Saravanan666/pypi-org huggingface dataset:
Package: autopaths
autopathsversion 1.6.0autopathsis a python package for dealing with file paths and automation.It has many convenience methods that apply to directory paths and/or file paths and contains several submodules that are useful when building pipelines. See below for examples and documentation.PrerequisitesSinceautopathsis written in python, it is compatible with all operating systems: Linux, macOS and Windows. The only prerequisite ispython3(which is often installed by default) along with thepip3package manager.To check if you havepython3installed, type the following on your terminal:$ python3 -VIf you do not havepython3installed, please refer to the sectionobtaining python3.To check you havepip3installed, type the following on your terminal:$ pip3 -VIf you do not havepip3installed, please refer to the sectionobtaining pip3.InstallingTo install theautopathspackage, simply type the following commands on your terminal:$ pip3 install --user autopathsAlternatively, if you want to install it for all users of the system:$ sudo pip3 install autopathsUsageBellow are some examples to illustrate the various ways there are to use this package.FilePathobjectHere are a few example usages of this object:from autopaths.file_path import FilePath
f = FilePath("input/raw/reads_56.fastq")
print(f.exists)
print(f.extension)
print(f.size)
print(f.contains_binary)
f.prepend('# This file was backed-up\n')
f.gzip_to('backup/old_reads/reads_56.fastq.gz')
f.move_to(f.parent)As you can see, once you have created a FilePath, many useful methods are available. No more need for longos.pathorshutilcommands of which you can never remember the syntax.To see the complete list of utility methods and properties, look at the source code. You can find lots of the common things you would need to do with file paths such asf.make_executable()etc. right at your fingertips.DirectoryPathobjectSimilar to a file path object. Here is an example usage of this object:from autopaths.dir_path import DirectoryPath
d = DirectoryPath("cleaned/reads/")
print(d.mod_time)
d.create_if_not_exists()
f = d + 'new.fastq'AutoPathsobjectYou can use this class like this when making pipelines to quickly refer to a predefined file path with a simple attribute lookup. This example explains it:class Sample(object):
    all_paths = """
                /raw/raw.sff
                /raw/raw.fastq
                /clean/trim.fastq
                /clean/clean.fastq
                """

    def __init__(self, base_dir):
        from autopaths.auto_paths import AutoPaths
        self.p = AutoPaths(base_dir, self.all_paths)

    def clean(self):
        shutil.move(self.p.raw_sff, self.p.clean_fastq)Extra documentationMore documentation is available at:http://xapple.github.io/autopaths/autopathsThis documentation is simply generated with:$ pdoc --html --output-dir docs --force autopaths
Package: autopayparking
AutoPayParkingPay and automatically renew PayByPhone parking using CLI.InstallationpipinstallautopayparkingUsageOmit--renewif you do not want to automatically renew parking:autopayparking--location-number123456--duration60--renew--cc-name"Michael Jordan"--cc-number1234567890--cc-expiration0125--cc-cvv1234--cc-zip-code12345--emailhello@example.com
Package: autopep8_autoline
autopep8-autolinePython Boilerplate contains all the boilerplate you need to create a Python package.Free software: MIT licenseDocumentation:https://autopep8-autoline.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2018-06-07)First release on PyPI.
Package: autopew
autopewAutomating sample targeting for geological microanalysis systems.InstallpipinstallautopewIf you want the most up to datedevelopmentversion, you can instead install directly from the GitHub repo. Note that breaking changes occur on this branch, and is not guaranteed to remain stable (check theDevelopment and Build Statusbelow). If you still want to try out the most recent bugfixes and yet-to-be-released features, you can install this version with:pipinstallgit+git://github.com/morganjwilliams/autopew.git@develop#egg=autopewFor more information, see the documentation'sinstallation page, and
theGetting Started Guide.Development & Build Statusmasterdevelop
Package: auto-phylo-pipeliner
auto-phylo-pipelinerauto-phylois a pipeline maker software for phylogenetic studies.auto-phylo-pipeliner is a graphical user interface to rapidly create and modify pipelines for auto-phylo.You can usethis scriptto run thepegi3s/auto-phylo-pipelinerDocker image (the current working directory will be mounted and used as working directory in the new container).
