Saravanan666/pypi-org huggingface dataset:
Package: deep-kolibri
KolibriA comprehensive multi modal machine learning platformContents├── README.md
├── configREADME.md: this documentationSetting up PyFreeLing in Mac OS SierraThere are 4 types of dependencies:Homebrew, a package manager to install software in MacFreeLing, an open source language analysis tool suitePython 3lxml, a Python library to work with XMLlibxml2andlibxsltC libraries which are dependencies oflxmlInstall HomebrewFollowNeil Gee's guideto install and set up homebrew for Mac OS SierraInstall FreeLingUse Homebrew to install FreeLing by running this command:brewinstallfreelingHomebrew will take care of any dependencies.Install Python 3You can install Python 3 with Homebrew following the instructions fromThe Hitchhiker's Guide to Pythonor following the very completeLisa Tagliaferri's guide.Basically:brewinstallpython3Install libxml2 and libxsltmacOS Sierra already provideslibxml2andlibxslt. They can be installed through Homebrew though:brewinstalllibxml2
brewinstalllibxsltInstall lxmlNow, you are ready to installlxml:pip3installlxmlOnce you have installed FreeLing and all the dependencies, you will always need to start a FreeLing analyzer in server modeStarting a FreeLing analyzer in server modeanalyze-fen.cfg--server--port50005&Install pyaudioinstall pyaudio in WindowsIntalling pyaudiocan be tricky in window platform and generally 'pip install pyaudio' will not work.
see the following stackoverflow response if you have any problem.https://stackoverflow.com/questions/52283840/i-cant-install-pyaudio-on-windows-how-to-solve-error-microsoft-visual-c-14Install pyaudio in mac os xFirst install portaudiobrewinstallportaudiothe run the following commandpipinstall--global-option='build_ext'--global-option='-I/usr/local/include'--global-option='-L/usr/local/lib'pyaudioinstall pocketsphinxInstaaling this library could be difficult on some systems.
If the command:pipinstallpocketsphinxdid not work for you then try the following stepsgitclone--recursivehttps://github.com/bambocher/pocketsphinx-pythoncdpocketsphinx-pythonEdit file pocketsphinx-python/deps/sphinxbase/src/libsphinxad/ad_openal.c.Change#include <al.h>
#include <alc.h>to#include <OpenAL/al.h>
#include <OpenAL/alc.h>and finally:pythonsetup.pyinstall
Package: deeplabcutcore
DeepLabCut-coreCore functionalities of DeepLabCut, excluding all GUI functions.Currently up to date withDeepLabCut v2.1.8.1. AND uses tensorflow 2.XPlease be aware, you can create projects, etc. with the full deeplabcut package. Here, you will need to create the training set and train, evaluate, etc. not inter-mixing with using the deeplabcut package (it currently supports tensorflow 1.x). We recommend looking at thisgoogle colab notebookto help you, andthis blog postabout our transitition to tensorflow 2.Install from GitHub:pip install git+https://github.com/DeepLabCut/DeepLabCut-corePyPi:pip install deeplabcutcoreDocumentation is located atDeepLabCut's main GitHub page.
Package: deepl-api
deepl-api-pyThis repository contains aPythonimplementation of theDeepL REST API.ContentsAPython packagefor easy integration into Python applications.Thedeeplunix-style commandline applicationfor integration into existing toolchains without any programming effort.Unit and integration tests.Please refer to the linked documentation for instructions on how to get started with the API and/or the CLI tool.FeaturesQuery your account usage & limits information.Fetch the list of available source and target languages provided by DeepL.Translate text.Not ImplementedSupport for the(beta) document translation endpoint.Support for advanced parameters ofHandling XMLin the translation endpoint (outline_detection, splitting_tags, non_splitting_tags, ignore_tags).See AlsoThere are comparable implementations forRustandRuby.
