Saravanan666/pypi-org huggingface dataset:
Package: projectalice-cli
Project Alice CLIThis is a Project Alice command line tool.It simplifies to the maximum the installation and maintenance of Project Alice.It is not meant to be installed on the device that runs/will run Alice, but on your main computer.It handles connecting to network discoverable devices through SSH and generates RSA keys for a passwordless connection.Although it's a command line tool, made possible thanks to the awesome "Click" package, it is using the wonderful "InquirerPy" package, a reboot of the deprecated "PyInquirer", to offer an interactive menu for people not used or wanting to type commands.UsersInstall this tool via pip, on your main computer:pip3 install projectalice-cliNote that you need Python 3.8 at leastDevs of this toolClone this repositoryOpen a terminal on whatever OS you areCD to the path where you cloned this repositoryCreate a python 3.8+ virtual environment:python -m venvActivate your virtual environmentInstall the package in dev mode:pip install --editable .UsageTypealicein your terminal to open the main menu or typealice --helpto discover the available commandsUseful informationThis tool stores its configurations in%USER_DIRECTORY%/.pacliThis tool stores its generated SSH certificates in%USER_DIRECTORY%/.sshThank You!jonah1024: A big thank you for making this work in macOs as well!
Package: projectalice-nlu-trainer
nluTrainerA decentralized NLU trainerThe idea behind this small tool is to provide a simple trainer on your Network for Alice to use. Training the NLU is a costly operation and your device running ProjectAlice might get slow at it the more skills you have. In order for Alice to use it, turn on the optiondelegateNluTrainingUsersTo use this, create a Virtual Environment wherever you wish on your main computer, be it Windows, Linux or Mac, on a Synology station, whatever network device that can run python. Make sure this device runs Python 3.7!python3.7 -m venv venvActivate your virtual environment and install the nlu trainer with pip:pip install projectalice-nlu-trainerThat's all you need to install!Devs of this toolClone this repositoryOpen a terminal on whatever OS you areCD to the path where you cloned this repositoryCreate a python 3.7 virtual environment:python -m venvActivate your virtual environmentInstall the package in dev mode:pip install --editable .UsageRun the trainer using this command, in your terminal, with admin rights as it needs to install the language packs:alice-trainer --host ALICE_IPYou can also define some other options with arguments:-h / --host: Define the Mqtt hostname, generally it's Alice's main unit IP address-p / --port: Define the Mqtt port, by default 1883-u / --user: Define a Mqtt username to connect with-s / --password: Define a Mqtt password to connect with-f / --tls_file: Define the path to your TLS certificate file to connect with, if you Mqtt server requires itAs you want it to be always running, you might want to automate it to run at computer boot.Messagesprojectalice/nlu/doTrain : Send this message to have the trainer train on the data in payload.Payload structure:{"language":"en","data":"the data to train the NLU on, as a json string"}projectalice/nlu/trainerReady : Sent when the trainer has started and connectedprojectalice/nlu/trainerStopped : Sent when the trainer is stoppedprojectalice/nlu/trainingFailed : Sent if the training failed with the reason as payloadprojectalice/nlu/trainingResult/# : Sent when the training is finished with the zipped result as a bytearray in payload. The mqtt topic last level is the file control hash (hashlib.blake2b(result.read_bytes()).hexdigest())Nice to knowThe trainer can only train if it's not already training.The trainer will download the language pack each time a training is askedYou can only train Snips NLU on this for nowYou are limited to Snips NLU supported languages
Package: projectalice-sk
