Saravanan666/pypi-org huggingface dataset:
Package: autoinsight
Introductionautoinsight is a UI automation library for window. It is aim to provide simplified workflow to the automation developers
to help them create a easy to maintain and robust test scripts.It is focus on Windows in the recent releases. It will be migrate to Linux in the future.Contribute to this projectDonateContribute codeDocumentationRequirementsOS
WindowPython 3.6+ 32/64 bitInstall Google Tesseract 32/64 bittesseract wikiAdd tesseract.exe into the system environment variable PATHInstall pywin32pywin32 releaseInstallationInstall with pip$ pip install autoinsightQuick demofromautoinsightimportButton,WindowOSdefdemo():camera=WindowOS().launchApp("camera")camera.setCurrent()Button("take photo").click()camera.close()if__name__=='__main__':demo()ConfigurationDevelopmentSetup development environmentSetup$ pip install -r requirements-dev.txtInstall Google Tesseract ORCRun all test$ nose2validate code syntax before commit$ flake8BuildInstall the build dependency$ python -m pip install --upgrade pip
$ python -m pip install -r requirements-dev.txt
$ python -m buildTestRun unit test on local machine before push to the repository$ nose2Create a new test module with add theinit.py to a new folder under the ./testsName the test file with test_*.pyMake sure each test case inherit from the unittest.TestCaseTestDocument and HelpFollow syntax of the Sphinx projectRoadmap0.0.1 [Current version 0.0.8]Init the project1.0.0Basic windows UI automation featuresBasic image based identification featuresKeyboard mouse handling etc.In the first version it will be built like a glue to the existing
automation libraries like pywinauto, pyautogui etc.Action loggingSnapshotScreen recordingSupport Google Chrome and Microsoft Edge interoperationOS interoperationDriver interoperationIntegrate with image identification and computer vision2.0.0Integrate with machine learning identificationIntegrate other browsersAdd mobile supportIntegrate with cloud ML APIs3.0.0Support NLP scriptAdd GUI4.0.0Support record and replay5.0.0Support game automationCopyrightsApache Software License
Package: autoinstall
package loader for auto installing Python packages.A package loader in the spirit of Zero Install that can be used toinject dependencies into the import process.To install::easy_install -U autoinstallordownload, unpack, python setup.py installortry the bootstrap loader. See below.To use::# You can bind any package name to a URL pointing to something# that can be imported using the zipimporter.autoinstall.bind("pymarc", "http://pypi.python.org/packages/2.5/p/pymarc/pymarc-2.1-py2.5.egg")import pymarcprint pymarc.__version__, pymarc.__file__Changelog::- added support for non top level packages.- cache files now use filename part from URL.- applied patch from Eric Seidel <eseidel@google.com> to add supportfor loading modules where the module is not at the root of the .zipfile.TODO::- a description of the intended use case- address other issues pointed out in:http://mail.python.org/pipermail/python-dev/2008-March/077926.htmlScribbles::pull vs. pushuser vs. systemweb vs. filesystemauto vs. manualmanage development sandboxesoptional interfaces...def get_data(pathname) -> string with file data.Return the data associated with 'pathname'. Raise IOError ifthe file wasn't found.");def is_package,"is_package(fullname) -> bool.Return True if the module specified by fullname is a package.Raise ZipImportError is the module couldn't be found.");def get_code,"get_code(fullname) -> code object.Return the code object for the specified module. Raise ZipImportErroris the module couldn't be found.");def get_source,"get_source(fullname) -> source string.Return the source code for the specified module. Raise ZipImportErroris the module couldn't be found, return None if the archive doescontain the module, but has no source for it.");Autoinstall can also be bootstraped with the nascent package loaderbootstrap module. For example::#  or via the bootstrap# loader.try:_version = "0.2"import autoinstallif autoinstall.__version__ != _version:raise ImportError("A different version than expected found.")except ImportError, e:# http://svn.python.org/projects/sandbox/trunk/bootstrap/bootstrap.pyimport bootstrappypi = "http://pypi.python.org"dir = "packages/source/a/autoinstall"url = "%s/%s/autoinstall-%s.tar.gz" % (pypi, dir, _version)bootstrap.main((url,))import autoinstallReferences::http://0install.net/http://www.python.org/dev/peps/pep-0302/http://svn.python.org/projects/sandbox/trunk/import_in_pyhttp://0install.net/injector-find.htmlhttp://roscidus.com/desktop/node/903
