Saravanan666/pypi-org huggingface dataset:
Package: pyEanGenerator
pyEanGeneratorPython package to:generate ean8 and ean13 barcodefrompyEanGeneratorimportEan8Generator,Ean13Generator# EAN 8testBarCode=Ean8Generator(myEan)## show barecode on windowtestBarCode.showBarcode()## save EAN as svg filetestBarCode.saveAsSvg("myEan.svg")## save EAN as png file (need pillow)testBarCode.saveAsImg("myEan.png")# EAN 13testBarCode=Ean13Generator(myEan)## show barecode on windowtestBarCode.showBarcode()## save EAN as svg filetestBarCode.saveAsSvg("myEan.svg")## save EAN as png file (need pillow)testBarCode.saveAsImg("myEan.png")verify if a string can be an ean8 or ean13frompyEanGeneratorimportisCorrectEan,EanType# test if ean8 or ean13isEan=isCorrectEan(myEan)# test if ean8isEan8=isCorrectEan(myEan,EanType.EAN8)# test if ean13isEan13=isCorrectEan(myEan,EanType.EAN13)calculate checksum digit of eanfrompyEanGeneratorimportcalculateDigitCheckcheckSumDigit=calculateDigitCheck(myEanWithouCheckSumDigit)
Package: pyeapi
The Python Client for eAPI (pyeapi) is a native Python library wrapper around
Arista EOS eAPI.  It provides a set of Python language bindings for configuring
Arista EOS nodes.The Python library can be used to communicate with EOS either locally
(on-box) or remotely (off-box). It uses a standard INI-style configuration file
to specify one or more nodes and connection profiles.The pyeapi library also provides an API layer for building native Python
objects to interact with the destination nodes. The API layer is a convenient
implementation for working with the EOS configuration and is extensible for
developing custom implementations.This library is freely provided to the open source community for building
robust applications using Arista EOS. Support is provided as best effort
through Github issues.
Package: pyeapi-fork
The Python Client for eAPI (pyeapi) is a native Python library wrapper around
Arista EOS eAPI.  It provides a set of Python language bindings for configuring
Arista EOS nodes.The Python library can be used to communicate with EOS either locally
(on-box) or remotely (off-box). It uses a standard INI-style configuration file
to specify one or more nodes and connection profiles.The pyeapi library also provides an API layer for building native Python
objects to interact with the destination nodes. The API layer is a convenient
implementation for working with the EOS configuration and is extensible for
developing custom implementations.This library is freely provided to the open source community for building
robust applications using Arista EOS. Support is provided as best effort
through Github issues.
Package: pyearcal
pyearcalGenerate your year calendar in Python. The result is a PDF file with 12 pages containing an image and a grid of days.Requirementspillow or PILreportlabDejaVu fonts (if you want pyearcal work out of the box)BeautifulSoup (optional)Python 3.8+Installationpipx install pyearcalUsagePrepare a directory with 12 images (different image providers are planned)Initialize calendar with all options.Language (locales for English, Czech, Slovak, Italian)Special days (national holidays are included + add your own)Fonts, coloursRender it to PDFUsage of the scriptUsage: pyearcal [OPTIONS] [OUTPUT]

Options:
  -s, --source PATH
  -l, --locale [en|cs|it|sk]
  -y, --year INTEGER
  -f, --font TEXT
  -d, --special-days TEXTExample code# Import important modulesfrompyearcalimportYearCalendarfrompyearcal.image_sourcesimportUnsortedImageDirectoryfromdatetimeimportdatefrompyearcal.l10nimportCzechLocaleyear=date.today().year+1# Use all pictures from "images" directoryimage_source=UnsortedImageDirectory("images")# Use Czech locale and holidayslocale=CzechLocale()# Set a few special daysspecial_days=[date(year,1,31)# Guido van Rossum's birthday]calendar=YearCalendar(year,image_source,locale,special_days)calendar.render("calendar.pdf")You can takeFlickrDownloaderas an inspiration for developing a more sophisticated image source.Example with real picturesIndia Faces Calendar 2014 (80 MB)
Package: pyease
Python Library with helpful functions for the Eclipse Advanced Scripting
Environment (EASE). Seehttps://www.eclipse.org/easeDocumentationRead thefull documentation on Github pages.InstallationYou can install the latest released version directly from PyPI.pip install pyeaseTo set up a development environment, clone the project and install it into a
virtual environment.git clone https://github.com/DSD-DBS/pyease
cd pyease
python -m venv .venv

source .venv/bin/activate.sh  # for Linux / Mac
.venv\Scripts\activate  # for Windows

pip install -U pip pre-commit
pip install -e '.[docs,test]'
pre-commit installContributingWe’d love to see your bug reports and improvement suggestions! Please take a
look at ourguidelines for contributorsfor details.LicensesThis project is compliant with theREUSE Specification Version 3.0.Copyright DB Netz AG, licensed under Apache 2.0 (see full text inLICENSES/Apache-2.0.txt)Dot-files are licensed under CC0-1.0 (see full text inLICENSES/CC0-1.0.txt)
Package: pyeasee
Easee EV Charger libraryThis library is an async thin wrapper aroundEasee's Rest APIInstallationYou can install the libray fromPyPI:pip install pyeaseeThe library is tested on Python 3.7 and Python 3.8Command line toolRunpython -m pyeasee -hfor help.Usage of the libraryDocsRead the API documentationhereSmall exampleSave the example to a file and run it like this: python3 example.py  
Username is the phone number that was used to register the Easee account with country code.