Project Alice skill kitThe Project Alice skill kit is a tool that helps create skills for Alice.FeaturesCreate new skillsValidate the format of all json filesInstallpip3installprojectalice-skThe skill kit supports tab completion forbashandzshit can be activated by adding this in your .bashrc:eval"$(_ALICE_SK_COMPLETE=sourceprojectalice-sk)"For zsh users add this to your .zshrc:eval"$(_ALICE_SK_COMPLETE=source_zshprojectalice-sk)"TestingIt is possible to run all validation tests we currently run against a skill when someone submits a PR locally using:projectalice-skvalidate--paths<pathnames>Further information on the validation tests can be foundhereAuto skills creationTo create the basic files needed for a skill to work, run:projectalice-skcreateThis saves you the hassle of creating the directory tree, the required files and so on. It also follows the strict conventions we made for skills and will avoid you trouble when submitting your skill for review.Contributors:maxbachmannlazza
Package: projectaria-client-sdk
Project Aria Client SDK For PythonThe Project Aria Client SDK with CLI provides robust capabilities for creating computer
vision and machine learning applications with the Project Aria glasses.The Client SDK currently offers the ability to:Connect and disconnect from the device via USB and WiFiRetrieve detailed device information and its current statusControl Aria recording capabilitiesControl Aria streaming capabilitiesAccess calibration data for the sensors you're recording withSubscribe and listen to Aria sensors dataVisualize streaming dataA CLI is installed as part of the SDK, which provides the ability to:Pair the glasses via USB or Wi-FiConnect to the glasses via USB or Wi-FiControl Aria recording capabilitiesControl Aria streaming capabilitiesRequirementsPython 3.8 - 3.11Platform: Mac Big Sur+, Fedora 36+, Ubuntu 22.04+A router such as Asus, Netgear or TP-Link with no firewall that supports Wi-Fi
6 to connect the glasses to the 5GHz band for when streaming over Wi-FiUpdate your glasses to the latest OS using the Aria Mobile Companion AppDocumentationProject Aria Client SDK DocumentationSamplesAfter installing the Project Aria Client SDK, extract the SDK sample apps to a
directory in your home folder by runningpython3 -m aria.extract_sdk_samples --output ~
cd ~/projectaria_client_sdk_samplesGo to theSetup Guideto get started.
Package: project-base-AB3NzaC1yc-setuptools
Diffusion Approximation for Demographic Inferencedadi implements methods for demographic history and selection inference from genetic data, based on diffusion approximations to the allele frequency spectrum. One of dadi's main benefits is speed: fitting a two-population model typically takes around 10 minutes, and run time is independent of the number of SNPs in your data set. dadi is also flexible, handling up to three simultaneous populations, with arbitrary timecourses for population size and migration, plus the possibility of admixture and population-specific selection.Originally dadi was initially developed by  Ryan Gutenkunst in the labs of Scott Williamson and Carlos Bustamante (https://bustamantelab.stanford.edu/) in Cornell's Department of Biological Statistics and Computational Biology. Ryan is now faculty in Molecular and Cellular Biology at the University of Arizona, and his group continues to work on dadi and other topics (http://gutengroup.mcb.arizona.edu).If you use dadi in your research, please cite RN Gutenkunst, RD Hernandez, SH Williamson, CD Bustamante "Inferring the joint demographic history of multiple populations from multidimensional SNP data" PLoS Genetics 5:e1000695 (2009).Getting startedSee the manual (https://dadi.readthedocs.io) and the example files in the source distribution. Full API documenation is available (https://dadi.readthedocs.io/en/latest/api/dadi/) and is in the source distribution, under doc/api/dadi/index.html .Also, please sign up for our mailing list, where we help the community with ∂a∂i. Please do search the archives before posting. Many questions come up repeatedly. (http://groups.google.com/group/dadi-user)The easiest way to install dadi is via conda,conda install -c conda-forge dadi.Notebook examples
Package: project-big-data
To-Do List Python LibraryOverviewThis project aims to create a comprehensive Python library for managing personal tasks (To-Do List).FeaturesThe application allows users to:Add a new task to the list with at least a name and a description.Mark a task as completed.Remove a task from the list.Display the list of ongoing tasks.Getting StartedThese instructions will get the project up and running on your local machine for development and testing purposes.PrerequisitesPython 3.xPoetryInstallationUsing DockerClone the repository:gitclonehttps://github.com/Nhurbis/projet_kit_big_data.gitcdprojet_kit_big_dataBuild and run the Docker container:dockerbuild-tles_meures.