Package: autoinstaller
# autoinstallerA package that automagically installs from PyPi everything you need as soon as you try import it.
For example, let’s assume that you do not have the tornado web server.>>> import tornado
Traceback (most recent call last):
   File "<stdin>", line 1, in <module>
ImportError: No module named tornadoBut if you have autoinstaller>>> import autoinstaller
>>> import tornado
...
Processing dependencies for tornado
...
Installed ...
Finished processing dependencies for tornado
>>>And from now on the package can be used without existing or restarting the process.
Package: auto-instr
Introductionauto-instr is a simple and user-friendly library for automating scientific instruments.It offers quick-set functions for configuring and measuring in a single line of code.It supports all common bench instruments such as power supply, oscilloscope, function generator, source meter, multimeter,temperature controller etc.LicenseThe code is distributed under MIT License.You can use auto-instr library in your project without any restrictions.Supported Python versionsauto-instr library supports Python 3.InstallationInstall usingpip(recommended, no separate download required).pip install auto-instrSource code, bug reports, patchesauto-instr on GitHub:https://github.com/arvind0790/auto_instrUser manualUser manual for auto-instr is available online at:https://auto-instr.readthedocs.io/ChangelogSee CHANGES.txt
Package: auto-iserv
Auto Iserv v.0.1.11This is a library for python, that can be used to create tools to automate Iservwithoutan API key
The only thing that is needed is a Iserv account with a username and password.
It is recommended to use a credential file, but you can hardcode your password and username.
This can be done by typing :gen-iserv-credentialThere are pre written Modules, but you can also create your own module automation.ContributingYou can make pull requests and I will be happy to look at them.
If you don't know what to contribute you could add more pre written modules.ExampleIf you want an example you might want to look atthisInstallationInstall this package using pip :pip install auto-iserv
Package: autoit
Automate it with Python.What is this?This Python 3 package aims to help you automate several GUI actions
easily through Python, like clicking, moving the mouse around, using
the keyboard, etc.How to install it?pip install autoitExternal requirements?Windows, orLinuxxdotoolto do anyaitoperation.Python’sXlibto useait.log(mouse/keyboard logger).How does it look like?importait# Click wherever the mouse isait.click()# Click with the right mouse buttonait.click('R')# Click at some positionait.click(140,480)# Click in the center of the screen with the middle buttonait.click(0.5,0.5,'M')# Click 10 pixels belowait.click(0j,10j)# Movement (absolute, percentage and relative) can also be doneait.move(140,480)ait.move(0.5,0.5)ait.move(60j,-9j)# Mouse position can also be retrievedx,y=ait.mouse()# Pressing keys can also be doneait.press('q','!','\n')# Exit vimait.press(*'\b'*10)# 10 backspaces# Writing things with the keyboard tooait.write('Hello world!\n')
Package: autoit-ripper
