Saravanan666/pypi-org huggingface dataset:
Package: exporter
exporterexporter is a simple package that helps to export Jupyter notebooks as a Python script.
Add#exportor# exportcomments anywhere in the notebook cell you want to export as a Python script. Cells in
the same notebook will be exported to the same Python script.You can also export codes from Jupyter notebooks and Python scripts as an image.Installationpip install exporterCheckPyPIfor all the versions available.Installation for Image Export FunctionalityTo work with image export functionality you need to installwkhtmltopdf.Ubuntu/Debiansudo apt-get install wkthtmltopdfMacOSbrew install wkhtmltopdfWindows and other optionsCheckWktmltopdfdownload page.Basic UsageAdd#exportor# exportcomments to cells you want to export.Option 1: Use command line.exporter notebook_path.ipynb output_path.pyFor all the options:exporter --helpOption 2: Use Python function.fromexporterimportexportexport("notebook_path.ipynb","oytput_path.py")Export Code as a ImageAdd# image-export-startand# image-export-endcomments
to the start and end of the code blocks you want to export.
(You can export more than one code block!)List all the available styles.image-exporter --stylesOption 1: Use command line.image-exporter script.py output_path styleorimage-exporter notebook.ipynb output_path styleFor all the options:exporter --helpOption 2: Use Python function.fromexporterimportimage_export,available_stylesprint(available_styles())image_export("script.py","exported_images","colorful")ExamplesSome examples with different styles.emacsfriendlynativevs
Package: export-file
Install$[sudo]pipinstallexport-fileFeaturescreate environment variables from text files - filename as variable name, content as valueignore not existing and empty filesUsageusage:export-filepath...Examples$export-filedescription.txtkeywords.txtexportDESCRIPTION="@accepts decorator to check arguments types"exportKEYWORDS="type decorator"$eval<<<export-filedescription.txtkeywords.txt
$echo$DESCRIPTIONrepodescriptionfindfiles:$ IFS=;find="$(find -H . -type f -name "*.txt")"
$ [[ -n "$find ]] && { IFS=$'\n';set $find; eval "$(export-file "$@")"; }
Package: export-ig
Export Images for IGAdd padding around image, drop shadows.How to UseInstall packages.pipinstallexport_igRunexport_ig--input_path"*.jpg"--output_folderpadded/--subfolder\--aspect_ratio4x5--shadow_offset32--radius12--shadow_colorgray\--pad100--bg_colorwhite\--n_jobs10input_path: glob string for input files. When using wildcard (*), make sure to
wrap it in quotes so that it does not get expanded by bash.output_folder: folder to contain processed images.subfolder: when set, theoutput_folderis created within theinput_pathfolder.aspect_ratio: aspect ratio of output image. Auto adjusted for portrait and landscape. Should be separated by "x".shadow_offset: offset for shadow (in pixels). negative number leads to shadow on top-left diagonal of the image.radius: blur radius for the shadow.shadow_color: can be either hex string value (with or without #) or color names in {white, black, gray}bg_color: color for the padded background.pad: amount (in pixels) to pad.n_jobs: how many threads to use.ExamplesBeforeAfter
Package: exportrecipe
This is a Buildout recipe, that can export buildout configuration to JSON file.
Later this exported file can be used to get exported settings and use them in
your project.Buildout provides extensive functionality for managing configuration, but does
not have tools to use this configuration anywhere else outside Buildout itself.
This recipe exports all settings to JSON file, allowing to use configuration
parameters outside Buildout.Usage[buildout]parts=settings[settings]recipe=exportrecipewebsite-url=http://example.com/This will generatesettings.jsonfile in your buildout directory with following content:{"website-url":"http://localhost:8000/"}exportrecipewill export all parameters from recipe’s section, exceptrecipeparameter.Now you can use this file for example in yoursettings.py:importjsonwithopen('settings.json')asf:settings=json.load(f)WEBSITE_URL=settings['website-url']Also you can use a helper:importexportrecipeconfig=exportrecipe.load('settings.json')WEBSITE_URL=config.website_urlIt is possible to change destination of exported file usingdestinationoption:[buildout]parts=settings[settings]recipe=exportrecipedestination=somewhereelse.jsonwebsite-url=http://example.com/This will generatesomewhereelse.jsonfile with following content:{"destination":"somewhereelse.json","website-url":"http://localhost:8000/"}Change History0.2 (2015-05-17)Initial public release.
Package: export-torrent-cache
Most torrent clients maintain a directory containing all the torrents that are currently loaded in the client.
However they are unorganized and typically have been renamed to the infohash of the torrent. This script processes these torrents
and restores them to their original name and organized by tracker based on the announce URL. It was written with private torrents in mind, which
generally only have one announce URL. If the script encounters a torrent with multiple announce URLs,
it will only consider the first URL for organization.This has only been tested with qBittorrent, but it should work with any directory containing a flat list of valid torrents. Subdirectories are not traversed.Dependencies:torrent_parserUsage:$ export_torrent_cache <source_dir> <destination_dir>Examples:$ ls ~/.local/share/data/qBittorrent/BT_backup/
[lots of .torrent files with unhelpful names]

