Saravanan666/pypi-org huggingface dataset:
Package: charlesbot-pagerduty-escalations
ACharlesbotplugin to create an incident in Pagerduty and assign it to a
specific service.How does this workThis plugin adds the following two!helptargets:!lassie <service> [optional message] - Triggers a Pagerduty incident and assigns it to that service
!lassie services - Lists all the available Pagerduty servicesCreating an escalation event triggers an incident in Pagerduty and assigns it
to the specified service. Using aSlackinterface that people are already
comfortable with, this could be a very useful and efficient way of getting the
attention of the right people during an emergency.Installationpipinstallcharlesbot-pagerduty-escalationsInstructions for how to run Charlesbot are over athttps://github.com/marvinpinto/charlesbot!ConfigurationFirst off, create one or more services in Pagerduty of type Generic API. This
plugin makes use of a service’sIntegration Keyto trigger escalation
events.In your Charlesbotconfig.yaml, enable this plugin by adding the following
entry to themainsection:main:enabled_plugins:-'charlesbot_pagerduty_escalations.pagerdutyescalations.PagerdutyEscalations'Then add apdescalationsdictionary block that looks something like:pdescalations:service_mappings:service_one_name:'s1_pd_key'service_two_name:'s2_pd_key'The name that you assign your service will be the name that shows up when a
person issues the!lassie servicescommand. The corresponding key here is
theIntegration Keyassociated with that service (in Pagerduty).Sample config filemain:slackbot_token:'xoxb-1234'enabled_plugins:-'charlesbot_pagerduty_escalations.pagerdutyescalations.PagerdutyEscalations'pdescalations:service_mappings:service_one_name:'s1_pd_key'service_two_name:'s2_pd_key'LicenseSee theLICENSE.txtfile for license rights and limitations (MIT).
Package: charlib
CharLib: An open-source standard cell library characterizer🔩 Supports combinational and sequential cells📈 Plots timing and I/O voltages🧑‍💻 Easy-to-use, with YAML-based configuration🐍 Implemented in Python 3 with a modified PySpice backend🌶️ Compatible with ngspice and XyceIntroductionCharLib is an open cell library characterizer originally based onlibretto. The current version supports timing characterization of combinational and sequential cells.InstallationCharLib can be installed fromPyPIusing pip:# Install our customized version of PySpice
pip install git+https://github.com/infinitymdm/PySpice

# Install CharLib
pip install charlibMake sure you also have a compatible circuit simulator.ngspiceandxyceare currently supported.Usagecharlib run path/to/library/config/CharLib searches the specified directory for a YAML file containing a valid cell library configuration, then characterizes the specified cells. Seeyaml.mdfor information on constructing a config file.The general process for using CharLib is as follows:Acquire SPICE files and transistor models for the cells you want to characterizeWrite a configuration YAML file for the libraryRun CharLibReferences[1] M. Mellor and J. E. Stine, "CharLib: an open-source characterization tool written in Python", 2023.[2] Synopsys, "What is Library Characterization?",https://www.synopsys.com/glossary/what-is-library-characterization.html, 2023[3] S. Nishizawa and T. Nakura, "libretto: An Open Cell Timing Characterizer for Open Source VLSI Design," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 論文ID 2022VLP0007, [早期公開] 公開日 2022/09/13, Online ISSN 1745-1337, Print ISSN 0916-8508,https://doi.org/10.1587/transfun.2022VLP0007,https://www.jstage.jst.go.jp/article/transfun/advpub/0/advpub_2022VLP0007/_article/-char/ja,[4] I. K. Rachit and M. S. Bhat, "AutoLibGen: An open source tool for standard cell library characterization at 65nm technology," 2008 International Conference on Electronic Design, Penang, Malaysia, 2008, pp. 1-6, doi: 10.1109/ICED.2008.4786726.[5] E. Salman, A. Dasdan, F. Taraporevala, K. Kucukcakar and E. G. Friedman, "Exploiting Setup-Hold-Time Interdependence in Static Timing Analysis," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 26, no. 6, pp. 1114-1125, June 2007, doi: 10.1109/TCAD.2006.885834.
Package: charLLM
Character-Level Language Models Repo 🕺🏽This repository contains multiple character-level language models (charLLM). Each language model is designed to generate text at the character level, providing a granular level of control and flexibility.🌟 Available Language ModelsCharacter-Level MLP LLM (First MLP LLM)GPT-2 (under process)Character-Level MLPThe Character-Level MLP language model is implemented based on the approach described in the paper "A Neural Probabilistic Language Model" by Bential et al. (2002).