E.g. +46xxxxxxxxx.importasyncioimportsysfrompyeaseeimportEaseeasyncdefasync_main():iflen(sys.argv)<3:print(f"Usage:{sys.argv[0]}<username> <password>")returnprint(f"Logging in using:{sys.argv[1]}{sys.argv[2]}")easee=Easee(sys.argv[1],sys.argv[2])sites=awaiteasee.get_sites()forsiteinsites:print(f"Site{site.name}({site.id})")equalizers=site.get_equalizers()forequalizerinequalizers:print(f"  Equalizer:{equalizer.name}({equalizer.id})")circuits=site.get_circuits()forcircuitincircuits:print(f"  Circuit{circuit.id}")chargers=circuit.get_chargers()forchargerinchargers:state=awaitcharger.get_state()print(f"    Charger:{charger.name}({charger.id}) status:{state['chargerOpMode']}")awaiteasee.close()asyncio.run(async_main())See also__main__.pyfor a more complete usage example.DevelopmentThis project usesblackfor code formatting andflake8for linting. To autoformat and run lint runmake lintAttribution, support and cooperationThis project was started by the late Niklas Fondberg, @fondberg. The repository has been inherited by his collaborators.
Package: pyeastmoney
获取东方财富网数据介绍本项目是一个获取东方财富网数据的Python库，目前支持的数据有：主要财务指标资产负债表利润表股票实际控制人安装pipinstallpyeastmoney导入Python包使用获得实际控制人fromeastmoney.f10importshareholder_researchshareholder=shareholder_research(code="SH600161")print(shareholder)脚本提供了两个脚本，可以直接使用：download_lrb.py下载利润表数据download_zcfzb.py下载资产负债表数据
Package: pyeasy
pyeasy======2014 05 16To make python programing easier1. read excel~~~~~~from pyeasy import OpenExcelf = OpenExcel('test.xls')f.read() # read allf.read('A') # read 'A' rowf.read(1) # f.read('1'), read '1' columnf.read('A5') # read 'A5' position2. print file tree~~~~~~
Package: py_easy_async
py_easy_asyncprovides simple interface for threading to easy perform async actions in Python versions 3.4 and upExample of simple async operationsimportpy_easy_asyncimporttimedefprint_with_sleep(word):time.sleep(1)print(word)return'done'print('first')py_easy_async.async(lambda:print_with_sleep('second'),lambdadone_string:print("done callback called with string:%s"%done_string))print('third')The above example will print the following:firstthirdseconddonecallbackcalledwithstring:doneExample of thread pool managementfrompy_easy_asyncimportpooldefmessage_handler(message):print('got message:',message)identifier=pool.run_thread(message_handler,name='Persistent-Thread')foriinrange(5):pool.message(identifier,"test message #%s"%i)pool.stop_thread(identifier)The above example will start thread that will wait for messages that it should process:Persistent-Threadstarting...gotmessage:testmessage#0gotmessage:testmessage#1gotmessage:testmessage#2gotmessage:testmessage#3gotmessage:testmessage#4Persistent-Threadexiting...LicenseReleased under the MIT license.Installationpipinstallpy_easy_async
Package: pyeasydcer
pyeasydcerPython Script which makes exporting Drupal default content in Drupal a lot easier than manually doing itWork DoneComplete support for DCER - Script can export any number of entities in just a matter of minutesWorks perfectly on unix systemsSupports Lando (lando users need to add lando parameter when running the script so as to enable lando mode)Work to be doneWindows supportMultithreading support to make the execution time more fasterPerksUser can export any number of entities in one goUser need not enter subscription name and path where local setup is located every time they export defult contentScript asks the user to enter config when they run it for the first timeFor the next 6 hours script will not ask user to input subscription or path making user's work a bit more easyAnd the best part is there is no need for the user to enter arguments in a particular order, user can enter arguments in any order the script will take care of the problem of handling all that stuff.RequirementsPython v3.7+pip3Usage:pyeasydcer <entity_type> <id's of entities separated by a comma(,)pyeasydcer <entity_type> <id's of entities separated by a comma(,) lando(if using lando enviroment)Refer topyeasydcer -helpto see the help section whenever you are confusedHOW TO USE THIS SCRIPTYou can directly install this script from pip as given belowpip3 install pyeasydcerIf you are cloning the repository, then you need to run it as given below.cd pyeasydcer/easydcerpython3main.py --helpPython is the FUTUREEnjoy Scripting 🙂
Package: py-easyDL
EasyDLEasyDL - Where Deep learning is meant to be easy.InstallationRun the following to install:pipinstallpy-easyDLUsageEasyDL uses the same methodology as Google's Tensorflow v2.x.
