Saravanan666/pypi-org huggingface dataset:
Package: cccp
CCCP - Semi Server Side Rendered ☭CCCP usesdominatefor generation of HTML in Python butextends it with JavaScript snippetsIncludes:Custom elements that can be rendered:Function declarations for simple DOM manipulationIndludes of external scripts (like jquery etc.)Render function that can take a single or lists ofdominate HTML elementsHTML tag manipulation using external sourcecode from GET'sCCCP currently includes the following functions:(They all work by fetching html from a remote endpoint and manipulating a HTML tag with a givenid)ReplaceHtml(url, id): Lets you replace the contents of an HTML tagAppendHtml(url, id): Lets you append to the end of a HTML tagPrependHtml(url, id): Lets you prepend to the beginning of a HTML tagUsageInstall fromPYPI(also installsdominate):$ pip install cccpImport modules:from dominate import tags as t
import cccpInclude needed definitions in HTML Head:t.head(
        [
            cccp.REQUIRED,
            cccp.BOOTSTRAP,
            cccp.CreateReplaceHtmlFunc()
        ]
    )
],
t.body(
    [
        div(id="pageContent")
    ]
)Use functions inside HTML to manipulate select DOM elements:t.button(
    "go to blog",
    onClick=cccp.replaceHtml(
        "http://127.0.0.1:9999/page/1", "pageContent"
    ),
)☝️This will replace the contents of the div"pageContent"with theHTMLitGET's from"http://127.0.0.1:9999/page/1"seeexamples/flask_example.pyfor a full demo!RoadMapSimple functions for replacing/appending/prepending of DOM elementsElements for popular js dependencies:axiosused for HTTP requests (performs GET requests)jqueryused for HTTP requests (does the DOM manipulation)Error handling in bundled javascript functionsSimplehtml formsusingjson-schemafor form validation etcImplement testschartjs:Element for including libraryFunctions for creating different kinds of interactive chartsMore DOM manipulation javascript functions:Function for creating aCometcall and replacing/prepending/appending incomming html to the DOMFunctions for deleting DOM elementsFunctions for pulling regularily (timer interupt GET's)0.0.1implement simple javascript functions for DOM manipulationscreate example using flask0.0.2fix bugsintroduce more js snippets0.0.3fix css snippet0.0.4add xkcd line chart snippet0.0.10drop xkcd chart and use chartjs0.0.11line chart take options
Package: cccs
Common python library for CCCSThis is a common library that will be use by our different project so we can re-use as much code as possible. It includes the following:Utility functionsClassification engineString manipulationDate manipulationDictionary flattening/un-flatening/mergingLogging setupNetworking validation (IP/Domain)Security related operations (Generating password/username/API keys...)Generate random IDElastic datastore supportMaintain connection with ElasticsearchEasy to use lucene base search/add/remove documents functionsMaintain indexes fields using predefined data modelPerform bulk operationsPerform index repair/re-shard/replication/reindex operationsFilestore supportProvides easy to use file storage for your project with multiple backendsHTTP (read only)FTP/SFTPAmazon S3Azure Blob storageLocal storageHas the concept of multiple levels of storageObject data model (ODM) supportValidate the data of your projectKeep the datastore index fields in sync with the modelRemote datatypesProvide datastructures accessible to multiple processes running of different machines for distributed high availability environmentsSupported data structures are the following:CountersEvent dispatcher/handlersHashGlobal LocksSetsQuota trackersQueues (Pubsub/Fifo/Priority)InstallationThis library is public and distributed via Pypi:pip install cccsDevelopmentIf you which to participate to the development of this library, you can setup your environment the folowing way.Install python 3.9+We only support newer version of python and will not support older versions. This library was meant to end up running in a container anyway.sudo apt update
sudo apt install software-properties-common
sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt install python3.9Install VSCodeThis is our prefered IDE and the repo is already preconfigured for it.sudo snap install codeClone the cccs_common_python repo into your git foldercd ~/git/
git clone git@github.com:CybercentreCanada/cccs_common_python.gitCreate a virtual env in the cccs_common_python foldercd ~/git/cccs_common_python/
python3.9 -m venv venvInstall required packages and library in your virtual environementcd ~/git/cccs_common_python/
source ./venv/bin/activate
pip install -e .Currently used byAssemblyline [https://github.com/CybercentreCanada/assemblyline]
Package: cccs-ipyaggrid
ipyaggridDocSee documentation:widgetti.github.io/ipyaggrid/.Demo notebooks are indocs/notebooksand available on mybinder (see link above).Creditsipyaggrid was created byLouis Raisonandoscar6echoand originally maintained athttps://gitlab.com/DGothrek/ipyaggrid.For more context, read the original articleHarnessing the power of ag-Grid in Jupyter.Mario BuikhuizenandMaarten Breddelstook over maintenance in 2022.
Package: ccd2iso
ccd2isoCommand-line utility to convert a CloneCD .img file to a .iso file.This is a fork ofccd2iso, a
project by Danny Kurniawan and Kerry Harris. Besides being Python-based and
easier to build on Windows, this fork adds a little more error handling and a
progress bar.InstallationYou can grab appropriate binaries for your system on thereleases
page. These are
self-contained and don't have any external dependencies. Either drop the
executable somewhere in your PATH or manually navigate to it each time you want
to use ccd2iso, I can't tell you what to do.Or if you prefer using pip:pipinstallccd2isoIf you go the pip route you'll need Python 3.8+, because I like thewalrus operatortoo much.Usageusage: ccd2iso [-f] [-q] [-v] [-?] img [iso]