Package: autopilotml
AutopilotmlAutomated machine learning library for analyticsInstallationpip install autopilotmlUsageLoad datafromautopilotmlimportload_data,load_database# For csv filesdf=load_data(path="dataset/titanic_train.csv",csv=True,**kwargs)# For excel notebookdf=load_data(path="dataset/titanic_train.xlsx",excel=True,**kwargs)# To Load data from Database# This framework supports sqlite, 'mysql', 'postgres', 'MongoDB'df=load_database(database_type='sqlite',sqlite_db_path='database.db',query='select * from employee_table')Data Preprocessingfromautopilotmlimportpreprocessing# If changing any values in the dictionary, whole dictionary has to be provided.df=preprocessing(dataframe=df,label_column='Survived',missing={'type':'impute','drop_columns':False,'threshold':0.25,'strategy_numerical':'knn','strategy_categorical':'most_frequent','fill_value':None},outlier={'method':'None','zscore_threshold':3,'iqr_threshold':1.5,'Lc':0.05,'Uc':0.95,'cap':False})Data Transformationfromautopilotmlimporttransformation# If the target_transform is true, then the function  return 3 objects, (e.g) dataframe, feature encoder and target encoder# else it will return 2 objects dataframe and feature encoderdf,encoder=transformation(dataframe=df,label_column='Survived',type='ordinal',target_transform=False,cardinality=True,Cardinality_threshold=0.3)Scaling# Here if target_scaling = True only applicable for regression then it will return 3 objects dataframe, feature scaler and target scalerfromautopilotmlimportscalingdf,scaler=scaling(df,label_column='Survived',type='standard',target_scaling=False)Feature Selecctionfromautopilotmlimportfeature_selectiondf,selector=feature_selection(dataframe=df,label_column='Survived',estimator='RandomForestClassifier',type='rfe',max_features=10,min_features=2,scoring='accuracy',cv=5)Model Trainingfromautopilotmlimporttrainingmodel=training(dataframe=df,label_column='Survived',model_name='SVC',problem_type='Classification',target_scaler=None,test_split=0.15,hypertune=True,n_epochs=100)MLFlow - Track the Model Training and model Parameters!mlflowui
Package: autopilot-tools
PX4/ArduPilot Autopilot toolsautopilot_toolsis a python package intended to be used as part of automated work with PX4 and Ardupilot autopilots such as hardware configuration, test scenarious providing and log analysis.After the installation the package is accessible as a few executables:autopilot-configuratoruploads the given firmware to the autopilot, reset paramters to default, upload the required parameters and perform force sensor calibration.test-scenariouploads the given mission to the autopilot, run it and wait until it is finished, then download the log from the vehicle and upload it toreview.px4.io. It returns a user the result of the flight and link to the flight report.Beside it the package allows to perform every step from a python script in a more customized way and to perform specific flight log analysis and to analyze an overall flight statistic based on multiple flight logs (total number of vehicle flight hours, flight distance, etc).1. User guide1.1. InstallationThe package is distrubuted viapypi.org/project/autopilot-tools/.pipinstallautopilot_tools1.2. Using as executablesAfter the installation, a few executables will appear:autopilot-configuratortest-scenarioFor usage details run them with--helpoption or refer to the corresponded README.md:src/autopilot_tools/utilities.1.3. Using as a moduleThe package can be imported as a module. This allows you to implement more customized behaviour and use extended features if you need.An example is shown below:fromautopilot_tools.vehicleimportVehiclefromautopilot_tools.analyzerimportAnalyzervehicle=Vehicle()vehicle.connect(device="serial")vehicle.upload_firmware(firmware_path_or_url)vehicle.configure(params_path)vehicle.load_mission(mission_path)res=vehicle.run_mission(mission_path)print(res)log_file=vehicle.load_latest_log(mission_path)analzyer=Analyzer()res=analzyer.analyse_log(log_file,analyze_requests=("airspeed","ice","esc_status"))print(res)2. Developer guide2.1. Installation from sourcesFor a developer it is expected to use the package inDevelopment Mode (a.k.a. “Editable Installs”)Clone the repository, install the package in development mode and use it in virtual environment:gitclonehttps://github.com/PonomarevDA/autopilot_tools.git
python3-mvenvvenv
./venv/bin/activate
pipinstall-e.2.2. DeploymentPlease, deploy initially ontest.pypi.org. Only if everything is fine, then deploy onpypi.org.Try the script below to get details:./deploy.sh--help3. LicenseThe package is distributed under MIT license.
