Saravanan666/pypi-org huggingface dataset:
Package: just-use-dataclass
just-use-dataclassSimple function to convert a python dict to a dataclass.If you want to know how the library works, the best place to look at is in thetestsIn short: it converts a dictionary to a dataclass by looking at the annotations in the dataclass and converting the
data in the dictionary to it.Installationpip install just-use-dataclassUsage and examplesSimple data type conversionfromdataclassesimportdataclassimporttypingfromjust_use_dataclassimportdict_to_dataclass@dataclassclassSimple:a:strb:intc:floatd:boole:typing.Optional[str]f:typing.Optional[str]data={"a":1,"b":"1","c":"2.0","d":True,"e":None,"f":42,}simple=dict_to_dataclass(data,Simple)print(simple)# Output:# Simple(a='1', b=1, c=2.0, d=True, e=None, f='42')Nested dataclass conversionfromdataclassesimportdataclassfromdecimalimportDecimalfromjust_use_dataclassimportdict_to_dataclass@dataclassclassC:value:str@dataclassclassB:value:intc:C@dataclassclassA:value_1:Decimalvalue_2:Decimalb:Bdata={"value_1":"23.23","value_2":49.0001,"b":{"value":1,"c":{"value":"test"},},}nested=dict_to_dataclass(data,A)print(nested)# Output:# A(value_1=Decimal('23.23'), value_2=Decimal('49.0001'), b=B(value=1, c=C(value='test'))Deeply nested typing conversionfromdataclassesimportdataclassimporttypingfromjust_use_dataclassimportdict_to_dataclass@dataclassclassCrazy:value:dict[str,dict[int,list[typing.Optional[str]]]]data={"value":{"test":{1:["hey",None,42]}}}crazy=dict_to_dataclass(data,Crazy)print(crazy)# Output:# Crazy(value={'test': {1: ['hey', None, '42']}})DevelopmentFork and clone the repoInstall poetry or just pytest, mypy and blackpoetryinstall# orpipinstall-UpytestmypyblackRun testspoetryrunpytest.Linting / Formattingpoetryrunmypy.
poetryrunblack.Use in productionThe library is really new. if you want to contribute feel welcome.
Otherwise don't use it in production (yet) :)
Package: just-utils
just_utilsA series of convenience functions to help training large image dataset with CNNinstallfrom sourcegitclonehttps://github.com/hansoluo/cvutils.gitcdcvutilspythoninstallsetup.pyfrom pypipipinstalljust_utilshow to usefromjust_utilsimportcheckfolder,read_yml,AverageMeterhow to update and pushsh push_pypi.sh
Package: justvpn
JUSTVPN一个方便使用江苏科技大学VPN访问网站的Python库对Python的request库中Session类进行了简单封装,Demo为访问知网依赖：bs4requestslxml安装方法：Ubuntu:sudo apt update && sudo apt upgradesudo apt install python python-pipsudo pip install justvpnArch Linux:sudo pacman -Syu python python-pipsudo pip install justvpn获取并运行测试样例:Ubuntu:sudo apt update && sudo apt upgradesudo apt install gitgit clone https://github.com/Koswu/justvpn.gitcd justvpn/testspython ./*.pyArch Linux:sudo pacman -Syu && sudo pacman -S gitgit clone https://github.com/Koswu/justvpn.gitcd justvpn/testspython ./*.py
Package: just-watch
📄 OverviewPython utility to watch thefile modification. There are similar
libraries:pyinotify,watchdog. These libraries
watch the file system event, but JustWatch is supported modificationonly.✏️ Usagequick startFirst of all, import classes fromjustwatch:fromjustwatchimportWatchManager,ObservermakeWatchManagerinstance and add file or directory:manager=WatchManager()manager.add_file("./README.md")manager.add_dir("./tests")makeObserverinstance and set callback:observer=Observer(manager)@observer.set_callbackdefcallback(item):print"Catch the modification of '{0}'".format(item.path)and runobserver.watchobserver.watch()example📥 Installation$ git clone git@github.com:alice1017/JustWatch.git
$ cd JustWatch
$ python setup.py build installTODO: I will upload pypi registry.👀 ContributionForks onGithubFind a bug? Send a pull request to get it merged and published.
