Saravanan666/pypi-org huggingface dataset:
Package: dcspy
DCSpyDCSpy is able to pull information from DCS aircraft and display on Logitech G-series keyboards LCD.
Features:Logitech device with 160x43 px (4 lines) monochrome LCD -G13,G15 (v1 and v2)andG510Logitech device with 320x240 px (8 lines) full RGBA LCD -G19Setup G-Keys to any toggle, switch or knob in cockpit -Setup of G-KeysSupport for all aircraft (official and mods) with clickable cockpits -DCS-BIOS aircraftModern looking GUI using Qt6/PySide6See more information onWikipage.Aircraft and instrumentsThere are to kinds of supported aircraft:Basic- allow to assign all G-Keys of Logitech keyboard to aircraft's instruments in cockpit (all clickable cockpits supported by DCS-BIOS)Advanced- additionally can display some information on LCD (listed below)Why such way? Basically advanced support is for aircraft which I own and therefore can test it.AdvancedF/A-18C Hornet UFC - Up Front ControllerF-16C Viper DED - Data Entry DisplayKa-50 Black Shark II and III - PVI-800 and autopilot channelsMi-8MTV2 Hip - autopilot channels and Radios informationMi-24P Hind - Autopilot channels and modes and Radios informationA-10C Warthog and A-10C II Tank Killer - Radio frequency informationF-14A and F-14B Tomcat - basic support for RIO CAPAV-8B Night Attack Harrier - Up Front Controller and Option Display UnitAH-64D Apache - Enhanced Up Front DisplayF-15E Eagle - Upfront Control Panelmore to come....RequirementsLogitech Gaming Software 9.04.49Gitit is necessary for using live version of DCS-BIOS, seeLive DCS-BIOS)DCS-BIOS 0.7.50or newer (can beinstalleddirectly from DCSpy)DCS World:2.9.2.49940Open Beta, but any version from 2.9.* branch should be fine.optional:Python 3.12but 3.8+ should be fine (seeinstallation)However, DCSpy 2.3.3 and earlier do not support Python 3.12Notes:If you upgrade DCSpy from 1.5.1 or older you can safely remove Logitech LCD SDK fromC:\Program Files\Logitech Gaming Software\LCDSDK_8.57.148. Since DCSpy version 1.6.0 use built-in SDK in LGS (Logitech Gaming Software).New ideasI have lots of plans and new ideas how to improve it internally and form user's perspective, but don't hesitate to contact me. Maybe it will motivate me to implement some new stuff. Please open issue if you find bug or have any crazy idea.
You are welcomedcspy Discordserver.ContributingYou want contribute, perfect see:contributingguide.CreditsMore detailshere.Sponsored by Jetbrains Open Source Support Program
Package: dcs-pylicense
PyLicensePyLicense is a CLI tool that queries license information from one of the
following package repositories: PyPI, Anaconda or conda-forge.PyLicense uses the online information of those repositories, e.g. the license
information that is listed onpypi.org/pypi/<packagename>, e.g.https://pypi.org/project/dcs-pylicense/.
While this means that the package must not be installed on the local system,
it also shows information about the lastest package version and not every
possible package version.InstallationTo install the package run$pipinstalldcs-pylicenseThe tool registers itself aspylicense.
To learn about the available arguments refer to its help:$pylicense--helpUsagePyLicense requires a file in the format of a requirements file.
The format is describedhere.To query license information of the packages run$pylicensepath/to/my/requirements.txt| name       | license   | version   ||:-----------|:----------|:----------|| black      | MIT       | 20.8b1    || pylint     | GPL       | 2.6.0     || pytest     | MIT       | 6.0.2     || pytest-cov | MIT       | 2.10.1    || sphinx     | BSD       | 3.2.1     || twine      | unknown   | 3.2.1     |It is also possible to read from stdin$cat/path/to/my/requirements.txt|pylicenseBy default the result is returned as a markdown table.
Other format options are available, e.g. output formatting as CSV.$pylicense--output-formatcsvpath/to/my/requirements.txtname|license|versionblack|MIT|20.8b1pylint|GPL|2.6.0pytest|MIT|6.0.2pytest-cov|MIT|2.10.1sphinx|BSD|3.2.1twine|unknown|3.2.1By default thePython Package Index (PyPI)is queried.
This can be changed with the--repositoryflag.For example to query the anaconda package repository use the following command$pylicense--repositoryanacondapath/to/my/requirements.txt| name       | license      | version   ||:-----------|:-------------|:----------|| black      | MIT          | 19.10b0   || pylint     | GPL-2        | 2.6.0     || pytest     | MIT          | 6.0.2     || pytest-cov | MIT          | 2.10.1    || sphinx     | BSD-2-Clause | 3.2.1     || twine      | Apache  2    | 2.0.0     |