Package: autopkg-wrapper
autopkg-wrapperautopkg_wrapperis a small package that can be used to runautopkgwithin CI/CD environments such as GitHub Actions.The easiest way to run it is by installing with pip.pipinstallautopkg-wrapperCommand Line Parameters-h,--helpShowthishelpmessageandexit--recipe-fileRECIPE_FILEPathtoalistofrecipestorun(cannotberunwith--recipes)--recipes[RECIPES...]Recipestorunwithautopkg(cannotberunwith--recipe-file)--debugEnabledebugloggingwhenrunningscript
--override-trustIfsetrecipeoverridetrustverificationwillbedisabled.(Default:True)--github-tokenGITHUB_TOKENAtokenusedtopublishaPRtoyourGitHubrepoifoverridesrequiretheirtrusttobeupdated
--branch-nameBRANCH_NAMEBranchnametobeusedwhererecipeoverrideshavefailedtheirtrustverificationandneedtobeupdated.Bydefault,thiswillbeintheformatof"fix/update_trust_information/YYYY-MM-DDTHH-MM-SS"--create-prIfenabled,autopkg_wrapperwillopenaPRforupdatedtrustinformation
--autopkg-overrides-repo-pathAUTOPKG_OVERRIDES_REPO_PATHThepathondisktothegitrepositorycontainingtheautopkgoverridesdirectory.Ifnoneisprovided,wewilltrytodetermineitforyou.ExampleAn example folder structure and GitHub Actions Workflow is available within theactions-demoCreditsautopkg_toolsfrom Facebookautopkg_toolsfrom Facebook, modified by Gusto
Package: autoplanner
Explications :pas degénération d’un .ics global et d’ICS pour chaque personneafficher un calendrierstatistiques par personne et par catégorie (# événements et temps total)respect des contraintes (#temps min, #temps max)limiter les agents possibles à ceux de l’organisationlimiter les catégories possibles à celles de l’organisationcréer un token par agentfaire une action pour fixer les agents sur les tâchesfaire un bouton pour fixer les agents des tâches passéesajouter le bonus pour les tâches
Package: autoplay
Sometimes I find make too old, autoplay unfrustrates me.Getting startedInstall withpip install autoplay.It will look for jobs inautoplay.ymlin the current directory or fallback
on theautoplay/autoplay.ymlfile which defines a few default jobs. The
twine job for example will build .po files and make a python package that it
will upload with twine, to automate python package release:autoplay debug twine
autoplay twine mode=dryrun
TWINE_USERNAME=... TWINE_PASSWORD=.. autoplay twineCreate a file with nameautoplay.ymlcontaining:---
env:
  someglobal: foo

---
name: example
env:
  example_var: ./autoplay-example
  multiline_var: |
    foo
    bar
setup:
- test -f $example_var || echo "$multiline_var" > $example_var
script:
- cat $example_var

---
name: test
requires:
- exampleThen, see the commands it would execute withautoplay run example mode=dryrun…In-developmentCLI Development EnvironmentWe’re investing in a development command that would allow to run several jobs
simultaneously, with anurwidbased interface. It would allow to define jobs like this
in your autoplay.yml:---
name: dev
script:
- eslint --watch
- yarn start
- django-admin runserver
- py.test --watchThat you could run withautoplay run dev mode=ide.Tox-like and docker based executorsThe default executor islinuxwhich executes in a bash subshell.
However other executors are available such asexecutor=docker(for
baking development environments) andexecutor=virtualenv(for build
matrix).
Package: autoplot
Autoplot is a Java application which can read data from many sources, such as ASCII tables, NASA CDF files, and HDF5 files.  It can also read data from data servers, such as the server at NASA/Goddard/CDAWeb, Das2Servers used by the Radio and
Plasma Wave Group at the University of Iowa, and servers supporting the HAPI API.Autoplot identifies data using “URIs”, which are one-line strings containing a data source ID and configuration to read the data.
These URIs can be created using the Autoplot application, available athttp://autoplot.org/.
Data are read into a standard data model, QDataSet, which is easily adapted to Python using “JPype”.