Convert CloneCD .img files to ISO 9660 .iso files.

positional arguments:
  img             .img file to convert
  iso             filepath for the output .iso file

optional arguments:
  -f, --force     overwrite the .iso file if it already exists
  -q, --quiet     don't output conversion progress
  -v, --version   show program's version number and exit
  -?, -h, --help  show this help message and exitUsage is pretty straightforward, just handccd2isoa .img file and a filepath to
spit out a .iso file. If you're lazy you can handccd2isojust the .img file and
it'll output to the same folder with the same filename, just with the extension
changed.Most of the time, you'll call it like this:ccd2isototally_legal_game_disc.imgIf you don't want to see a progress bar for some reason, pass--quietor-q.ccd2isowon't overwrite any .iso file unless you tell it to with-for--force. It uses a temporary file when reading the .img file, so even with-fyour .iso won't get overwritten with an invalid file. In rare cases, such
as when you have the iso file mounted in Windows,ccd2isowon't be able to
overwrite the file. When this happens it'll tell you, and give you the location
of the temp file containing your completely valid .iso data.As a libraryccd2isocontains aconvert()function that can be used outside of the
command-line interface, if for whatever reason you'd prefer to run conversions
from your own Python code:defconvert(src_file:BytesIO,dst_file:BytesIO,progress:bool=False,size:int=None)->None:"""src_file -- CloneCD disc image bytestream (typically with a .img extension)dst_file -- destination bytestream to write to in ISO 9660 formatprogress -- whether to output a progress bar to stdoutsize -- size of src_file, used to calculate sectors remaining for progress"""ccd2iso.clonecdalso contains some C-style structures representing the CloneCD
.img file format. This is completely based on Danny Kurniawan's research and I
can't take any credit for it.
Package: ccdfits
CCDFitsThis package provides utilities to work with .fits files that were taken with CCDs. It provides a FITS class to easily view and analyse images, along with useful functions to process them. It is particularly useful for Skipper CCD images, which can be calibrated by fitting gaussians to the zero- and one-electron peaks.InstallationI strongly recommend usingMinicondato create a virtual environment and install ccdfits and pre-requisites there.Pre-requisitesThis library has been developed for Python 3. It will not build in Python 2.ccdfitsrequires the following packages to be installed:numpyscipyastropymatplotlibIn addition, if you intend to useccdfits.processing, you will also need to install:scikit-learn (forcal2phys)scikit-image (forgenerateMask)Installing in a conda environmentCreate a new environment and install the prerequisites:conda create --name ccdfits numpy scipy astropy matplotlibActivate the newly created environment:conda activate ccdfitsInstall ccdfits via pip:pip install ccdfitsInstalling latest public version (may be different from that on pypi)pip install git+https://gitlab.com/nicolaseavalos/ccdfits.gitInstalling elsewhereAlthough not recommended, the following command should work in any case as long as pip for python 3 is installed in the system:pip3 install ccdfitsUsageThe following example shows how to load and view a .fits image. Replace'ccd-image.fits'with a string indicating the full or relative path to the image you are trying to load.# imports
from ccdfits import Fits
import matplotlib.pyplot as plt
plt.ion()

