Saravanan666/pypi-org huggingface dataset:
Package: deailab
deailabA DeAI JupyterLab extension.DeAILab is a JupyterLab extension to interact with theDecentralized AI Requestlibrary.RequirementsJupyterLab >= 4.0.0InstallTo install the extension, execute:pipinstalldeailabUninstallTo remove the extension, execute:pipuninstalldeailabTroubleshootIf you are seeing the frontend extension, but it is not working, check
that the server extension is enabled:jupyterserverextensionlistIf the server extension is installed and enabled, but you are not seeing
the frontend extension, check the frontend extension is installed:jupyterlabextensionlistContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the deailab directory# Install package in development modepipinstall-e".[test]"# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# Server extension must be manually installed in develop modejupyterserverextensionenabledeailab# Rebuild extension Typescript source after making changesjlpmbuildYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=FalseDevelopment uninstall# Server extension must be manually disabled in develop modejupyterserverextensiondisabledeailab
pipuninstalldeailabIn development mode, you will also need to remove the symlink created byjupyter labextension developcommand. To find its location, you can runjupyter labextension listto figure out where thelabextensionsfolder is located. Then you can remove the symlink nameddeailabwithin that folder.Testing the extensionServer testsThis extension is usingPytestfor Python code testing.Install test dependencies (needed only once):pipinstall-e".[test]"# Each time you install the Python package, you need to restore the front-end extension linkjupyterlabextensiondevelop.--overwriteTo execute them, run:pytest-vv-rap--covdeailabFrontend testsThis extension is usingJestfor JavaScript code testing.To execute them, execute:jlpm
jlpmtestIntegration testsThis extension usesPlaywrightfor the integration tests (aka user level tests).
More precisely, the JupyterLab helperGalatais used to handle testing the extension in JupyterLab.More information are provided within theui-testsREADME.Packaging the extensionSeeRELEASE
Package: deairequest
The Decentralised AI RequestEnable for any AI python code to be executed on decentralised AI compute.Supported AI compute:BacalhauRequired:
Have a working IPFS Desktop App running on the same machine. You can download ithere.Commands:python -m build # build the projectpython -m unittest # run all unit testsUsage:from deairequest import DeProtocolSelector as selectorbp = selector.DeProtocolSelector("Bacalhau")bp.get_docker_images()if a user wants a custom imagebp.add_docker_image("custom_images")For each request you need to set the docker image to usebp.set_docker_image("the docker image to use")To add datasets of type URL:bp.add_dataset(bp.get_url_data_type(),"https://www...")Of type File:bp.add_dataset(bp.get_file_data_type(),"/path/to/file/name.csv")Of type Directory:bp.add_dataset(bp.get_directory_data_type(),"/path/to/directory/")Of type IPFS:bp.add_dataset(bp.get_ipfs_data_type(),"AW233dfD23dsds32323sdds") # The IPFS CIDTo get all the datasets:bp.get_datasets()output: [{"url":"https://www..."},{"file":"/path/to/file/name.csv"},{"directory":"/path/to/directory/"},{"ipfs":"AW233dfD23dsds32323sdds"}]Afterwards you can submit a jobjob = bp.submit_job(Path("/path/to/notebook.jpynb"))get the logsstate = bp.get_state(job)and when the job is finished and the state changes from "InProgress" to either "Complete" or "Error"result = bp.get_results(job,Path("/path/to/output/directory/"))
Package: deal