It utilizes a multilayer perceptron architecture to generate text at the character level.InstallationWith PIPThis repository is tested on Python 3.8+, and PyTorch 2.0.0+.First, create avirtual environmentwith the version of Python you're going to use and activate it.Then, you will need to installPyTorch.When backends has been installed, CharLLMs can be installed using pip as follows:pipinstallcharLLMWith GITCharLLMs can be installed using conda as follows:gitclonehttps://github.com/RAravindDS/Neural-Probabilistic-Language-Model.gitQuick TourTo use the Character-Level MLP language model, follow these steps:Install the package dependencies.Import theCharMLPclass from thecharLLMmodule.Create an instance of theCharMLPclass.Train the model on a suitable dataset.Generate text using the trained model.Demo for NPLM(A Neural Probabilistic Language Model)# Import the class>>>fromcharLLMimportNPLM# Neural Probabilistic Language Model>>>text_path="path-to-text-file.txt">>>model_parameters={"block_size":3,"train_size":0.8,'epochs':10000,'batch_size':32,'hidden_layer':100,'embedding_dimension':50,'learning_rate':0.1}>>>obj=NPLM(text_path,model_parameters)# Initialize the class>>>obj.train_model()## It outputs the val_loss and image>>>obj.sampling(words_needed=10)#It samples 10 tokens.Model Output GraphFeel free to explore the repository and experiment with the different language models provided.ContributionsContributions to this repository are welcome. If you have implemented a novel character-level language model or would like to enhance the existing models, please consider contributing to the project.LicenseThis repository is licensed under theMIT License.
Package: charlogger
charloggerA logging library for Python.I've been using this myself for a while, and I thought that I may as well release it.It's filled with bad code, but now that it is public, I'll probably improve it over time.InstallationYou can install charlogger withpip install charlogger.How to useSimple exampleimportcharloggerlogger=charlogger.Logger()logger.info("What a great logging library!")Advanced exampleimportcharlogger# All parameters are optional.logger=charlogger.Logger(debug=True,# Whether to enable the output of debug logsdefault_prefix="your prefix",color_text=False,# Whether to have the info text be coloredlog_file_patj=open("log.txt","a"),# The file to put logs inindent_level=8,# The indentation of the text when output.centered=True# Whether to center text in the console.)logger.info("What a great logging library!")My personal configuration (best)importcharloggerlogger=charlogger.Logger(debug=True,default_prefix="<TIME> | WORKER-001",color_text=True)logger.info("What a great logging library!")More in-depth documentationdefaultPrefixWhen initializing a Logger, you have the option ofdefault_prefix.For now, if you add"<TIME>"anywhere in that string, it will replace it with the time of the logging.For instance, the following code will print18:26:15 | hi! | i > What a great logging library!importcharloggerlogger=charlogger.Logger(debug=True,defaultPrefix="<TIME> hi!")logger.info("What a great logging library!")Logging methodsPossible argumentsimportcharloggerlogger=charlogger.Logger()logger.info("What a great logging library!")# i > What a great logging library!logger.info(title="DOCUMENTATION",data="What a great logging library!")# i > [DOCUMENTATION] What a great logging library!All possible methodsimportcharloggerlogger=charlogger.Logger()logger.info("What a great logging library!")logger.warn("What a great logging library!")logger.error("What a great logging library!")logger.debug("What a great logging library!")logger.valid("What a great logging library!")logger.invalid("What a great logging library!")logger.plus("What a great logging library!")logger.paid("What a great logging library!")Special methodsimportcharloggerlogger=charlogger.Logger()# I can't imagine this one being all that useful. It's more there for my personal projects that use it,logger.choice(1,"Option 1")# 1 > Option 1# Will wait for user input in the console.name=logger.ask("What is your name?")# ? > What is your name? >print(name)
Package: charlotte
charlotteLightweight and expandable spider framework.InstallpipinstallcharlotteExampleimportjsonimportasynciofromcharlotte.spiderimportBaseSpiderclassSpider(BaseSpider):asyncdefon_start(self):response=awaitself.fetch('https://blog.qiaohong.org/api/v1/articles')items=json.loads(response.body)awaitasyncio.wait([self.fetch('https://blog.qiaohong.org/api/v1/articles/'+item['slug'],parser=self.parse_detail)foriteminitems['data']['articles']])defparse_detail(self,res):print(res.body.decode('utf-8'))if__name__=='__main__':Spider().run()DocumentationCheckwikifor details.LICENSEMIT
Package: charlybot
charly-bot----------charly-bot est un bot discord implémenté en Python. C'est un petit utilitaire possédant quelques fonctionnalités utiles. Chaque fonctionnalité est une simple commande a saisir:Youtube=======1. Lire les informations d'une vidéo2. convertir une vidéo youtube (viméo..) en MP3Twitter=======1. Afficher les informations d'un utilisateur2. Tweeter3. Follow un utilisateur4. Unfollow un utilisateur5. Rechercher des tweetsMétéo=====1. Affiche la météo du jourDropbox=======1. Liste des dossiers2. Uploader3. Créer un dossier4. Supprimer5. Déplacer6. Copier7. partager8. Télécharger10. Afficher le compte11. ...Autres=====1. Changer de status2. Envoyer une image dans un channel
Package: charm4py
Charm4py (Charm++ for Python-formerly CharmPy-) is a distributed computing and
parallel programming framework for Python, for the productive development of fast,
parallel and scalable applications.