Here are some imports from our package.importeasyDLfromeasyDL.preprocessing.imageimportload_single_image,\load_images_from_directory,load_images_from_classes_directoryfromeasyDL.preprocessing.csvimportload_csvfromeasyDL.preprocessing.datasetsimportmnist,cifar10,cifar100fromeasyDL.preprocessing.utilsimportshuffle,normalizefromeasyDL.modelsimportModel,load_modelfromeasyDL.activationsimportTanh,Softmax,Sigmoid,ReLU,LeakyReLU,Step,IdentityfromeasyDL.layersimportDense,MaxPooling2D,Conv2D,Flatten,Dropout,BatchNormfromeasyDL.optimizersimportGradientDescent,Adam,RMSProp,AdaGrad,MomentumGD,NesterovGDfromeasyDL.visualizationimportplot_losses,plot_accuracyfromeasyDL.lossesimportBinaryCrossEntropy,CategoricalCrossEntropy,\SparseCategoricalCrossEntropy,MeanSquaredErrorfromeasyDL.evaluationimportplot_evaluation_matrix,plot_confusion_matrixThis is an example using our package.# Preprocessing(X_train,Y_train),(X_test,Y_test)=mnist.load_data()X_train=normalize(X_train[:4000])Y_train=Y_train[:4000]X_test=normalize(X_test[:1000])Y_test=Y_test[:1000]# Create a modelmodel=Model()# Adding layersmodel.add(Conv2D(6,kernel_size=(5,5),input_shape=X_train.shape[1:]))model.add(BatchNorm())model.add(ReLU())model.add(MaxPooling2D())model.add(Conv2D(16,kernel_size=(5,5)))model.add(BatchNorm())model.add(ReLU())model.add(MaxPooling2D())model.add(Flatten())model.add(Dense(120))model.add(BatchNorm())model.add(ReLU())model.add(Dense(84))model.add(BatchNorm())model.add(ReLU())model.add(Dense(10))model.add(Softmax())# Compiling the modelmodel.compile(loss='sparse_categorical_crossentropy',optimizer=Adam(lr=0.01))# Training the modelmodel.fit(X_train,Y_train,validation_data=(X_test,Y_test),epochs=10,batch_size=64,verbose=True)# Plotting losses and accuraciesplot_losses(model)plot_accuracy(model)# Predicting labels using the modelpredictions=model.predict(X_test)# Plotting confusion matrixplot_confusion_matrix(Y_test,predictions)# Printing evaluation matrixplot_evaluation_matrix(Y_test,predictions)# Save the model into a .pkl filemodel.save('PATH/TO/FILE.pkl')# Load a saved .pkl modelmodel=load_model('PATH/TO/FILE.pkl')
Package: pyeasydriver
Simple software driver for stepper motors controlled by the SparkFun EasyDriver motor controller board.Installpip install pyeasydriverUsagefrompyeasydriver.easydriverimportEasyDriver,StepDirectionfromgpiozeroimportDevicefromgpiozero.pins.rpigpioimportRPiGPIOFactoryimportRPi.GPIOasrpigpiorpigpio.setmode(rpigpio.BCM)rpigpio.setwarnings(False)Device.pin_factory=RPiGPIOFactory()if__name__=="__main__":STEP_PIN=20DIR_PIN=21ENABLE_PIN=25MS1_PIN=24MS2_PIN=23driver=EasyDriver(step_pin=self.STEP_PIN,dir_pin=self.DIR_PIN,ms1_pin=self.MS1_PIN,ms2_pin=self.MS2_PIN,enable_pin=self.ENABLE_PIN)driver.step(200,direction=StepDirection.FORWARD)driver.step(200,direction=StepDirection.REVERSE)
Package: pyeasyeda
pyeasyedaSince exploratory data analysis is an imperative part of every analysis, this package aims at providing efficient data scrubbing and visualization tools to perform preliminary EDA on raw data. The package can be leveraged to clean the dataset and visualize relationships between features to generate insightful trends.Functionsclean_up- This function takes in a pandas dataframe object and performs initial steps of EDA on unstructured data. It returns a clean dataset by removing null values and identifying potential outliers in numeric variables based on a defined threshold.birds_eye_view- This function takes in a pandas dataframe object and visualizes the distributions of variables in the form of histograms and density plots. It also generates a correlation heatmap for numeric variables to study their relationships.close_up- This function accepts a pandas dataframe object creates a scatterplot of the variable(s) most strongly correlated with the dependent variable. The plot also produces a trend line to model the correlation between the variables.summary_suggestions- This function takes in a pandas dataframe object and outputs a table of summary statistics for numeric and categorical variables and a table for percentage of unique values in the categorical variables.Other packages that offer similar functionality are:datascience_edaQuickDAeasy-data-analysisInstallation$pipinstallpyeasyedaUsageAfter installing the package through the command above, please run the following commands in the terminal from the root of the project repo as a quick demo.python