Package: jut
jut - JUpyter notebook Terminal viewer.The command line tool view the IPython/Jupyter notebook in the terminal.Installpip install jutUsage$jut--help
Usage:cli.py[OPTIONS]PATH

Options:-he,--headINTEGERRANGEDisplayfirstncells.Defaultis10-t,--tailINTEGERRANGEDisplaylastncells-p,--single-pageShouldtheresultbeinasinglepage?-f,--full-displayShouldallthecontentsinthefiledisplayed?--force-colorsForcecoloredoutputevenifstdoutisnotaterminal-s,--startINTEGERRANGEDisplaythecellsstartingfromthecellnumber-e,--endINTEGERRANGEDisplaythecellstillthecellnumber--exclude-output-cellsExcludethenotebookoutputcellsfromtheoutput--no-cell-borderDon'tdisplaytheresultinacellwithborder--helpShowthismessageandexit.ASCIICinema Demo (First version)Note: Command line arguments may be different, usejut --helpto get upto date command line optionsDisplay first five cellsDisplay last five cellsDownload the file and display first five cellsUsage$jutdebug/file.ipynb
...$juthttps://raw.githubusercontent.com/fastai/fastbook/master/06_multicat.ipynb--tail10...
Package: juta-icons
==============Juta_cms_icons==============New Icon Admin Field.Detailed documentation is in the "docs" directory.Quick start-----------1. pip install juta-icons2. Add "juta_cms_icons" to your INSTALLED_APPS setting like this::INSTALLED_APPS = [...'juta_cms_icons',]3. Start the development server and visit http://127.0.0.1:8000/admin/to create a poll (you'll need the Admin app enabled).4. To use the Iconfield do as follows:*in App's models.py import the libraryfrom juta_cms_icons.fields import IconFieldclass GoogleIcon(models.Model):icon_field = IconField()5. To Add new fonts You will need to reinstall the selected.json file with the icons library
Package: jute
Jute is an interface module for Python 3 that verifies both providers and
receivers of the interface.Although duck typing is generally considered the Pythonic way of dealing with
object compatibility, it assumes that syntactic compatibility implies semantic
compatibility.  Interfaces provide an explicit way to express semantic
compatibility.Most existing interface modules for Python (e.g.abcandzope.interface)
check that implementing classes provide all the attributes specified in the
interface.  But they ignore the other side of the contract, failing to ensure
that the receiver of the interface only calls operations specified by the
interface.Thejutemodule allows verification of both providers of the interface and
receivers of the interface, to ensure that code works with any provider of the
interface, not just the provider with which it was tested.Documentation is available athttp://jute.readthedocs.org/
Package: jutge-joapuiib
jutgeThis is CLI judge to validate SQL and Java exercises.It runs the provided code in a docker dedicated docker container and
runs some tests to validate its correctness.It supports:Output comparison.Unit tests (Only SQL for now).JSON results.Git integration.Use Git tag.Deadlines (using commit date).Install requerimentsgitclonehttps://github.com/joapuiib/jutgejutge-joapuiib
python3.8-mpipinstalljutge-joapuiibExample usage$check_repo.py-ddir/repositories.csv

$grade_repo.pytestcase_file.ymldirectory/TODOInstallation and usageTestcase files documentationYAML validators for each judgeJutge version requeriment in tests fileSQL JudgeNormalize output new line endingsrun_object instead of run_exercise and run_test
Package: jutl
_       _   _ _     
   (_)_   _| |_(_) |___ 
   | | | | | __| | / __|
   | | |_| | |_| | \__ \
  _/ |\__,_|\__|_|_|___/