# set the image path
fits_path = 'ccd-image.fits'

# load and view the image
img = Fits(fits_path)
img.view()Complete documentation is in process.ChangelogVersion 1.0FITS class renamed to FitsSome documentation inside the codeVarious changes throughout the libraryHotfix 0.3.1Optimized for installation via pipVersion 0.3.0Addedskp2raw_lowmemfunction toccdfits.processingHotfix 0.2.1Addedsubtract_baselineoption toccdfits.processing.raw2procVersion 0.2.0Addedskp2rawfunction toccdfits.processing
Package: ccdgen
Compile Commands Database GENeratorAboutA Python script to generate acompile_commands.jsondatabaseby capturing the output ofmake. This script was originally created to provide
compilation databases formakebasedC/C++ projects in Visual Studio Code.InstallationLatest PyPi releasepipinstallccdgenUsagepython3 -m ccdgen --extensions <arguments...> -- <your build command>Arguments:OptionDefaultDescription-h,--helpShow help message and exit-c,--compiler(auto detect)Specify compiler-d,--dir./Working directory to runmakefrom-e,--extensionsExtension(s) for source files-o,--output./compile_commands.jsonOutput fileFor example, to runmake allas the build command for a C project:python3-mccdgen--extensions.c--makeallExample Visual Studio Code task:{"version":"2.0.0","tasks":[{"label":"ccdgen","type":"shell","command":"python","osx":{"command":"python3"},"args":["-m","ccdgen","--extensions",".c","--","make","all"]}]}LimitationsThe script relies on the Python standard library modulesargparse,json,os,subprocessandsys.This script relies onmakeechoing the compiler commands it runs to
stdout. If compiler commands are prefixed in the Makefile with@ormakeis run in silent mode, the output cannot be captured.The build must succeed to generate a full compilation database, though
warnings are not a problem.Currently only tested with Python 3.10 on macOS Ventura and Windows 10.Other ToolsCMake(since version 2.8.5) can be used as is to generatecompile_commands.jsonby adding-DCMAKE_EXPORT_COMPILE_COMMANDS=ONwhen
calling it. This only works for Unix Makefile builds.Bearis much more advanced tool for
generating compilation databases forclangtooling. macOS, Linux and FreeBSD
are currently supported.
Package: ccdingtalk
Installpip3 install ccdingtalk --upgrade --userSend Message using CCDingTalkWebhookMessagefrom ccdingtalk import CCDingTalkWebhookMessage

chat_bot = CCDingTalkWebhookMessage(webhook_url)
r = chat_bot.send_text(msg=msg, at_mobiles=at_mobiles)Send with several webhooks (auto load balance) using CCDingTalkWebhookMessageQueuefrom ccdingtalk import CCDingTalkWebhookMessageQueue

def __webhook_urls() -> list:
    api = 'https://oapi.dingtalk.com/robot/send?access_token='
    tokens = [
        'token1',
        'token2',
        'token3',
        'token4',
        'token5',
    ]
    results = []
    for token in tokens:
        results.append(api + token)
    return results


__shared_msg_queue = CCDingTalkWebhookMessageQueue(__webhook_urls())


def send_ding_msg(msg: str, at_mobile=''):
    __shared_msg_queue.add_message(msg, [at_mobile])Reply Message using CCDingTalkReplyfrom ccdingtalk import CCDingTalkReply

class DingBotRequestHandler(BaseHTTPRequestHandler):

    def do_GET(self):
		response = CCDingTalkReply.text_msg("This is GET request")
		response_bytes = response.encode()
		self.send_header("Content-Type", "text/html; charset=utf-8")
		self.send_header("Content-Length", str(len(response_bytes)))
		self.end_headers()
		self.wfile.write(response_bytes)

