Saravanan666/pypi-org huggingface dataset:
Package: expy
# OverviewExpy is an simple-yet-powerful experiment framework builder for cognitive tasks. It's aimed at setting up an experiment without struggling with the manual production of stimuli, data loading and storing, or the other time-consuming works.**Highlights**:- Various stimuli modules (not need for preparation of massive stimuli pictures).- Various procedure-controlling modules (instruction, tip, rest-stage, etc.)- Convenient for stimuli loading and responses recording.- Convenient for getting participants' response data (from keyboard, mouse, or joystick).- Sending triggers easily.- Easy pause or exit from the program.**Limitation**:- Not good at drawing complex shape (e.g.,grating) as stimuli (however, you could draw them as loaded pictures).---## DocumentationSee http://expy.readthedocs.io/en/latest/ for introduction, tutorials, and reference manual.---# Installation instructionsExpy has been tested on Python3.X 64bit.(Current it might be unfit for older versions like Python2.7. But since Python2 will become obsolete in the years to come, why not drop it anyaway and take Python3 instead?)The simplest way to install Expy is through the Python Package Index (PyPI), which ensures that all required dependencies are established. This can be achieved by executing the following command:```pip install expy```or:```sudo pip install expy```###*Required Dependencies*- numpy- pandas- scipy- pygame- pyaudio- wave- pyserial---# Simple example (An RSPV demo)```python# coding:utf-8from expy import * # Import the needed functionsstart() # Initiate the experiment environmentfor w in 'ABCDE12345':drawText(w) # Draw something on the canvas(not the screen)show(0.2) # Display current canvas on the screen, and keep for 0.2s```
Package: expybox
ExpyBoxExpyBox is a Jupyter notebook toolbox for model interpretability/explainability.
It lets you create interactive Jupyter notebooks to explain your model.DocumentationUsageThis package is meant to be used inside of Jupyter notebook, other usage makes little to no sense.
First you need to import and instantiate the ExpyBox class:fromexpyboximportExpyBoxexpybox=ExpyBox(train_data,predict_function,kernel_globals=globals())Now you can use the supported interpretability methods like  this
(for list of supported methods refer to thedocumentation):expybox.lime()which creates a form:In this form you can set up explained instance (if it's necessary for the selected method)
and method parameters. After clicking onRun Interactthe method will be executed
and its output will be shown below the form.You can then change the parameters or the explained instance and pressRun Interactagain which will rerun the method with new parameters.You can find an example Jupyter notebook inexamplesfolder.InstalationBecause ofalibipackage ExpyBox requires64-bitPython 3.7 or higher.
It is also recommended to create separate virtual enviroment - you can use Pythonsvenv.Otherwise the installation process is the same as for other packages, just use pip:pipinstallexpybox
Package: expyct
ExpyctPartial matching of any Python object.Explore the docs »Report Bug·Request FeatureTable of ContentsExpyctGetting StartedPrerequisitesInstallationUsageRoadmapContributingLicenseContactAcknowledgementsExpyctPartial matching of any Python object.importexpyctasexpdeftest_my_function():result=my_function()assertresult==exp.Float(optional=True,close_to=0.076,error=0.01)Using Expyct is a good idea when you need to assert something in a test case but there is some non-determinism.For example, rounding errors prevent you from comparing afloatexactly. Or a timestamp is created on-the-fly, and
therefore changes every test run.In these cases, you need to be able to set specific constraints on the expected value. That is what Expyct is for!The constraints can be provided as constructor arguments. For examplen == Number(min=3, max=5)is only true whennis between 3 and 5.Some other examples of classes areFloat,String,AnyandDateTime. As you can see, they closely match the
built-in Python types.The library also comes with many commonly used data validators likeANY_UUIDwhich matches any UUID string.