import pandas as pd
from pyeasyeda.clean_up import clean_up
from pyeasyeda.birds_eye_view import birds_eye_view
from pyeasyeda.close_up import close_up
from pyeasyeda.summary_suggestions import summary_suggestions
df = pd.read_csv("tests/data/penguins_test.csv")
clean_up(df)
plots = birds_eye_view(df)
close_up(df, 1)
summary_suggestions(df)Please check our official documentation for the example usage of the package atpyeasyeda/exampleon Read the Docs.DocumentationThe official documentation is hosted atpyeasyedaon Read the Docs.ContributorsThis python package was developed by James Kim, Kristin Bunyan, Luming Yang and Sukhleen Kaur. The team is from the Master of Data Science program at the University of the British Columbia.ContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensepyeasyedawas created by James Kim, Kristin Banyan, Luming Yang and Sukhleen Kaur. It is licensed under the terms of the MIT license.Creditspyeasyedawas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.
Package: pyeasyedit
PyEasyEditPyEasyEdit is a lightweight, feature-rich text editor built with PyQt6 and QScintilla. Designed to offer a flexible and efficient editing environment, PyEasyEdit supports syntax highlighting for multiple programming languages, file management capabilities, and customizable themes, making it an ideal choice for developers and writers alike.FeaturesSyntax Highlighting: Supports syntax coloring for Python, JavaScript, HTML, CSS, and more, making code easier to read and write.Auto Completion: Source code auto-completionJedi Support: Auto-completion now includes jedi inspectionTab to space conversion: Critical for pythonFile Management: Open, edit, and save files with an intuitive interface. Recent files are tracked for quick access.Search and Replace: Powerful search and replace functionality to easily modify your documents.Custom Dialogs: Includes custom dialogs for searching, replacing, and more, enhancing the user experience.Theme Customization: Comes with a set of predefined themes and allows for custom color schemes.Extensibility: Designed with extensibility in mind, allowing for additional features and languages to be added.Getting Started via PipCreate a virtual env for Python:mdpyeasyeditcdpyeasyedit
python-mvenvvenv
venv\Scripts\activate
pipinstallpyeasyedit
python-mpyeasyeditGetting Started From SourcePrerequisitesBefore you begin, ensure you have met the following requirements:Python 3.9 or later installed on your system.PyQt6 and QScintilla libraries installed. You can install these using pip:pipinstallPyQt6QScintillaInstallationClone the repository to your local machine:gitclonegit@github.com:scottpeterman/pyeasyedit.gitcdpyeasyedit
pipinstall-rrequirements.txtRunning PyEasyEditTo start the editor, run the following command from the terminal:python-mpyeasyeditOptionally, you can specify a file to open directly:python-mpyeasyedit/path/to/your/file.txtUsageFile Menu: Use the File menu to open, save, or create new documents.Edit Menu: Access search and replace functions through the Edit menu.Help Menu: Contains the About dialog that provides information about the editor and a link to the project's GitHub page.LicensePyEasyEdit is released under the GPLv3 License. See the LICENSE file for more information.AcknowledgmentsSpecial thanks to the PyQt and QScintilla teams for providing the powerful libraries that made this project possible.Learn more about PyQt and Qt atRiverbank ComputingandQt Group, respectively.# Create a source distribution and a wheel, upload to pypipythonsetup.pysdistbdist_wheeltwineuploaddist/*
Package: pyeasyencrypt
