Saravanan666/pypi-org huggingface dataset:
Package: circulation-import
circulation-importSet of tools facilitating the process of importing book collections into SimplyE's Circulation Manager by using SFTP protocol.Architecturecirculation-import consists of two parts:clientresponsible for uploading content to the SFTP server, waiting for a report, downloading it and converting it to CSV formatserverresponsible for watching for new book collections, importing them into CM using itsdirectory_importscript and uploading a report to the SFTP serverPicture below illustrates the architecture of the solution:Another picture below contains a sequence diagramUsageUpdate all the submodules:gitsubmoduleupdate--remote--recursivecdcirculation-lcp-test
gitsubmoduleupdate--remote--recursivecd..Run the LCP testbed:docker-compose--filecirculation-lcp-test/docker-compose.yml--env-filecirculation-lcp-test/.envup-dFollow the instructions in LCP testbed'sREADME.md fileto set it upRun the server:docker-compose--filecirculation-lcp-test/docker-compose.yml--filedocker-compose.yml--env-filecirculation-lcp-test/.envup-dCreate and activate a virtual environment:python-mvenv.venvsource.venv/bin/activateInstallcirculation-importfrom PyPi:pipinstallcirculation-importRun the client:python-mcirculation-importclientimport\--collection-name=lcp\--data-source-name=data_source_1\--books-directory=./circulation-lcp-test/lcp-collection/collection\--covers-directory=./circulation-lcp-test/lcp-collection/collection\--reports-directory=./reports\--metadata-file=./circulation-lcp-test/lcp-collection/collection/onix.xml\--metadata-format=onix\--configuration-file=./configuration/client-configuration.yml\--logging-configuration-file=./configuration/logging.ymlGo toreportsfolder and find a report in CSV format
Package: circum-hc-sr04
circum-hc-sr04HC-SR04 with Raspberry Pi sensor plugin forcircum.InstallRaspberry Pipip3installcircum-hc-sr04[rpi]Other Linux DistributionsNOTE: This configuration is not tested or supported beyond installation.First, install the libgpiod python bindings, this will vary by distribution. In Debian, Ubuntu, or derivatives usesudo apt install python3-libgpiod.pip3installcircum-hc-sr04[linux]UsageUsage:circum-endpointhc-sr04[OPTIONS]Options:--num-samplesINTEGERThenumberofsamplestoaverageperreading.--trigger-pinINTEGERThepinusedtotriggertheHC-SR04.[required]--echo-pinINTEGERThepintheHC-SR04willsignaltheechoon.[required]--speed-of-soundINTEGEROverridethespeedofsoundtoacalibratedvalueinm/s.--thresholdINTEGEROnlyregisteranobjectifitisatleastthresholdcmcloserthanthefurthestdistancereturnedsofar.Thisaccountsforunmovingobjectsinthesensorsrangeatthecostofmissingmovingobjectsthatarepresentwhenthesensorstarts.--helpShowthismessageandexit.To get more accurate readings, you can calibrate the sensor. Place an object a known distance from the sensor and pass the appropriate values to the calibration script. This will result in a value that can be passed to the endpoint sensor.Usage:calibrate-hc-sr04[OPTIONS]Options:--trigger-pinINTEGERThepinusedtotriggertheHC-SR04.[required]--echo-pinINTEGERThepintheHC-SR04willsignaltheechoon.[required]--samplesINTEGERThenumberofsamplestocalibratewith.--distanceINTEGERThedistancetothecalibrationobjectincm.[required]--helpShowthismessageandexit.
Package: circum-kinect
circum-kinectKinect sensor plugin forcircum.InstallKinect V2Install the PyKinect2 prerequisites described on thePyKinect2 GitHub, but do not install the package from pypi.pip3installcircum-kinect[pykinect2]Kinect V1WARNING: This version has not been tested without hardware. It has been installed and run to the point of creating the NUI runtime. Beyond that, all bets are off.WARNING: This is more complicated and brittle than installing the Kinect V2 options. If at all possible, we recommend updating to and using the Kinect V2.Install the WDK using the directionshereInstall any 1.x version of the Kinect for Windows SDK.Install theBuild Tools for Visual Studio, ensure that the ATL features are selected.pip3installcircum-kinect[pykinect]BothInstall all the prerequesites described above and use the following pip command:pip3installcircum-kinect[pykinect,pykinect2]UsageUsage:circum-endpointkinect[OPTIONS]Options:--version[1|2]PyKinectversiontouse.--helpShowthismessageandexit.