A Python library fordesign by contract(DbC) and checking values, exceptions, and side-effects. In a nutshell, deal empowers you to write bug-free code. By adding a few decorators to your code, you get for free tests, static analysis, formal verification, and much more. Readintroto get started.FeaturesClassic DbC: precondition, postcondition, invariant.Tracking exceptions and side-effects.Property-based testing.Static checker.Integration with pytest, flake8, sphinx, and hypothesis.Type annotations support.External validators support.Contracts for importing modules.Can be enabled or disabled on production.Colorless: annotate only what you want. Hence, easy integration into an existing project.Colorful: syntax highlighting for every piece of code in every command.Memory leaks detection: deal makes sure that pure functions don't leave unexpected objects in the memory.DRY: test discovery, error messages generation.Partial execution: linter executes contracts to statically check possible values.Formal verification: prove that your code works for all input (or find out when it doesn't).Zero-dependency runtime: there are some dependencies for analysis tools, but nothing of it is required on the production.Fast: each code change is benchmarked and profiled.Reliable: the library has 100% test coverage, partially verified, and runs on production by multiple companies since 2018.Deal in 30 seconds# the result is always non-negative@deal.post(lambdaresult:result>=0)# the function has no side-effects@deal.puredefcount(items:List[str],item:str)->int:returnitems.count(item)# generate test functiontest_count=deal.cases(count)Now we can:Runpython3 -m deal lintorflake8to statically check errors.Runpython3 -m deal testorpytestto generate and run tests.Just use the function in the project and check errors in runtime.Read more in thedocumentation.Installationpython3-mpipinstall--user'deal[all]'ContributingContributions are welcome! A few ideas what you can contribute:Add new checks for the linter.Improve documentation.Add more tests.Improve performance.Found a bug? Fix it!Made an article about deal? Great! Let's add it into theREADME.md.Don't have time to code? No worries! Just tell your friends and subscribers about the project. More users -> more contributors -> more cool features.To run tests locally, all you need istask. Runtask allto run all code formatters, linters, and tests.Thank you :heart:
Package: dealcloud-api-wrapper
DealCloud API WrapperThis package provides a simple wrapper for interacting with the DealCloud REST API.InstallationThe package can be installed throughpip:pip install dealcloud-api-wrapperThe package depends onrequests,requests_oauthlib, andoauthlib.ExampleUsing the package is simple:fromdealcloud_api_wrapperimportdc_client# Initialize Client objectdc=dc_client.Client(hostname='your hostname here',client_id='your client id',client_secret='your client secret')# Call schema/data methods (more examples in dc_schema and dc_data classes)dc_schema_result=dc.schema_get_entrytypes()dc_data_result=dc.data_get_row_entry(entryTypeId,query={'your query'},params={'your params'})
Package: dealib
Project descriptiondealibis a library developed in Python for conducting Data Envelopment Analysis (DEA).User documentation can be foundhttps://artyomviryutin.github.io/dealib.Library provides following models and options:Models:Envelopment modelMultiplier modelSlack modelAdditive modelSuper-efficiency modelDirect modelMulti-directional modelOrientation:InputOutputReturns to scale (RTS):Variable returns to scale (VRS)Constant returns to scale (CRS)Decreasing returns to scale (DRS)Increasing returns to scale (IRS)SourceThe latest version can be found athttps://github.com/ArtyomViryutin/dealibInstallationUsing pippip install dealibUsing gitgit clone https://github.com/ArtyomViryutin/dealib.git
Package: deal-solver
deal-solverz3-powered solver (theorem prover) fordeal.python3-mpipinstalldeal-solverCLIFor CLI usage, see thedeal documentation. The solver doesn't provide a CLI on its own.APIDeal-solver is created specifically for deal. So, if you want to use it with another tool, you have to mimic deal. It's not hard, though. SeeTestTheoremimplementation intests/helpers.py.The project stateThis is an experimental project. it supports only limited subset of syntax an types. Still, it works for some simple cases. So, give it a try, it is free.