AndTODAYwhich matches any datetime occurring on the current day.Checking nested data structures is easy as well.SeeUsage examplesGetting StartedPrerequisitesSupported and tested for:Python 3.6Python 3.7Python 3.8Python 3.9InstallationpipinstallexpyctOr install using any Python package manager like conda, pipenv or poetry.UsageSee below examples of how to use Expyct withpytest.Simple example:importexpyctasexpfrommyclassimportMyClassdeftest_my_function():result=my_function()assertresult==exp.AnyValue(instance_of=MyClass,vars={"property":"value"})More complicated nested example:importexpyctasexpfromdatetimeimportdatetimedeftest_my_function():result=my_function()assertresult=={"first_name":exp.String(regex="(mary)|(peter)",ignore_case=True),"last_name":"Johnson","signup_date":exp.DateTime(after=datetime(2020,1,2),before=datetime(2020,3,5)),"details":{"number":exp.Int(min=2),"amount":exp.Float(close_to=2.3,error=0.001),"purchases":exp.List(exp.Dict(keys={"id","product","category"}),non_empty=True),},"time_of_purchase":exp.OneOf([exp.TODAY,exp.THIS_HOUR]),"type":exp.AnyType(subclass_of=str),"item_ids":exp.Set(subset_of=[1,2,3]),"metadata":exp.Dict(keys_any=exp.Collection(superset_of=["a","b"])),"context":exp.ANY,}RoadmapSee theopen issuesfor a list of proposed features (and known issues).ContributingAny contributions you make aregreatly appreciated.Fork the ProjectCreate your Feature Branch (git checkout -b feature/AmazingFeature)Commit your Changes (git commit -m 'Add some AmazingFeature')Bump the version inexpyct/__version__.pyfollowingSemVerPush the Branch (git push origin feature/AmazingFeature)Open a Pull RequestBefore starting to contribute to Expyct, please installpre-committo make sure your changes
get checked for style and standards before committing them to repository:$ pre-commit installLicenseDistributed under the MIT License. SeeLICENSEfor more information.ContactPlease file an issue on Github.Acknowledgementsothneildrew/Best-README-Template
Package: expylain
# `expylain``expylain` is a Python package for Jupyter notebooks that enables rapidinteractive exploration of random processes. It is designed for ease-of-use inlearning contexts.## Example`expylain` works by taking `Data` and defining `Step`s that work on the data.Each `Step` is just a Python function that takes in data from the previous`Data` or `Step`. `Data` and its `Steps` are grouped in a `Process`.For example, to flip a coin that lands heads with probability `p`:```pythonfrom random import randomdef flip(coin, p=0.5):return coin[0] if random() < p else coin[1]Process([Data(['H', 'T']),Step(flip),])```**Output:**```Data: ['H', 'T']|flip  |v'H'[Rerun]```The real power of `expylain` results when using its built-in support forinteractive functions:```pythonProcess([Data(['H', 'T']),# Specify a (start, end, step) for the arg pStep(flip, p=(0, 1, 0.1)),])```**Output:**```Data: ['H', 'T']|flip  | p: 0 --- | ---- 1  [0.5]|v'H'[Rerun]```This allows you to interact and visualize random processes:```pythonfrom random import choicesfrom bqplot import pyplot as pltdef flip_n(coin, p=0.5, n=100):return choices(coin, weights=[p, 1-p], k=n)def plot_flips(flips):heads, tails = flips.count('H'), flips.count('T')plt.bar(['H', 'T'], [heads, tails])Process([Data(['H', 'T']),Step(flip_n, p=(0, 1, 0.1), n=(50, 500, 50)),Step(plot_flips),])```**Output:**```Data: ['H', 'T']|flip_n  | p:  0 --- | --- 1    [0.5]| n: 50 --- | --- 500  [100]|v['H', 'T', ..., 'H']|plot_flips|v<bar_chart>[Rerun]```Processes can be composed, giving high expressivity. The `Repeat` constructorallows the output of multiple runs of a process to become an input to a nextstep:```pythondef count_heads(flips):return flips.count('H')heads_in_n_flips = Process([Data(['H', 'T']),Step(flip_n, p=(0, 1, 0.1), n=(50, 500, 50))Step(count_heads)],name='heads_in_n_flips',)distribution_of_heads = Process([Repeat(heads_in_n_flips, times=1000),Step(plt.hist),])```**Output:**```+-------------------------------------------+|   Data: ['H', 'T']                        ||             |                             ||     