AutoIt-RipperWhat is thisThis is a short python script that allows for extraction of "compiled" AutoIt scripts from PE executables.ReferencesThis script isheavilybased on 3 resources, definitely check them out if you want to dig a bit deeper into AutoIt stuff:http://files.planet-dl.org/Cw2k/MyAutToExe/index.htmlGithub mirror IGithub mirror IIhttps://github.com/sujuhu/autoithttps://github.com/Cisco-Talos/clamav-devel/blob/31824a659dff37ae03e3419395bb68e659c2b165/libclamav/autoit.cSupported AutoIt versionsReady:EA05AutoIt3.00EA06AutoIt3.26Unknown:JB01AutoHotKeyJB01AutoIT2Installationpython3-mpipinstallautoit-ripperor, if you'd like to install the version from sources:gitclonehttps://github.com/nazywam/AutoIt-Ripper.gitcdAutoIt-Ripper
pipinstall.RunningFrom a python script:fromautoit_ripperimportextract,AutoItVersionwithopen("sample.exe","rb")asf:file_content=f.read()# EA05 for v3.00+, EA06 for v3.26+# Omitting `version` or passing None will try both versionscontent_list=extract(data=file_content,version=AutoItVersion.EA06)From the commandline:autoit-rippersample.exeout_directoryHelp message:autoit-ripper--help
usage:autoit-ripper[-h][--verbose][--ea{EA05,EA06,guess}]fileoutput_dir

positionalarguments:fileinputbinaryoutput_diroutputdirectory

optionalarguments:-h,--helpshowthishelpmessageandexit--verbose,-v--ea{EA05,EA06,guess}extractaspecificversionofAutoItscript(default:guess)Format documentation(In progress)AU3 headerFieldLengthencryption (EA05)encryption (EA06)Notes"FILE"4MT(0x16FA)LAME(0x18EE)static stringflag4xor(0x29BC)xor(0xADBC)auto_strflag (* 2)MT(0xA25E + flag)LAME(0xB33F + flag)UTF-8/UTF-16path_len4xor(0x29AC)xor(0xF820)pathpath_len (* 2)MT(0xF25E + path_len)LAME(0xF479 + path_len)Path of the compiled scriptcompressed1NoneNoneis the script compresseddata_size4xor(0x45AA)xor(0x87BC)compressed data sizecode_size4xor(0x45AA)xor(0x87BC)uncompressed data sizecrc4xor(0xC3D2)xor(0xA685)compressed data crc checksumcreation date4NoneNonefile creation date (high)creation date4NoneNonefile creation date (low)last update date4NoneNonelast edit date (high)last update date4NoneNonelast edit date (low)datadata_sizeMT(checksum + 0x22af)LAME(0x2477)script dataDifferences between v3.00 and v3.26+v3.00v3.26Code storagegreped by magic"SCRIPT" resource (/greped by magic?)String encodingUTF-8UTF-16Encryptionxor/custom MT19937xor/LAME cryptCode encryption keydynamicstaticCompressionyesyesCode "compilation"noyesMagicEA05EA06
Package: autojmp
autojmpAn autojump implementation applicable toany shellandany OSby restoringXython/rtpy.Keep things simple and portable, do not fuck your brain.Common ConfigurationsexportAUTOJMP_MAX_CACHE=999exportAUTOJMP_WORD_ANA_LEN=3# 3-gram is precise enough!ZshFirstly installautojmp:pip install autojmp.Then, append the following contents to your~/.zshrc:autoload-Uadd-zsh-hook

add-zsh-hook-Uzchpwd(){emulate-Lzshajmpupdate"$pwd"}j(){cd"$(ajmpcomplete$@)"}Using it in this way:github>jdeskgit
github>pwd/c/Users/<USER>/Desktop/github
github>jgit
github>pwd/c/Users/<USER>/githubPowerh Shellfunctioncd(){Set-Location"$@"||returnajmpupdate"$pwd"}functionj(){Set-Location$(ajmpcomplete"$@")}MotivationCurrently I have to work on Windows and I do needzsh. This leads me to MSYS2.
However,autojumpinstallation does not work for MSYS2.
Hence I restored my own autojump implementation made years ago.