It is built on top ofCharm++, a C++ adaptive runtime system that has seen
extensive use in the scientific and high-performance computing (HPC) communities
across many disciplines, and has been used to develop applications that run on a
wide range of devices: from small multi-core devices up to the largest supercomputers.Please see theDocumentationfor more information.Short ExampleThe following computes Pi in parallel, using any number of machines and processors:fromcharm4pyimportcharm,Chare,Group,Reducer,FuturefrommathimportpiimporttimeclassWorker(Chare):defwork(self,n_steps,pi_future):h=1.0/n_stepss=0.0foriinrange(self.thisIndex,n_steps,charm.numPes()):x=h*(i+0.5)s+=4.0/(1.0+x**2)# perform a reduction among members of the group, sending the result to the futureself.reduce(pi_future,s*h,Reducer.sum)defmain(args):n_steps=1000iflen(args)>1:n_steps=int(args[1])mypi=Future()workers=Group(Worker)# create one instance of Worker on every processort0=time.time()workers.work(n_steps,mypi)# invoke 'work' method on every workerprint('Approximated value of pi is:',mypi.get(),# 'get' blocks until result arrives'Error is',abs(mypi.get()-pi),'Elapsed time=',time.time()-t0)exit()charm.start(main)This is a simple example and demonstrates only a few features of Charm4py. Some things to note
from this example:Chares(pronounced chars) are distributed Python objects.AGroupis a type of distributed collection where one instance of the specified
chare type is created on each processor.Remote method invocation in Charm4py isasynchronous.In this example, there is only one chare per processor, but multiple chares (of the same
or different type) can exist on any given processor, which can bring flexibility and also performance
benefits (like dynamic load balancing). Please refer to thedocumentationfor more information.ContactWe would like feedback from the community. If you have feature suggestions,
support questions or general comments, please visit ourforumor emails us at <charm@cs.illinois.edu>, orMain author at <jjgalvez@illinois.edu>
Package: charmcord
CharmCordCharmCord is the best python string-based package for Discord bot creators!Stats ✨v0.22.0Added$getJsonand$sendDMMade errors command specific (says which command and function)Made functions able to read both mentions and IDsCharmCordSetupsInstallCharmCordpipinstallCharmCordWarning: Package is still in beta, use at your own risk | feel free to report issuesSimple Bot:fromCharmCordimportCharmClient# ---------------Imports--------------------bot=CharmClient(prefix="!",case_insensitive=False,intents=("all",))bot.variables({"money":199})bot.on_ready(Code="$console[Bot is Ready]")bot.command(name="add-money",code="""$setUserVar[$args[1];money;$args[2]]$sendMessage[$channelID;Added $$args[2] to $userName[$args[1]]'s account]"""# !add-money 123456789 300# This would add money to the user variable then# send a confirmation message in the channel it# was invoked)bot.command(name="Ping",# Command Namecode="""$sendMessage[$channelID; Pong!! $ping]"""# Command Code)bot.run("*******<<TOKEN>>***********")Slash Interactions/Outside Commands/Activity:fromCharmCordimportCharmClient,setActivity# ---------------Imports--------------------# Activity message is the actual status, the type is whether it'll# be a game status, listening status, etcact=setActivity(message="my servers",typing="watching")# For Commands outside the main.py file, you should add the# load_command_dir parameter with the name of your command filebot=CharmClient(prefix="!",case_insensitive=False,intents=("all",),activity=act,load_command_dir="Commands")bot.on_ready(code="$console[Bot is Ready]")bot.slash_command(name="repeat",# Name of the slash commandargs=["sentence"],# The required argumentsdescription="Repeats what you say",# Description of commandcode="""$slashSend[$slashArgs[1]]"""# Code running on the command)bot.run("*******<<TOKEN>>***********")New and still a work in progressContributors ✨
Package: charmcraftcache
charmcraftcacheReinventing the wheelFast first-time builds forcharmcraft—on a local machine or CIInstallationInstallpipx:https://pipx.pypa.io/stable/installation/pipx install charmcraftcacheUsageccc add