flip_n  | p:  0 --- | --- 1    [0.5]  ||             | n: 50 --- | --- 500  [100]  ||             |                             ||             v                             | heads_in_n_flips|    ['H', 'T', ..., 'H']                   ||             |                             || count_heads |                             ||             v                             ||             48                            |+-------------------------------------------+|Repeat(1000) |v[48, 49, ..., 50]||v<histogram>[Rerun]```## Getting StartedRun these commands in your terminal to install `expylain` and its Jupyterextension:```pip install expylainjupyter nbextension enable --py --sys-prefix expylain```
Package: expy-python
ExPyThe sophisticated tool needed for scientific computing.Documentation:https://youseitakei.github.io/expySource code:https://github.com/YouseiTakei/expyContributing:coming soonBug reports:coming soonWebsite:coming soonIt provides:useful rendering formula, Formula deformation.simply converting Jupyter notebook to PDF based on nbconvert.To get the latest version :fromhttps://pypi.python.org/pypl/experiment-python/$ pip install expy-pythonTo get the latest version do:$ git clone git://github.com/YouseiTakei/expy.git$ cd expy$ python setup.py installDocumentation and usage:Everything is at: coming soonFrom this directory, start Jupyter notebook and:>>>fromexpyimportF,x_,y_,>>>f=F(y_,x_**x_)>>>f.set(x_,0)>>>f.tex()Convert your Jupyter notebook. start cmd line and:$ nbc -a -p -tUsage Example:UsageDetailnbc -hcheck args helpnbc -i test.ipynbconvert to pdfnbc -a test_dirconvert all file in your directorynbc -r test.pdfremove converted pdf file or all files in directorynbc -i test.ipynb -o htmlconvert to htmlnbc -a test_dir   -o htmlconvert all files to htmlnbc -r test_dir   -o htmlremove all html files in directorynbc -i test.ipynb -p result\today\use output pathnbc -i test.ipynb -t data\article.tplxuse your templateOther Usage Hints:If you want to change template file, you can edit file in~/.expy/latex/article.tplxIf you don't have auth and can't install this, you can use$pip install expy-python --userIf you can't convret pd.DataFrame, you should run 'ep.init_ep()'Call for Contributions:If you have found ExPy to be useful in your work, research or company,
please consider making a donation to the project commensurate with your resources.
Package: expyriments
expyrimentsOrganize, run, track and share experiments & data.Getting Started•Features•Documentation•Support•Contribution•ChangelogTODOHighlightsTODOGetting StartedInstallationRequirements: Python 3.6+.pipinstallexpyrimentsUsageTODOSupport & FeedbackThis project is maintained byBenjamin Räthlein,Lukas Masuch, andJan Kalkan. Please understand that we won't be able to provide individual support via email. We also believe that help is much more valuable if it's shared publicly so that more people can benefit from it.TypeChannel🚨Bug Reports🎁Feature Requests👩‍💻Usage Questions🗯General Discussion❓Other RequestsFeaturesTODODocumentationCLI InterfaceTODOPython ClientTODOContributionPull requests are encouraged and always welcome. Read ourcontribution guidelinesand check outhelp-wantedissues.Submit Github issues for anyfeature request and enhancement,bugs, ordocumentationproblems.By participating in this project, you agree to abide by itsCode of Conduct.Thedevelopment sectionbelow contains information on how to build and test the project after you have implemented some changes.DevelopmentRequirements:DockerandActare required to be installed on your machine to execute the build process.To simplify the process of building this project from scratch, we provide build-scripts - based onuniversal-build- that run all necessary steps (build, check, test, and release) within a containerized environment. To build and test your changes, execute the following command in the project root folder:act-b-jbuildRefer to ourcontribution guidesfor more detailed information on our build scripts and development process.LicensedMIT. Created and maintained with ❤️  by developers from Berlin.