Package: circumplex
circumplexcircumplexis a Python package for analyzing and visualizing circumplex data. It provides a set of tools for analyzing and visualizing circumplex data, following the Structural Summary Method. This project is a Python implementation based on the Rcircumplexpackage. Our goal is to provide a similar functionality and experience for Python users.[!WARNING]
This project is still under development. We're working hard to make it as good as possible, but there may be bugs or missing features. If you find any issues, please let us know by submitting an issue on Github.Getting StartedTo get started withcircumplex, you'll need to install it first. You can do this by running the following command:pipinstallcircumplexDocumentationThis documentation is designed to help you understand and usecircumplexeffectively. It's divided into several sections:Tutorials: Practical examples showing how to use our project in real-world scenarios.API Reference: Detailed information about our project's API.Contribute: Information on how you can contribute to our project.ContributingWe welcome contributions from the community. If you're interested in contributing, please get in touch or submit an issue on Github.LicenseThis project is licensed under the GNU GPLv3 License. For more information, please see thelicense.mdfile.Project layoutmkdocs.yml     # The configuration file.
docs/
    index.md   # The documentation homepage.
    about.md   # The about page.
    license.md # The license page.
    tutorials/ # Tutorial pages.
        Introduction to SSM Analysis.ipynb  
    ...        # Other markdown pages, images and other files.
src/circumplex/
    circumplex.py
Package: circus-logstash
# Circus-LogstashA logger to be used in Circus that ships logs via a Redis queue to Logstash. If there is interest in other brokers they should be able to be added to this project# Installation```pip install circus-logstash```# UsageIn your Circus config add the stream class and some info```stdout_stream.class = circus_logstash.circus_logstash.LogstashRedisLoggerstdout_stream.refresh_time = 0.3stdout_stream.urls = redis://localhost:6379/0stdout_stream.service = service_namestdout_stream.redis_namespace = logstash:app:productionstdout_stream.subclass = FileStreamstdout_stream.subclass_filename = '/var/log/...'stdout_stream.field_extra_field = 'field_value'````urls` is a comma separated list of Redis urls to connect to. These are done in round robin if there are any failures connection/writing.`service` Used throughout for namespacing the log lines`redis_namespace` The list to write logs to`subclass` A class to use as well (like writing files still)Any options prefixed with `subclass_` will be passed to the init of the subclassAny options prefixed with `field_` can be used to include extra field:value pairs in the Logstash events. This is useful to include extra metadata about this process.
Package: circus-mattbanderson
Circus is a program that runs and watches processes and sockets.
Circus can be used as a library or through the command line.Links:Full Documentation :https://circus.readthedocs.ioHow to Contribute :https://circus.readthedocs.io/en/latest/contributing/Mailing List :https://groups.yahoo.com/neo/groups/circus-dev/infoRepository & Issue Tracker :https://github.com/circus-tent/circusIRC : Freenode, channel #mozilla-circus
Package: ciresbot
Telegram BotSend data through the telegram bot API. Currently, supports sending messages
and photos.InstallationInstall with pippip install ciresbotUsagePython ModuleCreating a bot requires only its token. To send messages or photos it needs
to know the chat id of the recipient(s) (see below how to obtain the chat ids).fromtelegrambotimportTelegramBotbot=TelegramBot("MyBotToken")bot.send_message("Hello World",chat_id="12345")bot.send_photo("./dog.jpg",caption="Cute dog",chat_id="12345")Ideally, the token bot should not be hardcoded, the module also comes with some utilities
to read your tokens from a file. It expects a csv file with the following format:# tokens.csv
botName,token
MyBot,MyBotToken12345Also, you can read your chats from a csv file:chatName,chatId,bot
MyChat,12345,MyBotIf you have a file with the above specifications you can use the utility functions