Package: dcss-api
dcss-apidcss-apiis an easy to use Rust and Python wrapper forDungeon Crawl Stone Soup's (DCSS) Webtilewebsocket API. It supports logging in, starting a game and sending commands during game play.DocumentationThe documentation for thedcss-apican be foundhere. The best way to start is to look at the examplesherefor Rust andherefor Python. Please see theSetupin order to be able to run these examples.In depth documentation about the DCSS websocket API can also be foundhere(not yet finalized).SetupBuilding DCSS WebtileThe API works for both local and public version of DCSS Webtiles. To run on a public server, you must limit the connection to a maximum of one command every 100 milliseconds (i.e. 10 commands per seconds), by setting thespeed_msoption to100while connecting. Follow any other rules required by the server's owner.Due to this, it is preferred to run the API against a local version of DCSS Webtile. You can find installation information on theDCSS Webtiles Server page.A summary (after installing all prerequisites):gitclone"https://github.com/crawl/crawl.git"cdcrawl/crawl-ref/source/
gitcheckoutstone_soup-0.29
makeWEBTILES=y
pythonwebserver/server.pyBuilding PythonThe python package fordcss-apiis aPyO3Python wrapper for the Rust package. It can be built using the following commands:mkdirpyo3
python-mvenvpyo3sourcepyo3/bin/activate
pipinstallmaturinpatchelf
maturindevelop-rTestingIn order to runcargo testorpytest, a local DCSS Webtile, with thestone_soup-0.29orstone_soup-0.30branch, must be exposed onlocalhost:8080and two users must be created:UsernameandUsername2, both with the password set toPassword.
Package: dc-stat-think
DataCamp Statistical Thinking utilitiesUtility functions used in the DataCamp Statistical Thinking courses.Statistical Thinking in Python Part IStatistical Thinking in Python Part IICase Studies in Statistical ThinkingInstallationdc_stat_think may be installed by running the following command.pip install dc_stat_thinkUsageUpon importing the module, functions from the DataCamp Statistical Thinking courses are available. For example, you can compute a 95% confidence interval of the mean of some data using thedraw_bs_reps()function.>>>importnumpyasnp>>>importdc_stat_thinkasdcst>>>data=np.array([1.2,3.3,2.7,2.4,5.6,3.4,1.3,3.9,2.9,2.1,2.7])>>>bs_reps=dcst.draw_bs_reps(data,np.mean,size=10000)>>>conf_int=np.percentile(bs_reps,[2.5,97.5])>>>print(conf_int)[2.218181823.60909091]ImplementationThe functions include in dc_stat_think are notexactlylike those students wrote in the DataCamp Statistical Thinking courses. Notable differences are listed below.The doc strings in dc_stat_think are much more complete.The dc_stat_think module has error checking of inputs.In most cases, especially those involving bootstrapping or other uses of thenp.randommodule, dc_stat_think functions are more optimized for speed, in particular usingNumba. Note, though, that dc_stat_think does not take advantage of any parallel computing.If you do want to use functionsexactlyas written in the Statistical Thinking courses, you can use thedc_stat_think.originalsubmodule.>>>importnumpyasnp>>>importdc_stat_think.original>>>data=np.array([1.2,3.3,2.7,2.4,5.6,3.4,1.3,3.9,2.9,2.1,2.7])>>>bs_reps=dc_stat_think.original.draw_bs_reps(data,np.mean,size=10000)>>>conf_int=np.percentile(bs_reps,[2.5,97.5])>>>print(conf_int)[2.209090913.59090909]CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template and then modified.
Package: dcs-worklog
Worklog - Simple CLI util to track work hoursWorklog is a simple and straight-forward tool to track working times via CLI.
It uses a plain text file as its storage backend which makes it easy to
process the logged information with other tools.Getting startedYou need to have Python >= 3.6 installed.pipinstalldcs-worklogPlease follow thedocumentation on
readthedocsto learn how to use the CLI
tool.DevelopmentClone this repository and install the development version:pipinstall-e".[develop]"Run tests viapytest--covworklogCreate a releaseAttention: This should not be needed. Releases are auto-generated from the
*GitHub CI. See theconfiguration file.To create a release usegit flow, update the version number in setup.py first.
Then execute the following commands:pythonsetup.pysdistbdist_wheel
twineupload--skip-existing-rpypidist/*
Package: dcs-xkcd-cli