Package: exPython
pacotepypipacotepypiÃ© um simples pacote para exibir nÃºmeros de 1 a 9 em Python.DependÃªnciasPython 3.6ou posteriorPacotenumpyComeÃ§ando o usoVocÃª vai precisar instalar o pacotepacotepypi, para isso basta executar:pip install pacotepypiFunÃ§Ã£oexibir ()- Mostra nÃºmeros de 1 a 9
Package: exql
exqlPersist Excel/CSV sheets to MySQL (and vice versa)Installationpip install exqlHow it worksConvert a directory into a database and the .csv and .xls files in that directory to tables (or vice versa i.e. database/table to director/.csv). Currently, only .csv/.xsl to MySQL conversion is supported.directory <==> database
CSV/Excel sheets in directory <==> tables in databaseFor example,MyDir           <->     CREATE SCHEMA MyDir;
|-file1.csv     <->     CREATE TABLE file1 (...);
|-file2.xlsx    <->     CREATE TABLE file2 (...);UsageImport exql and create an Exql object passing your MySQL username, password, etc.fromexqlimportexqlexql_obj=exql.Exql("root","mysql@123","localhost",3306,False)Create a database by passing path of directory to be converted to a DB. A sample directory is present in theresourcesdirectoryexql_obj.create_db_from_directory("/path/demo_university_db")Similarly, other methds can be used to create individual tables, delete rows, etc.MethodDescriptioncreate_db_from_directoryCreate MySQL DB with name same as the directory name and tables built using .csv/.xlsx files present within the directorycreate_table_from_csvPersist data from a .csv/.xslx file to a single MySQL tableinsert_in_tableInsert data from .csv into existing tableselect_into_csvSelect rows read from a DB using the provided query into a .csvdelete_from_dbDelete rows matching column-value pairs provided in .csv from MySQL tablewrite_db_to_dirCreate a directory containing all tables of a DB saved as .csv filesNoteIn the .xsl or .csc files, SQL commands can be provided directly. Thus, the .csv or .xsl can have SQL queries as followsstudent_idnameageadded_onINTVARCHAR(100)INTDATETIMEPRIMARY KEYNOT NULLNOT NULL100001(SELECT UPPER('John Keats'))45now()100002'William Shakespeare'23now()(SELECT COUNT(*) FROM table2)'Robert Frost'54now()Cells containing text must be enclosed in inverted commas or else they would be interpreted as SQL keywords/identifiersRefer to theresourcesfolder for .csv/.xsl file templates needed for table creation/insertion/deletion
Package: exquires
Website:http://exquires.caPyPI:http://pypi.python.org/pypi/exquiresGitHub:http://github.com/aturcotte/exquiresLicense:BSD 2-Clause LicenseAuthors:Adam Turcotte and Nicolas RobidouxOnline DocumentationThe documentation for the latest release version ofEXQUIREScan be
viewed online athttp://exquires.ca.Building the DocumentationTheEXQUIRESdocumentation/website is built usingSphinx.Before building the documentation, you must first perform the following tasks:Install Sphinx ($ sudoapt-getinstallpython-sphinx)InstallEXQUIRESTo produce the HTML documentation (same as the online documentation):From thedocsdirectory, run:$ make htmlThis will produce HTML documentation in the_build/html/directoryOpen_build/html/index.htmlwith your browserTo produce the PDF manual:From thedocsdirectory, run:$ make latexpdfThis will produce LaTeX files in the_build/latexdirectory and run them
through pdflatexOpenexquires.pdfto view the manual.
