Saravanan666/pypi-org huggingface dataset:
Package: jupytorg
Org to IPYNBPreambleIt should be remembered that the use of the operating system known as "Emacs" is prohibited by the Geneva Conventions and makes any user liable to a crime against humanity.Indeed, this ignominy, whose violence and horror remain indescribable to us, is still far too widely used within the Linux community. There are many other tools available, such as ed, vim, nano... How can its use be justified, especially if it is shameless?We are appalled and dumbfounded by this aberration. It is this service to humanity that has motivated us in this project. It's to save those who suffer from this evil. It is for you. You, who have desperately sought a solution. You, who have been desperate to get out of this trap. You, who represent that flickering glimmer of hope for a better future.Résiste !
Prouve que tu existes !
Cherche ton bonheur partout, va,
refuse ce monde égoïste !
Résiste.
Suis ton cœur qui insiste !
Ce monde n'est pas le tien, viens,
bats-toi, signe et persiste !
Résiste !Requirementspandocjupyter notebookpip3installjupyterjupyter-c-kerneljupyterlabnotebooktheninstall_c_kernel--usergccOpenMPYou can test whether everything works using this command and this :gcc-fopenmpcode_block.c-ocodeblock
./code_block// OpenMP header#include<omp.h>#include<stdio.h>#include<stdlib.h>intmain(intargc,char*argv[]){intnthreads,tid;// Begin of parallel region#pragma omp parallel private(nthreads, tid){// Getting thread numbertid=omp_get_thread_num();printf("Welcome to GFG from thread = %d\n",tid);if(tid==0){// Only master thread does thisnthreads=omp_get_num_threads();printf("Number of threads = %d\n",nthreads);}}}PrincipleWe take a.orgfile and convert it tohtmland ajsonusingpandoc <filename>.org -o out.htmlandpandoc <filename>.org -o out.json.
Then we parse those intermediate renderings to extract the bits of code and generate a usablejson IPYNB.UsageUsage: jupytorg src=input_file_path (optional type=code_block_language dest=output_file_path)
    input_file_path : the path to input the file
    output_file_path : the path to output the file (default is output_file.ipynb)Example with anewcourse.orgfile:jupytorgsrc=~/Documents/2A/OpenMP/newcourse.orgdest=~/Documents/2A/OpenMP/newcourse.ipynbIt reads the.orgfile in the specified folder and drops the coonverted jupyter notebook into the same folder. All that remains is to open it with VSCode.
Package: jupytray
JupytrayRun the Jupyter notebook server as a little app in the system tray.That way you don't have to keep a separate command window open just for the server.This app is made for Windows.(It should be portable to Mac/Linux, as the GUI uses the cross-platform 'Qt' framework.
Pull requests for such a port are welcome).InstallationMake sure PyQt5 is installed:conda install pyqtThen run:pip install jupytrayThis will get you theFinally, runjupytray-shortcuts installThis will add shortcuts to the Windows Start menu and Startup folder.UsageOpen the Start menu, typeJupytray, and hit enter.This should start the tray app and the Jupyter notebook server.The app will also auto-run at system restarts. (This can be disabled in the settings menu).DeinstallationFirst remove the Windows shortcuts:jupytray-shortcuts uninstallThen remove the Python package:pip uninstall jupytray
Package: jupyverse-auth
jupyverse-authA JupyterLab extension for authentication.This extension is composed of a Python package namedjupyverse-authfor the server extension and a NPM package namedjupyverse-authfor the frontend extension.InstallTo install the extension, execute:mambacreate-njupyverse-auth-dev
condaactivatejupyverse-auth-dev
mambainstallpipnodejs

pipinstall-e.