Package: deepl_cli
deepl-cliDeepL TranslatorCLI usingplaywright-pythonNote:This project works without DeepL API key. With DeepL API, useDeepLcom/deepl-pythonInstallpipinstalldeepl-cliUsageCLI$ deepl -h
usage: deepl [-h] (-f PATH | -s) [--fr FR] --to TO [-t MS] [-v] [-V]

DeepL Translator CLI without API Key

optional arguments:
  -h, --help            show this help message and exit
  -f PATH, --file PATH  source text file to translate (default: None)
  -s, --stdin           read source text from stdin (default: False)
  --fr FR               input language (default: auto)
  --to TO               output language (default: None)
  -t MS, --timeout MS   timeout interval (default: 5000)
  -v, --verbose         make output verbose (default: False)
  -V, --version         show program's version number and exit

valid languages of `--fr`:
{'fi', 'cs', 'lv', 'nl', 'el', 'auto', 'ru', 'da', 'sv', 'it', 'uk', 'zh', 'ko', 'et', 'de', 'en', 'es', 'bg', 'lt', 'ja', 'pl', 'tr', 'id', 'sk', 'sl', 'hu', 'fr', 'ro', 'pt'}

valid languages of `--to`:
{'fi', 'cs', 'lv', 'nl', 'lt', 'ja', 'el', 'pl', 'ru', 'tr', 'da', 'sv', 'pt', 'id', 'it', 'sk', 'sl', 'hu', 'fr', 'uk', 'zh', 'ko', 'et', 'de', 'en', 'ro', 'es', 'bg'}PackagefromdeeplimportDeepLCLIdeepl=DeepLCLI("en","ja")deepl.translate("hello")#=> "こんにちわ"If you use with asyncio, UseDeepLCLI.translate_async. Seeexamples/async.py.LicenseMIT
Package: deep-leaps
deep-leaps is a deep learning training framework written based on DDD (data driven development). It has the following features.Training/testing procedure abstracted by graphthe training & testing procedure is based on graphs. then, you can add or remove nodes in the graph at runtime. For example, if you want to visualize the model in the middle of training, you can add a visualization command at runtime. this does not affect training.Instruction modification at runtimeIf you want to modify the data or force the learning rate to be adjusted, you can modify the instruction using ipc at runtime.Code modification at runtimedeep-leaps allows code modification at runtime. you can command the python file recompile command at runtime using ipc.Installpip install deep-leapsmake workspaceRun the following python command in the project root.fromdeepleaps.app.appimportAppApp.make_workspace('./')result:|--exampleDataset
|    |--0001.jpg
|    |--0002.jpg
|    |--0000.jpg
|--resource
|    |--output
|        |--README.md
|    |--configs
|        |--dataloader
|            |--exampleDataLoader.yaml
|        |--model
|            |--SimpleLayerModel.yaml
|        |--dataset
|            |--Example.yaml
|        |--command
|            |--default_runnable_command.yaml
|        |--trainer
|            |--ExampleContainer.yaml
|        |--default.yaml
|--src
|    |--dataloader
|        |--Exampledataset.py
|        |--TensorTypes.py
|        |--transforms.py
|    |--model
|        |--SimpleConv.py
|    |--trainer
|        |--ExampleContainer.py
|    |--ipc
|        |--CustomCommand.py
|--client.py
|--main.pCommandUnlike the existing framework, deep-leaps is executed depending on the command.