Package: exr-aws
AWS boto3 helper libsFeaturesCommon use cases covered under single methodsKeeps build files clean and powerfullInstallationYou can install exr-builder from the Python Package Index (PyPI) or from
source.Using pip$pipinstallexr-awsUsing easy_install$easy_installexr-awsExampleTODOContributors/ContributingIf you want to make changes the repo is athttps://github.com/exrny/exr-aws. You will needpytestto run the tests andexr-buildertool to build modules$nbtestIt will be great if you can raise apull
requestonce
you are done.If you find any bugs or need new features please raise a ticket in theissues sectionof the
github repo.Licenseexr-builder is licensed under aMIT
licenseChanges0.1.0 - 04/02/2018Initial release.
Package: exrc
eXRCReddit OAuth2 client to access Reddit resources viaOAuth2, powered byhttpx&websocket-client.Package Installation GuideRequiresPython 3.11+pip package managerInstall from sourcepip install -e git+https://github.com/eXhumer/pyeXRC.git@python3#egg=exrcInstall from PyPIpip install exrcLicensingThis project is licensed under OSI ApprovedGNU AGPLv3ONLY.
Package: exreporter
Exreporter is an MIT Licensed library, written in Python to report internal server errors and exceptions in background applications to issue trackers such as Github.This will help in reducing the dependency on error emails for internal server error notifications and to manage them in a single, right place. Reported issues contain everything a developer needs, debugging got a whole lot simpler.Also it should be easy to use:fromexreporter.credentialsimportGithubCredentialsfromexreporter.storesimportGithubStorefromexreporterimportExReportergc=GithubCredentials(user="username",repo="repo-name",auth_token="personal-token")gs=GithubStore(credentials=gc)reporter=ExReporter(store=gs,labels=['Bug'])reporter.report()FeaturesCreates issues in issue trackersAggregate same kind of issuesHandle multiple occurrenceUsageUsage reference available athttps://exreporter.readthedocs.org/en/latest/usage.htmlDocumentationDocumentation is available athttps://exreporter.readthedocs.org/.TODOSAdd support for BitbucketHistory0.1.0 (2014-12-11)First release on PyPI.0.1.1 (2014-12-15)Change development status to Alpha.Also add contrib module - django_middlewares0.1.2 (2015-04-04)Change public APIRefactor github issue search
Package: exsimple
sources:https://github.com/XenoAmess/EXsimplerelease:https://pypi.org/project/exsimple/# living examplehttp://dailypaste.com/# what is it:It is used as a public, open, share net-disc.Yes,it supports multi-files upload in one turn.Actually it is a light Web application framework  exactly easy to deploy , which has implyments of POST,GET,HEAD methods.# drag it to move!It might be really hard to notice it without Instructions.![dragit](pic/drag.gif)# enter a not-in-use url, and press Enter,then press new-folder button,boom!a new folder appears!It might be really hard to notice it without Instructions,too.![dragit](pic/newFolder.gif)# clone git repo and zip it into current folder for download!You know some people have bad connection to some git repo, so this can be used as a cache.![dragit](pic/gitClone.gif)You must have git installed on the server machine before you do that.# cache files from url to server!Sometimes we just need this.![dragit](pic/cache.gif)Do not cache large files tohttp://dailypaste.com.I have only 20G ssd there.Feel free to do that on your own vps.# get it in a iframe, and it would be streamline smartly!<iframe src=”http://dailypaste.com/” frameborder=”0” scrolling=”no” width=”404” height=”604”>Dailypaste!</iframe># Do not upload a file with a same name to a file in the same folder.doing that would replace the old file with the new one,the old file just rest-in-peace.this is used for people to update their own file,not used to f**k up others’ file.I hope nobody shall be that bad person,making fun in others’ pain.