
Amulet Map EditorA new Minecraft world editor and converter that supports all versions since Java 1.12 and Bedrock 1.7.Running compiled buildsDownload the zip file for your operating system from the list ofcompiled builds. (Currently Windows only)Extract the contained folder to a location on your computer and run the executable.Running from SourceIf you are running a compiled build you do NOT need to do this.InstallPython 3.9+We recommend setting up apython virtual environmentso you don't run into issues with dependency conflicts.runpython -m pip install amulet-map-editorto install the library and all its dependencies.runpython -m amulet_map_editorto run the programNotesIf you have python 2 installedpythonmay point to the wrong version in which case you will have to swap outpythonforpython3When installing from source the following dependencies will be installednumpywxpythonpyopenglAmulet-CoreThe library to handle loading and saving data to the world formats.Amulet-NBTThe library to handle reading and saving NBT and SNBT.PyMCTranslateThe library to handle block, block entity, entity and biome translation. between versionsMinecraft-Model-ReaderThe library to handle loading block models and textures from a resource pack for use in the renderer.Amulet-LevelDBThe wrapper for Mojang's custom LevelDB.ContributingFor information about contributing to this project, please read thecontributionfile.
Package: amulet-nbt
Amulet-NBTAmulet-NBT is a Python 3 library, written in Cython, for reading and writing both binary NBT and SNBT.SNBT (or Stringified-NBT) is the JSON like format used in Java commands.InstallingRun this command to install from PyPi.pip install amulet-nbt~=2.0DocumentationSee ourreadthedocs sitefor the full documentation of this library.DevelopmentTo develop the library you will need to download the source and run this command from the root directory.pip install -e .[dev]This will build the library in-place and expose it to python.
Since this code is compiled you will need to run it again each time you change cython code.LinksDocumentation -https://amulet-nbt.readthedocs.ioGithub -https://github.com/Amulet-Team/Amulet-NBTWebsite -https://www.amuletmc.com/
Package: amulet-runtime-final
amulet-runtime-finalDeclare final Python classes and methods at runtime.This module provides a decorator based interface to declare final classes and methods that are enforced at runtime.
This module is inspired by and is compatible withtyping.final.
SeePEP-591for more details on this topic.InstallationPython 3.6 or higher is required.You can simply install this module frompip.python -m pip install amulet-runtime-finalUsageThe main component of this module is thefinaldecorator that
can be used to decorate classes and methods inside a class. As
such:Classes decorated with @final cannot be subclassed.Methods decorated with @final cannot be overriden in subclasses.For example with classes:fromruntime_finalimportfinal@finalclassFoo:...classBar(Foo):# Raises RuntimeError...And with methods:fromruntime_finalimportfinalclassFoo:@finaldeffoo(self):...classBar(Foo):deffoo(self):# Raises RuntimeError...And with other decorators:fromruntime_finalimportfinalclassFoo:@final@propertydeffoo(self):...@final@staticmethoddefbar():...@final@classmethoddefbaz(cls):...classBar(Foo):@propertydeffoo(self):# Raises RuntimeError...@staticmethoddefbar():# Raises RuntimeError...@classmethoddefbaz(cls):# Raises RuntimeError...With property setters:fromruntime_finalimportfinalclassFoo:@propertydeffoo(self):...# Note that the `final` decorator must only be applied to the last definition.@final@foo.setterdeffoo(self,foo):...