the basic training process can be applied as follows. please check the example project for more details.DEFAULT:[$root( $TRAINER_CONTAINER_LOAD->$TRAINING_LOADER( $MAIN_MODEL_LOAD->$TRAINING_BATCH( $TRAINING_STEP )->MAIN_MODEL_SAVE) )]DEFINE:TRAINER_CONTAINER_LOAD:command:'TrainerContainerLoaderCommand'args:'resource/configs/trainer/ExampleContainer.yaml'finish:TrueMAIN_MODEL_LOAD:command:'ModuleLoadClass'required:['MODEL','OPTIMIZER']base_path:'$base'finish:Trueargs:MODEL:_reload:Falseuse_hook:Truefile_name:$latest.idClientCOMMAND_CONTROLLER:ipc_host:'127.0.0.1'ipc_port:1568You can specify ipc_host and ipc_port through configuration. Using this address, you can communicate with the training network model. the communication example is as follows.importsocketimportthreadingfromstructimportpackhost='127.0.0.1'port=1568client_socket=socket.socket(socket.AF_INET,socket.SOCK_STREAM)client_socket.connect((host,port))try:whileTrue:data=input(':')length=pack('>Q',len(data))client_socket.sendall(length)client_socket.sendall(data.encode())ack=client_socket.recv(1)print('send ack ok')exceptExceptionase:print(e)client_socket.close()
Package: deeplearing-tools
📦 setup.py (for humans)This repo exists to providean example setup.pyfile, that can be used
to bootstrap your next Python project. It includes some advanced
patterns and best practices forsetup.py, as well as some
commented–out nice–to–haves.For example, thissetup.pyprovides a$ python setup.py uploadcommand, which creates auniversal wheel(andsdist) and uploads
your package toPyPiusingTwine, without the need for an annoyingsetup.cfgfile. It also creates/uploads a new git tag, automatically.In short,setup.pyfiles can be daunting to approach, when first
starting out — even Guido has been heard saying, "everyone cargo cults
thems". It's true — so, I want this repo to be the best place to
copy–paste from :)Check out the example!Installationcdyour_project# Download the setup.py file:#  download with wgetwgethttps://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.py-Osetup.py#  download with curlcurl-Ohttps://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.pyTo DoTests via$ setup.py test(if it's concise).Pull requests are encouraged!More ResourcesWhat is setup.py?on Stack OverflowOfficial Python Packaging User GuideThe Hitchhiker's Guide to PackagingCookiecutter template for a Python packageLicenseThis is free and unencumbered software released into the public domain.Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any means.
Package: deeplearning2020
Begleitendes Python Package zum KursEine praktische Einführung in Deep Learning für Computer VisionaufOpenHPI.$pipinstall--upgradedeeplearning2020In einemjupyter notebookwie Google Colab geht das mit!pipinstall--upgradedeeplearning2020Das Package enthält einige von uns bereitgestellte Hilfsfunktionen und erlaubt es euch, eure für die Übungen trainiertenkerasModelle zur Bewertung abzugeben.Nutzung der Hilfsfunktionenfromdeeplearning2020importhelpershelpers.plot_predictions(...)# BeispielNutzung zur Übungsabgabefromdeeplearning2020importSubmissionSubmission('<token>','<assignment-id>',model).submit()Der<token>und die<assignment-id>wird dir für die Abgabe mitgeteilt.
Package: deep-learning-utils
dl-utils: Utilities for Deep Learning with PyTorchContentThis package contains mainly loss functions, model definitions and metrics in both functional and modular and (whenever possible) pure PyTorch implementations.InstallationFrom sourcepip install git+https://github.com/justusschock/dl-utilsFrom PyPipip install deep-learning-utilsSubpackagesCurrently there are the following subpackages:dlutils.data: contains data utilities (so far just a dataset for random fake data)dlutils.losses: extends the losses given in PyTorch itself by a few more loss functionsdlutils.metrics: implements some common metricsdlutils.models: contains Nd implementations of many popular modelsdlutils.models.gans: contains many basic gan implementations, but so far not for arbitrary dimensionsdlutils.optims: containis additional optimizersdlutils.utils: contains additional utilities such as tensor operations and module loadingNoteMost of this code was only tested sparely and not with a proper CI/CD and unittests. I'm currently working on that and any contributions are highly welcomed.All implementations are done for pure PyTorch. You can employ them in whatever training framework you want (like [pytorch/ignite]{https://github.com/pytorch/ignite) orPytorch-Lightning) or in your custom training loops
Package: deeplenstronomy
Welcome todeeplenstronomy!deeplenstronomyis a tool for simulating large datasets for applying deep learning to strong gravitational lensing.