dockerrun-it-p7860:7860les_meuresAccess the application in your web browser at:http://0.0.0.0:7860/Using PoetryClone the repository:gitclonehttps://github.com/Nhurbis/projet_kit_big_data.gitcdprojet_kit_big_dataSet up a virtual environment and install dependencies:poetryinstallTask Manager CLIThe Task Manager CLI is a command-line tool for managing your tasks and task lists. Here is a guide on how to use it.InstallationEnsure you have installed all the necessary dependencies and configured your Python environment correctly before running the application.Commandspythontask_manager_cli.pycreate_tasklist<title>
pythontask_manager_cli.pyadd_task<tasklist_id><name><description>
pythontask_manager_cli.pycomplete_task<tasklist_id><task_id>
pythontask_manager_cli.pydelete_task<tasklist_id><task_id>
pythontask_manager_cli.pyshow_incomplete_tasks<tasklist_id>Example Usage:pythontask_manager_cli.pycreate_tasklist"My Task List"pythontask_manager_cli.pyadd_task1"Go Shopping""Buy milk, eggs, and bread"pythontask_manager_cli.pycomplete_task11pythontask_manager_cli.pyshow_incomplete_tasks1TestingWe use pytest for unit testing. Run the tests using the following command:pytest--cov=modeltests/DocumentationThe documentation for this project is generated using Sphinx. To build the documentation locally, run the following commands in the docs folder:makehtmlThen, opendocs/_build/html/index.htmlin a web browser.CI/CDThis project is set up with a CI/CD pipeline using GitHub Actions. Any push to the main branch triggers the pipeline, which runs tests, checks code coverage, and deploys the documentation.SécuritéAs part of this project, and in order to facilitate the teacher's grading process, the decision was made to leave the database connection string visible in the code (instead of using environment variables). Additionally, we are directly returning the _id values to facilitate the use of the very simplistic gradio interface. In a real production environment, these choices would not have been made.
Package: project-cli
project_cliA commandline interface for creating structured Python projects.Installationpip install project_cliUsagepython -m project_cliIf you trustproject_clito make the right decisions, you can say ‘yes’ to all prompts:python -m project_cli -yDetailed informationHere is an example project structure created by this tool for a runnable project:> proj_name
    __init__.py
    __main__.py
> tests
    __init__.py
    context.py
    test_main.py
README.rst
setup.pyYou can run your app as follows:python -m proj_nameYou can run tests as follows:python -m unittest discover testsYou can also install your project in your own pip repository (or in a virtual environment) to make it runnable anywhere on your system:pip install -e .Note: the-eflag is optional. It will keep your pip repository synchronized with your source code.MetaRamon Hagenaars -ramon.hagenaars@gmail.comThis structure was inspired byKenneth Reitz.
Package: project-composer
A convenient system to structure and compose applications from a modular project.Basically, you give it a project manifest that will be used to organize your various
project parts. Parts can be classes, text files or you can implement another part
kind.DependenciesPython>=3.8;click>=8.0;colorlog;tomli;LinksRead the documentation onRead the docs;Download itsPyPi package;Clone it on itsGithub repository;
Package: projectend
projectendcalculate the end of projects.pipinstallprojectend
projectendexample.tomlexample:[project]name="Mein Projekt"start=2021-05-05# In hoursworkday=8.0[[project.tasks]]name="DEV Entfernen Kolab-Attribute"# In hourseffort=4[[project.tasks]]name="DEV Mailbestellung"effort=5[[project.tasks]]name="DEV Mehrfachrollen"effort=6[[project.tasks]]name="DEV Person nicht angelegt"effort=4[[project.tasks]]name="DEV Polygon"effort=8[[project.tasks]]name="DEV Umzubenennende Accounts"effort=6[[project.tasks]]name="Verzögerungen"effort=8[[project.resources]]name="dave"from=2021-05-08to=2021-05-16# Per dayhours=4# 0 = monday - 4 friday, empty = all weekdaysweekdays=[0,2,3][[project.resources]]name="hans 1"from=2021-05-05to=2021-05-13hours=4[[project.resources]]name="hans 2"from=2021-05-14to=2021-06-01hours=2exceptions=[2021-05-18][[freedays]]name="Auffahrt"date=2021-05-13[[freedays]]name="Pfingstmontag"date=2021-05-24[[freedays]]name="Nationalfeiertag"date=2021-08-01output:Simulating project: Mein Projekt

Week 18
Wed 2021-05-05    4.6 days (    37 hours) left