    def do_POST(self):
		response = CCDingTalkReply.text_msg("This is POST request")
		response_bytes = response.encode()
		self.send_header("Content-Type", "text/html; charset=utf-8")
		self.send_header("Content-Length", str(len(response_bytes)))
		self.end_headers()
		self.wfile.write(response_bytes)
Package: ccdl
ccdlThis is a package for downloading online comics.Supported sites:binb*:r.binb.jpwww.cmoa.jpbooklive.jptakeshobo.co.jpwww.comic-valkyrie.comfutabanet.jpcomic-polaris.jpwww.shonengahosha.co.jpcomic_action:comic-action.comcomic-days.com *comic-gardo.com *comic-zenon.comcomicborder.comkuragebunch.commagcomi.compocket.shonenmagazine.com *shonenjumpplus.com *tonarinoyj.jpviewer.heros-web.comcomic_earthstar:viewer.comic-earthstar.jpcomic_walker:comic-walker.comganma:ganma.jpurasunday:urasunday.com
Package: ccdt
简介简体中文|Englishchipeak_cv_data_tool主要用于多种数据集(计算机视觉)格式之间的相互转换,如coco、labelme等。另外还集成数据、文件、视频等文件常用的处理功能。主要特性集成多种计算机视觉标注格式相互转换支持各类数据集的筛选,分配与切割集成多种文件、图像、视频处理功能模块可拓展,用户可自定义数据格式提供python模块包,命令行等便捷方式安装pip install ccdt快速入门请参考快速入门文档学习 chipeak_cv_data_tool 的基本使用。相关标注工具labelme:https://github.com/wkentaro/labelme命令行功能实现数据支持集格式：labelme格式数据集https://github.com/wkentaro/labelmeCOCO格式数据集数据处理功能：数据集标注文件相互转换截取目标保存为图像(目前支持:矩形框,)图像(文件)处理：按比例或者文件数目划分数据(列如:文件分配或者训练测试集划分)视频处理：视频切片成图像图像合成为视频python模块功能实现数据支持集格式：labelme格式数据集https://github.com/wkentaro/labelmeCOCO格式数据集数据处理功能：数据集标注文件相互转换截取目标保存为图像(目前支持:矩形框,)图像(文件)处理：按比例或者文件数目划分数据(列如:用于文件分配或者训练测试集划分)视频处理：视频切片成图像图像合成为视频开源许可证该项目采用GNU General Public License v3.0 开源许可证。更新日志最新的月度版本 v1.0 在 2021.11.08 发布。已支持的数据集：COCO数据集Via标注数据集Labelme标注数据集已更新的功能：labelme数据集抠图coco数据集转labelme数据集labelme数据集转coco数据集根据标签类别筛选labelme数据集贡献指南无致谢无引用@misc{ccdt2021,
  author =       {詹勇},
  title =        {{ccdt: Annotation conversion and file video processing tools}},
  howpublished = {url{https://github.com/chipeak/chipeak_cv_data_tool.git}},
  year =         {2023}
}ChiPeak的其它项目ccdt: chipeak_cv_data_tool AI数据处理工具箱欢迎加入 ChiPeak 社区扫描下方的二维码可关注 芯峰科技团队的官方网站，加入芯峰科技 团队的官方交流我们会在 ChiPeak 社区为大家📢 分享 AI 框架的前沿核心技术💻 解读 ccdt 常用模块源码📰 发布 ChiPeak 的相关新闻🚀 介绍 ChiPeakDetection 开发的前沿算法🏃 获取更高效的问题答疑和意见反馈🔥 提供与各行各业开发者充分交流的平台干货满满 📘，等你来撩 💗，ChiPeak 社区期待您的加入 👬安全徽章
Package: ccdxt
CCDXT – CryptoCurrency Decentralized eXchange Trading LibraryTable of ContentsAbout The ProjectBuilt WithGetting StartedInstallationSupported Cryptocurrency ExchangesRoadmapContributingLicenseContactAbout The ProjectHere's why:ccxt only has centralized exchange not on Decentralizedeach swap has there own functionIt is intended to be used by coders, developers, technically-skilled traders, data-scientists and financial analysts for building trading algorithms.(back to top)Built WithGetting Startedfromccdxt.exchangeimportKlayswap,Meshswap,Orbitbridgeif__name__=="__main__":klayswap=Klayswap()klayswap.account=''klayswap.privateKey=''#Klayswap Token Balanceprint(klayswap.fetch_balance(['KETH','ZEMIT']))#Meshswap Token Swapprint(meshswap.create_swap(0.1,'USDC',0.0000000000001,'oZEMIT'))orbitbridge=Orbitbridge()orbitbridge.account=klayswap.accountorbitbridge.privateKey=klayswap.privateKey#Orbitbridge Token bridgeprint(orbitbridge.create_bridge(0.1,'ZEMIT','KLAYTN','MATIC',meshswap.account))InstallationBelow is an example of how you can instruct your audience on installing and setting up your app. This template doesn't rely on any external dependencies or services.pippipinstallgit+https://github.com/MunSunouk/ccdxt.gitClone the repogitclonehttps://github.com/MunSunouk/ccdxt.git(back to top)Supported Cryptocurrency Exchangeslogochainidnamever1Klayswap2Klex Finance3Pala swap4Pangea swap5neuron swap6claimswap7definix6Mesh swap7Orbit bridge(back to top)RoadmapMulti chains SupportklaytnpolygonfantometheriumMulti call SupportCross chsins SupportOptimism path SupportAsync Support(back to top)LicenseDistributed under the MIT License. SeeLICENSE.txtfor more information.(back to top)ContactContributor :@munseon_ugProject Link:https://github.com/MunSunouk/ccdxt(back to top)
Package: cc-email-templates
Conflict Cartographer Email TemplatesThis package contains email templates packages as Jinja2 templates, exposed via
a set of functions.Installationpip install cc-email-templatesUsageimport cc_email_templates 