 |__/Overviewjutils is a simplePython 3.10+package which gives the user various tools. These tools are broken down into sub-modules in which the user can import individually.Table of contentsOverviewTable of contentsInstall & useTestObjectivesCreditsLicenceLinksInstall & useFrom terminal:pip install jutlFrom python environment:from jutl import <submodule>where<submodule>is one from the following:averagescalculatorsconverterscryptographydatastructuresecxeptionsformattinglanguagelogicpipeliningsorterstimersutilitiesTestClone repository:git clone https://github.com/JordanWelsman/jutils.gitBuild module for testing:python3 setup.py bdist_wheelInstall module locally:pip install jutl -e .Run tests with PyTest:pytest test/<submodule>where<submodule>is onefrom the above list.ObjectivesPublish a package of tools I have developed that I use in production applications.Help other users improve their workflows and contribute to more performant applications.Creditsjutils was created, developed, and is currently maintained byJordan Welsman.Licencejutils is developed and distributed under theMITlicense.NoteSeeLICENSEfor more details.Links:file_folder:See this project on GitHub:gift:See this project on PyPI:cat:Follow me on GitHub:briefcase:Connect with me on Linkedin:email:Send me an email
Package: jutlautil
jutlautilPackage for simple utilities that I find myself using in multiple projects.Installingpip install jutlautilto install from PyPI. No dependencies.Utilitiesanchor.set_anchor()Sets the working directory for a project by following a simple heuristic: it looks in the current directory for a file called.anchor, and if it doesn't find it, it goes to the parent directory and looks again. It keeps doing this until it either finds the file or runs out of directories to search. If it finds the file, it sets the working directory to that file's location. This is analogous to (and inspired by) R'sherepackage.
Package: juts
JutsJupyter widgets for scheduling processes and visualizing the resulting
(live) data. While it is designed to use custom data-specific visualizations
(plot widgets) based on ipywidgets, visualizations for time series data
(bqplot), animations (matplotlib) and 3D data (ipyvolume) are included.QuickstartTo start a process a so-called job has to be set up. A job consists of a Python
function and a configuration. The function contains the code (machine learning,
simulation, ....) to be executed,
forexample:import time as tim
def wait_n_times_x_ms(config, process_queue=None, return_dict=None):
    n = config["parameter"]["n"]
    x = config["parameter"]["x"]
    
    time = list()
    time_series = list()
    for i in range(n):
        time.append(i)
        time_series.append(i / x)
        
        process_queue.put(dict(progress=int(i/n * 100),
                               time=i,
                               time_series=i/x))
        tim.sleep(x)The configuration(s) can be read from a yaml file likethis:wait_40_times_100_ms:
    parameter:
        n: 40
        x: 0.1
        
wait_10_times_300_ms:
    parameter:
        n: 10
        x: 0.3or can be defined as python dictionary.Screencast min example.webmAlso live data can be monitored during script execution:Screencast min example live.webmA simulation exampleA more practical relevant example is the following simulation of a reaction
wheel pendulum under state feedback control.Screencast pendulum.webmWidgets can be easily connected if required:Screencast pendulum link.webmSince the simulation runs quite
fast, a loop was put after it which sends the data with a delay. This shows that
a job could also record live data from an experiment, so one could compare the
simulation data with the measurements from a real pendulum.Screencast pendulum live.webmVisualizing 3D dataAn example plot widget to view 3D data is also included.
