Saravanan666/pypi-org huggingface dataset:
Package: caen-felib
caen_felibThe official Python wrapper for the CAEN FELib.InstallYou need to install both the latest version of CAEN FELib and an implementation like the CAEN Dig2 fromthe CAEN website.Then, install this module and have fun.ExamplesFew examples may be found on the official documentation and in the function docstrings.This example show the simplest way to perform a data acquisition with the scope firmware:importnumpyasnpfrommatplotlibimportpyplotaspltfromcaen_felibimportdevice,errorwithdevice.connect('dig2://<host>')asdig:# Resetdig.cmd.Reset()# Read-only parametersnch=int(dig.par.NumCh.value)adc_nbit=int(dig.par.ADC_NBit.value)# Configuration parametersreclen=4096dc_offset=50pre_trigger=128# Set some digitizer parametersdig.par.AcqTriggerSource.value='SwTrg'dig.par.RecordLengthS.value=f'{reclen}'dig.par.PreTriggerS.value=f'{pre_trigger}'# Set some channel parametersforchindig.ch:ch.par.DCOffset.value=f'{dc_offset}'# Set enabled endpoint to activate decodedig.endpoint.par.ActiveEndpoint.value='scope'# Configure endpointdata_format=[{'name':'TIMESTAMP','type':'U64',},{'name':'WAVEFORM','type':'U16','dim':2,'shape':[nch,reclen],},{'name':'WAVEFORM_SIZE','type':'U64','dim':1,'shape':[nch],},]# Store endpoint nodeep_scope=dig.endpoint.scope# set_read_data_format returns allocated buffersdata=ep_scope.set_read_data_format(data_format)timestamp=data[0].valuewaveform=data[1].valuewaveform_size=data[2].value# Configure plotplt.ion()figure,ax=plt.subplots(figsize=(10,8))lines=[]foriinrange(nch):line,=ax.plot([],[])lines.append(line)ax.set_xlim(0,reclen-1)ax.set_ylim(0,2**adc_nbit-1)# Start acquisitiondig.cmd.ArmAcquisition()dig.cmd.SwStartAcquisition()# Acquisition loopwhileTrue:# Send triggerdig.cmd.SendSwTrigger()# Wait for eventtry:dig.endpoint.scope.read_data(100,data)excepterror.Errorasex:ifex.code==error.ErrorCode.TIMEOUT:# Timeout expired, waiting againgcontinueelifex.code==error.ErrorCode.STOP:# End of run, exit the loopprint('End of run.')breakelse:# Other critical error, propagate itraiseexforiinrange(nch):lines[i].set_data(np.arange(0,waveform_size[i]),waveform[i])ax.title.set_text(f'Timestamp:{timestamp}')figure.canvas.draw()figure.canvas.flush_events()# Stop acquisitiondig.cmd.DisarmAcquisition()DocumentationPython API is described on the CAEN FELib library documentation, starting from CAEN FELib v1.2.3.ReferencesRequirements and documentation can be found athttps://www.caen.it/products/caen-felib-library/.
Package: caenhv
caenhv🤔 What is this?This is an unofficial Python package to interface with CAEN high voltage power supplies over USB (RS232 protocol).⚠️ DisclaimerThe features of this package are based on my needs at the time of writing.
I have done very limited testing on a single model (DT1471ET) but it should also work for other CAEN power supplies also
supporting RS232.If you use this package, it is very possible you find a bug or some oversight.
You are encouraged to make apull requestor to create
anissueto report a bug, to request additional features or to suggest
improvements.⚙️ InstallationInstallation viapipis supported.