email_txt, email_html = cc_email_templates.call_to_action_email(
      title = "My call to action",
      content_above = "Please click my link",
      action_button_text = "Link",
      action_link = "http://www.example.com"
   )

send_email(..., html_content = email_html, content = email_txt)CreditsBase template was "forked" and adapted fromthis repo
Package: ccentral
python-ccentralPython client for CCentral configuration management. Client communicates
directly with etcd.WebUI for configuration management and monitoring metrics can be found
fromhttps://github.com/slvwolf/ccentral.Example Usageimport ccentral

cc = ccentral.CCentral("my_service", "etcd-host:1234")
cc.add_field("config_a", "Dynamic configuration", default="test", description="Configuration string")

# Read configuration
print(cc.get("config_a"))

# Increment counters
cc.inc_instance_counter("run")

# Set text info
cc.add_instance_info("version", "1.2")

# Set text info (common in cluster)
cc.add_service_info("shared_key", "shared_value")
Package: ccepy
La biblioteca para python 3ccepypermite trabajar con
el grupo de puntos de una curva elíptica y desarrollar protocolos
criptográficos basados en curvas elípticas. También permite hacer
operaciones con cuerpos finitos y con enteros módulo un primo.Toda la información acerca de su uso y su instalación
se encuentra detallado en la documentación.El programaccepyse ha desarrollado para el Trabajo Fin
de Grado,Curvas Elípticas en Criptografía.Enlaces:DocumentaciónCurvas Elípticas en Criptografía
Package: ccex_api
Client for CCex API written in Python Currently supports all
ticker/public/private endpoints.InstallationVia pip:pip install ccex_apiUsageccex = CCexAPI()
ccex.tickers.tickers_coinnames()
ccex.public.get_market_summaries()# credentials are required for private endpoints access
ccex = CCexAPI(‘api_key’, ‘api_secret’)
ccex.private.get_balances()Offer a coffee or a beerIf you enjoyed this free software, and want to thank me, you can offer
me something for a coffee, a beer, or more, I would be happy :)Bitcoin : 13K5w1SXX7HTiKKQ1tQPerBKw1V6i65rsAEthereum : 0x2e693665b99d0b631c60ae0b9b7735d43c27e9cbDash : XwuAZapWHt5VU86ZBb5N2SDHK3t9XJUtGuDoge : DDf9jQkC17vWJkG6VsKPLo2oTnw4qY8XWd
Package: cceyes
CCEyes LibraryIntroductionCCEyes is a Python CLI and library for theCCEyesproject that allows you to easily access the CCEyes API as a provider.InstallationpipinstallcceyesUsageCLIroot@cceyes:~$cceyeskey
EnteryourAPIkey:
APIkeysaved!root@cceyes:~$cceyesdatasets|jq{"key":"xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx","datasets":[{"provider":"BetaSeries","type":"TV Series"}]}root@cceyes:~$cat~/productions.json|cceyesupsert|jq{"success":true}Libraryimportcceyesfromcceyes.modelsimportProduction,ProductionDataset,ProductionMetacceyes.config.set_config('api','key','xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx')# your ETL logic goes here# examples are located in examples/ folderproductions=[Production(title="The Mandalorian",content="The travails of a lone gunfighter in the outer reaches of the galaxy, far from the authority of the New Republic.",dataset=ProductionDataset(type="TV Series",provider="BetaSeries",),meta=ProductionMeta(id=68726,title="The Mandalorian",image="https://api.betaseries.com/pictures/shows?key=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx&id=68726",),)]cceyes.providers.upsert(productions)LicenseMITResourcesCCEyes WebsiteCCEyes PlatformCCEyes Platform SpecsCCEyes API DocumentationFundingFunded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or EACEA. Neither the European Union nor the granting authority can be held responsible for them.Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or EACEA. Neither the European Union nor the granting authority can be held responsible for them.