This one relies onipyvolume.Screencast 3d.webm
Package: juungle
NOTE: ALTHOUGH THIS PROJECT WORKS, IT IS STILL UNDER HEAVY DEVELOPMENT AND THINGS WILL CHANGE BEFORE v1.0juungle-pythonPython package to access Juungle.net APIInstallation$ python -m pip install juungleRunning from source$ git clone https://github.com/Juungle/juungle-python.git juungle
$ cd juungle
$ python -m pip -r requirements.txtUser credentials for Juungle.netUsing a config fileCreate a fileuser-config.iniwith juungle.net credentials
in the same directory of your code:LOGIN_USERNAME="username@email"
LOGIN_PASSWORD="password"OR While creaing the objectInside the codefromjuungle.nftsimportNFTsnfts=NFTs('username@email','password')UsageList all WAIFUs nfts that are being sale for 0.01 BCH or lessfromjuungle.nftimportNFTsnfts=NFTs()nfts.available_to_buy=Truenfts.purchased=Falsenfts.token_group='WAIFU'nfts.get_nfts()fornftinnfts.list_nfts:ifnft.price_bch<=0.01:print(nft.token_name)List all my NFTsfromjuungle.nftimportNFTSnfts=NFTs()nfts.get_my_nfts()fornftinnfts.list_nfts:print(nft.token_name)List all my NFTs prices in USD and EURTo query prices we going to use coingecko apipip install pycoingeckofromjuungle.nftimportNFTSfrompycoingeckoimportCoinGeckoAPInfts=NFTs()nfts.get_my_nfts()# Query pricecg=CoinGeckoAPI()bch_price=cg.get_price(ids='bitcoin-cash',vs_currencies=['usd','eur'])['bitcoin-cash']msg="NFT:{}with price{}USD or{}EUR"fornftinnfts.list_nfts:print(msg.format(nft.token_name,bch_price['usd'],bch_price['eur'])Tokens Group IDsBecause tokens/group name are not unique we have to use the HEX id that can be
found at thesimpleledger.info.Juungle-python package provides a list of IDs just to make easier of the most
common toekns:Token NameToken IDWAIFUa2987562a405648a6c5622ed6c205fca6169faa8afeb96a994b48010bd186a66
Package: juxtematics
JuxtematicsOverviewSmall library designed to facilitate the analysis and computation of kinematic data related to sports movements in a two-dimensional space.Codebase are adopted fromKinoveaandkineticstoolkitFeaturesBody Joints Tracking:Easily input and track the positions of key body joints in a two-dimensional space.Data Preprocessing:Perform data preprocessing tasks such as interpolation, filtering, and smoothing to enhance the quality of kinematic data.Kinematic Computations:Compute essential kinematic metrics, including velocities, accelerations, and angles, to gain insights into sports movements.Customizable Processing:Configure preprocessing and post-calculation options based on your specific analysis requirements.Installationpipinstalljuxtematics
Package: jvc-projector-remote-improved
JVC Projector Remote ImprovedThis implements new features, improvements, and optimizations based on work inhttps://github.com/bezmi/jvc_projector. This was made with NZ models in mind. Almost every function will work with NX models but I do not guarantee operability for them.This is designed to work with my Home Assistant plugin:https://github.com/iloveicedgreentea/jvc_homeassistantInstallation# Assuming you have a venv with >=python3.9
pip install jvc-projector-remote-improvedQuick StartSet your network password if you have an NZ model first.jvc=JVCProjector(host="ipaddr",connect_timeout=60,password="password")# Commands are passed as a single string delimited by a comma# Everything executes async in the background. Sync interfaces are provided# open menucmd=jvc.exec_command("menu, menu")# press left buttoncmd=jvc.exec_command("menu, left")# set picture mode to frame adapt HDRcmd=jvc.exec_command("picture_mode, frame_adapt_hdr")# turn oncmd=jvc.power_on()UsageSeequick-startfor importingThe commands are structured to use simple keywords and options:Command: low_latency
Option: off
code: jvc.exec_command("low_latency, off")Command: picture_mode
Option: hdr_plus