To install the latestpublished version, run:pipinstallcaenhvTo install the package from source, including test dependencies, clone the repository and run:pipinstall.[test]👨‍💻 UsagefromcaenhvimportCaenHV# automatically detect serial port and baudrate (can be manually set)caen=CaenHV()# get the first module. CAEN supports multiple modules over the same connection# typically only one module should be presentmodule=caen[0]# get channel number 2channel=module.channel(2)# print current 'vset' and 'vmon' valuesprint(f"vset:{channel.vset}")print(f"vmon:{channel.vmon}")# switch channel off and offchannel.off()channel.on()# set a new value of 'vset'channel.vset=300.0# 300 V
Package: caeops
"CloudAEyeis an intelligent cloud service, providing SaaS-based operations management. The AI-powered workflow provides observability services with logs, metrics and notifications. It focuses on contextual awareness and automatically surfaces anomalous services. CloudAEye offers frictionless management of an incident and root-cause analysis to reduceMTTD (mean time to detect)andMTTR (mean time to repair). CloudAEye SaaS provides comprehensiveCommand Line Interface (CLI)for end-to-end management of all services. It provides syntax, CLI options, and usage examples for each CLI operation. Read more about caeopshere"
Package: caer
Caer - Modern Computer Vision on the FlyCaer is alightweight, high-performanceVision library for high-performance AI research. We wrote this framework to simplify your approach towards Computer Vision by abstracting away unnecessary boilerplate code giving you theflexibilityto quickly prototype deep learning models and research ideas. The end result is a library quite different in its design, that’s easy to understand, plays well with others, and is a lot of fun to use.Our elegant,type-checkedAPI and design philosophy makes Caer ideal for students, researchers, hobbyists and even experts in the fields of Deep Learning and Computer Vision.OverviewCaer is a Python library that consists of the following components:ComponentDescriptioncaerA lightweight GPU-accelerated Computer Vision library for high-performance AI researchcaer.colorColorspace operationscaer.dataStandard high-quality test images and example datacaer.pathOS-specific path manipulationscaer.preprocessingImage preprocessing utilities.caer.transformsPowerful image transformations and augmentationscaer.videoVideo processing utilitiesUsually, Caer is used either as:a replacement for OpenCV to use the power of GPUs.a Computer Vision research platform that provides maximum flexibility and speed.InstallationSee the CaerInstallationguide for detailed installation instructions (including building from source).Currently,caersupports releases of Python 3.6 onwards; Python 2 is not supported (nor recommended).
To install the current release:$pipinstall--upgradecaerGetting StartedMinimal Exampleimportcaer# Load a standard 640x427 test image that ships out-of-the-box with caersunrise=caer.data.sunrise(rgb=True)# Resize the image to 400x400 while MAINTAINING aspect ratioresized=caer.resize(sunrise,target_size=(400,400),preserve_aspect_ratio=True)For more examples, see theCaer demosorRead the documentationResourcesPyPiDocumentationIssue trackingContributingWe appreciate all contributions, feedback and issues. If you plan to contribute new features, utility functions, or extensions to the core, please go through ourContribution Guidelines.To contribute, start working through thecaercodebase, read theDocumentation, navigate to theIssuestab and start looking through interesting issues.Current contributors can be viewed either from theContributorsfile or by using thecaer.__contributors__command.Asking for helpIf you have any questions, please:Read the docs.Look it up in our Github Discussions (or add a new question).Search through the issues.LicenseCaer is open-source and released under theMIT License.BibTeXIf you want to cite the framework feel free to use this (but only if you loved it 😊):@article{jasmcaus,title={Caer},author={Dsouza, Jason},journal={GitHub. Note: https://github.com/jasmcaus/caer},volume={2},year={2020-2021}}
Package: caeroc
A python package for compressible flows. A dynamic toolkit which enables
you to make use of the formulae governing compressible flows.RequirementsPython 2.7, >=3.4pylab (numpy, scipy and matplotlib)ashwinvis/scikit-aero >= 0.2PyQt5 / PySide (optional, but recommended for GUI)pandas (optional: for making tables)colorlog (optional: for coloured log)InstallationTo install from PyPI:pipinstall-egit+https://github.com/ashwinvis/scikit-aero.git#egg=scikit-aero# Any of the followingpipinstallcaerocpipinstallcaeroc[pyqt]pipinstallcaeroc[pyside]To install development versions ofcaerocandscikit-aeropipinstall-egit+https://github.com/ashwinvis/caeroc.git#egg=caeroc--process-dependency-links--trusted-hostgithub.comIf the current configuration of the GUI does not work for you,
regenerate it by running:cdcaeroc/gui./configureLaunchSimply run in your terminalcaeroc-appDevelopmentDevelopment mode will installcaerocusing soft links.gitclone--recursivehttps://github.com/ashwinvis/caeroc.gitcdcaerocpythonsetup.pydevelopcd../scikit-aeropythonsetup.pydevelopFeatures[x] Command-line tool which opens a Qt based GUI calculatorIn development[ ] Save data as a database[ ] Plotting graphs[ ] Generate gas tables[ ] Calculate flow characteristics: Coefficient of pressure, lift and
drag for basic profiles.CourtesyThe idea for a compressible aerodynamics calculator in the form an
online JS tool had been implemented byWilliam
Devenporthere.