Package: dealstat
=================DealStat Utilities=================.. image:: https://img.shields.io/pypi/v/dealstat.svg:target: https://pypi.python.org/pypi/dealstat.. image:: https://img.shields.io/travis/ecatkins/dealstat.svg:target: https://travis-ci.org/ecatkins/dealstat.. image:: https://readthedocs.org/projects/dealstat/badge/?version=latest:target: https://dealstat.readthedocs.io/en/latest/?badge=latest:alt: Documentation Status.. image:: https://pyup.io/repos/github/ecatkins/dealstat/shield.svg:target: https://pyup.io/repos/github/ecatkins/dealstat/:alt: UpdatesDealStat Utilities* Free software: MIT licenseDealstat--------Generic functions that may be moved to specific modules at some point:::from dealstat.dealstat import *# generate random letter based ID of given lengthmy_id = unique_id(30)Boto--------Simplifies some of AWS' Boto3 functionality (at the moment, just S3)* First save `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` as environment variables::from dealstat.boto import Botos3 = Boto('s3')location1 = {'bucket':'<some-bucket>', 'key': '<some-key'>}location2 = {'bucket':'<some-other-bucket>', 'key': '<some-other-key'>}# Get temporary pre-signed urlurl = s3.get_temp_url(location1)# Move object from one bucket/key to anothers3.move_object(location1, location2)# Upload filefile_path = '/some/file/path.txt's3.upload_file(file_path, location1)# Download filedestination_file_path = 'local/file/path2.txt's3.download_file(destination_file_path, location2)# List contents of bucket# Use prefix='some-prefix' to search for specific key prefixes# Use exclude_dirs=True to not return directories in results3.list_bucket('<some-bucket'>, prefix=None, exclude_dirs=True)Machine Learning--------Random utilities useful in ML prototyping* Download and use Standform NLP Glove Embedings ::from dealstat.ml import EmbeddingsEmbed = Embeddings()# Download embeddingsEmbed.download_embeddings()# Unzip embeddingsEmbed.extract_embeddings()# Generate embeddings look up dict for given dimensiondim = 200embedding_dict = Embed.generate(loc='.', dim=dim)Credits-------This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template... _Cookiecutter: https://github.com/audreyr/cookiecutter.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage=======History=======0.1.0 (2018-08-23)------------------* First release on PyPI.
Package: dealtape-python-sdk
# Recurrent.ai DealTape SDK for Python概述DealTape数据推送SDK安装方式使用PIP进行安装（以Linux系统为例）$pipinstalldealtape也可以直接安装解压后的安装包sudopythonsetup.pyinstall快速使用# -*- coding: utf-8 -*-fromdealtapeimportCallLog,DealTapeClientfromdatetimeimportdatetimebusiness='YOUR_BUSINESS_KEY'# 企业的唯一标识，即在企业DealTape系统中的二级域名client=DealTapeClient(business=business)item=CallLog(url="CALLLOG_AUDIO_URL",# 电话录音的urlid="CALLLOG_UNIQUE_IDENTIFIER",# 电话在客户内部系统中的唯一标示staff_id="STAFF_ID",# 该电话坐席的唯一标示customer_id="CUSTOMER_ID",# 客户的唯一标示deal_closed=True/False,# 该电话是否成单timestamp=TIMESTAMP# 电话的拨打时间（datetime.datetime类型, 或是int类型的unix时间戳）)resp=client.push_calllog(item)ifnotresp.ok:print(resp.text)
Package: dean
simplestatVery minimal statistics module. Useful when you dont have the disk space for numpyOnly contains the following functions (and only for 1d arrays):
mean(q)
std(q,m=None)#can set m=mean(q) to save computation time
min(q)
argmin(q)
max(q)
argmax(q)
statinf(q)
return information about the object as dictionary
sstr(q)
statinf+json.dumps(indent=2)
sprint(q)
print(sstr())
Package: deap-er
DEAP-ERDEAP-ER is a complete rework and refactor of the original DEAP evolutionary
computation framework library for Python 3.9, 3.10 and up.
It seeks to make algorithms explicit and data structures transparent.
It works in perfect harmony with parallelization mechanisms such as
multiprocessing andRay.DEAP includes the following features:Genetic algorithm using any imaginable representationList, Array, Set, Dictionary, Tree, Numpy Array, etc.Genetic programming using prefix treesLoosely typed, Strongly typedAutomatically defined functionsEvolution strategies (including CMA-ES)Multi-objective optimisation (NSGA-II, NSGA-III, SPEA2, MO-CMA-ES)Co-evolution (cooperative and competitive) of multiple populationsParallelization of the evaluations (and more)Hall of Fame of the best individuals that lived in the populationCheckpoints that take snapshots of a system regularlyBenchmarks module containing most common test functionsGenealogy of an evolution, that is also compatible withNetworkXExamples of alternative algorithms : Particle Swarm Optimization, Differential Evolution, Estimation of Distribution AlgorithmDocumentationSee theDocumentationfor the user guide, tutorials and the reference manual.Installationpipinstalldeap-erImportingfromdeap_erimportbase,creator,tools,env,gpContributingPlease read the CONTRIBUTING.md file before submitting pull requests.