xkcd cli toolGet your daily dose ofxkcddirectly from the terminal! 🤩https://user-images.githubusercontent.com/3976183/163873282-f586f312-2643-4b77-af79-89e344091b2f.mp4xkcdis a webcomic created byRandall Munroe.
It is a comic of Language, Math, Romance and Sarcasm and acouple of other categories.Ifkitty,itermor any terminal that has support for thesixelfile format is used as the terminal, the xkcd comic will be rendered directly in the terminal, otherwise the default viewer for PNG images is used.
This tool requiresfzfto be installed on the machine to filter available comics by their title.InstallationWith pipInstall this package directly from thePython Package Index (PyPI).
The CLI tool requires Python >= 3.8 to be installed.$pipinstalldcs-xkcd-cliThis will install a CLI tool namedxkcdwhich can be used as described below.With pipxInstallation withpipxis similar to the pip variant above, but usespipxinstead ofpip.$pipxinstalldcs-xkcd-cliNote that with pipx, this package can be tried out without the need to install it permanently.$pipxrundcs-xkcd-cli<args>UsageSearch by title$xkcdshowThis functionality requiresfzfto be installed.Show latest xkcd comic$xkcdshow--latestShow random xkcd comic$xkcdshow--randomShow xkcd comic by its ID$xkcdshow--comic-id207Upscaling / width of comicsBy default images are upscaled to match the terminal dimensions.
This behavior can be controlled with the--terminal-scale-up / --no-terminal-scale-upoptions.
Images can be also rendered with an explicit width by using the--widthCLI option.$xkcdshow--comic-id207--no-terminal-scale-up# disable scaling$xkcdshow--comic-id207--width1200# set explicit widthDisable rendering in terminals$xkcdshow--no-terminal-graphicsThis command will disable the automatic image protocol detection and directly open the image with the help ofxdg-openin the default image viewer.Disable or update cacheUnder the hood this tool uses a cache which is updated once per day transparently.
The cache is used to remember the list of xkcd comics from thearchive.To disable the cache, use the following command$xkcdshow--no-cacheTo update the cache manually, use the following command$xkcdupdate-cacheDevelopmentThis repository manages Python dependencies withpoetry.
To install the package and its dependencies run:$poetryinstallThe code is formatted withblackand type checked withpyright.Then run the the following commands to lint and test the code:$poetryrunpython-mblack--check--diff.# tests for any lint issues$poetryrunpython-mblack.# auto-formats the code$poetryrunpython-mpyright# runs static code analysis$poetryrunpython-mpytest--cov="xkcd_cli/"--cov-reportterm--cov-reporthtml# run tests with code coverage report
Package: dcTMD
Features•Installation•Tutorials•DocsdcTMDThis package aids in the analysis of dissipation-corrected targeted molecular dynamics (dcTMD) simulations. The method enforces rare unbinding events of ligands from proteins via a constraint pulling bias. Subsequently, free energy profiles and friction factors are estimated along the unbinding coordinate. For a methodological overview, see ourarticle.S. Wolf, and G. Stock,Targeted molecular dynamics calculations of free energy profiles using a nonequilibrium friction correction.,J. Chem. Theory Comput.2018 14 (12), 6175-6182,doi:10.1021/acs.jctc.8b00835This package will be published soon:V. Tänzel, M. Jäger, D. Nagel, and S. Wolf,Dissipation Corrected Targeted Molecular Dynamics,in preparation 2023We kindly ask you to cite these articles in case you use this software package for published works.FeaturesIntuitive usage via module and CISklearn-style API for fast integration into your Python workflowSupports Python 3.8-3.10Multitude ofpublicationswith dcTMDImplemented Key FunctionalitiesEstimation of free energy profiles and friction factors along the unbinding coordinate of ligands as described byWolf and Stock 2018.Analysis of separate unbinding pathways as described byWolf et al. 2022.InstallationThe package will be available on PiPY and conda. Until then, install it via:python3-mpipinstallgit+ssh://git@github.com/moldyn/dcTMD.gitUsageCheck out the documentation for an overview over all modules as well as the tutorials.RoadmapNew Features:Gaussian error estimation2d distribution WorkSet plotsEstimator plots: free energy, friction & bothNormality plotConfidence intervalsExponential estimator classDiscuss gaussian kernel borders
Package: dc_tools
Towel Stuff provides such and such and so and so. You might find
it most useful for tasks involving <x> and also <y>. Typical usage
often looks like this:#!/usr/bin/env python