This project is pushing more functionalities as an offline tool and
allowing users to dynamically use the formulae for specific cases.Thanks to the scikit-aero team for being the backend
Package: caerp-oidc-client
Pyramid Oidc client library for caerppythonsetup.pyinstallAdd a client in your OpenId Authentication (e.g: Keycloak)To configure your open id connect client in a SSO server like Keycloak.Host :https://caerp.mycae.coopImportantCreate a custom realm (don't use the master realm, you'll face serious security problems : all users would have admin rights on Keycloak)Add a clientClientID : caerp_client_idName : Free choiceRoot URL :https://caerp.mycae.coopHome URL :https://caerp.mycae.coopValid Redirect URIs :https://caerp.mycae.coop/*Valid post logout redirect URIs :https://caerp.mycae.coop/loginWeb Origins :https://caerp.mycae.coopAdmin URL : NothingClient Authentication : TrueAuthentication Flow : Check the followingStandard FlowImplicit flowDirect access grantsDisable Consent requiredBackchannel logout url :https://caerp.mycae.coop/oidc_backend_logoutBackchannel logout session required: TrueRetrieve the client secretIn the "Credentials" section of the keycloak client view, retrieve the client's secret (you need it to configure caerp)Configure your client : caerpIn your caerp application's ini filepyramid.includes = ...
                   caerp_oidc_client.modelsLater in the same ini fileendi.authentification_module=caerp_oidc_client

oidc.client_secret=<Secret token from the OIDC server>
oidc.client_id=caerp_client_id
oidc.scope=openid roles
oidc.auth_endpoint_url=<Keycloak auth endpoint url>
oidc.token_endpoint_url=<Keycloak id token endpoint url>
oidc.logout_endpoint_url=<Keycloak logout endpoint url>Keycloak's url are in the formhttps://keycloak/realms/**mycustom realm name**/protocol/openid-connect/authhttps://keycloak/realms/**mycustom realm name**/protocol/openid-connect/tokenhttps://keycloak/realms/**mycustom realm name**/protocol/openid-connect/logout
Package: caerus
caeruscaerusis Python package to compute the local-minima with the corresponding local-maxima within the given time-frame. This approach is designed to for stock-market valley and peak detection.Here are just a few of the things that caerus does well:
- Ouput contains detected start-stop regions of local minima and maxima.
- Figures are created.
- Parameter gridsearch.
- Designed for the detection of complex trend movements.⭐️ Star this repo if you like it ⭐️Install caerus from PyPIpipinstallcaerusImport caerus packagefromcaerusimportcaerusDocumentation pagesOn thedocumentation pagesyou can find detailed information about the working of thecaeruswith examples.ExamplesExample: Detect peak and valleys in BitcoinExample: Detect peak and valleys in FacebookExample: GridsearchSupportThis project needs some love! ❤️Contribute to this project by feature requests, idea discussions, reporting bugs, opening pull requests, or through Github Sponsors. Your help is highly appreciated.If you wish to buy me aCoffeefor this work, it is very appreciated :)MaintainersErdogan Taskesen, github:erdogant
Package: caesar
CaesarA command line e-mail helperUsageSave email id and password in a configuration file. Henceforth, password
for email id will be extracted from file itself. Don’t worry about
password readibility in configuration file, it’s encoded.$:caesar-scabc@gmail.comEnterpassword:Save server settings, IP and port number to send mail using the mailing
client. The first value given eg: ‘ymail’ in following sample will be
used henceforth for referring the server’s settings.$:caesar-ssymailsmtp.mail.yahoo.com587To further use this server settings for mailing,$:caesar-cymailThis will allow sending mail using a yahoo email idWith caesar sending a single line mail is as easy as blinking an eye.$:caesar-m'Your message here'Enterrecipientsaddress:abc@yahoo.comGiveasubject:SubjecthereEnterlogindetailsEmail:abc@gmail.comMailsentAdd all files to be attached in one go!$:caesar-ffile1.txtfile2.pyEnterrecipientsaddress:abc@yahoo.comGiveasubject:AttachingfilesEnterlogindetailsEmail:abc@gmail.comMailsentType your message in editor along with attachments$:caesar-fIMG.jpg-e-m'hey'Enterrecipientsaddress:abc@yahoo.com###Message opens up in vim here###Giveasubject:hiEnterlogindetailsEmail:abc@gmail.comMailsentThis is not it, you can mix and match options according to your need.
Send message along with attachments or open an editor for typing
message.$:caesar-m'Your message here'-ffile1file2OR$:caesar-m'Your message here'-ffile1file2-eEnjoy e-mailing!!!