Package: autojoiner
autojoinerA CLI tool to automate the joining of Zoom or Cisco Webex meetings at scheduled times irrespective of operating system.Uses Selenium to automate the joining of meetings, and uses Task Scheduler orschtasks(Windows) /crontab(Linux) to schedule meetings.Currently supported featuresSchedule the joining of a meeting:autojoiner add [--repeat-weekly] <meeting_link> <start date> <time to join> <task name>where,start date is in format YYYY-MM-DDtime is in format HH:mmImmediately join a meeting (automated using Selenium):autojoiner join <meeting_link>How to installThis package is hosted on PyPi, which means installation as simple as running one command:pip install autojoiner
Package: autokakao
Automation Kakao for MacKakaotalk open chatting room and send message automatically with applescript.APIFirst import package.fromautokakao.wrapperimportKakaoAutomationOpen kakao application manuallykakao=KakaoAutomation()kakao.open_kakao()Open chat room with chat room namekakao=KakaoAutomation()kakao.open_chatroom("CHATROOM NAME")Write a message to sendkakao=KakaoAutomation()kakao.write_message("YOUR MESSAGE")Examplefromautokakao.wrapperimportKakaoAutomationkakao=KakaoAutomation()kakao.open_kakao()kakao.open_chatroom("윤서준")foriinrange(1000):kakao.write_message("윤서준 바보")InstallationpipinstallautokakaoLicenseMIT
Package: autokattis
autokattisUpdated Kattis API wrapper as of May 2023 after the major UI/UX change.SetupSimply install it as a Python package.$pipinstallautokattisUse CasesLoginConstruct aKattisobject that takes in the username and the password.fromautokattisimportKattiskt=Kattis('username','password')kt=Kattis('username')# which will then prompts you for the passwordwhere'username'is your Kattis username/email and'password'is your Kattis account password.Both should be provided as Python strings.Similarly if you want to login to the NUS version of Kattis.fromautokattisimportNUSKattiskt=NUSKattis('username','password')kt=NUSKattis('username')Problem-specifickt.problems()# problems you have solved so farkt.problems(show_partial=False)# exclude partial submissionskt.problems(*[True]*4)# literally all problems on Kattiskt.problems_v2()# problems you have solved so farkt.problems_v2(show_non_ac=False)# literally all problems on Kattiskt.list_unsolved()# let's grind!kt.plot_problems()# plot the points distributionkt.plot_problems(filepath='plot.png')# save to a filepathkt.plot_problems(show_partial=False)# plot fully solved submissionskt.problem('2048')# fetch info about a problemkt.problem('2048','abinitio','dasort')# fetch multiple in onekt.problem_authors()# list down all problem authorskt.problem_sources()# list down all problem sourcesUser-specifickt.stats()# your best submission for each problemkt.stats('Java')# all your Java submissionskt.stats('Python3','Cpp')# multiple languageskt.achievements()# do I have any?kt.suggest()# what's the next problem for me?Ranklistkt.ranklist()# people around youkt.ranklist(top_100=True)# show top 100kt.ranklist(country='Singapore')# country leaderboardkt.ranklist(country='SGP')# use alpha-3 code insteadkt.ranklist(university='National University of Singapore')# university leaderboardkt.ranklist(university='nus.edu.sg')# use university domain insteadNUS-specifickt.courses()# current and recently ended courseskt.offerings('CS3233')# course offeringskt.assignments('CS3233_S2_AY2223')# course assignments but course ID not providedkt.assignments('CS3233_S2_AY2223','CS3233')# course assignmentsConvert to DataFrameAs simple as this!kt.problems().to_df()kt.ranklist().to_df()Useful ReferencesOld UI Kattis API wrapper:https://github.com/terror/kattis-apiMost of the work inautokattisis heavily inspired and motivated by this repository.Kattis official CLI tool:https://github.com/Kattis/kattis-cliSince Kattis has provided an official tool to automate submissions, there won't be such feature inautokattis.Contributingasdf
Package: autokeras
Official Website:autokeras.comAutoKeras: An AutoML system based on Keras.
It is developed byDATA Labat Texas A&M University.
The goal of AutoKeras is to make machine learning accessible to everyone.Learning resourcesA short example.importautokerasasakclf=ak.ImageClassifier()clf.fit(x_train,y_train)results=clf.predict(x_test)Official website tutorials.The book ofAutomated Machine Learning in Action.The LiveProjects ofImage Classification with AutoKeras.InstallationTo install the package, please use thepipinstallation as follows:pip3installautokerasPlease follow theinstallation guidefor more details.Note:Currently, AutoKeras is only compatible withPython >= 3.7andTensorFlow >= 2.8.0.CommunityAsk your questions on ourGitHub Discussions.Contributing CodeHere is how we manage our project.We pick the critical issues to work on fromGitHub issues.