ccc packFor best results, addcharm-strict-dependencies: trueto your charmcraft.yaml.How it worksWhy are charmcraft builds slow?Instead of downloading wheels from PyPI (which pip does by default), charmcraft builds Python package wheels from source (i.e. with pip install--no-binary).Caching mechanismcharmcraft builds each charm base in a separate LXC container[^1]. Within each container, pip has aninternal cachefor wheels built from source & for HTTP responses.charmcraft 2.5 moved the pip internal cache to the LXC host machine, so that one pip cache is used for all LXC containers. (This increases the chance of a cache hit—a faster build.)However, charmcraft builds are still slow the first time the wheel is built. This happens on CI runners, when you update dependencies, use a new machine/VM, or contribute to a new charm.charmcraftcachesolves the slow first build.charmcraftcache-hubmaintains alist of charms. For each charm, every Python dependency is built from source & uploaded to a GitHub release.ccc packdownloads these pre-built wheels to charmcraft's pip cache (and then runscharmcraft pack).Isn't this just a worse version of PyPI?Pretty much. The only difference is charmcraftcache-hub wheels are built from source on our runners, instead of built by the package maintainer.[^1]: Unless--destructive-modeis enabled
Package: charm-crypto
Charm is a framework for rapidly prototyping advanced cryptosystems. Based on the Python language, it was designed from the ground up to minimize development time and code complexity while promoting the reuse of components.Charm uses a hybrid design: performance intensive mathematical operations are implemented in native C modules, while cryptosystems themselves are written in a readable, high-level language. Charm additionally provides a number of new components to facilitate the rapid development of new schemes and protocols.Features of Charm include:Support for various mathematical settings, including integer rings/fields, bilinear and non-bilinear Elliptic Curve groups
Base crypto library, including symmetric encryption schemes, hash functions, PRNGs
Standard APIs for constructions such as digital signature, encryption, commitments
A “protocol engine” to simplify the process of implementing multi-party protocols
An integrated compiler for interactive and non-interactive ZK proofs
Integrated benchmarking capabilityPrior to install, you need GMP and PBC. See documentation:http://jhuisi.github.io/charm/install_source.html
Package: charmed-kubeflow-chisme
Charmed Kubeflow ChismeChisme: a Spanish word for gossip, or a story worth telling to your friends.This repository is for chisme within the Charmed Kubeflow team's codebase - it is a collection of helpers for use in
both the Charmed Operators maintained by theCharmed Kubeflowteam as well as anyone else who benefits from them.ContentsExceptions: A collection of standard Exceptions for use when writing charms.Kubernetes: Helpers for interacting with KubernetesLightkube: Helpers specific to using or extendingLightkubePebble: Helpers for managing pebble when writing charmsReusable Charm Components: TheComponentabstraction that encapsulates any piece of logic for a Charm, a reusable reconcile functionCharmReconcilerthat executesComponents, and a collection ofComponentsfor things like running Pebble containers or deploying Kubernetes resourcesRock: Utilities for testing ROCKsStatus Handling: Helpers for working with Charm Status objectsTesting: Utilities for testing CharmsTypes: Reusable typing definitions, useful for adding type hintsPublishing to PyPiTo publish a new release to Pypi:Updatesetup.cfgto the new version
and commit it to the repo via a completed PRApply local git tag according to the formatX.X.X(semantic versioning) on the main branchPush tag to the repo. Example:git push origin 0.0.8GitHub Action will create a new release on GitHubEdit release via GitHub UI and click publishGitHub Action will automatically publish the same commit to PyPi repository
Package: charmed-traceback