import dc_type
    typeUchar = dc_type('UCHAR')
    typeuchar_p = dc_type('UCHAR*',512)A SectionLists look like this:FirstSecond. Can be multiple lines but must be indented properly.A Sub-SectionNumbered lists look like you’d expect:hi theremust be goingUrls arehttp://like.thisand links can be
writtenlike this.
Package: dcttools
PythonDiCTionairyTOOLS. Rudimentary, outdated, everywhere
else found.InstallationPlease see theInstallation Guide(Github Repo Link) for details.UsagePlease read theAPI Documentationfor usage and theWorklow Reference(Github Repo Link) for taking full
advantage of this project foundation (NoxandPoetryusage in particular).ContributingContributions are very welcome.
To learn more, see theContributor Guide(Github Repo Link).LicenseDistributed under the terms of theMIT license(Github Repo Link),dcttoolsis free and open source software.IssuesIf you encounter any problems,
pleasefile an issuealong with a detailed description.CreditsThis project was created using theMathias Ammontweaked version of theHypermodern-Pythonproject foundation proposed byClaudio Jolowicz.
Package: dc_type
Towel Stuff provides such and such and so and so. You might find
it most useful for tasks involving <x> and also <y>. Typical usage
often looks like this:#!/usr/bin/env python

import dc_type
    typeUchar = dc_type('UCHAR')
    typeuchar_p = dc_type('UCHAR*',512)A SectionLists look like this:FirstSecond. Can be multiple lines but must be indented properly.A Sub-SectionNumbered lists look like you’d expect:hi theremust be goingUrls arehttp://like.thisand links can be
writtenlike this.
Package: dcu.active-memory
Backup your files to Amazon Web Services in a way that slowly forgets! I’ve learned that this way is refered to as the [‘Grandfather, father, son’](http://en.wikipedia.org/wiki/Backup_rotation_scheme#Grandfather-father-son) strategy.This script copies a file to Amazon S3 and rotates it.The filename will have a date stamp added before the first . in the filename.Do notadd a timestamp yourself, this will cause the script to treat the file as a unique file and the rotation won’t work!Rotation works as follows:
- Keep files from the last X days
- After that, keep Y files spaced at least a week apart
- After that, keep Z files spaced at least 30 days apart## Installationpip install dcu.active-memory## UsageExport the following environment variables:
-export AWS_ACCESS_KEY_ID=yourkeyidhere-export AWS_SECRET_ACCESS_KEY=yoursecretkeyYou can also use one of the other methods supported by boto.upload_rotate.py bucket prefix file.Seepython upload_rotate.py -hfor more info.
Package: dc_ui
Towel Stuff provides such and such and so and so. You might find
it most useful for tasks involving <x> and also <y>. Typical usage
often looks like this:#!/usr/bin/env python