It works by wrapping the functionalities oflenstronomyin a convenient yaml-style interface, allowing users to embrace the astronomer part of their brain rather than their programmer part when generating training datasets.InstallationWith conda (Recommended)Step 0: Set up an environment. This can be done straightforwardly with acondainstallation:conda create -n deeplens python=3.7 jupyter scipy pandas numpy matplotlib astropy h5py PyYAML mpmath future
conda activate deeplensStep 1:pip install lenstronomyStep 2:pip install deeplenstronomyWith pipStep 1:pip install deeplenstronomyGetting Started and Example NotebooksStart by reading theGetting Started Guideto familiarize yourself with thedeeplenstronomystyle.After that, check out the example notebooks below:Notebooks fordeeplenstronomyUtilitiesCreatingdeeplenstronomyConfiguration FilesGenerating DatasetsVisualizingdeeplenstronomyImagesUtilizing Astronomical SurveysDefining Your Own Probability DistributionsUsing Your Own Images as BackgroundsSimulating Time-Series DatasetsNotebooks for Applyingdeeplenstronomyto Machine Learning AnalysesUsingdeeplenstronomyfor Active LearningUsingdeeplenstronomyfor Classification and RegressionNotebooks for Suggested Science CasesA Walkthrough of Usingdeeplenstronomyfor ScienceAPI Documentationdeeplenstronomyis designed so that users only need to work with their personal configuration files and the dataset generatation and image visualization functions.
However, if you would like to view the full API documentation, you can visit thedocspage.CitationIf you usedeeplenstronomyin your work, please include the following citations:@article{deeplenstronomy,
  doi = {10.21105/joss.02854},
  url = {https://doi.org/10.21105/joss.02854},
  year = {2021},
  publisher = {The Open Journal},
  volume = {6},
  number = {58},
  pages = {2854},
  author = {Robert Morgan and Brian Nord and Simon Birrer and Joshua Yao-Yu Lin and Jason Poh},
  title = {deeplenstronomy: A dataset simulation package for strong gravitational lensing},
  journal = {Journal of Open Source Software}
}

@article{lenstronomy,
    title     =   "lenstronomy: Multi-purpose gravitational lens modelling software package",
    journal   =   "Physics of the Dark Universe",
    volume    =   "22",
    pages     =   "189 - 201",
    year      =   "2018",
    issn      =   "2212-6864",
    doi       =   "10.1016/j.dark.2018.11.002",
    url       =   "http://www.sciencedirect.com/science/article/pii/S2212686418301869",
    author    =   "Simon Birrer and Adam Amara",
    keywords  =   "Gravitational lensing, Software, Image simulations"
}ContactIf you have any questions or run into any errors with the beta release ofdeeplenstronomy, please don't hesitate to reach out:Rob Morganrobert [dot] morgan [at] wisc.eduYou can also message me on the DES, DELVE, LSSTC, deepskies, or lenstronomers Slack workspaces
Package: deepler
deeplerdeepler is a learning support tool that records the number of words that appear through DeepL.
You can learn frequently used words efficiently.# DeepL API Free Plan is here.# https://www.deepl.com/pro#developer$exportDEEPL_AUTH_KEY=<YOURAPIKEY>

$pipinstalldeepler
$deepler
usage:deepler[-h]{translate,hist,configure}...
deepler:error:thefollowingargumentsarerequired:{translate,hist,configure}Overview# default configuration$deeplerconfigure--show{"ignores":[],"hist_file":"~/.config/deepler/counts.json","min_length":4,"source_lang":"EN","target_lang":"JA","count_lang":"EN"}$deeplertranslate--text"deepler is a learning support tool that records the number of words that appear through DeepL."inputtext(EN)deeplerisalearningsupporttoolthatrecordsthenumberofwordsthatappearthroughDeepL.

outputtext(JA)deeplerは、DeepLを通じて出現した単語の数を記録する学習支援ツールです。

$deeplerhist('that',2)('deepler',1)('learning',1)('support',1)('tool',1)('records',1)('number',1)('words',1)('appear',1)('through',1)('deepl',1)$deeplertranslate--text"deepler is a learning support tool that records the number of words that appear through DeepL."inputtext(EN)deeplerisalearningsupporttoolthatrecordsthenumberofwordsthatappearthroughDeepL.

outputtext(JA)deeplerは、DeepLを通じて出現した単語の数を記録する学習支援ツールです。

$poetryrundeeplerhist--num-words3[main]('that',4)('deepler',2)('learning',2)$poetryrundeeplerhist--min-count3[main]('that',4)Currently, only space-separated languages can be counted.