They will be added to thisProject.
Some of the issues will then be added to themilestones,
which are used to plan for the releases.Refer to ourContributing Guideto learn the best practices.Thank all the contributors!Cite this workHaifeng Jin, François Chollet, Qingquan Song, and Xia Hu. "AutoKeras: An AutoML Library for Deep Learning."the Journal of machine Learning research6 (2023): 1-6. (Download)Biblatex entry:@article{JMLR:v24:20-1355,author={Haifeng Jin and François Chollet and Qingquan Song and Xia Hu},title={AutoKeras: An AutoML Library for Deep Learning},journal={Journal of Machine Learning Research},year={2023},volume={24},number={6},pages={1--6},url={http://jmlr.org/papers/v24/20-1355.html}}AcknowledgementsThe authors gratefully acknowledge the D3M program of the Defense Advanced Research Projects Agency (DARPA) administered through AFRL contract FA8750-17-2-0116; the Texas A&M College of Engineering, and Texas A&M University.
Package: autokernel
Quick start guide|Documentation|Gitter ChatAbout autokernelAutokernel is primarily a kernel configuration management tool.
Its main purpose is to generate a kernel.configfile from
a more formal description of your configuration.
To help you writing the configuration, it comes with some helpful features:Detect kernel options for your system (based on information from/sys)Manage the kernel configuration in a more structured and sane way.
Option conflict detection and conditional expressions for configuration statements
allow writing a sound and modular configuration that can be used with multiple kernel versions.Build the kernel (and initramfs) and install them on the systemYou may use it for any combination of the above, There is no need to
use it as a build system if you only want to detect options for your device.Please have a look at theIntroductionsection from the documentation, which explains more about what
this tool is designed for, and how it works.Detecting kernel optionsAutomatically satisfying a kernel optionQuick startTo get started right away, please check out theQuick start guide.
For in-depth command explanations, visit theUsage section.InstallationYou can use pip to install autokernel, or run from source:pippipinstallautokernelFrom sourcegitclone"https://github.com/oddlama/autokernel.git"cdautokernel
pipinstall-rrequirements.txt
./bin/autokernel.py--helpAfterwards you should runautokernel setuponce to create a default configuration
in/etc/autokernel.Kernel hardeningA special note if you are interested in hardening your kernel:
Be aware that autokernel provides a preconfigured module for kernel
hardening (hardening.conf), which is
compatible with any kernel version >= 4.0. Every choice is also fully documented
and explanined. Feel free to adjust it to your needs.AcknowledgementsI would like to especially thank the following projects and people behind them:kconfiglibfor the awesome python library to load and process Kconfig files, whithout which this project would have been impossible.sympyfor the sophisitcated symbolic logic solverlarkfor the great parsing libraryLKDDbfor providing the awesome Linux Kernel Driver Database (which is used for option detection)KSSPfor the great list of kernel hardening optionsCLIP OSfor their well documented and well chosen kernel optionskconfig-hardened-checkfor the collection of options from several kernel hardening resources
Package: autokey
ContentsAboutInstallationZero-installation MethodDocumentationSupportBug reports and Pull RequestsRunning the unit testsChangelogLicenseAboutAutoKey, a desktop automation utility for Linux and X11, formerly hosted atOldAutoKey. Updated to run on Python 3.Important: This is an X11 application, and as such will not function 100% on distributions that default to using Wayland instead of Xorg.InstallationPlease remove previous installations of both AutoKey and AutoKey-py3 fully before installing!For detailed installation instructions, please visit theInstallationpage. in our wiki.Zero-installation MethodAutoKey can also be used directly from the cloned repository. This is useful, e.g., for trying