jupyterlabextensiondevelop.--overwrite
jlpm
jlpmrunbuildAuthentication with GitHubYou will need to authorize JupyterLab to access your GitHub information. You can register a new
OAuth applicationhere:Application name: JupyterLabHomepage URL:http://127.0.0.1:8000/labAuthorization callback URL:http://127.0.0.1:8000/auth/github/callback127.0.0.1and8000are the IP and port number, respectively. You might have to change them
according to your particular setup.This will generate a client ID for you, and you must also generate a client secret.When launching jupyverse, you must pass the client ID and secret:jupyverse--config=path/to/config.tomlWhereconfig.tomllooks like this:[authenticator]client_id="your_client_id"client_secret="your_client_secret"
Package: jupyXplorer
This project aims to generate some util notebooks to get data exploration.It’s based on nbconvert and simply offer you a easy way to analise a feature value (or set of them) of a dataset.InstallationIn order to install the utility just use pip:pipinstalljupyXplorerWe provide you a docker image to get started quickly, take a look athypnosapos/jupyxploreratdockerhuband select the best one fit your needs.UsageBefore notebook generation take a look at our config file example (tests/e2e/sample_config.yaml).jupyxplorer-cconfig.yaml-o.outputAll notebooks will be ready in directory “.output” of the example above.Once notebooks are generated we can use them in your jupyter to show results of data analysis.As we said above, you may use a docker container instead:dockerrun-it-v</path/my_config.yaml>:/tmp/my_config.yaml</path/output>:/tmp/outputhypnosapos/jupyxplorer:latestjupyxplorer-c/tmp/my_config.yaml-o/tmp/outputIf you want to use some required files to execute notebooks before generation (-eor–executeargument), provide the value of argument “input-dir” (–input-dir, or the short form-i).
Here you have an example:jupyxplorer-i.input-cconfig.yaml-o.output-eThe resources under that directory would be particular requirement files for python and local dataset files.DevThe development lifecycle is managed by aMakefileand CircleCI, where all steps are executed through docker containers.
Typemake helpto see all available commands.
Package: juq.py
juqCLI for viewing/slicing Jupyter notebooks (name is inspired by "jqfor Jupyter")Installationpipinstalljuq.pyUsagejuq cellsSlice/Filter cells:juqcells--help# Usage: juq cells [OPTIONS] CELLS_SLICE [NB_PATH]##   Slice/Filter cells.## Options:#   -m, --metadata / -M, --no-metadata#                                   Explicitly include or exclude each cell's#                                   "metadata" key. If only `-m` is passed, only#                                   the "metadata" value of each cell is printed#   -o, --outputs / -O, --no-outputs#                                   Explicitly include or exclude each cell's#                                   "outputs" key. If only `-o` is passed, only#                                   the "outputs" value of each cell is printed#   -s, --source / -S, --no-source  Explicitly include or exclude each cell's#                                   "source" key. If only `-s` is passed, the#                                   source is printed directly (not as JSON)#   -t, --cell-type TEXT            Only print cells of this type. Recognizes#                                   abbreviations: "c" for "code", {"m","md"}#                                   for "markdown", "r" for "raw"#   --help                          Show this message and exit.juq merge-outputsMerge consecutive "stream" outputs (e.g. stderr):juqmerge-outputs--help# Usage: juq merge-outputs [OPTIONS] [NB_PATH]##   Merge consecutive "stream" outputs (e.g. stderr).## Options:#   -i, --in-place       Modify [NB_PATH] in-place#   -o, --out-path TEXT  Write to this file instead of stdout#   --help               Show this message and exit.e.g.:juqmerge-outputs-inotebook.ipynbUseful for situations like:jupyter-book#973nbval#138juq papermill-cleanjuqpapermill-clean--help# Usage: juq papermill-clean [OPTIONS] [NB_PATH]##   Remove Papermill metadata from a notebook.##   Removes `.metadata.papermill` and#   `.cells[*].metadata.{papermill,execution,widgets}`.## Options:#   -i, --in-place       Modify [NB_PATH] in-place#   -o, --out-path TEXT  Write to this file instead of stdout#   --help               Show this message and exit.
Package: juqueue
JuQueueComputation and workflow management system fortime-constrainedcluster environments.