Thu 2021-05-06    4.1 days (    33 hours) left
Fri 2021-05-07    3.6 days (    29 hours) left

Week 19
Mon 2021-05-10    2.6 days (    21 hours) left
Tue 2021-05-11    2.1 days (    17 hours) left
Wed 2021-05-12    1.1 days (     9 hours) left
Fri 2021-05-14    0.9 days (     7 hours) left

Week 20
Mon 2021-05-17    0.6 days (     5 hours) left
Wed 2021-05-19    0.4 days (     3 hours) left
Thu 2021-05-20    0.1 days (     1 hours) left
Fri 2021-05-21   -0.1 days (    -1 hours) left

The project ends on 2021-05-22
Package: project-euler-python
Project-Euler=============Introduction-------------http://projecteuler.net/Project Euler is a website dedicated to a series of computational problems intended to be solved with computer programs. The project attracts adults and students interested in mathematics and computer programming. Here we will solve them using Python with purely functional programming style.Some people have expressed their concerns about making the solutions of the Euler Project public. While the risk of having people using them unjustly certainly exists (shame on them), the benefits of sharing knowledge should exceed this petty inconvenient.Project Euler Python=======================简介---------用Python 3.x计算Project Euler 开发环境是Win7/Eclipse Juno/Pydev文件简介------------* [.euler.py](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- 运行主入口* [.euler_pdb.py](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- 动态调试模块* [.euler_profiling.py](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- profiling测试模块* [.euler_unitest.py](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- unitest测试模块* [.euler.lib](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- 算法库* [.euler.lib.ext](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- 标准数据类型扩展库* [.euler.lib.data](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- 数据文件处理模块* [.euler.lib.utilities](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- 小实用库* [.euler.problem](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- 问题代码库* [.euler.problem.problem](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- 问题入口类* [.euler.problem.problem_x_x](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- 问题代码库* [euler.data](https://github.com/ifooth/ProjectEuler-Python/blob/master/src/_euler.py) -- 问题需要的数据文件开发编码规范==========代码的布局-------------Eclipse Juno+PyDev 默认编码命名约定----------1. 包名与的总是全部小写的ASCII字母 lowcaselowcase2. 模块名全部是小写的ASCII字母,运行下划线3. 类名是个一名词，采用大小写混合的方式，每个单词的首字母大写4. 函数名方法名是一个动词，采用大小写混合的方式，第一个单词的首字母小写，其后单词的首字母大写5. 变量名 除了变量名外，所有实例，包括类，类常量，均采用大小写混合的方式，第一个单词的首字母小写，其后单词的首字母大写6. 常量名 常量的声明，应该全部大写，单词间用下划线隔开9. 方法与变量名 参见函数名与全局变量名继承的设计----------1. _表示内部变量与函数 可以认为protected2. __表示私有变量与函数 可以认为private
Package: projectframe
ProjectFrame for data manipulationThis is a Python package for easy and efficient manipulation
of multiple DataFrame-like objects.InstallIf you dont already have numpy and scipy installed, it is best to downloadAnaconda, a python distribution that has them included.https://continuum.io/downloadsDependencies can be installed by:pip install -r requirements.txtPyPI install, presuming you have all its requirements installed:pip install projectframeUsagefromprojectframeimportProjectFrameimportnumpyasnp# Create datapf=ProjectFrame()
Package: project-generator
Project generatorSource code is often times simple but building it is difficult when more than one person is involved.
Developers like what they like: IDE, compiler, debugger and really all we want is to produce an executable.
Sharing project files decoding XML in commit messages because someone was debugging and changed compile options before commiting distracts from doing what you want to do; develop software.This project allows you to define a project in text using YAML files and generate IDE project files
based on the rules defined in records. No one should ever commit IDE specific project file to a repository again!All open sourced - licensed under Apache v2.0 license.Current StatusThe project is in alpha phase. Check issues for the ongoing tasks or todo tasks.Project generator currently generaters projects for the following tools (IDE, Makefile, etc..):uVision4 and uVision5IARMakefile (GCC ARM)Makefile (ARMCC)Cmake (GCC ARM)CoIDE (GCC ARM)Eclipse (Makefile with GCC ARM)Sublime (Makefile with GCC ARM)Visual studio (Makefile with GCC ARM)We appreciate any help and you are more than welcome to send a pull request or create a new issue in this repository.