as in the following example:fromtelegrambotimportTelegramBotfromtelegrambot.utilsimportread_token_file,get_chat_idtoken=read_token_file("./tokens.csv","MyBot")ifnottoken:raiseValueError("Token not found")chat_id=get_chat_id("MyChat","./chats.csv")ifnotchat_id:raiseValueError("Chat id not found")bot=TelegramBot(token)success,status_code,message=bot.send_message("Hello",chat_id)ifsuccess:print(f"Message sent successfully:{message}")else:print(f"Failed to send message{status_code}")Command Line ToolThe command line tool supports the following modes:message: Send a text message through Telegram using a bot.photo: Send a photo through Telegram using a bot.updates: Get the latest updates of the bot from Telegram.OptionsCommon options that can be used with all modes:--bot, -b: Name or token of the bot that will be used (required).--token, -t: Whether a token was passed. If not, it is assumed that the bot name was passed.--bot-file, -f: Name of the CSV file containing the token(s) of the bot(s). Required if the bot name was passed.--chat, -c: Name or ID of the chat where the info will be sent (required).--id, -i: Whether a chat ID was passed. If not, it is assumed that the chat name was passed.--chat-file, -cf: Name of the CSV file containing the ID(s) of the chat(s). Required if the bot name was passed.Specific options for each mode:Message Mode--message, -m: Text of the message (required).Photo Mode--photo, -p: Path to the photo file (required).--caption, -cp: A caption for the photo (optional).ExamplesSending a message using a bot:telegrambotmessage--botMyBot--message"Hello, World!"--chatMyChat--bot-file./bot.csv--chat-file./chat.csvSending a photo using a bot:telegrambotphoto--botMyBot--photo./photo.jpg--caption"A picture"--chatMyChat--bot-file./bot.csv--chat-file./chat.csvGetting updates of a bottelegrambotupdates--botMyBot--bot-file./bot.csvObtaining chat idsTo obtain the chat id, first add the bot to a new chat or an existing one. Then send a message to the
chat. Wait a few seconds and after that get the updates of the bot, you can use the CLI. In the updates
the chat id will appear.LicenseCreated by Daniel Ibarrola. It is licensed under the terms of the MIT license.
Package: ciri
Ciri helps you build schema definitions for your application; giving you a foundation to perform validation, serialization and encoding.FeaturesPython 3/2 supportSerialize data to basic Python typesDeserialize data back to schema objectsSchema encodingPolymorphic schemasComposable FieldsControllable error handlingPre/post processors available on fieldsSimple APIInstall$ pip install ciriDocumentationDocumentation can be found athttp://ciri.hellouser.net/.Exampleimportdatetimefromciriimportfields,Schema,ValidationErrorclassActor(Schema):first_name=fields.String()last_name=fields.String()classMovie(Schema):title=fields.String()released=fields.Date()cast=fields.List(Actor())movie=Movie()output=movie.serialize({'title':'Good Will Hunting','released':datetime.date(1998,1,9),'cast':[{'first_name':'Matt','last_name':'Damon'},{'first_name':'Ben','last_name':'Affleck'},{'first_name':'Robin','last_name':'Williams'}]})# output:# {'cast': [{'last_name': 'Damon', 'first_name': 'Matt'},#           {'last_name': 'Affleck', 'first_name': 'Ben'},#           {'last_name': 'Williams', 'first_name': 'Robin'}],#  'released': '1998-01-09',#  'title': 'Good Will Hunting'}
Package: cirillo
CirilloCirillo is a simple command-line application that helps you stay focused and productive by using
the Pomodoro technique. With cirillo, you can easily set work and break times, and the application
will notify you when it's time to take a break.InstallationYou can install the application by cloning the repository and running the following
commands in your terminal:pipinstallcirilloUsageTo use Cirillo, open your terminal and type the following command:cirilloThis will start the Pomodoro timer with default settings of 25 minutes of work time and 5 minutes of
break time. If you want to set custom times, you can use the --work and --rest options, like this:cirillo--work30--rest10This will set the work time to 30 minutes and the break time to 10 minutes.You can also enable desktop notifications by using the --notify option:cirillo--notifyThis will enable desktop notifications for the Pomodoro timer. Note that this option is only
available on Mac and Linux systems that support notifications.Once you start the timer, Cirillo will display a progress bar in the terminal, and notify you when
it's time to take a break. When the break is over, Cirillo will automatically start another work
session.
Package: cirkel
# CIRKEL<img src=”https://raw.githubusercontent.com/zmic/cirkel/master/examples/test_0.jpg” width=400px height=400px>## How to install itOn Windows:pip install cirkelORclone this repository, build the binary with Visual Studio 2017/2019 and run setup.py## How to  use itSee example.py## Disclaimer
Disclaimer: I wrote this code in a hurry during a two week period in 2014, for quick experimentation. It was never refactored or cleaned up as it should be. It works, and it’s not inscrutable, but does NOT meet my professional standards for deliverable source code.