import dc_type
    typeUchar = dc_type('UCHAR')
    typeuchar_p = dc_type('UCHAR*',512)A SectionLists look like this:FirstSecond. Can be multiple lines but must be indented properly.A Sub-SectionNumbered lists look like you’d expect:hi theremust be goingUrls arehttp://like.thisand links can be
writtenlike this.
Package: dcurves
ContributorsShaun Porwal (shaun.porwal@gmail.com)Rohan Singh (singhrohan@outlook.com)dcurvesDiagnostic and prognostic models are typically evaluated with measures of accuracy that do not address clinical
consequences. Decision-analytic techniques allow assessment of clinical outcomes, but often require collection of
additional information that may be cumbersome to apply to models that yield continuous results. Decision Curve
Analysis is a method for evaluating and comparing prediction models that incorporates clinical consequences,
requiring only the data set on which the models are tested, and can be applied to models that have either continuous or
dichotomous results. The dca function performs decision curve analysis for binary and survival outcomes. Review the
DCA tutorial (towards the bottom) for a detailed walk-through of various applications. Also, seewww.decisioncurveanalysis.orgfor more information.Table Of ContentsThe documentation follows the best practice for
project documentation as described by Daniele Procida
in theDiátaxis documentation frameworkand consists of four separate parts:TutorialsHow-To GuidesReferenceExplanationQuickly find what you're looking for depending on
your use case by looking at the different pages.Project Overview::: dcurvesIn-depth tutorial and explanations:https://www.decisioncurveanalysis.orgContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to changePlease make sure to update tests as appropriateLicenseApache 2.0Notesetup.py is deprecated now that dependencies are managed bypoetrypackage managerUsing towncrier to document changes for this projectcreating a newsfragment example (format is PR/Issue#.type for newsfragment): poetry run towncrier create -c "Added support for Python 3.11." 18.additionMake sure the newsfragments are tracked by git before buildingbuilding newsfragments example (dryrun with draft): poetry run towncrier build --draft --version 1.0.6.4Creating custom towncrier types: check pyproject.toml for example, as all of those are custom types
Package: dcustat
dcustat一个能够简洁的显示海光 DCU 设备状态的命令行工具；之前使用GPU时习惯了使用工具gpustat查看GPU状态，使用海光的 DCU 设备之后发现并没有类似的工具，于是仿照gpustat自己写了一个；
显示效果如下图：依赖说明python版本要求：python>=3.8；该工具的底层是调用的命令rocm-smi，所以在使用该工具前需要确保 DCU 的固件和驱动都正常安装。安装说明pip install dcustat使用说明使用如下命令单次获取当前 dcu 设备信息：dcustat使用如下命令动态刷新当前 dcu 设备信息，默认每2秒刷新一次：dcustat --watch可选参数如下：usage: dcustat [-h] [-i [INTERVAL]] [--light] [--debug] [-v]