Package: amundsenatlastypes
Amundsen Atlas TypesKickstart your Apache Atlas to support Amundsen using the prebuilt functions and required entity definitions.Installation:The package is available on PyPi, which you can install using below.pipinstallamundsenatlastypesUsage:Connecting to Apache Atlas:amundsenatlastypesuses environment variables to connect to Apache Atlas.Following are the environment variables need to be set in order to connect to
Apache Atlas.-ATLAS_HOST[default=localhost]-ATLAS_PORT[default=21000]-ATLAS_USERNAME[default=admin]-ATLAS_PASSWORD[default=admin]Kickstart Apache AtlasA single python function is available that you can use to apply all required entity definitions.
You can run this function as many times as you want, and it will not break any existing functionality, that means
that it can also be implemented in your pipelines.fromamundsenatlastypesimportInitializerinit=Initializer()init.create_required_entities()There also is a functionality to initiate your existing data to work accordingly with Amundsen.
To create required relations you need to setfix_existing_data=Truewhile calling thecreate_required_entities().fromamundsenatlastypesimportInitializerinit=Initializer()init.create_required_entities(fix_existing_data=True)Sample Dataamundsenatlastypesprovides sample data so you can populate your Atlas not only with entity definitions but also
concrete entities.Prerequisitespipinstallamundsenatlastypes[samples]Table Sample Datafromamundsenatlastypes.schema.table.sample_dataimportSampleTableDatatable_loader=SampleTableData()table_loader.create()Dashboard Sample Datafromamundsenatlastypes.schema.dashboard.sample_dataimportSampleDashboardData# Fill below variables with appropriate valuestable_guid=''user_guid=''loader=SampleDashboardData(table_guid,user_guid)loader.create()Functionality:amundsenatlastypesprovides a number of functions that can be used separately to
implement/apply entity definitions of Apache Atlas, which are availablehere.You can also simply access the individual entity definitions in JSON format by importing them
fromhere.Sample Dataamundsenatlastypesprovides sample data so you can populate your Atlas not only with entity definitions but also
concrete entities.
Package: amundsen-common
Amundsen CommonAmundsen Common library holds common codes among micro services in Amundsen.
For information about Amundsen and our other services, visit themain repository. Please also see our instructions for aquick startsetup  of Amundsen with dummy data, and anoverview of the architecture.RequirementsPython >= 3.6Dochttps://www.amundsen.io/amundsen/
Package: amundsencommon-azure
Amundsen CommonAmundsen Common library holds common codes among micro services in Amundsen.
For information about Amundsen and our other services, visit themain repository. Please also see our instructions for aquick startsetup  of Amundsen with dummy data, and anoverview of the architecture.RequirementsPython >= 3.6Dochttps://www.amundsen.io/amundsen/
Package: amundsen-common-rudeserver
Amundsen CommonAmundsen Common library holds common codes among micro services in Amundsen.
For information about Amundsen and our other services, visit themain repository. Please also see our instructions for aquick startsetup  of Amundsen with dummy data, and anoverview of the architecture.RequirementsPython >= 3.6Buildint Pypi DistroUpdate version in setup.pyGrab account credentials for PyPihttps://pypi.org/Build and upload distro:# clean
deactivate
rm -rf venv/
rm -rf dist/