Package: cirkit
# CirKit (Python interface)CirKit is a synthesis and optimization frameworks for classical logic networks.
It is implemented based on various
[EPFL logic sythesis libraries](https://github.com/lsils/lstools-showcase).## Example`python import cirkit cirkit.read_aiger(aig=True,filename="file.aig")cirkit.ps(aig=True) cirkit.cut_rewrite(aig=True) cirkit.lut_mapping(aig=True) cirkit.collapse_mapped(aig=True) cirkit.ps(lut=True) cirkit.write_bench(lut=True,filename="file.bench")`## EPFL logic sythesis librariesCirKit and Revkit are based on the [EPFL logic synthesis](https://lsi.epfl.ch/page-138455-en.html) libraries.  The libraries and several examples on how to use and integrate the libraries can be found in the [logic synthesis tool showcase](https://github.com/lsils/lstools-showcase).
Package: cir-model
IntroductionThecir-modellibrary implements theCentered Isotonic Regression(CIR) model.[1] CIR is a variant ofIsotonic Regression(IR), which is a nonparametric regression model which only assumes that the data generating function is monotonically increasing or decreasing. The function can take any monotonic form that minimizes the sum of squared errors.scikit-learnhas implemented Isotonic Regression asIsotonicRegression.[2]In some scenarios, the assumption of monotonicity is too weak. IR can result in a function that has constant, non-decreasing intervals. In some applications, like dose-response curve fitting or in cumululative distribution function estimation, it can be safe to make the additional assumption ofstrict monotonicity: at any point the function should be increasing, not just non-decreasing (or vice versa: decreasing, not just non-increasing). This additional requirement results in a function with the desirable property that the inverse function is a unique mapping, because there are no longer ranges of constant intervals.Centered Isotonic Regression(CIR) is similar to IR, but with the additional assumption of strict monotonicity. The algorithm is described in detail in [1]. The plot below shows a comparison of IR (in blue) and CIR (in red) fitted to the same datapoints (in green).This Python library,cir-model, implementsCenteredIsotonicRegressionin line with the algorithm in [1].cir-modeluses theIsotonicRegressionimplementation ofscikit-learn. Therefore,CenteredIsotonicRegressiontakes the same parameters asIsotonicRegressionand is completely compatible withscikit-learn. You can use it for example inscikit-learnpipelines.You can installcir-modelusingpip:pip install -U cir-modelExamplesTo fit a CIR model:>>>fromcir_modelimportCenteredIsotonicRegression>>>x=[1,2,3,4]>>>y=[1,37,42,5]>>>model=CenteredIsotonicRegression().fit(x,y)>>>model.transform(x)array([1.,14.5,28.,28.])Finding the inverse of the CIR model above, for example for the valuexfor whichy=25:>>>fromscipyimportoptimize>>>optimize.newton(lambdax:model.transform([x])-25,2)array([2.77777778])ReferencesCentered Isotonic Regression: Point and Interval Estimation for Dose-Response Studies, Assaf P. Oron & Nancy Flournoy, Statistics in Biopharmaceutical Research, Volume 9, Issue 3, 258-267, 2017Scikit-learn: Machine Learning in Python, Fabian Pedregosa et al., JMLR 12, 2825-2830, 2011
Package: cirq
Cirq is a Python library for writing, manipulating, and optimizing quantum
circuits and running them against quantum computers and simulators.Installation and DocumentationCirq documentation is available atquantumai.google/cirq.Documentation for the latestpre-releaseversion of cirq (tracks the repository’s main branch; what you get if youpip install--precirq), is availablehere.Documentation for the lateststableversion of cirq (what you get if youpip install cirq) is availablehere.InstallationDocumentationTutorialsFor a comprehensive list all of the interactive Jupyter Notebooks in our repo (including the ones not yet published to the site) open our repo inColab.For the latest news regarding Cirq, sign up to theCirq-announce email list!Hello QubitA simple example to get you up and running:importcirq# Pick a qubit.qubit=cirq.GridQubit(0,0)# Create a circuitcircuit=cirq.Circuit(cirq.X(qubit)**0.5,# Square root of NOT.cirq.measure(qubit,key='m')# Measurement.)print("Circuit:")print(circuit)# Simulate the circuit several times.simulator=cirq.Simulator()result=simulator.run(circuit,repetitions=20)print("Results:")print(result)Example output:Circuit:
(0, 0): ───X^0.5───M('m')───
Results:
m=11000111111011001000Feature requests / Bugs / QuestionsIf you have feature requests or you found a bug, pleasefile them on Github.For questions about how to use Cirq post toQuantum Computing Stack Exchangewith thecirqtag.How to cite CirqCirq is uploaded to Zenodo automatically. Click on the badge below to see all the citation formats for all versions.Cirq Contributors CommunityWe welcome contributions! Before opening your first PR, a good place to start is to read ourguidelines.We are dedicated to cultivating an open and inclusive community to build software for near term quantum computers.