Package: cc-faice
CC-FAICEFAICE (Fair Collaboration and Experiments) is part of the Curious Containers project. It enables researchers to perform and distribute reproducible data-driven experiments defined in the RED format.For more information please refer to the Curious Containersdocumentation.AcknowledgementsThe Curious Containers software is developed atCBMI(HTW Berlin - University of Applied Sciences). The work is supported by the German Federal Ministry of Economic Affairs and Energy (ZIM project BeCRF, grant number KF3470401BZ4), the German Federal Ministry of Education and Research (project deep.TEACHING, grant number 01IS17056 and project deep.HEALTH, grant number 13FH770IX6) and HTW Berlin Booster.
Package: ccfcsharp
Lab2 C# code conventions analyzer and fixerAfter successful installation project can be used command:CSharpCCF (-v|-fx) -(p|d|f) <path>Command line optionsOptions:
  -v, --verify                    Verify files without editing.

  -fx, --fix                      Rewrite files

  -d, --directory TEXT            Absolute or relative path to directory with 
                                  files to be fixed.

  -p, --project TEXT              Absolute or relative path to project with 
                                  files to be fixed.

  -f, --file TEXT                 Absolute or relative path to file to be fixed.

  -h, --help                      Show this message and exit.`Note: any other input is equivalent to--help
Package: cc-feishu
概览飞书的 Python SDK如何安装pip3installcc-feishu如何使用引入模块fromcc_feishu.clientimportClientfeishu=Client(app_id='填写你的机器人的 app_id',app_secret='填写你的机器人的 app_secret')Test直接在根目录执行pytest即可，会读取 pytest.ini 的配置，并进行测试
Package: ccfit2
ccfit2ccfit2is a package for working with magnetometry data, specifically those from AC susceptibility, DC decay, and DC Waveform measurements.Although the main use ofccfit2is to extract and later fit temperature/field dependent relaxation rate data from these experiments, the modular nature
ofccfit2means that the user is free to include any ofccfit2's functionality in their own work.Documentation and InstallationTo get started, head to the online documentation forccfit2here.DevelopersInstall in editable mode by runningpip install -e .in the repository HEAD.ReferenceWe request that any data processed with ccfit2 is accompanied bybothof the following citationsWilliam J. A. Blackmore, Gemma K. Gransbury, Peter Evans, Jon G. C. Kragskow, David P. Mills, and Nicholas F. Chilton. Characterisation of magnetic relaxation on extremely long timescales. Phys. Chem. Chem. Phys., 2023, 25, 16735-16744. URL:https://dx.doi.org/10.1039/d3cp01278fDaniel Reta and Nicholas F. Chilton. Uncertainty estimates for magnetic relaxation times and magnetic relaxation parameters. 	Phys. Chem. Chem. Phys., 2019, 21, 23567-23575. URL:https://dx.doi.org/10.1039/C9CP04301B