Package: caesarcipher
A Python package and command line script for encoding, decoding and cracking
messages with theCaesar Shift Cipher.Table of ContentsFeaturesInstallationUsageDevelopmentMetaFeaturesEncodingDecodingCracking (decoding ciphertext without known offset)Arbitrary cipher offsetsCommand Line InterfaceTest suiteSupport for both Python 2 and 3PEP8.  Praise the Dark LordInstallationThe latest version can be installed viapip.$pipinstallcaesarcipherIf that doesn’t work, giveeasy_installa try:$easy_installcaesarcipherUsageCommand LineEncoding a message:$caesarcipher--encode"This is a message I want to encode."Encoding a message with a specific offset:$caesarcipher--offset14--encode"This is a message I want to encode."Decoding a ciphertext with a specific offset:$caesarcipher--offset14--decode"W kobh hc sbqcrs hvwg ghfwbu."Cracking a ciphertext without knowing the offset:$caesarcipher--crack"W kobh hc sbqcrs hvwg ghfwbu."LibraryEncoding a message:>>>fromcaesarcipherimportCaesarCipher>>>cipher=CaesarCipher('I want to encode this string')>>>cipher.encoded'W kobh hc sbqcrs hvwg ghfwbu.'Encoding a message with a specific offset:>>>fromcaesarcipherimportCaesarCipher>>>cipher=CaesarCipher('I want to encode this string.',...offset=14)>>>cipher.encoded'W kobh hc sbqcrs hvwg ghfwbu.'Decoding a ciphertext with a specific offset:>>>fromcaesarcipherimportCaesarCipher>>>cipher=CaesarCipher('W kobh hc sbqcrs hvwg ghfwbu.',...offset=14)>>>cipher.decoded'I want to encode this string.'Cracking a ciphertext without knowing the offset:>>>fromcaesarcipherimportCaesarCipher>>>cipher=CaesarCipher('W kobh hc sbqcrs hvwg ghfwbu.')>>>cipher.cracked'I want to encode this string.'DevelopmentHackingTo hack on the project, clone theGitHub repo:$gitclonehttps://github.com/RobSpectre/Caesar-Cipher.gitThen install in avirtualenv.$pipinstall-e./TestsThe project usesNosefor tests.  Simply run from the project root.$nosetests-vGo ahead and check on coverage and PEP8 while you’re at it!$nosetests-v--with-coverage--with-tissueMetaWritten byRob SpectreUsed for Hacker Olympics London 2014Released underMIT LicenseSoftware is as is - no warranty expressed or implied.TheCaesar Shift Cipheris known to be ridiculously easy to crack, as evidenced
by this very package.  Do not confuse with actual cryptography or use in
anything that is important - it’s just a fun math problem for a sunny vacation
afternoon.
Package: caesar-cipher-test
CAESAR CIPHERCaesar cipher is a Python library for dealing with encode and decode.Algorithm of Caesar CipherThe algorithm of Caesar cipher holds the following features −1.Caesar Cipher Technique is the simple and easy method of encryption technique.2.It is simple type of substitution cipher.3.Each letter of plain text is replaced by a letter with some fixed number of positions down with alphabet.The following diagram depicts the working of Caesar cipher algorithm implementationUse the package managerpipto install foobar.pipinstallcaesar_ciphercomingsoonUsageimportcaesar_ciphercomingsoon# encodedcaesar.encode.('hello')# returns 'mjqqt'# decodedcaesar.decode('mjqqt')#returns 'hello'ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: caesar-deco
==============CAESAR DECODER==============.. image:: https://img.shields.io/pypi/v/caesar_deco.svg:target: https://pypi.python.org/pypi/caesar_deco.. image:: https://img.shields.io/travis/alejogaci/caesar_deco.svg:target: https://travis-ci.org/alejogaci/caesar_deco.. image:: https://readthedocs.org/projects/caesar-deco/badge/?version=latest:target: https://caesar-deco.readthedocs.io/en/latest/?badge=latest:alt: Documentation StatusCaesar decoder Utility* Free software: MIT license* Documentation: https://caesar-deco.readthedocs.io.Features--------* TODOSpecial Information-------Caesar is a type of encryption widely used in cryptography due to its "simplicity". It consists of replacing each letter of the message that is wanted to be encrypted by another one that is a fixed number of positions later in the alphabet. For example, with a displacement of 5 the letter A would be the F and the letter B would be the GWith this package you can decrypt any message encrypted in caesar without needing to know the displacementCredits-------This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template... _Cookiecutter: https://github.com/audreyr/cookiecutter.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage=======History=======0.1.0 (2018-03-11)------------------* First release on PyPI.