Please read ourcode of conductfor the rules of engagement within our community.For real time informal discussions about Cirq, join ourcirqdevGitter channel, come hangout with us!Cirq Cynqueis our weekly meeting for contributors to discuss upcoming features, designs, issues, community and status of different efforts.
To get an invitation please join thecirq-dev email listwhich also serves as yet another platform to discuss contributions and design ideas.See AlsoFor those interested in using quantum computers to solve problems in
chemistry and materials science, we encourage exploringOpenFermionand
its sister library for compiling quantum simulation algorithms in Cirq,OpenFermion-Cirq.For machine learning enthusiasts,Tensorflow Quantumis a great project to check out!For a powerful quantum circuit simulator that integrates well with Cirq, we recommend looking atqsim.Finally,ReCirqcontains real world experiments using Cirq.Cirq is not an official Google product. Copyright 2019 The Cirq Developers
Package: cirq-aqt
Cirqis a Python library for writing, manipulating, and optimizing quantum
circuits and running them against quantum computers and simulators.This module iscirq-aqt, which provides everything you’ll need to run Cirq quantum algorithms on AQT quantum computers.DocumentationTo get started with the Alpine Quantum Technologies, checkout the following guide and tutorial:Access and authenticationGetting started guideInstallationTo install the stable version of onlycirq-aqt, usepip install cirq-aqt.
To install the pre-release version of onlycirq-aqt, usepip install cirq-aqt –pre.Note, that this will install both cirq-aqt and cirq-core as well.To get all the optional modules installed as well, you’ll have to usepip install cirqorpip install cirq –prefor the pre-release version.
Package: cirq-core
Cirq is a Python library for writing, manipulating, and optimizing quantum
circuits and running them against quantum computers and simulators.This module iscirq-core, which contains everything you’d need to write quantum algorithms for NISQ devices and run them on the built-in Cirq simulators.
In order to run algorithms on a given quantum hardware platform, you’ll have to install the right cirq module as well.InstallationTo install the stable version of onlycirq-core, usepip install cirq-core.
To install the pre-release version of onlycirq-core, usepip install cirq-core –pre.To get all the optional modules installed as well, you’ll have to usepip install cirqorpip install cirq –prefor the pre-release version.
Package: cirq-dev
This is a development version of Cirq and may be unstable.For the latest stable release of Cirq seehere.Cirq is a Python library for writing, manipulating, and optimizing quantum
circuits and running them against quantum computers and simulators.InstallationFollow theseinstructions.Hello QubitA simple example to get you up and running:importcirq# Pick a qubit.qubit=cirq.GridQubit(0,0)# Create a circuitcircuit=cirq.Circuit(cirq.X(qubit)**0.5,# Square root of NOT.cirq.measure(qubit,key='m')# Measurement.)print("Circuit:")print(circuit)# Simulate the circuit several times.simulator=cirq.Simulator()result=simulator.run(circuit,repetitions=20)print("Results:")print(result)Example output:Circuit:(0,0):───X^0.5───M('m')───Results:m=11000111111011001000DocumentationSeehereor jump into thetutorial.ContributingWe welcome contributions. Please follow theseguidelines.We useGithub issuesfor tracking requests and bugs. Please post questions to theQuantum Computing Stack Exchangewith thecirqtag.
For informal discussions about Cirq, join ourcirqdevGitter channel.See AlsoFor those interested in using quantum computers to solve problems in
chemistry and materials science, we encourage exploringOpenFermionand
its sister library for compiling quantum simulation algorithms in Cirq,OpenFermion-Cirq.Alpha DisclaimerCirq is currently in alpha.We are still making breaking changes.
Wewillbreak your code when we make new releases.
We recommend that you target a specific version of Cirq, and periodically bump to the latest release.
That way you have control over when a breaking change affects you.Cirq is not an official Google product. Copyright 2018 The Cirq Developers
Package: cirq-ft
Cirq-FT: Cirq for Fault-Tolerant algorithmsCirq-FT is a Python library for rapid prototyping and resource estimation of fault tolerant
algorithms that extends the quantum computing SDKCirq.InstallationCirq-FT is currently in beta mode and only available as a pre-release.
To install the pre-release version ofcirq-ft, usepipinstallcirq-ft--preNote, that this will install both cirq-ft and cirq-core as well.To get all the optionalCirqmodules installed as well, usepip install cirqorpip install cirq –prefor the pre-release version.