$ export_torrent_cache ~/.local/share/data/qBittorrent/BT_backup/ ~/torrents_backup
Processing ~/.local/share/data/qBittorrent/BT_backup/[infohash].torrent 
All torrents processed succesfully

$ tree ~/torrents_backup
~/torrents_backup
├── Tracker URL
│   ├── Original_Filename.torrentInstallationFrom PyPI$ pip install export_torrent_cacheFrom source repository$ git clone https://github.com/codeclem/export_torrent_cache
$ cd export_torrent_cacheFrom here you can manually installtorrent_parserand run theexport_torrent_cache.pyscript directly, or build and install a package like so:$ python setup.py sdist
$ pip install dist/export_torrent_cache-0.1.tar.gzWhich will also fetch and installtorrent_parseras a dependency for you.
Package: export-to-telegraph
export_to_telegraphLibrary for export webpage to Telegraph.usageimport export_to_telegraph
export_to_telegraph.TOKEN = YOUR_TELEGRAPH_TOKEN
telegraph_url = export_to_telegraph.export(webpage_url)If export failed,telegraph_urlwill be None.how to generate tokenToken is not needed if you don't plan to edit the generated telegraph.Example code:from html_telegraph_poster import TelegraphPoster
poster = TelegraphPoster()
api_response = poster.create_api_token(shortname, longname)
token = api_response['access_token']how to installpip3 install export_to_telegraph
Package: exposan
What isEXPOsan?TheEXPOsanpackage contains systems developed using theQSDsanpackage. A list of the developed systems is included in QSDsan’sdocumentation. Please refer to the individual README files within each system module for loading instructions and exemplary results.InstallationThe easiest way is throughpip, in your command-line interface (e.g., Anaconda prompt, terminal):pipinstallexposanIf you need to upgrade:pip install -U exposanor for a specific version (replace X.X.X with the version number):pip install exposan==X.X.XIf you want to install the latest GitHub version at themain branch(note that you can still use the-Uflag for upgrading):pip install git+https://github.com/QSD-Group/EXPOsan.gitNoteIf this doesn’t give you the newestexposan, trypip uninstall exposanfirst.Also, you may need to update someexposan’s dependency package (e.g., ‘qsdsan,biosteam,thermosteam) versions in order for the newexposanto run.or other fork and/or branch (replace<USERNAME_OF_THE_FORK>and<BRANCH_NAME>with the desired fork and branch names)pip install git+https://github.com/<USERNAME_OF_THE_FORK>/EXPOsan.git@<BRANCH_NAME>You can also download the package fromPyPI.To get the git version (use thedepthflag to choose how many commit histories you want to clone):gitclonehttps://github.com/QSD-Group/EXPOsan.git--depth=1then navigate into the repository (cd EXPOsan) and install the required packages:pipinstall–rrequirements.txtNoteUsing thedepthflag will only clone the main branch by default, if there are other branches and you want them, then use theno-single-branchflag, i.e.gitclonehttps://github.com/<YOUR_USERNAME>/EXPOsan.git--depth=1--no-single-branchAuthors and ContributingEXPOsanis developed by the Quantitative Sustainable Design Group led by members of theGuest Groupandother developersthat have contributed to the repository.Yalin Li) is the currently maintainer of this repository and package.Please refer to theContributing to QSDsansection of the documentation for instructions and guidelines. If you find yourself struggle with the installation/setting up the environment, this extended version ofinstallation instructionsmight be helpful to you.Stay ConnectedIf you would like to receive exciting news related to the QSDsan platform, you can subscribe to email updates usingthis form(don’t worry, you will be able to unsubscribe :)). Thank you in advance for your interest!License informationPlease refer to theLICENSE.txtfor information on the terms & conditions for usage of this software, and a DISCLAIMER OF ALL WARRANTIES.
Package: exposed-github-user-emails-scanner
showExposedGitHubEmailsIs a crawler which lists all email addresses used in commits of a specific GitHub user using the GitHub API.It iterates through all public respositories owned by the user and all commits in each of these repositories.InstallationInstall the package with pippip install exposed-github-user-emails-scannerUsageTypeshowExposedGitHubEmails  --helpto view the help.usage: showExposedGitHubEmails [OPTION]... -u USERNAME