code: jvc.exec_command("picture_mode, hdr_plus")You can also run multiple commands in a row by just giving it a listjvc.exec_command(["picture_mode, hdr_plus","motion_enhance, off"])Useprint_commands()to get all the latest support commands. This is dynamically generated at runtime so it is always up to date.Currently Supported CommandsPower on/offLens Memory/Installation ModesInput HDMI 1 or 2Power and Low Latency StatusLow Latency Mode on/offMenu and arrow buttons (Menu, LRUD, back)MaskingLaser power low/med/highLaser Dimming off/auto1/auto2E-shift on/offAperture off/auto1/auto2Anamorphic modesAnd many othersUseful Meta functionsThese are opinionated presets so you can have a one-click action to set your settings up for the desired task. This is also supported in home assistant as a service.async_gaming_mode_hdr()async_gaming_mode_sdr()async_hdr_picture_mode()async_sdr_picture_mode()async_is_on()async_get_low_latency_state()Supported ModelsNZ7/NZ8/NZ9 (Network password is required)NX5/NX7/NX9Most likely any other D-ILA projector, and possibly older models with ethernet cables.Home Assistant# configuration.yamlremote:-platform:jvc_projectorsname:nz7password:passwordhost:192.168.1.2scan_interval:30Development# Create venvpython3-mvenv.venvsource.venv/bin/activate# Edit envcp.env.template.env# edit .env with valuesAdding new commandsAll commands are stored in Enums withincommands.py. Add them usingthis guideas a reference.TestingJVC_TEST_POWER: true/false to test power functions
JVC_TEST_FUNCTIONS: true/false to test various button functionsYou can run the test at the local device or run a mock server I made (WIP) to test commands# Venv in one windowpythonmock/mochrie.py# Run tests in other windowsource.envexportJVC_HOST=127.0.0.1
maketest
Package: jvc-proxy
A tiny server that acts as a proxy between a client and a JVC projector such a
projector. JVC projectors insist on an additional 3-way handshake (PJ_OK,
PJREQ, PJACK) in addition to the normal TCP 3-way handshake. This means that
certain home automation appliances may have timing difficulties communicating
with the projector as they lack the protocol knowledge to implement the
additional handshake.SeeJVC Projector Control codesfor the actual codes to effectively manage a JVC projector.Using the serverStart the server, proxy between localhost and ‘my-projector’ on the usual JVC
control port number (20554).$ jvc_proxy -l DEBUG -r 2 -t 1 my-projectorBinds the server to an IP address / hostname that is accessible external to the
machine (i.e. not localhost). Set logging level to DEBUG (will log the actual
bytes proxied). Will retry failed connections to the projector twice. Allows 1
second timeout on network operations.$ jvc_proxy --proxy_host my-pc -l DEBUG -r 2 -t 1 my-projectorAvailable arguments:usage: jvc_proxy.py [-h] [--jvc_port JVC_PORT] [--proxy_host PROXY_HOST]
                    [--proxy_port PROXY_PORT] [-t TIMEOUT] [-v VERBOSE]
                    [-l {ERROR,WARNING,INFO,DEBUG}] [-r RETRIES]
                    [-w RETRY_WAIT]
                    jvc_host

positional arguments:
  jvc_host              JVC host to proxy to. Default: 20554.

optional arguments:
  -h, --help            show this help message and exit
  --jvc_port JVC_PORT   JVC port number to connect to.
  --proxy_host PROXY_HOST
                        Proxy server host/IP to bind to. Default: localhost.
  --proxy_port PROXY_PORT
                        Proxy server port number to listen on. Default: 20554.
  -t TIMEOUT, --timeout TIMEOUT
                        Timeout for network operations (seconds). Default: 2.
  -v VERBOSE, --verbose VERBOSE
                        Whether or not to output proxied data. Default: False.
  -l {ERROR,WARNING,INFO,DEBUG}, --loglevel {ERROR,WARNING,INFO,DEBUG}
                        Logging level. Default: ERROR.