This system is aimed at compute clusters, on which users are accounted
for the runtime of an entire node orminimum resource allocation units(e.g. at the Jülich Supercomputing Centre (JSC)).Work in progress and potentially unstable. Thewikiprovides further documentation.ConceptRunsDefines the command and its corresponding parameters.Defines an Executor which determines environment variables, virtual environments, etc...Commands should be robust to termination, i.e.Should resume from previous computation if terminated.If the Node shuts down/fails, the Run will be requeued.Upon failure, must return a non-zero status code. [will not be requeued]Must return status code 0 if completed. [will not be requeued]ExperimentA logical group of Runs.ClustersEach Cluster (currentlylocalandslurm) defines a group of nodes.A ClusterManager manages NodeManagers on computation nodes (e.g. via SLURM jobs).Each NodeManager specifies a certain number of Slots and manages the execution of Runs in Python subprocesses.As Runs are (un-)queued from/to the Cluster, or are completed/failed, the number of nodes is rescaled as necessary.For now, the system is aggressive in minimizing the number of nodes, e.g.Assume 4 nodes (each with 4 slots), each executing a single RunThen 3 nodes are cancelled (along with the runs) and rescheduled to the remaining node.InstallationFrom sourcegitclonehttps://github.com/tran-khoa/JuQueuejuqueuecdjuqueue
pipinstall-e.# (optional) Start with example definitionscp-rexample_defs~/defsVia pippipinstalljuqueueUsagejuqueue--def-dir[PATH]--work-dir[PATH]A minimal user interface is offered atlocalhost:51234.
For more advanced usage, JuQueue can be controlled via FastAPI's interactive docs
available atlocalhost:51234/docs.DocumentationFor now, refer to the examples inexample_defs/and FastAPI's docs,
available atlocalhost:51234/docsorlocalhost:51234/redoc.
Package: juraHP
SSH Client FrameworkThis framework is to be used for DevOps, Infrastructure As Code and Network Automation projects.Advantages:Simple, Fast and Secure method to:Create automated tools toRename HP Switches interfaces connected to Cisco Access-PointsCreate automated tools toRename Cisco Access-Points interfaces that are connected to HP SwitchesHow to use the framework.Example 1To rename the:"pip install juraHP" in your machine"from juraHP import robot"robot.run_rename()For support: Please contact david.johnnes@gmail.com.
Package: juraSSH
SSH Client FrameworkThis framework is to be used for DevOps, Infrastructure As Code and Network Automation projects.Advantages:Simple, Fast and Secure method to:Create automated tools tobackup Routers, Switches and Access-PointsCreate automated tools fordynamic network configuration generationCreate automated tools forconfigurations roll-outCreate automated tools fornetwork devices auditCreate automated tools fornetwork devices inventory generationCreate automated tools fornetwork devices trouble-shootingHow to use the framework.Example 1To send a single command to multiple remote machines in parallel:"pip install juraSSH" in your machine"from juraSSH import oneCMD"my_hosts = ["8.8.8.555", "4.4.4.444"]oneCMD.run_one_cmd(username, password, "show clock", my_hosts)Example 2To send multiple commands to multiple remote machines in parallel:"pip install juraSSH" in your machine"from juraSSH import multipleCMDs"my_hosts = ["8.8.8.555", "4.4.4.444"]commands = ["show clock", "show ip int brief", "show version"]multipleCMDs.run_multiple_cmds(username, password, commands, my_hosts)You can execute multiple command on hundreds or thousands devices in parallel !!.
Package: jure
Jupyter Browser ReloadFlow-saving tool that automatically reloads Jupyter Notebook in a browser
when its source .py file is changed and executes all changed cells.It usesJupytext- to synchronize .ipynb and .py filesWatchdog- to watch for .py file changesSelenium- to have a full control over a browser with opened Jupyter NotebookWhy JureJupytext is a great tool that for instance allows user to benefit from static code analysis of Jupyter Notebooks. However I always struggled with this workflow: after each edit of .py file I needed to manually reload browser and execute all changed cells.Jure automatically reloads browser on each .py file change, so it would instantly show actual notebook content. Additionally it scrolls to last changed cell and executes all cells that were changed.InstallationThe most non-trivial part is install ChromeDriver on you computer, here'ssample link for Ubuntufor reference.