Package: deepl-fastapi
deepl-fastapi[]Your own deepl server via fastapi, cross-platform (Windows/Linux/MacOs) with API for OmegaTInstallationCreate a virual environment: optional but recommended
e.g.,# Linux and friendspython3.7-mvenv.venvsource.venv/bin/activate# Windows# py -3.7 -m venv .venv# .venv\Scripts\activatepipinstalldeepl-fastapior (if your use poetry)poetryadddeepl-fastapiorpip install git+https://github.com/ffreemt/deepl-fastapi.gitorClone the repohttps://github.com/ffreemt/deepl-fastapi.gitgitclonehttps://github.com/ffreemt/deepl-fastapi.gitandcd deepl-fastapi`pip install -r requirements.txtorpoetry installUsageStart the serverUse uvicorn directly (note thedeepl_servermodule, notrun_uvicorn)uvicorndeepl_fastapi.deepl_server:appordeepl-fastapi# this option is available only if installed via pip install or poetry addorpython3.7-mdeepl_fastapi.run_uvicornor run the server on the external net, for example at port 9888uvicorn deepl_fastapi.deepl_server:app --reload --host 0.0.0.0 --port 9888Explore and consumePoint your browser tohttp://127.0.0.1:8000/text/?q=test&to_lang=zhOr in python code (pip install requestsfirst)importrequests# geturl="http://127.0.0.1:8000/text/?q=test me&to_lang=zh"print(requests.get(url).json())# {'q': 'test me', 'from_lang': None, 'to_lang': 'zh',# 'trtext': '考我 试探我 测试我 试探'}# posttext="test this and that"data={"text":text,"to_lang":"zh"}resp=requests.post("http://127.0.0.1:8000/text",json=data)print(resp.json())# {'q': {'text': 'test this and that', 'from_lang': None, 'to_lang': 'zh', 'description': None},# 'result': '试探 左右逢源 检验 审时度势'}Interactive Docs (Swagger UI)http://127.0.0.1:8000/docsOmegaTFake MTplugin setupCopyomegat-plugin-fake-mt-1.0.0.jar（available athttps://github.com/briacp/omegat-plugin-fake-mt）to OmegaT\plugins （e.g., C:\Program Files\OmegaT\plugins）RunOmegaTand setupomegat-plugin-fake-mtOmegaT/Preferences/MachineTranslation/FakeMT/ConfigureName:FakeDeeplMTURL:http://localhost:8000/textSourceParameter:from_langTargetParameter:to_langTextParameter:q
Package: deepl-fastapi-pw
deepl-fastapi-pwYour own deepl server via fastapi and playwright, cross-platform (Windows/Linux/MacOs) with API for OmegaTInstallationCreate a virual environment: optional but recommended
e.g.,# Linux and friendspython3.8-mvenv.venvsource.venv/bin/activate# Windows# py -3.8 -m venv .venv# .venv\Scripts\activatepipinstalldeepl-fastapi-pwor (if your use poetry)poetryadddeepl-fastapi-pworpip install git+https://github.com/ffreemt/deepl-fastapi-playwright.gitorClone the repohttps://github.com/ffreemt/deepl-fastapi-playwright.gitgitclonehttps://github.com/ffreemt/deepl-fastapi-playwright.gitandcd deepl-fastapi-playwright`pip install -r requirements.txtorpoetry installUsageStart the serverpython  -m deepl_fastapi_pwOr use uvicorn directly (note thedeepl_servermodule, notrun_uvicorn)uvicorndeepl_fastapi_pw.deepl_server_async:apporpython-mdeepl_fastapi_pw.deepl_server_asyncor run the server on the external net, for example at port 9888uvicorn deepl_fastapi_pw.deepl_server:app --reload --host 0.0.0.0 --port 9888Explore and consumePoint your browser tohttp://127.0.0.1:8001/text/?q=test&to_lang=zhOr in command line:python-c"import httpx; print(httpx.get('http://127.0.0.1:8001/text/?to_lang=zh&q=test 1\ntest 2').json())"# output: {'q': 'test 1\ntest 2', 'from_lang': None, 'to_lang': 'zh', 'trtext': '测试 1\n测试 2', 'translation': '测试 1\n测试 2'}Or in python code (pip install requestsfirst)importrequests# geturl="http://127.0.0.1:8001/text/?q=test me&to_lang=zh"print(requests.get(url).json())# {'q': 'test me', 'from_lang': None, 'to_lang':# 'zh', 'trtext': '考我', 'translation': '考我'}'translation'is there forOmegaTplugin. Refer to theOmegaT Fake MT plugin setuppart