Helper procedures from the autoplot package convert QDataSets into ndarrays.Autoplot/Python Interface ToolsInstall usingpip install autoplotimportautoplotasap# Download autoplot.jar if needed and return Python bridge objectap.init()# Create Autoplot Data Set.  This object manages loading the data and then containing it until extracted.apds=ap.APDataSet()# Set URIapds.setDataSetURI('http://autoplot.org/data/swe-np.xls?column=data&depend0=dep0')# Get the dataapds.doGetDataSet()print(apds.toString())# http://autoplot.org/data/swe-np.xls?column=data&depend0=dep0# data: data[dep0=288] (dimensionless)# dep0: dep0[288] (days since 1899-12-30T00:00:00.000Z) (DEPEND_0)# Extract data valuesvv=ap.to_ndarray(apds,'data')tt=ap.to_ndarray(apds,'dep0')frommatplotlibimportpyplotaspltplt.plot(tt,vv)plt.show()ContactJeremy Faden <faden@cottagesystems.com>
Package: autoplotlib
Quickly generate plots in Python by simply describing them through text.For example, simply use the prompt "create a scatter plot with name labels" instead of endlessly searching the docs and stackoverflow. Given such a prompt, theautoplotlibPython library uses the OpenAI API to automatically generate the corresponding code and plot - saving you time and effort.WarningThis package is experimental. The package can execute code output from language models. Albeit unlikely, always check and confirm no malicious code was generated by the model before execution. Use at your own risk.InstallationInstall the Python package:pip install autoplotlibGet an OpenAI API key bysigning up hereif you don't have one already.UsageThe following is an example of plotting a pandas dataframe using theautoplotliblibrary. Theplot()function takes a prompt describing the plot and the data to plot. The function returns the plot, the generated code, and the full response from the OpenAI API.# set the OpenAI API keyimportosos.environ["OPENAI_API_KEY"]="<YOUR_API_KEY>"importautoplotlibasapltimportpandasaspddata=pd.DataFrame([[29,177],[33,186],[48,161],[53,173],[67,152]],index=["Alice","Bob","Charlie","Dave","Eve"],columns=["age","height"],)figure_description="""Plot the data as scatterplot between height and age.Add the names as labels next to the data points.Ensure the labels don't overlap.Mark people taller than 170 with a star instead of a point."""code,fig,llm_response=aplt.plot(figure_description,data=data)ContributingSee thedevelopment guidefor information about contributing.Potential future featuresAdd sandboxing of code execution (see here)LicenseMIT License
Package: autoplotter
AutoPlotterautoplotter is a python package for GUI based exploratory data analysis. It is built on the top of dash.InstallationUse the package managerpipto install autoplotter.$pipinstallautoplotterUsagefromautoplotterimportrun_app# Importing the autoplotter for GUI Based EDAimportpandasaspd# Importing Pandas to read csvdf=pd.read_csv("https://raw.githubusercontent.com/ersaurabhverma/autoplotter/master/Data/data.csv")# Reading datarun_app(df,mode="inline",host="127.0.0.1",port=5000)# Calling the autoplotter.run_app in inline moderun_app(df,mode="external",host="127.0.0.1",port=5000)# Calling the autoplotter.run_app in external mode[]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.SupportSupport me by following onGithubandLinkedIn.LicenseMIT license
Package: autopop
AutoPop: Auto Populate Google Doc Tables using LLMsDescriptionAutoPop is a Python package designed to automatically populate tables in Google Docs using Large Language Models (LLMs). The package leverages the power of LLMs to generate content for various aspects of a Google Doc, making it easier to create comprehensive and informative tables without manual effort.FeaturesAuto-populate tables in Google Docs with data generated by LLMs.
Supports various types of LLMs including GPT-4, Claude, etc.
Easy to use with a simple Python API.
Highly customizable to suit different use-cases.InstallationTo install the package, run:pip install autopopDependenciesrequests
selenium
openaiUsageTBDContributingContributions are welcome! Please read the contributing guidelines to get started.LicenseThis project is licensed under the MIT License. See LICENSE.md for details.ContactFor questions and support, please contactdavid.schwartz@devfactory.com.
Package: autopoputils
AutoPopUtils: Auto Populate Google Doc Tables using LLMs utilitiesDescriptionTBDFeaturesTBDInstallationTo install the package, run:pip install autopoputilsDependenciesrequests
seleniumUsageTBDContributingContributions are welcome! Please read the contributing guidelines to get started.LicenseThis project is licensed under the MIT License. See LICENSE.md for details.ContactFor questions and support, please contactdavid.schwartz@devfactory.com.