A crawler which lists all email addresses used in commits of a specific GitHub user using the GitHub API.

optional arguments:
  -h, --help            show this help message and exit
  -u USER, --user USER  username of the user whose public repositories should be scanned
  -r REPOSITORY, --repository REPOSITORY
                        name of specific repository which should be scanned (default is all repositories)
  -t TOKEN, --token TOKEN
                        provide a GitHub token to increase the API quota which can be used by this script
  -v, --verbose         verbose mode
  -d DELAY, --delay DELAY
                        the delay between to requests in seconds (default is 1 second)
  --api-url API_URL     specify the URL to the GitHub Api (default is "https://api.github.com")
  --no-forks            ignore forked repositoriesExample$ showExposedGitHubEmails -u AFictionalUsername
[+] Scan for public repositories of user AFictionalUsername
[+] Found 4 public repositories
[+] Scan repository my_first_project
[+] Scan repository project_2
[+] Exposed emails and names:
         41277220+aficionalusername@users.noreply.github.com - John Doe
         john.doe@hotmail.com                                - JD; John Doe
         john.doe@company.com                                - John Doe (Software Eng.)
Package: exposure
ExposureWith Exposure you can compute the exposure for a photo camera based
on settings of the camera and metrics of the environment.Installationpip install exposureUsage>>> from exposure import Av, Tv, Sv, Bv, Iv, Exposure
>>> from decimal import Decimal
>>> from fractions import FractionAperture>>> Av.from_stop(1)
Av f/1.4

>>> Av.from_focal_length_and_diameter(10, 5)
Av f/2.0

>>> Av.from_fstop(Decimal("1.4"))
Av f/1.4

>>> Av.from_fstop(Decimal("22")).stop
Fraction(9, 1)

>>> Av.from_fstop(Decimal("22")).fstop
Decimal('22')Speed>>> Sv.from_iso(100)
Sv 100 ISO

>>> Sv.from_stop(Fraction(1, 1))
Sv 200 ISO

>>> Sv.from_iso(100).stop
Fraction(0, 1)

>>> Sv.from_iso(100).iso
100Shutter>>> Tv.from_stop(1)
Tv 2 sec

>>> Tv.from_time(Fraction(10, 13))
Tv 10/13 sec

>>> Tv.from_time(Fraction(2, 1)).stop
Fraction(1, 1)

>>> Tv.from_time(Fraction(2, 1)).time
Fraction(2, 1)Brightness>>> Bv.from_foot_lamberts(1)
Bv 3.4 cd/m2

>>> Bv.from_candelas(109)
Bv 109.2 cd/m2

>>> Bv.from_stop(3)
Bv 27.4 cd/m2

>>> Bv.from_stop(3).stop
Fraction(3, 1)

>>> Bv.from_stop(3).candelas
27.4

>>> Bv.from_stop(3).foot_lamberts
8Incident Light>>> Iv.from_foot_candles(25)
Iv 269.2 lux

>>> Iv.from_lux(1076)
Iv 1076.0 lux

>>> Iv.from_stop(3)
Iv 537.6 lux

>>> Iv.from_lux(1076).stop
Fraction(4, 1)

>>> Iv.from_lux(1076).lux
1076.0

>>> Iv.from_lux(1076).foot_candles
99.9Exposure>>> tv = Tv.from_stop(1)
>>> av = Av.from_stop(2)
>>> sv = Sv.from_stop(2)
>>> bv = Bv.from_stop(1)
>>> iv = Iv.from_stop(1)

The exposure is in balance when

>>> tv + av == sv + bv
True

or

>>> tv + av == sv + iv
True

This can also be used to compute a needed setting, like

>>> Tv.from_exposures(sv, bv, av)
Tv 2 sec
>>> Tv.from_exposures(sv, bv, av) == tv
True