# venv
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt 

# build / test
python3 setup.py install
python3 -bb -m pytest tests

# make dist
ls dist/
python3 setup.py sdist
ls dist/

# upload
pip install twine
twine upload dist/*
Package: amuni-pysample
amuni_pysampleLooking to up skill and have some fun building a personal AI, I started to get more serious about Python. This repo is part rant, part jotting down the choices I made after reading articles from people who know a lot more.Using this repo via gitgit clonehttps://github.com/amishamuni/amuni_pysample.gitcd amuni_pysamplepython -m venv env : Create a virtual env.\env\Scripts\activate : Activate the virtual envpython -m main : Invoke and play around modifying what you wantpytest : To run the sample test or any that you adddeactivate : Deactivate virtual environmentUsing this repo from TestPyPImkdir trialcd trialpython -m venv envpython -m pip install --index-urlhttps://test.pypi.org/simple/--no-deps amuni-pysample==x.y.zTestPyPI doesnt have the pytest and streamlit versions I specify so install them manually using pippython -m sample.mainA sample repo for pythonThis template uses a src layout, and will iterate to use the following:requirements.txtto specify the dependencies required.pyproject.tomlto specify project metadata and build tools in a tool agnostic format.Blackas a code formatter,mypyas a type checker,Ruffas a fast linter,pyromaas a packaging linter.Build toolswith pip as build frontend, setuptools as build backend.pytestfor a test suite.pre-commitas a pre-commit tool, to automate checks to be run on your code before a commit.Github actionsto automate building, testing and deploying code.TestPyPIandPyPIto distribute the package as per recommended process, viatwineFurther readinghttps://github.com/pypa/sampleproject/tree/mainhttps://packaging.python.org/en/latest/guides/tool-recommendations/https://packaging.python.org/en/latest/flow/https://docs.python.org/3/tutorial/index.html
Package: amunra-sphinx-theme
SummaryAmunraprovides a lightweight, easy-to-use, responsive theme for Sphinx based on Bootstrap 4.
It features a minimalist top navigation bar which can be configured manually
or using Sphinx’s standardtoctreedirective.DemoSee the theme in action here:https://barentsen.github.io/amunra-sphinx-theme/(view source)https://docs.lightkurve.org/(view source)InstallationInstall the theme:pip install amunra-sphinx-themeConfigure it in your Sphinx’sconf.pyconfiguration file
as follows:html_theme = "amunra_sphinx_theme"Configure the theme options by adding the following snippet
in yourconf.pyfile:html_theme_options = {
    # Title shown in the top left. (Default: ``project`` value.)
    "navbar_title": "Amunra",

    # Links to shown in the top bar. (Default: top-level ``toctree`` entries.)
    "navbar_links": [
        ("Quickstart", "quickstart"),
        ("Tutorials", "tutorials/index"),
        ("API", "api/index"),
        ("About", "about/index"),
    ],

    # If ``github_link`` is set, a GitHub icon will be shown in the top right.
    "github_link": "https://github.com/barentsen/amunra-sphinx-theme",

    # Text to show in the footer of every page.
    "footer_text": "Created with ♥ by Geert Barentsen.",

    # Google Analytics ID. (Optional.)
    "analytics_id": "UA-XXXXX-X"
}Optional: create a nice splash page for your project by including the
following code in yourindex.rstfile:.. title:: Your-Project-Title

.. container:: lead

    Your-Project-Title

    A short description of your project.

    .. raw:: html

        <a href="quickstart.html" class="btn btn-primary">Quickstart →</a>
Package: amuse-fresco
FrescoFresco aims to simulate observations of particle-based simulations, such as
those of a star cluster. It creates an observation-like image from a list of
stars and/or gas particles. Supported filetypes include AMUSE-type hdf5 files,
Starlab files and plaintext files.For stars, the temperature and radius are calculated using a stellar evolution
code, if these are not already present in the dataset.Gas particles may also be read. In combination with stars, these will cause
reflection from nearby stars and optionally extinction of light from
background. Without stars, Fresco will make a density plot of the gas.
Optionally, the gas may also be indicated with contour lines.A random field of background and foreground stars may be added to the image, as
a way to make the image more natural looking and/or to provide a background
that may be obscured by the gas/dust particles.RequirementsPython 3.6 or higherNumpyScipyMatplotlibAMUSE (https://github.com/amusecode/amuse)a stellar evolution code (e.g. SSE or SeBa, for calculating stellar luminosities and radii)optional: Fi (for calculating dust extinction)Astropyamuse-masc (recommended)Usageimport matplotlib.pyplot as plt
from amuse.datamodel import Particles
from amuse.units import units, nbody_system
from amuse.community.sse.interface import SSE
from amuse.ext.masc import make_a_star_cluster
from amuse.ext.fresco import make_fresco_image
?make_fresco_image  # See options
stars = make_a_star_cluster.new_cluster()
gas = Particles()
se = SSE()
se.particles.add_particles(stars)
from_se = se.particles.new_channel_to(stars)
from_se.copy()
image, vmax = make_fresco_image(
    stars, gas,
    mode=["stars"],
    return_vmax=True,
)
plt.imshow(image)
plt.show()AuthorsFresco is developed by Inti Pelupessy and Steven Rieder