Charmed TracebackJetBrains style Tracebacks everywhere.Automatically apply traceback styling akin to Jetbrains Traceback highlighting, providing much easier debugging and log searching, as-well as feel more at home away from PyCharmInstallationThrough pip:pip install charmed-tracebackBuild with poetry:pip install Poetrypoetry buildUsageCharmed Traceback can be executed as a module:python -m charmed_traceback somefile.pyCharmed Traceback also works well within a script or even directly in the interpreter REPL. Standard usage will re-stylize the output, unless it's being redirected to a pipe:importcharmed_tracebackcharmed_traceback.add_hook()If want to retain the charmed style even when stderr is being piped, tack on an always=True argument:importcharmed_tracebackcharmed_traceback.add_hook(always=True)There are also a couple of convenience imports, which get the footprint down to one line:# Same as add_hook()importcharmed_traceback.auto# Same as add_hook(always=True)importcharmed_traceback.alwaysWhen implementing with a project that alternates between having access to development dependencies and not having those dependencies, it would be most convenient to provide a context manager to use this Charmed Tracebacks:importcontextlibdefdev_charm_traceback_handler()->None:withcontextlib.suppress(ImportError):importcharmed_traceback.auto# This call can be left in a project regaurdless of the presence of Charmed Traceback package.dev_charm_traceback_handler()
Package: charmer
|PyPI version| |Build Status|charmer===========A commandline interface for creating structured Python projects.Installation''''''''''''::pip install charmerUsage'''''::python -m charmerIf you trust ``charmer `` to make the right decisions, you can say 'yes' to all prompts:::python -m charmer  -yDetailed information''''''''''''''''''''Here is an example project structure created by this tool for a runnable project:::> proj_name__init__.py__main__.py> tests__init__.pycontext.pytest_main.pyREADME.rstsetup.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 ``-e`` flag is optional. It will keep your pip repository synchronized with your source code.Meta''''Ramon Hagenaars - ramon.hagenaars@gmail.comThis structure was inspired by `Kenneth Reitz <https://github.com/kennethreitz/samplemod>`_... |PyPI version| image:: https://badge.fury.io/py/project-cli.svg:target: https://badge.fury.io/py/project-cli.. |Build Status| image:: https://travis-ci.org/ramonhagenaars/project-cli.svg?branch=master:target: https://travis-ci.org/ramonhagenaars/project-cli
Package: charm-gems
charm-gemsThis repository contains the gems C++ code and python bindings used in Freesurfer's Sequence-Adaptive Multimodal SEGmentation (SAMSEG) (Puonti et al., NeuroImage, 2016) and in SimNIBS 4.0 Complete Head Anatomy Reconstruction Method (CHARM) (Puonti et al., NeuroImage, 2020) to create individualized head models for electric field simulations.InstallationThe compiled charm-gems library is available via pip ≥ 19.3, for python 3.6, 3.7 and 3.8pipinstall--upgradepip
pipinstallcharm-gemsAfterwards the package can be imported by callingimportcharm_gemsasgemsManual InstallationRequirementsA C++ compiler compatible with C++ 11Python ≥ 3.6CMakeMake (Linux/MacOS)Visual Studio (Windows)zlib (for windows, seehttps://github.com/horta/zlib.install)PreparationThis repository uses submodules. To start it, usegitsubmoduleinit
gitsubmoduleupdateLinux/MacOSBuild ITKmkdir ITK-build
cd ITK-build
cmake \
    -DBUILD_SHARED_LIBS=OFF \
    -DBUILD_TESTING=OFF \
    -DBUILD_EXAMPLES=OFF \
    -DCMAKE_BUILD_TYPE=Release \
    -DCMAKE_INSTALL_PREFIX=../ITK-install \
    ../ITK
make install
cd ..Install charm-gemsITK_DIR=ITK-install python setup.py installWindows (Tested on Visual Studio 2019)Build ITKmd ITK-build
cd ITK-build
cmake.exe ^
    -DBUILD_SHARED_LIBS=OFF ^
    -DBUILD_TESTING=OFF ^
    -DBUILD_EXAMPLES=OFF ^
    -DCMAKE_BUILD_TYPE=Release ^
    -DCMAKE_INSTALL_PREFIX=..\ITK-install ^
    ..\ITK
cmake --build . --config Release --target Install
cd ..Install charm-gemsset ITK_DIR=ITK-install
python setup.py install