>>> Av.from_exposures(sv, bv, tv)
Av f/2.0

>>> Sv.from_exposures(tv, bv, av)
Sv 400 ISO

>>> Sv.from_exposures(tv, iv, av)
Sv 400 ISOFuture work:from_exifDisclaimerThis package is based onhttp://dougkerr.net/Pumpkin/articles/APEX.pdf
Package: exposure-fusion
# Exposure FusionPython implementation of exposure fusion of multiple images, using the alghorithm described in:Mertens, Tom, Jan Kautz, and Frank Van Reeth. “Exposure fusion.” Computer Graphics and Applications, 2007. PG’07. 15th Pacific Conference on. IEEE, 2007.## RequirementsPython 2.7 or Python 3OpenCV python module (cv2)## Installation` pip install exposure_fusion `## Usage
See`example.py`
Package: exppy
exppy - module that automates numerical experimentsThis module is intended for performing numerical experiments with continuous parameters. Currently, parameters of the model can be randomized with uniform or log-uniform distributions in the given range. Simple random, latin hypercube or generalized subset designs can be used (supported bypyDOE2package).Example:fromexppyimportLHSDesign,Experimentfrommathimportsin,cosimportpylabclassMyDesign(LHSDesign):spec=(('x',(0,6.28,'uniform',10)),('y',(0,6.28,'uniform',10)))samples=50classMyModel:# model can be any class, but it is required to have 'solve' method# which takes sample `d` as argument and returns dict of results `res`defsolve(self,d):x,y=d.x,d.yres={'F':sin(x)*cos(y),'G':x*y}returnres# Evaluate experiments and dump everything to 'test' directory:ex=Experiment(MyDesign(),MyModel(),dirname='test')ex.run()# Plot 'F'x=ex.design.xy=ex.design.yF=ex.result.Fpylab.tricontour(x,y,F,levels=14,linewidths=0.5,colors='k')cntr=pylab.tricontourf(x,y,F,levels=14,cmap="RdBu_r")pylab.colorbar(cntr)pylab.plot(x,y,'ko',ms=3)pylab.title('$\sin(x)\cos(y)$\n(%dLHS samples)'%ex.design.samples)The resulting figure looks like this:For more hints look into thetest_exppy.pyfile. Docs are in plans...
Package: expr2gct
expr2gctgenerate gct file (version 1.2, for GSEA or ssGSEA) from gene expression matrix file.
note that gene expression matrix file should be tab delimited file.Installationinstall from pip$ pip install expr2gctinstall from source$ git clone https://github.com/sxropensource/expr2gct.git
$ cd expr2gct
$ python setup.py installUsage$ expr2gct --help
usage: expr2gct [-h] -e EXPR [-d DESC] -g GCT

optional arguments:
  -h, --help            show this help message and exit
  -e EXPR, --expr EXPR  Gene expression matrix file(tab delimited only), first
                        row is sample names, first column is gene symbols
  -d DESC, --desc DESC  gct file need DESCRIPTION for column 2 for every gene,
                        If not provided, default use gene symbol(column 1)
                        instead. Note that if you provide a DESCRIPTION file,
                        every row reprents a gene. eg, the first row in
                        DESCRIPTION file represents the first gene in
                        expression file.
  -g GCT, --gct GCT     Where to save gct file
Package: expr-calc
Calc InterpreterAn interpreter modeled after a calculator implemented in Python 3.
The program currently only supports basic mathematical expressions.
The package uses Reverse Polish Notation also known as postfix expression
internally to easily represent mathematical expressions. This is powerful
as it allows operators to beorganisedin such a way that precedence
isabsolutemeaning an operator that is encountered first will always
be executed first.However, it is obvious that postfix is notnormalor rather not usually
taught in schools and thus infix expression is still the way for the user
to write expressions. The interpreter uses a modified Shunting-Yard algorithm
to produce Abstract Syntax Trees. Evaluation of ASTs is trivial, and they are
flexible making it easy to extend the grammar and functionality later on.InstallationThe package is available in PyPI and can be installed via pip.pipinstallexpr-calc#orpython3-mpipinstallexpr-calcUsageThe best way to run the program currently is to execute the REPL and
can be done in a python file or through your terminal.Assuming your present working directory is inside the cloned repo, you
can run the following command without the comment.# inside /clone_path/expr_calc/python-mexpr_calcThe test suite can also be ran withpytestwhen inside the cloned repopytest# or python -m pytestExampleOnce inside the REPL, you can start evaluating expressions. Currently,
only operators listed inFeaturesare supported.calc>1+12calc>345--500845calc>-2
-2