After that it's simplypip install jureUsageFirst, you need to sync your .ipynb file with .py with Jupytext, seeofficial manual.Then launch a Jupyter Notebook server (jupyter notebook ...).Then runjure--token=[TOKEN]--jupyter_root_dir=[ROOT_DIR]--notebook_path=[NOTEBOOK_PATH]Where[TOKEN]as an access token which is required to access Jupyter Notebook from browser,[ROOT_DIR]is a path to directory from whichjupyter notebook ...command was executed and[NOTEBOOK_PATH]is a path to the notebook .ipynb file you'll work with.LimitationsThis is an experimental and unstable product, any issues, suggestions, feature requests and PRs are appreciated. Current problems:Only Google Chrome web browser is supportedSelenium might be inconvenientNo password auth / remote notebook hostsIn some rare cases user needs to reload browser tab manuallyFor large notebooks page reload might be too slow (tough one)
Package: jureqex
Jupyter rquirements extractorA simple library with a command to extract the requirements from a Jupyter or Colab notebook and extract their versions from your local environment. This can also be used in Google Colab's notebooks in orther to extract that information from their environment.Installationpip install jureqexUsagejureqex --path /path/to/notebook_folder --name notebook_name.ipynb --save /path/to/requirements.txtInstall from GitHub and use it in ColabFirst you need to download the Coalb notebook and update it in Colab's workspace.!git clone https://github.com/IvanHCenalmor/JupyterReqExtractor.git
!python -m pip install -e ./JupyterReqExtractor
!jureqex --path /content --name XXX.ipynb --save /content/requirements.txt
Package: juridecomposer
JuridecomposerThe Juridecomposer package can be used to transform Dutch laws structured as .xml files into pandas dataframes.
Input laws can be retrieved fromwetten.nl.Example usagefrom juridecomposer.juridecomposer import xml_to_dataframe
output_dataframe = xml_to_dataframe("path/to/law/xml")The output dataframe will consist of the following columns:Brontekst: raw extracted text;Nummer: specifies the chapter (hoofdstuk) number;Lid: specificies the section (afdeling) number;Opsomming niveau 1: specifies the article (artikel) number;Opsomming niveau 2: specifies the component (onderdeel) number;Opsomming niveau 3: specifies the second component (onderdeel) number, if available;Versie: specifies the version number;jc 1.3: permanent link to specific section.
Package: jurn
jurn 📝🦄A tool for logging work progress throughout the week. Features tags and pretty output. Log entries stored in a local sqlite database.Installationpip install jurnWriting Entriesjurn log -m 'Wrangled cats via lasso.'TaggingYou can add tags to logs for hierarchical organization and display.jurn log -m 'Wrangled cats via lasso.' -t 'Physical Fitness'You can tab complete within the tag option. For example, if you typed in:jurn log -m 'Wrangled cats via lasso.' -t 'Physical <TAB>jurn would return the following bash-style autocomplete suggestions based on your history of previously used tags:Physical Fitness
Physical SecurityThis helps ensure youre messages stay organized.NOTE: To enable autocompletion, you must add this to your~/.bashrc.eval "$(_JURN_COMPLETE=bash_source jurn)"If using other shells, please reference theClick documentationfor the specific line you need to add.You can also have subcategories by tagging with#, e.g.jurn log -m 'Wrangled cats via lasso.' -t 'Physical Fitness#Cardio'Printing (to the screen)jurn print -d weekResult:2022-11-01 to 2022-11-07
  • Physical Fitness
    • Cardio
      • Wrangled cats via lasso.
    • Strength
      • New PR benching 2 mules.
  • Physical Security
    • Installed new locks on the doors.
    • Added storage to camera recording devices.DatabaseThe jurn database is stored in the following location by default:~/.jurn/jurn.dbYou can override this with the--db-path <folder path> --db-filename <filename>options.Early EndThe--early-endoption bypassesjurnfrom executing if the specified amount of time has not passed since the last entry:jurn --early-end 60 log -tThis option may be useful to supressjurnprompting too frequently if adding to a .bashrc file or schedule. For example, the above example command inserted into a .bashrc file will remind you to log your work withjurnonlyif at 60 minutes have passed since the last log entry.More CommandsUsejurn --helpto view all available options.