pyeasyencryptDescriptionThe purpose of this module is to simplify the way of encrypting and decrypting strings at python with a simple passwordExample of Python codeimportlogging,os# pip install pyeasyencryptfrompyeasyencrypt.pyeasyencryptimportencrypt_string,decrypt_stringlevel=os.getenv("LOGGER","INFO")logging.basicConfig(level=level)logger=logging.getLogger(__name__)defmain():logger.info("Example")clear_string='stringA'password="my password"encrypted_string=encrypt_string(clear_string,password)decrypted_string=decrypt_string(encrypted_string,password)logger.info(f"clear_string={clear_string}decrypted_string={decrypt_string}password={password}encrypted_string={encrypted_string}")logger.debug("Done")if__name__=='__main__':main()AuthorName: Jordi Redondo
Email:jordipromotions@gmail.comgit repo:https://github.com/redcorjo/pyeasyencrypt.gitInstallpip install pyeasyencryptVersion: 2023010803
Package: pyeasyga
IntroductionA simple and easy-to-use implementation of a Genetic Algorithm library in Python.pyeasygaprovides a simple interface to the power of Genetic Algorithms
(GAs). You don’t have to have expert GA knowledge in order to use it.Homepage:https://github.com/remiomosowon/pyeasygaPyPI:https://pypi.python.org/pypi/pyeasygaDocumentation:http://pyeasyga.readthedocs.org.Issues / Feedback:https://github.com/remiomosowon/pyeasyga/issuesFree software: BSD licenseInstallationAt the command line, simply run:$ pip install pyeasygaOr clone this repository and runpython setup.py installfrom within the project directory. e.g.:$ git clone https://github.com/remiomosowon/pyeasyga.git
$ cd pyeasyga
$ python setup.py installFor alternative install methods, see the INSTALL file or the Installation
section in the documentation.ExamplesSee the Usage section in the documentation for examples. The example files can
be found in theexamplesdirectory.NoteCurrently under active developmentHistoryv0.3.02015-04-07Added Python 3.4 support without breaking Python 2 compatibility (thanks toyasserglez)v0.2.52014-07-09Added an example that solves the8 Queens Puzzle2014-07-09Modified the GeneticAlgorithm class initialisation parametersMade changes to USAGE documentationAdded EXAMPLE documentation as a separate sectionv0.2.42014-07-07Refactored most of the code; Made GeneticAlgorithm class more OOPMade changes to INSTALLATION documentationv0.2.32014-07-05Fixed breaking python 2.6 buildv0.2.22014-07-05Removed duplicate ‘Example’ documentation; now maintaining only one copy in
examples/README.rstAdded link to jeffknupp’s sandman repo in HISTORYModified release option in Makefile to also upload project documentationAdded INSTALLATION and EXAMPLE sections to README.rstRemoved easy_install installation step from documentation (pip is
sufficient)Added a simple example of usage to docs/usage.rstReduced the default GA population and generation size (to allow applications
that use the different parameters to run quickly)Modified tests to account for the new default population, generation sizeAdded docstrings to all methodsv0.2.02014-07-04First upload to pypi.Added changes made to HISTORY (pypi upload, new version)v0.1.02014-06-23Start ofpyeasygadevelopment.2014-07-03Implemented all of basic GA functionalityFix issue with odd-numbered population that causes an off-by-one error in the
population sizeSet default ga selection function to tournament_selectionCreated examples to show how to use the libraryStart versioning (better late than never); copied jeffknupp’s
update_version.sh fromsandmanselected versioning standard:major.minor.micro (e.g. 2.1.5)major => big changes that can break compatibilityminor => new featuresmicro => bug fixes
Package: py-easy-html
Easy HTMLGenerate HTML using python and also convert to PDF.Installationpipinstallpy-easy-htmlGetting startedGeneral usageh1=generate_tag('h1',body='This is a h1',class_name="your_class",id_name="your_id",self_closing=False)Output<h1class="your_class"id="your_id">This is a h1</h1><!-- With self_closing=True --><h1class="your_class"id="your_id"/>You can also do nested tagsh1=generate_tag('h1',body=generate_tag('span',body='Span inside h1'))Output<h1><span>Span inside h1</span></h1>And also multiple nested tagsh1=generate_tag('h1',style={"display":"flex","justify-content":"space-between","align-items":"center",},body=[generate_tag('span',body='First Span'),generate_tag('span',body='Second'),],)Output<h1style="display: flex;justify-content: space-between;align-items: center;"><span>First Span</span><span>Second</span></h1>