Package: deareis
DearEISA GUI program for analyzing, simulating, and visualizing impedance spectra.Table of contentsAboutChangelogContributingLicenseAboutDearEIS is a Python package that includes a program with a graphical user interface (GUI) for working with impedance spectra.
An application programming interface (API) is also included that is primarily for batch processing.
The target audience is researchers who use electrochemical impedance spectroscopy (EIS) though the program may also be useful in educational settings.The GUI program implements features such as:projects that can contain multiple experimental data sets and analysis resultsreading certain data formats and parsing the experimental data contained withinvalidation of impedance spectra using linear Kramers-Kronig tests or the Z-HIT algorithmestimation of the distribution of relaxation times (DRT)construction of circuits, e.g., by parsing circuit description codes (CDC) or by using the included graphical editorsupport for user-defined circuit elementscomplex non-linear least squares fitting of equivalent circuitssimulation of the impedance spectra of circuitsvisualization of impedance spectra and/or various analysis resultsSee theofficial documentationfor instructions on how to  install DearEIS, screenshots and guides, and the API reference.Those who would prefer to only use an API (or a command-line interface (CLI)) for everything may wish to usepyimpspecinstead.ChangelogSeeCHANGELOG.mdfor details.ContributingIf you wish to contribute to the further development of DearEIS, then there are several options available to you depending on your ability and the amount of time that you can spare.If you find bugs, wish some feature was added, or find the documentation to be lacking, then please open an issue onGitHub.If you wish to contribute code, then start by cloning the repository:git clone https://github.com/vyrjana/DearEIS.gitThe development dependencies can be installed from within the repository directory:pip install -r ./dev-requirements.txtCreate a new branch based on either themainbranch or the most recent development branch (e.g.,dev-*), and submit your changes as a pull request.Note that some of the core functionality of DearEIS is based onpyimpspecand thus certain changes (e.g., parsers for data formats) should be contributed to that project instead.Code contributions should, if it is applicable, also include unit tests, which should be implemented in files placed in thetestsfolder found in the root of the repository along with any assets required by the tests.
It should be possible to run the tests by executing therun_tests.shscript, which uses the test discovery built into theunittestmodule that is included with Python.SeeCONTRIBUTORSfor a list of people who have contributed to the DearEIS project.LicenseCopyright 2023 DearEIS developersDearEIS is licensed under theGPLv3 or later.The licenses of DearEIS' dependencies and/or sources of portions of code are included in the LICENSES folder.
Package: dearmor
dearmorDeobfuscatepyarmorencryption.It is best to use it with the pyc files extracted from the exe file, but exe file should work.
Working only on windows.It was not checked with custom pyarmor modes, only with the default configuration.MethodDearmor injects a dll into the running process, which calls a python function to run custom code. Using the custom code dearmor calls each function the exists in the file and deobfuscate it.Rundearmor -i {file_path}The files will be created in a folder called "dump" in the same directoryTo change the files from pyc to py, usedocompyle++installationpip install dearmorContributeJust ask away or make a pull request.
If something is unclear open an issueDesclaimerThis repo is for educational purposes only. I take no responsibility for its usage.Tested versions:3.63.73.83.9
Package: dearprudence
dearprudenceInternal Python library filled with sugar for swallowing downscalingCMIP6 parameter files.Examplesimportdearprudencetasmax_spec=dearprudence.read_params("GFDL-ESM4-tasmax.yaml")print(tasmax_spec[0].ssp)# Cmip6Record(activity_id='ScenarioMIP',#             experiment_id='ssp370',#             table_id='day',#             variable_id='tasmax',#             source_id='GFDL-ESM4',#             institution_id='NOAA-GFDL',#             member_id='r1i1p1f1',#             grid_label='gr1',#             version='20180701')tasmax_spec[0].variable_id="foobar"dearprudence.write_params("pointlessly_modified.yaml",tasmax_spec)ifdearprudence.cmip6_catalog_has(tasmax_spec[0].ssp):print("Exists in CMIP6 In The Cloud!")InstallationInstall withpipusing:pipinstalldearprudencedearprudencerequires Python > 3.9. No external packages are required. Theintake_esmpackage needs to be installed to usedearprudence.check_cmip6_catalog().Install the unreleased bleeding-edge version of the package with:pipinstallgit+https://github.com/brews/dearprudenceSupportSource code is available online athttps://github.com/brews/dearprudence/. This software is Open Source and available under the Apache License, Version 2.0.DevelopmentPlease file bugs in thebug tracker.Want to contribute? Great! Fork the main branch and file a pull request when you're ready. Please be sure to write unit tests and followpep8. Fork away!