Package: jusho
Easy wrapper for the zip code data of JapanPowered byYamato NagataGitHubUseful exampleHEREUsing sqlite3 for the whole data. Runs really fast and uses less memory.fromjushoimportJushopostman=Jusho()print(postman.from_zip_code('160-0021'))# '1600021', '〒1600021' and whatever is valid# 〒160-0021, 東京都 新宿区 歌舞伎町(TOKYO TO SHINJUKU KU KABUKICHO)print(postman.prefectures)# [('アイチケン', '愛知県', 'AICHI KEN'), ('アオモリケン', '青森県', 'AOMORI KEN'), ('アキタケン', '秋田県', 'AKITA KEN'), ('イシカワケン', '石川県', 'ISHIKAWA KEN'), ('イバラキケン', '茨城県'...print(postman.cities_from_prefecture('大阪府',type='kanji'))# [('ミシマグンシマモトチョウ', '三島郡島本町', 'MISHIMA GUN SHIMAMOTO CHO'), ('オオサカシミヤコジマク', '大阪市都島区', 'OSAKA SHI MIYAKOJIMA KU'), ('オオサカシフクシマク', '大阪市福島区', 'OSAK...print(postman.towns_from_city('大阪府','三島郡島本町','kanji'))# [<Address: 〒618-0000, 大阪府 三島郡島本町 以下に掲載がない場合(OSAKA FU MISHIMA GUN SHIMAMOTO CHO IKANIKEISAIGANAIBAAI)>, <Address: 〒618-0015, 大阪府 三島郡島本町 青葉(OSAKA FU MISHIMA GUN SHIMAMOTO CHO AOBA)>, <Address: 〒618-0013, 大阪府 三島郡島本町 江川(OSAK...aoba=postman.address_from_town('大阪府','三島郡島本町','青葉','kanji')print(aoba.hyphen_zip)# 618-0015"""Address object has a lot of info"""aoba.admin_division_code:str# 全国地方公共団体コード(Administrative divisions Code)aoba.old_zip_code:str# the old zip codeaoba.zip_code:str# the zip codeaoba.prefecture_kana(_kanji,_eng):str# prefecture name in hiragana, kanji, and Englishaoba.city_kana(_kanji,_eng):str# city name in hiragana, kanji, and Englishaoba.town_area_kana(_kanji,_eng):str# town area name in hiragana, kanji, and Englishaoba.multiple_zip_code:bool# whether the area has alter zip codesaoba.multiple_address:bool# whether the zip code includes multiple `Banchi`aoba.has_chome:bool# whether the area has `Chome` which means subdivided areasaoba.multiple_town_area:bool# whether the zip code includes multiple areas
Package: juspy
juspyjuspy is a library for making EDA and Modelling in Python quick and convinient. It's built on top of:pandasnumpyseabornand many such great librariesOur reccomended path of getting started withjuspyDownload & installAnacondaOpenAnaconda PromptInAnaconda Prompttypecondainstall-cconda-forgejupyterlaband thenpipinstalljuspyjupyterlabIncase if you're having any trouble regarding installation or dependencies, kindly make sure you're using updated versionscondaupdatecondacondaupdatepipcondaupdatepythonAnd now try the above steps againDemo Notebooks:To test library's proper installation and working:importjuspyprint(juspy.__version__)fromjuspyimportgreetprint(greet.namastey())jpplot.confusion_matrix()importnumpyasnpimportseabornassnsfromsklearn.metricsimportconfusion_matrixy_true=[0,1,0,1,0,1,0]y_pred=[1,1,1,0,1,0,1]cf_matrix=confusion_matrix(y_true,y_pred)fromjuspyimportplotasjpplotjpplot.confusion_matrix(cf_matrix)jpplot.piechart()importpandasaspddf_name=pd.read_csv("https://raw.githubusercontent.com/juspreet51/juspy/main/src/juspy/datasets/default.csv")fromjuspyimportplotasjpplotjpplot.piechart(df_name["student"])Future Release:from juspy.linear_models importLinearRegressionfromjuspy.linear_modelsimportLinearRegressionaslin_reg
Package: justai
JustAIPackage to make working with Large Language models in Python super easy.Author: Hans-Peter Harmsen (hp@harmsen.nl)Current version: 2.1.6InstallationInstall the package:python-mpipinstalljustaiCreate an OpenAI acccounthereCreate OpenAI api keyshereCreate a .env file with the following content:OPENAI_API_KEY=your-openai-api-keyOPENAI_ORGANIZATION=your-openai-organization-idUsagefromjustaiimportAgentif__name__=="__main__":agent=Agent('gpt-3.5-turbo')agent.system=lambda:"You are a movie critic. I feed you with movie titles and you give me a review in 50 words."message=agent.chat("Forrest Gump")print(message)outputForrest Gump is an American classic that tells the story of
a man with a kind heart and simple mind who experiences major
events in history. Tom Hanks gives an unforgettable performance, 
making us both laugh and cry. A heartwarming and nostalgic 
movie that still resonates with audiences today.Using the examplesInstall dependencies:python-mpipinstall-rrequirements.txtBasicpythonexamples/basic.pyStarts an interactive session. In the session you dan chat with GPT-4 or another model.Returning jsonpythonexamples/return_types.pyYou can specify a specific return type (like a list of dicts) for the completion.