optional arguments:

  -h, --help            show this help message and exit

  -i [INTERVAL], --interval [INTERVAL], --watch [INTERVAL]
                        动态刷新模式；INTERVAL为刷新间隔，单位：秒；默认每2秒刷新一次；

  --light               使用较亮的模式显示，如果显示器渲染出来的结果较暗，可以打开该参数；

  --debug               Debug模式时允许在程序出错的情况下打印更多的调试信息；

  -v, --version         show program's version number and exit参数 --light 说明有的显示器渲染结果中部分指标比较暗，如下图左侧所示。此时可以添加上 --light 参数，所有的结果都会以更亮的形式进行显示，如下图右侧所示。dcustat --watch --light默认加--light参数显示内容说明sxcs-k8s-master-01  Mon Aug  7  17:35:53 2023
 ID   温度,   风扇,  AvgPwr / PwrCap,  显存,  Core
[0] 43.0°C,  0.0%,  20.0W / 450.0W,  0.0%,  0.0%
[1] 43.0°C,  0.0%,  20.0W / 450.0W,  0.0%,  0.0%
[2] 43.0°C,  0.0%,  20.0W / 450.0W,  0.0%,  0.0%
[3] 43.0°C,  0.0%,  20.0W / 450.0W,  0.0%,  0.0%header：第1行为header，展示的信息从左到右依次为机器名称、当前时间；title：第2行为title，title是对后面展示的信息的各字段的说明：ID列是显卡的id；温度列是显卡的当前温度；风扇列是显卡风扇的当前转速；AvgPwr列是平均功率；PwrCap列是显卡的功率上限；显存列是当前显存的使用率；Core列是当前计算资源的使用率。Reference本项目的灵感、排版展示、以及代码的整体结构都是源自gpustat，本项目只是将其工作适配到了海光 DCU 设备上；LicenseMIT License
Package: dcvalidator
DCValidatordcvalidatoris a Python package designed for educational purposes to showcase Dependency Confusion attacks. It is not intended for real-world use and should not be used in production systems.InstallationpipinstalldcvalidatorIran National Code ValidationThe package provides a function is_nationalcode for validating Iran National Codes. The function takes a string representing the National Code and returns True if the code is valid and False otherwise.Executing theis_nationalcodefunction in this package will simulate a Dependency Confusion attack for educational purposes. As part of this simulation, the code intentionally runs an OS command to obtain directory information.Please Note:This simulated attack is for educational use only.Do not use this tool in a production environment.The project maintainers are not responsible for any misuse of this tool.fromdcvalidatorimportis_nationalcode# Validate Iran National Coderesult=is_nationalcode('1234567890')ifresult:print("Valid National Code")else:print("Invalid National Code")Important NotesEducational Purpose Only: This project is meant for educational purposes and should not be used with malicious intent.Responsible Disclosure: If you discover any security vulnerabilities or potential risks, please follow responsible disclosure practices and report them to the maintainers.ContributingContributions are welcome! If you find issues or have improvements, feel free to open an issue or submit a pull request.LicenseThis project is licensed under the MIT License - see the LICENSE file for details.
Package: dcw
Data Collection and WranglingThedcwmodule provides a framework for collecting and wrangling data.!!! warning
This isv0.x.xwork-in-progress. There are large, often backwards incompatible, changes between releases.Installation$pipinstalldcwRunning Data PipelinesPipelines can be run in one of two ways:Thedcw-pipelineCLI tool can be used to run data pipelines expressed using thedcwframework.Thedcw.etl.pipeline.run_pipelinefunction may be used
from your own application.!!! note
When running these commands while developing, prefix the commands withpoetry run.E.g. `poetry run dcw-pipeline -h`$dcw-pipeline-h
usage:dcw-pipeline[-h][--verbose]{list,run,help}...

DCWPipelines.

options:-h,--helpshowthishelpmessageandexit--verbose,-vEnableverboselogging

commands:{list,run,help}listListavailablepipelinefactoriesrunRunapipelinehelpShowhelpforapipelineA demo pipeline may be found atdcw.etl.demo_pipeline:List the pipelines in a module:$dcw-pipelinelistdcw.etl.demo_pipeline
Availablepipelines:
+----------------------------------+----------------------------------------------------------------------------+|Path|Description|+==================================+============================================================================+|dcw.etl.demo_pipeline.MyPipeline|Extractsequentialnumbers,squarethem,andloadtheresulttoamockdb.|+----------------------------------+----------------------------------------------------------------------------+Show the help message and parameters for a pipeline:$dcw-pipelinehelpdcw.etl.demo_pipeline.MyPipeline
Extractsequentialnumbers,squarethem,andloadtheresulttoamockdb.

options:-h,--helpshowthishelpmessageandexit--limitLIMITRun a pipeline from the command line and provide arguments:$dcw-pipelinerundcw.etl.demo_pipeline.MyPipeline----limit102024-01-19T09:49:36-0500dcw.cli.pipelineINFO:RunningMyPipelinewithoptionslimit=10(pipeline.py:67)Loaded0Loaded1Loaded4Loaded9Loaded16Loaded25Loaded36Loaded49Loaded64Loaded81FlushedtheloaderDevelopingThis Python project is managed usingpoetry, tested usingpytest, and documented usingmkdocs.Create Virtual Environment and Run TestsCreate a virtual environment and install all dependencies into it:$poetryinstallRun tests inside the virtual environment:$poetryrunpytestBuildingPoetry can be used to build a wheel and source distribution:$poetrybuildServe Documentation$poetryrunmkdocsserveDocumentation files can be built usingpoetry run mkdocs build.