Package: dearpygui-ext
(This library is available under a free and permissive license however, if you EnjoyDear PyGuiplease consider becoming aSponsor)Dear PyGui Extensionsis a collection of useful tools, abstractions, and simplification layers built with/forDear PyGuiusers.InstallationEnsure you have at least Python 3.6 64bit anddearpygui.pip install dearpygui_ext

or

pip3 install dearpygui_extResourcesDocumentationcomprehensive documentaion, tutorials, and examples.Feature Trackerall proposed new features.Bug Trackercurrent bugs and issues.SupportIf you are having issues or want to help, here are some places you can go:Github DiscussionsDiscord ForumRedditSponsorsIf you enjoyDear PyGuiandDear PyGui Extensionsplease consider becoming asponsor.OngoingDear PyGuidevelopment is financially supported by users and private sponsors.These include:🏢Anthony TanbakuchiCorporate Sponsor🏆Dean KeinanPartner Sponsor🏆何凌锋Partner Sponsor🏆Anthony DoupePartner Sponsor🏆Ray HeasmanPartner Sponsor🏆Marco StuderPartner Sponsor🏆ScriptsPartner Sponsor🥇Caden BloxhamGold Sponsor🥇Yan ZaretskiyGold Sponsor🥇Leron GrayGold Sponsor🥇TrinnikGold Sponsor🥇Barney ManneringsGold Sponsor🥇RB BlackstoneGold Sponsor🥇Charles RayGold SponsorThank you to all othersponsorsfor keeping this project moving forward!CreditsDeveloped byJonathan Hoffstadt,Preston Cothren, and every direct or indirect contributor.Omar Cornutfor all his incredible work onDear ImGui.Evan Pezentfor all his work onImPlot.Johann Muszynskifor all of his work onimnodes.LicenseDear PyGuiandDear PyGui Extensionsare licensed under theMIT License.
Package: dearpygui-extend
DearPyGui_ExtendExtensions and custom widgets forDear Py GUIInstallation:pip install dearpygui-extendAPI Documentation:**Also check "examples" folder.Movable GroupsAdd Drag'n'drop ability to groups ("swap" or "replace" behaviors):Usage:importdearpygui.dearpyguiasdpgimportdearpygui_extendasdpgewithdpge.movable_group():dpg.add_text('Some text')...File browserA custom filebrowser with extended functionality.Features:Supportsfile sequenceentries:image.001.jpg, image.002.jpg, image.003.jpg --> 'image.###.jpg (001-003)'Multi-selection (pick single or multiple files/sequences)Breadcrumb path with navigation icons & folder quick accessFiletype filtersSorting (smart sorting for collapsed sequences)Draggable items (ability to expand file sequences on a drop callback)[!NOTE]
RequiresFileseqpackage:pip install fileseqUsage:importdearpygui.dearpyguiasdpgimportdearpygui_extendasdpgedpge.add_file_browser(initial_path='~/Downloads/images',collapse_sequences=True,sequence_padding='#')LayoutA simple, responsive, text-based layouting system that abstracts table creation process away from the user.Example:LAYOUT example center center
  COL left_menu 0.2
  COL
    ROW 0.3
      COL left_content
      COL right_content
    ROW
      COL bottom_content
  COL right_menu 0.2will produce this layout:Usage:importdearpygui.dearpyguiasdpgimportdearpygui_extendasdpge# use "tab" for identationlayout='''LAYOUT example center centerCOL left_menu 0.2COLROW 0.3COL left_contentCOL right_contentROWCOL bottom_contentCOL right_menu 0.2'''# create layoutwithdpg.window():dpge.add_layout(layout,border=True)# accessing layout paneswithdpg.group(parent='left_content'):#add widgetsdpg.add_text('User login:')dpg.add_input_text(label='username')dpg.add_input_text(label='password')dpg.add_button(label='Login')