The plan is to support as many IDE as possible , same applies for targets/MCU.How to use itThere are two options, how to use it. Either you downloadpypi packageor you can clone this repository to your project directory.Using packageOnce installed, test if project_generator is recognized:progen --versionThis should print the current installed version. You can use progen or project_generator as a command.Using directly the repositoryIn case of using this repository directly, be aware, the project generator is using relative paths. To solve this, invoke run.py with arguments as you would if using the package. Something like: python run.py --version. This helps with debugging the package.Getting startedAn example how to use progenbaremetal blinky examplesor more advancedmbed blinky examples.DocsTo get familiar with it, read our wiki. Good start isGetting started guide (wiki). There are other sections which describe the each blocks of the project generator.Add a new target/mcuWe use project generator definitions, which is a separate python module and contains mcu/target database plus parser to obtain those from tools projects, visit github pagehere.Dependencies for Project generatorPython 2.7.x/3.xpyYAMLSetuptoolsJinja2xmltodictproject generator definitions
Package: project-goldberg-common
project-goldberg-commonThis is the develop branch of the project-goldberg-common repository. This branch is used for development and testing of the project-goldberg-common library. The master branch is used for releases.How to use this package inside other projects in development environmentFirst you need to clone the project-goldberg-common repository:Then you need to install the project-goldberg-common package in editable mode:poetryadd--editable<path-to-project-goldberg-common-repository>
Package: projectile
projectileA tile-on-demand tile server built with PIL and Tornado.MotivationWe want to store a high-resolution image in memory on the server as a numpy
array. Then when a client requests a particular tile, we can make the PNG of the
requested tile by slicing the numpy array and using PIL to write the resulting
PNG back to the client through a StringIO stream.This is primarily intended for building interactive visualizations in research
settings where we might want to skip the time- and/or disk-intensive tile
generation step required by typical tile servers.DemoInstall projectile$ pip install projectileServe a test image from theUSC-SIPI Image Database:$ projectile sanfranManually request a particular tile by navigating tohttp://localhost:8000/2/1/2.png.Try zooming and panning in the demo client by navigating tohttp://localhost:8000/.Serve one of your own images (any format readable by PIL) with$ projectile some_image.tiffor, if you have data in a numpy.npyfile,$ projectile some_image.npyLoad an image in grayscale mode and apply a colormap:$ projectile --mode L --cmap viridis pentagonStress testingTo test the performance limits of on-demand tiling, download thishigh resolution map of Great Britain(8,150 × 13,086 pixels, file size: 102.74 MB) from Wikimedia Commons.Grayscale performance test:$ projectile britain.jpg -m LReducing tile resolution when running in color:$ projectile britain.jpg --tile_size 128Dependenciesnumpy>=1.13.3Pillow>=4.3.0tornado>=4.5.2matplotlib>=2.1.0APIURL schemeThe server will serve grayscale and RGB images in their original colors at/<z>/<x>/<y>/
.pngwhere<z>is the zoom level,<x>and<y>specify the coordinates of the
tile at that zoom level (0/0is the top left tile), and
specifies the
image tile resolution in pixels (must be a power of 2).The server will serve colormapped versions of a grayscale image at/<z>/<x>/<y>/
/<cmap>/<vmin>/<vmax>.pngwhere<cmap>is the name of a matplotlib colormap, and<vmin>and<vmax>specify the range of image pixel values linearly interpolate against the
colormap (pixel values outside this range will be clipped).Using a custom clientIf you like the projectile backend but just want to use a simple custom client
contained in a single HTML filecustom_client.html, you can run$ projectile array.npy --client custom_client.htmlto make projectile serve your client instead of the included demo client.Using projectile in your existing Tornado web applicationThe core functionality is exposed in theTileHandlerclass defined inserver.py, which you can use in your own Tornado web
applications:fromtornadoimportwebfromprojectile.serverimportTileHandler...app=web.Application([(r'/([0-9]+)/([0-9]+)/([0-9]+)/([0-9]+).png',TileHandler,dict(array=array)),...])...Launching projectile from your own Python codeYou can also launch a server from your own Python code with therun()function
defined inserver.py:fromprojectile.serverimportrunrun(array)CreditsThe demo client is lifted fromhttp://bl.ocks.org/mbostock/5914438, with the
addition of a small filtering check to prevent the client from requesting tiles
which lie beyond the image boundaries.