inhttps://github.com/ffreemt/deepl-fastapi# post
text = "test me \n and him"
data = {"text": text, "to_lang": "zh"}
resp = requests.post("http://127.0.0.1:8001/text", json=data)
print(resp.json())
# {'q': {'text': 'test me \n and him', 'from_lang': None,
# 'to_lang': 'zh', 'description': None}, 'result': '考验我 \n  我和他'}NBText longer than 1500 characters will be trimmed to 1500. This is what thedeepl.comwebpage can handle (used to be 5000 characters).The packagedeepl-fastapi-pwis in essence a browser from your local IP (although a proxy can be used, refer to get-pwbroser's doc for setting up). Hence if you send too many requests too frequently, your IP may be blocked bydeepl.comtemporarily, which of course will also disabledeepl-fastapi-pw.Interactive Docs (Swagger UI)http://127.0.0.1:8001/docs
Package: deepl-grpc
deepl-grpc[]deepl grpc, server and client, cross platform (Windows/MacOS/Linux)InstallationInstallgrpcio-reflectiongrpc-reflectioncannot be installed usingpoetry add. Usepip install grpcio-reflectioninstead.Install the rest as usualpipinstalldeepl-grpcorpoetryadddeepl-grpcor clone the repo (git clone https://github.com/ffreemt/deepl-grpc.git) and install from it. For examplegitclonehttps://github.com/ffreemt/deepl-grpc.gitcddeepl-grpcpython3.8-mvenv.venv# require python3.7+# for Linux/MacOS, you'd need to install venv and dev if you haven't done so# sudo apt install python3.8-venv# sudo apt install python3.8-devsource.venv/bin/activate# or in Windows do: .venv\Scripts\activatepipinstallgrpcio-reflectionpipinstall-rrequirements.txt# or poetry install --no-devpython-mdeepl_grpc.deepl_clientUsagepythoncodefromdeepl_grpc.deepl_clientimportDeeplClientfromlinetimerimportCodeTimerclient=DeeplClient()text="test this and that"withCodeTimer(unit="s"):result=client.get_url(message=text)# Code block took: 1.99860 sprint(result.message)# 试探 左右逢源 检验 审时度势to_lang="de"withCodeTimer(unit="s"):result=client.get_url(message=text,to_lang=to_lang,)# Code block took: 2.02847 sprint(result.message)# "Testen Sie dieses und jenes a Testen Sie dies und das a testen Sie dies und das Testen Sie dieses und jenes"InteractiveStart the grpc serverpython-mdeepl_grpc.deepl_serverThe first run in Linux may take a while sincechromium(~1G) needs to be downloaded. In Windows, Chrome will be used if it's available.Start the clientpython-mdeepl_grpc.deepl_client# to chinese# python -m deepl_grpc.deepl_client de  # to germanWebUIDownloadgrpcuiand run, for example in Windowsgrpcui.exe-plaintext127.0.0.1:50051to explore the server in the same manner as Postman for REST.pyppeteer issues in LinuxYou may encounter the following error in Linux:chromium/linux-588429/chrome-linux/chrome: error while loading shared libraries: libX11-xcb.so.1: cannot open shared object file: No such file or directoryYou may wish to try this fix in Ubuntuhttps://medium.com/@cloverinks/how-to-fix-puppetteer-error-ibx11-xcb-so-1-on-ubuntu-152c336368sudoapt-getinstallgconf-servicelibxext6libxfixes3libxi6libxrandr2libxrender1libcairo2libcups2libdbus-1-3libexpat1libfontconfig1libgcc1libgconf-2-4libgdk-pixbuf2.0-0libglib2.0-0libgtk-3-0libnspr4libpango-1.0-0libpangocairo-1.0-0libstdc++6libx11-6libx11-xcb1libxcb1libxcomposite1libxcursor1libxdamage1libxss1libxtst6libappindicator1libnss3libasound2libatk1.0-0libc6ca-certificatesfonts-liberationlsb-releasexdg-utilswgetMore coming soon