Package: caesarplus
CaesarPlusAn advanced caesar cypher python moduleWhat is CaesarPlusCaesarPlus is a advanced caesar cypher python module that is more secure than caesar cypherIt makes a unique encryption every time you encode a pieceInstallationpip install caesarplusRequirementsPython 3.8 and above.How To UseExample#To importimportcaesarplusascp#To encode datacp.encode("Example")([4,4,1,7,5,0,6],'I|btulk')#To decode datacp.decode([4,4,1,7,5,0,6],'I|btulk')'Example'EncodeTheencode()function encodes data in the CaesarPlus encryption methodExamplecaesarplus.encode("Example")([4,4,1,7,5,0,6],'I|btulk')Each encryption is uniqueTheencode()function will outputkey,dataWarning:You can only decode the data with the key CaesarPlus makesDecodeThedecode()function decodes data in the CaesarPlus encryption methodExamplecp.decode([4,4,1,7,5,0,6],'I|btulk')'Example'To decode it must bekeybeforedataand thekeymust be an array/list.Thedecode()function will outputdata/the decoded text.Warning:You must use the correct key to decode the encrypted text.How it works
Package: caex2
Sven van der Burg
Dafne van Kuppevelt
Author-email:s.vanderburg@esciencecenter.nlKeywords: Extract,Exercises
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Carpentries Instructors
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown
Provides-Extra: publishing
License-File: LICENSE# CaEx2 (CArpentries EXercises EXtractor)
## What does it do?
No more copy-pasting, automatically extract all exercises from a carpentries lesson.## How to install?
Install with pip:` pip install caex2 `## How to use?`commandline caex2 {LESSON_URL}--output{OPTIONAL_OUTPUT_FILE} `### Example
To extract all exercises from the [deep learning lesson](https://github.com/carpentries-incubator/deep-learning-intro):`commandline caex2https://github.com/carpentries-incubator/deep-learning-intro`This creates a new file calledexercises-document.mdwith all exercises in the lesson,
grouped and ordered by episode.## Current support
This package currently supports carpentries lessons in the ‘old’ style, it has been tested on:
*https://github.com/carpentries-incubator/deep-learning-intro*https://github.com/datacarpentry/r-socialsci(episodes are in Rmarkdown)
*https://github.com/datacarpentry/python-socialsci
Package: caf
Caf (content addressable files) is a CLI utility that allows you to:Create random files usingcaf genVerify the generated files have not been tampered withcaf verifyThat’s it.  Generate files with random content and verify the files haven’t
changed.  Thecaf gencommand gives control over both the number of files
to create as well as the size of the files created.  It even lets you specify
the distribution of file sizes (more on that in a bit).Caf is also designed in a way that allows for parallel file generation as well
as parallel file validation.  It can seamlessly scale up to billions of files.For example, create a set of random files up to 10MB (the default file size
is 4k):$ caf gen --max-disk-usage 10MBYou can then verify the files are all there:$ caf verifyThe--helpoutput of thecaf gencommand contains many more examples.
Package: cafcore
CAF CorePurposeContains common functions used in data processing. Spoilers: quality assurance, quality control, file io, and some data transformation functionsLicenseAs a work of the United States government, this project is in the public domain within the United States.Additionally, we waive copyright and related rights in the work worldwide through the CC0 1.0 Universal public domain dedication.Using this packageTODO: update once we have a second user
Package: caf.distribute
CAF DistributeA module of CAF for distributing demand across matrices.The Common Analytical Framework (CAF) is a toolkit of transport planning and appraisal
functionalities.
It's part of a project to make a lot of the useful transport related functionality
more widely available and easily accessible.
Other modules include:CAF.ToolkitCAF.SpaceCAF.VizContributingCAF.Distribute happily accepts contributions.The best way to contribute to this project is to go to the issues tab and report
bugs or submit a feature request. This helps CAF.Distribute become more stable
and full-featured. Please check the closed bugs before submitting a bug report
to see if your question has already been answered.
Package: cafe
cafe: Classifying Antibodies for ExpressionAboutA Python package, or wrapper, that transforms FASTA files into a data format suitable for machine learning classification.This is a research project during my computational biology internship at EMD Serono, Research and Development Institute in Billerica, MA underDr. Yves Fomekong Nanfack. The idea is to have each amino acid as a feature (with its respective numerical value based on solubility, hydrophobicity, etc. from the literature) and see if it is possible to predict antibodies that have high affinity or other ideal characteristics.Thedata_transformmodule reads in FASTA files, extracts the amino acid sequence, splits each amino acid into its own columns, replaces each amino acid with a value provided by the user (as a file), and outputs a pandas dataframe(s).Themlmodule performs classic machine learning tasks such as splitting the data, standardizing the data, model selection, training, and evaluating.InstallationPlease have Python 3.7 installed.Once Python 3.7 is installed, you can install the package as so:pip3 install cafeUsagePlease see the examples folder.# cafe