calc>123^4228886641calc>32/1.521.33333333333333333333333333

calc>123*45656088calc>34%54calc>4^1/20.5

calc>4^(1/2)2.0FeaturesInfix expressionsBasic operators such as+, -, *, /, %, ^Tokens created from an expression can also be fetched to be manipulated if one wanted to do soExpressions are transformed into m-ary Tree objects connected to each otherFeatures I want to add latervariable supportcustom functionsmore mathematical functions such assin,cos,tan, etcand possibly a simple symbolic computation supportResourcesReverse Polish NotationShunting Yard AlgorithmFloating-point arithmeticCalculator test suite
Package: exprec
ExprecExprec records your experiments so you can compare different runs and easily reproduce results.Track your experiments for experiment comparison and reproducabilityMinimum setup: only two lines of code requiredFramework agnostic - works with any machine learning/deep learning frameworkExperiments are saved locally - nothing is saved in the cloudInstallationpipinstallexprecUsageMinimal examplefromexprecimportExperimentwithExperiment()asexperiment:# YOUR CODE HEREAn experiment is recorded in thewithstatement. This includes recording the terminal output, the source code used and the packages that are installed at the time the experiment runs. You can also add parameters, scalars and images to the experiment (see below).DashboardRunexprecin your terminal to start the dashboard.exprechas to be run from the same folder as you started your python script.Now visithttp://localhost:8080/in your browser to see the dashboard. If the client and the exprec server run on different machines, set the flag--host=0.0.0.0when startingexprec. This allows any client with access to the server to see the dashboard.More code examplesfromexprecimportExperimentwithExperiment(title='My experiment',tags=['tag1','tag2'])asexperiment:experiment.set_parameter('test_parameter',5)foriinrange(10):experiment.add_scalar('2x',2*i,step=i)experiment.add_scalar('3x',3*i,step=i)withexperiment.open('filename.txt',mode='w')asfp:fp.write('test\n')# This creates a file in the experiment's folder (`.exprec/<experiment-id>/files/filename.txt`).raiseValueError('Invalid value')# The experiment will finish with status 'failed'. The exception is also logged.ExamplesScripts underexamples/demonstrate how to use this package.APIExperimentExperiment(title='',tags=[],verbose=True,exceptions_to_ignore=['KeyboardInterrupt'],name='')set_parameterExperiment.set_parameter(name,value)Sets the parameter to the given value.Only one value can be recorded per parameter. You can overwrite a previously set parameter.add_scalarExperiment.add_scalar(name,value,step=None)Records the scalar's value at a given step.add_imageExperiment.add_image(name,image,step)Adds an image at a given step.Args:
    name (str): The name of the image
    image: The image to save. Should either be a Pillow image, or a numpy array which can be converted to a Pillow image.
    step (int)openExperiment.open(filename,mode='r',uuid=None)Opens a file in the experiment's folder.Args:
    filename (str): A filename or path to a filename
    mode (str): The mode in which the file is opened. Supports the same modes as Python's built-in `open()` function.
    uuid (str, None): A previous experiment's id. If given, it will look for the filename in the previous experiment's
        saved files. Only supports 'r' mode when a uuid is given.
Returns:
    A file objectWhy "Exprec"?Exprec is short for Experiment recorder.LicenseMIT License
Package: expresscheckout
Python Library for Juspay Express Checkout APIInstallationPrerequisites:Ensure that you have installed the ‘requests’ package for python,If not, open the terminal and type ‘pip install requests’NOTE: If pip is not installed, install pip by download get_pip.py from thehttps://bootstrap.pypa.io/get-pip.pyand
run the script in your terminalProcedureRun the following command in your terminalpip install expresscheckoutYou can use the library by including the following import statement in your python scriptimport expresscheckout as JuspayNow, you can use the library as followsJuspay.api_key = ‘your_api_key’
Juspay.Orders.create(order_id=1,amount=100.0)For more instructions on how to use the library, please refer to the documentation athttps://apidocs.juspay.in
Package: express-cli
express-cliplatform9 express cliStatusPurposePlatform9 Express CLIA CLI for Platform9 ExpressUsageIf you've cloned this project, and want to install the library (and all
development dependencies), the command you'll want to run is::$ pip install -e .[test]If you'd like to run all tests for this project (assuming you've written
some), you would run the following command::$ python setup.py testThis will triggerpy.test <http://pytest.org/latest/>, along with its popularcoverage <https://pypi.python.org/pypi/pytest-cov>plugin.Lastly, if you'd like to cut a new release of this CLI tool, and publish it to
the Python Package Index (PyPI <https://pypi.python.org/pypi>_), you can do so
by running::$ python setup.py sdist bdist_wheel
$ twine upload dist/*This will build both a source tarball of your CLI tool, as well as a newer wheel
build (and this will, by default, run on all platforms).Thetwine uploadcommand (which requires you to install thetwine <https://pypi.python.org/pypi/twine>_ tool) will then securely upload your
new package to PyPI so everyone in the world can use it!