  -r RETRIES, --retries RETRIES
                        Number of retries to allow in connection to the JVC
                        host. Default: 0
  -w RETRY_WAIT, --retry_wait RETRY_WAIT
                        Seconds to wait between connection retries. Default:
                        5.Starting the server by defaultUse the included jvc_proxy.service to start the server as a systemd
unit.
Package: jvig
jvigPronounced d͡ʑvʲik (from 🇵🇱dźwig), it's a GTFS Viewer, created using Flask.jvig is still work-in-progress, butit works.InstallationInstall Python (at least 3.9) and pip. Consult your OS repositories for the package names,
but these are usuallypython3andpython3-pip. If you use a system without a package manager,
I'd strongly recommend using one, like brew (for MacOS) or Chocolatey (for Windows).After that, install jvig using pip:pip install --upgrade jvig.Usagejvig /path/to/gtfs.zipor (if the place where pip install scripts is not in PATH):python3 -m jvig /path/to/gtfs.zipjvig can open both folders and ZIP archives.jvig itself doesn't contain a GUI - rather it spawns a web server on localhost and port 5000.
After seeing* Running on http://127.0.0.1:5000on the console, open uphttp://127.0.0.1:5000.WARNING: This is a development server.jvig uses the default Flask server, which is not suitable for opening up to the Internet.
jvig only binds to the loopback address, and the server is only accessible from your own computer.Please don't serve jvig to the whole web.Features/TodosShown GTFS tablesagenciesstopsroutestripsfrequenciescalendarsfarestransferspathwaysfeed_infoattributionstranslationsshapesOther improvementssearch (provided by the browser)verify dark modefile-picker if no file was providedbetter loading screenLicenseGNU GPL v3 or later.
Full text available in file license.md.IconAwful, I know. Make a better one if you want to.Currently it's these 2 things combined:https://thenounproject.com/term/crane/1689627/(bought the rights to use)https://material.io/resources/icons/?icon=directions_bus&style=outline(apache 2.0)DevelopmentThis project usesisortandblackfor file formatting andpyrightfor type checking.
The maximum line length is increased to 99, and the type checking is set to strict.CI runs the following commands to help maintain high code quality:$black--check.$isort--check.$pyright$python-mpytestIf you use VS Code I recommend using the following settings:{"[python]":{"editor.codeActionsOnSave":{"source.organizeImports":true},"editor.formatOnSave":true},"js/ts.implicitProjectConfig.checkJs":true,"python.formatting.provider":"black","python.languageServer":"Pylance","python.linting.enabled":false,}
Package: jvirtualenv
[![PyPI version](https://badge.fury.io/py/jvirtualenv.svg)](https://badge.fury.io/py/jvirtualenv)[![codebeat badge](https://codebeat.co/badges/7bd988f9-7f2c-4701-951e-92dfe16be5ab)](https://codebeat.co/projects/github-com-minghu6-jvirtualenv-master)# jvirtualenvA micro Java environment switch which inspired by `virtualenv`.## OS Supports:Linux and any other OS whose shell is bash or zsh.Windows support is a TBD (low priority though).## Requirements:1. JDK(*Oracle JDK*) should be placed on a folder whose name is `java`and its name should startswith `jdk`. (maybe need `sudo updatedb`)Exp: `/opt/java/jdk-9`,`/opt/java/jdk1.8.0_144`Or you can edit the config file directly. (not recommented)The config file should be as followed:```[{"tag": "9","version": "9","bit": "64","home": "/opt/java/jdk-9"},{"tag": "1.8:0:64","version": "1.8.0_144","bit": "32","home": "/opt/java/jdk1.8.0_144"}]```2. Python3## Usage:1. `pip3 install jvirtualenv`2. `jvirtualenv list-tag` (view all jdk tag)3. `jvirtualenv -j 1.8 <myproject>` (if 1.8 is prefix of someone tag)4. `source <myproject>/bin/activate` (activate virtual java env)5. `deactivate` (deactivate the virtualenv)**FOR EXCELLENT PYTHON3 AND VIRTUALENV!**