# notice:some codes are modified from others’ in their blogs.I had put links on the front these codes.of course I had no complete rights with these codes.thanks for the original authors to write blogs to teach me so much.thank you.if you are one of these authors,but you don’t want me use your code ,please tell me.I will rewrite that part.# how to use:simple: (in windows)double click.it will show start and show you what you wanna know.(in linux)cd to the folder witch exsimple.py in.python3 exsimple.pyit will show start and show you what you wanna know.advanced:open the score code to change whatever you want.also,notice that if you use pypy3 instead of python3,it might run far faster.nuitka is even far more faster than pypy.but it is not so easy to use.pypi:pip install exsimplescreen -dmS exsimple exsimple# Acceleration solutionA acceleration solution of this project is hold on: [SpeedyExsimple](https://github.com/XenoAmess/SpeedyExsimple).Which is used on current version of dailypaste.comPlatform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Package: exsnap
exsnapAutomate the downloading of Snapchat memories usingmemories_history.jsonfrom a data export request.How to useInstall the package viapip install exnsap.Perform adata requestwith Snapchat.Download your data zip when created and extractjson/memories_history.json.Runexsnapin the folder of your choice.You can specify-ifor the location of the JSON if not in the current working directory,
or it has a different name.You can specify-ofor the output folder if you don't want the current working directory.
Package: exso-kamabay-beautify
beautify the appearance of the application in the terminal.what can be done, give the text color, text background, change the font, choose a banner according to the category of your choice.Method PropertyfontstringstextArtlist_artlist_fontdecorationhelp_me_brorandom_fonturl_stringslist_ascii_artlist_decorationFontslist font 1list font 2Artart list 1art list 2Decorationdecor list 1decor list 2Banner list namecategory banner list namethe color of the strings.frombeautifyimportBeautify# Beautify(**kwargs).method_nameprint(Beautify(string="Hello Dunia Apa Kabar?",font="scammer",color="#magenta",#can use,name color,hex,rgbbg_color=None).font)#can use,name color,hex,rgbthe class keyword in the method.Beautify(kwargs).fontstringfontcolorbg_colorBeautify(kwargs).decorationdecorationreverse “True/False”colorbg_colorBeautify(kwargs).stringsstringcolorbg_colorBeautify(kwargs).url_strings(kwargs)in Beautify()urlcolorbg_colorin url_strings()Attribute ‘default None’Class ‘default None’Beautify(kwargs).textArtstringcolorfontdecorationbg_colorBeautify(kwargs).random_fontstringfont1font2font3font4colorbg_colormethod to see all list.Beautify(category=category banner list name).list_ascii_artBeautify().list_fontBeautify().list_artBeautify().list_decoration
Package: exsort
IntroductionI found Python doesn’t have a convenient module to sort huge list that is
unable to fit in memory.Installationexsort is distributed onPyPIas a universal
wheel and is available on Linux/macOS and Windows and supports
Python 2.7/3.5+ and PyPy.$pipinstallexsortLicenseexsort is distributed under the terms of theMIT License.
Package: exsource-tools
ExSource-ToolsAn experimental Python library for validating and using theExSource Specificationwhich is in the early stage of development.This packages adds the following command:exsource-make exsource.ymlThis will attempt to processexsource.ymlto create inputs. The first instance of this proof of principle implementation supports OpenSCAD and some FreeCAD files. FreeCAD exporter will expect there to be a PartDesign Body calledBody, it can export this to STEP and/or STL.
Package: exspy
exSpyis a Python package extending the functionality for multi-dimensional
data analysis provided by theHyperSpylibrary. It is
aimed at helping with the analysis of X-rays Energy Dispersive Spectroscopy (EDS)
and Electron Energy Loss Spectroscopy (EELS).Go to the documentation for instructions on how to install exSpy and start an
analysis:Read the docs.Everyone is welcome to contribute. Please read ourcontributing guidelinesand get started!Development of exSpy is documented in thechangelog.