Package: autopost
autopostA social media auto-poster for a blog.Supported sites:Twitter (currently untested)Mastodon (any instance)Reddit (any subreddit)BlueskyInstallationautopostrequires Python 3.11 or newer, and is available on PyPI:python-mpipinstallautopostUsageusage: autopost [-h] [-V] [-v] [--dry-run] [--config-file CONFIG_FILE] {manual,atom} ...auto-posts social media updatespositional arguments:{manual,atom}manual              auto-post manuallyatom                auto-post from an Atom RSS feedoptions:-h, --help            show this help message and exit-V, --version         show program's version number and exit-v, --verbose         be more verbose while running (default: False)--dry-run             perform a dry-run (default: False)--config-file CONFIG_FILEthe file to load for configuration (default: ./autopost.toml)ExamplesTo do anything meaningful withautopost, you'll need to configure
it. Seeautopost.example.tomlfor an example configuration file.Once configured, you can useautopostto make a post manually:$autopostmanual"test"--url"https://example.com"--tagsfoobar🎉 reddit:/r/enosuchblog: https://reddit.com/r/enosuchblog/comments/zldk8y/test/🎉 mastodon:@yossarian@infosec.exchange: https://infosec.exchange/@yossarian/109509443715725349...where--tagsis optional.Alternatively, you can useautopost atomto retrieve a post from an Atom-style
RSS feed:autopostatomhttps://example.com/feed.xmlIn both cases, you can pass--dry-runto see whatautopostwouldpost
instead of actually doing it:$autopost--dry-runatomhttps://blog.yossarian.net/feed.xmldry run: would have posted Modernizing my 1980s sound system with URL:https://blog.yossarian.net/2022/11/07/Modernizing-my-1980s-sound-system and tags: ['howto', 'workflow', 'music']
Package: auto-pr
auto-prA command line tool to perform bulk updates across multiple GitHub repositories.How to installWithpipx(recommended):pipxinstallauto-prWith pip:pipinstallauto-prUsageInitFirst initialise the project directory by running theinitcommand within an empty directory.auto-prinit--api-key=<github_token>--ssh-key-file=<path-to-ssh-key>Where<github_token>is a GitHubpersonal access tokenwhich hasrepoanduser:user:emailscope.Next modify the generatedconfig.yamlfile with your desired configurations.credentials:api_key:<github_token>ssh_key_file:/path/to/ssh/key/to/push/.ssh/id_rsapr:body:>Body of the PR that will be generatedCan be multi-line :)branch:auto-pr# The branch name to use when making changesmessage:Replace default pipelines with modules# Commit messagetitle:'Myawesomechange'# Title of the PRrepositories:# Rules that define what repos to update-mode:addmatch_owner:<org/user>update_command:-touch-my-fileRepositoriesYou can define the list of repositories to pull and build into the database to update using a list of rules.mode- eitheraddorremove- used to either match or negatepublic(optional) - pull only public or private, leave out for botharchived(optional) -  archived or non-archived, leave out for bothmatch_owner(optional) - the owner or user to pullmatch_name(optional) - a list of regular expressions to match against to pullThe flags of the filter rules are optional not specifying will run the command on all repositories that the token has access too.Update CommandThis is the list containing the command to be executed along with the arguments passed to it. It will be executed from
the root of each repository that is processed.If an error occurs during the execution it will be displayed in the output but will not halt the execution.Seeexample commandsPullAfter you have configured the project you can now pull the repositories down that match your rules.auto-prpullThis will generate adb.jsonfile within your workdir containing a list of mapped repositories and their state.This command can be run multiple times, if there are new matching repositories found they will be merged into the existing database.TestOnce thepullcommand has finished setting up the work directory you can now run test to check what the changes that will be made by the script will yield.RunWhen you're confident with the changes output from thetestcommand you can finally executerun.auto-prrunThis will perform the changes to a branch on the locally cloned repository and push the branch upstream with the information you provided withinconfig.yaml.See--helpfor more information about other commands and their  usage.ResetYou can reset the list of repos indb.jsonusingauto-pr reset all, orauto-pr reset from FILEWhen usingauto-pr reset from FILE, the list of repos should be provided as a newline separated list of repos like<owner>/<name>, e.g:getyourguide/test
getyourguide/auto-prSecurityFor sensitive security matters please contactsecurity@getyourguide.com.LegalCopyright 2021 GetYourGuide GmbH.auto-pr is licensed under the Apache License, Version 2.0. SeeLICENSEfor the full text.