out a new version without removing a current installation.Start the Autokey daemoncdlibpython3-mautokey.gtkui# or for KDEpython3-mautokey.qtuiStart the Autokey UI (if desired) by appending the –configure or -c command line switch to the end of the command.The commands accept CLI switches just like the regular installation, sopython3 -m autokey.qtui -lcworks as expected.DocumentationDocumentation fornew features. For older features, please refer to the original AutoKey’sscripting API,wiki, andStack Overflow.Examples of AutoKey scripts can be found bysearching GitHuband reading AutoKey’swiki.SupportPlease do not request support on the issue tracker. Instead, head over to the autokey-usersGoogle Groupsforum,StackOverflow, onIRC(#autokey on Freenode), orGitterweb-based chat.We’d appreciate it if you take a look atProblem reporting guidebefore posting. By providing as much information as you can, you’ll have a much better chance of getting a good answer in less time.Bug reports and Pull RequestsBug reports and PRs are welcome. Please use theGitHub Issue Trackerfor bug reports. When reporting a suspected bug, please test against latestgit HEADand make sure to include as much information as possible to expedite troubleshooting and resolution. For example,required:How to reproduce the issue you are experiencingPython tracebacks, if anyVerbose logging information obtained by starting the frontend (autokey-gtkorautokey-qt) from terminal with the--verboseoption.Running the unit testsThe unit test suite has two additional requirements:Pytest (https://github.com/pytest-dev/pytest,https://pypi.org/project/pytest/)PyHamcrest (https://github.com/hamcrest/PyHamcrest/,https://pypi.org/project/PyHamcrest/)Running the test suite is integrated intosetup.py. The tests can be run by executingpython3 setup.py testfrom the repository root directory.ChangelogThe changelog is locatedHere.LicenseGNU GPL v3.See the LICENSE file alongside this README for a plain text copy of the license text.
Package: autolab
AutolabPython package for scientific experiments automationThe purpose of this package it to provide easy and efficient tools to deal with your scientific instruments, and to run automated experiments with them, by command line instructions or through a graphical user interface (GUI).Created by Quentin Chateiller, Python drivers from Quentin Chateiller and Bruno Garbin, for the C2N-CNRS (Center for Nanosciences and Nanotechnologies, Palaiseau, France) ToniQ team.Visithttps://autolab.readthedocs.io/for the full documentation of this package.
Package: autolabel
AutolabelAutolabel is an image labeling tool.
Currently images are labeled usingResNet18-152implemented bypytorch.
Autolabel can be used as a cli tool or as a library.Installationpython setup.py installCommand line usageSee--helpfor a command overviewUsage: autolabel [OPTIONS] [IMAGES]...

Options:
  --batch-size INTEGER
  --sep TEXT                      Separator
  --top INTEGER
  -o, --output FILENAME           Output file
  -m, --model [resnet18|resnet34|resnet50|resnet101|resnet152]
  --help                          Show this message and exit.In the simplest form this mean:autolabelimage.jpgAutolabel supports reading file names from STDIN:find/myimages-typef-iname'*.jpg'|autolabelLibrary usagefromautolabel.imageimportImageListDatasetfromautolabel.classifier.resnetimportResnet18ClassifierfrompathlibimportPathclassifier=Resnet18Classifier()images=[Path('/path/to/image.jpg'),Path('/path/to/another/image.png')]dataset=ImageListDataset(images)res=classifier.predict(dataset,top=top)forp,decodedinres.items():print(p,decoded)
Package: auto-labeling-pipeline
Auto labeling pipelineAuto labeling pipeline helps doccano to annotate a document automatically. This package is intended to be used from the inside of doccano. You shouldn't use this package directly.InstallationTo install auto-labeling-pipeline, simply run:pipinstallauto-labeling-pipelineHow to contributeYou can contribute this project by adding new templates as follows:Add a new request model class tomodels.py.Add a new template(Jinja2 format) totemplates/directory.Add a new template class tomappings.py.Add a new option tomenu.py.Testing.LicenseMIT