This is useful when you want to extract structured data from the completion.To define a return type, just pass return_json=True to agent.chat().See the example code for more details.Interactivepythonexamples/interactive.pyStarts an interactive session. In the session you dan chat with GPT-4 or another model.Special commandsIn the interactive mode you can use these special commands which each start with a colon:SyntaxDescription:resetresets the conversation:loadnameloads the saved conversation with the specified name:savenamesaves the conversation under the specified name:inputfilenameloads an input from the specified file:modelgpt-4Sets the AI model:max_tokens800The maximum number of tokens to generate in the completion:temperature0.9What sampling temperature to use, between 0 and 2:n1Specifies the number answers given:stop["\n", " Human:", " AI:"]Up to 4 sequences where the API will stop generating further tokens:byequits but saves the conversation first:exit or :quitquits the program
Package: just-another-imgscrapper
just-another-imgscrapperA utility for scrapping images from a HTML doc.Usesasynciofor fast concurrent download.InstallationBinary installers for the latest released version are available at thePython Package Index (PyPI).$pipinstalljust-another-imgscrapperUsage1. From cli$imgscrapper-hTo get HTML doc, extract image links fromsrcattribute of<img>tags and download.$ imgscrapper "http://foo.com/bar"
[2023-06-06 23:22:56] imgscrapper.utils:INFO: ### Initializing Scrapping ###
[2023-06-06 23:23:01] imgscrapper.utils:INFO: ### Downloaded 41 images out of extracted 41 links ###Downloads toimgs/dir in working dir. If dir does not exists, creates.2. From module>>>fromimgscrapperimportImgScrapper>>>d=ImgScrapper()>>>d.download("http://foo.com/bar")>>>3Specify path to store downloaded images.>>>d=ImgScrapper()>>>d.url="http://foo.com/bar">>>d.path="/path/download">>>d.download()# returns no. of successful downloads>>>3Some servers will block the scrapping, respect robots.txt and only used in allowed hosts.You can add request headers.>>>...>>>d.request_header={'User-Agent':'Mozilla/5.0 (X11; Linux x86_64; rv:102.0) Gecko/20100101 Firefox/102.0','DNT':'1',}>>>...You can select specific type ofimgtags only by passingattrsdict.<!-- >http://helloworld.com<--><html><body><imgsrc="https://foo.com/bar.png"class="apple ball"><imgsrc="/foo.jpg"class="cat bar"></body><html>To select only images withclass: cat>>>d=ImgScrapper()>>>d.url="http://helloworld.com">>>d.attrs={'class':'cat',}>>>d.download()>>>1# http://helloworld.com/foo.jpgThe downloader gives uniqueuuidfilename to downloaded images preserving the image extension.>>>d=ImgScrapper(url="http://helloworld.com",attrs={'class':'cat'},max=5,path="/home/images")>>>d.download()>>>5Limit the no. of image downloads by passingmaxvalue.Liscensejust-another-imgscrapperis released under the MIT liscense. See LISCENSE for details.ContactConnect with me on twitter@deshritbaral