Saravanan666/pypi-org huggingface dataset:
Package: gshell
gshell = Google Drive + ShellNavigate in Google Drive as you do on shell.Installationpipinstallgshell

gshellinit# login to your google accountUsage$gshellinfo--with-id0B9P1L--7Wd2vaGl4bDZaV2lESTQ
Id:0B9P1L--7Wd2vaGl4bDZaV2lESTQ
Name:20160502_gdown
Path:20160502_gdown
Mime:application/vnd.google-apps.folder
Created:2016-05-0200:17:25
Modified:2017-12-2301:56:42
Shared:True
ViewUrl:https://drive.google.com/open?id=0B9P1L--7Wd2vaGl4bDZaV2lESTQ

$gshellcd--with-id0B9P1L--7Wd2vaGl4bDZaV2lESTQ

$gshellpwd20160502_gdown

$gshellll
IdNameTypeSizeCreated
0B9P1L--7Wd2vT3Zxem1OdTMtWU0gdown-1.0.2.tar.gzbin1.9KB2016-05-0200:24:49
0B9P1L--7Wd2vU3VUVlFnbTgtS2cspam.txtbin5.0B2016-05-0200:19:31

$gshelldownloadspam.txt
Downloadingspam.txt->spam.txt
Downloaded0B9P1L--7Wd2vU3VUVlFnbTgtS2cat5.0B/s,total5.0B

$catspam.txt
spamCommandsUsage:gshell[OPTIONS]COMMAND[ARGS]...

Options:-V,--versionShowtheversionandexit.--helpShowthismessageandexit.

Commands:aboutshowaccountstatuscdchangedirectorydownloaddownloadfileinfoshowfileinformationinitinitializegshelllllistfilesindetaillslistfilesmkdirmakedirectoryopenopencurrentsiteonbrowserpwdprintcurrentworkingdirectoryrmremovefilesharesharefileswitchswitchuseruploaduploadfile
Package: gshell.py
gshell.pyA port of GLib's gshell.c to Python 3.InstallYou should be able to install this via pypi in your environment of choice:pipinstallgshell.pyYou can then use it by importing fromgshell:fromgshellimportg_shell_parse_argv,g_shell_quote,g_shell_unquoteAPII haven't found a nice way to turn the docstrings ingshell.pyinto a simple
markdown document - sphinx is incredibly overkill and won't output markdown!
So for now I'd encourage you toread the docstrings in the source code.Development and TestsI use Conda for development. You can create an environment using the includedenvironment.ymlfile by runningconda env create, and then runningconda activate gshell.py.Tasks are via make, and includetest,lint,clean,packageandpublish.LicenseThis library is available via the same license as GLib, which is the LGPL 2.1
or later. See the COPYING file for more details.
Package: gshttpservice
Install$python3setup.pybdist_wheel
$cddist&&pip3install./*.whlLaunch http service$python3-mgshttpservice9527APICreate instancePOST   /api/graphservice/createInstance> body
> {
>    "num_workers": 2,
>    "vineyard_shared_mem": "4Gi"
> }See more  parameter details fromDocGet instanceGET  /api/graphservice/getInstanceLoad dataPOST  /api/graphservice/loadData> body
> {
>    "type": "LOCAL",
>    "directed": true,
>    "oid_type": "string",
>    "instance_id": "<graphscope instance id>",
>    "dataSource": {
>        "nodes": [
>            {
>                "label": "v",
>                "location": "",
>                "config": {
>                    "header_row": true,
>                    "delimiter": ","
>                }
>            }
>        ],
>        "edges": [
>            {
>                "label": "e",
>                "location": "",
>                "srcLabel": "v",
>                "dstLabel": "v",
>                "config": {
>                    "header_row": true,
>                    "delimiter": ","
>                }
>            }
>        ]
>    }
>}Get graph schemaGET  /api/graphservice/graphSchema> params
> {
>     "graph_name": ""
> }Gremlin queryGET  /api/graphservice/query/gremlin> params
> {
>    "graph_name": <graph for gremlin query>,
>    "gremlinSQL": "g.V('1')"
> }Close instanceGET /api/graphservice/closeInstance> params
> {
>     "instance_id": <graphscope instance to close>,
> }Upload filePOST /api/graphservice/uploadFile> header
> {
>   Content-Type: multipart/form-data
> }
>
> body
> {
>   file=@file_path,
>   instance_id="instance_id"
> }

> example
> curl -i -X POST -H "Content-Type: multipart/form-data" -F "file=@file1" -F "file=@file2" -F "instance_id=xxx" -w %{http_code} http://localhost:9527/api/graphservice/uploadFile
Package: gsimporter
gsimportergsimporter is a python library for using GeoServer’s importer API.Installingpip install gsconfigorgit clonehttps://github.com/boundlessgeo/gsimporter.gitcd gsimporter
pip install .Getting HelpPlease use the Github project athttp://github.com/boundlessgeo/gsimporterfor any bug reports (and pull requests are welcome, but please include tests where possible.)Running TestsThe tests are integration tests. These require having a running GeoServer instance with the community/importer modules installed. Because some of the tests use a postgres database, a data base is required to run.It is strongly advised to run with a data directory you don’t care about.The test suite will first attempt to verify a connection to GeoServer and a connection to the database. If the default values are not appropriate, provide them via environment variables on the command line or viaexport. For example:GEOSERVER_BASE_URL=http://localhost:8080 python setup.py testA convenient way to deal with connection or other settings (besides setting things up to use the defaults) is to put them all in a bash (or other shell) script.The tests are designed to create a workspace namedimporterandimporter2for use in testing.importerwill be set to the default workspace. As much as possible, things are cleaned up after test execution.To run all of the tests, one way is viasetup.py.python setup.py testshould do the trick.If developing and finer grained control is desired, specific tests and other flags can be provided usingpython test/uploadtests.py. Supported arguments are:–cleandelete layers and stores in the test workspaces. useful for cleanup.–skip-teardowndon’t delete things after running. may cause errors but useful for a single test.To run a single case (or drop the method name to run the whole class):python test/uploadtests.py ErrorTests.test_invalid_file
Package: gsindex
Geometrical Separability Index (GSI)This is a python wrapper of the Geometrical Separability Index (GSI) based on the MATLAB code proposed in [1] and originally proposed by Chris Thornton in [2].[1] Greene, J. (2001). Feature subset selection using thornton’s separability index and its applicability to a number of sparse proximity-based classifiers. In Proceedings of Annual Symposium of the Pattern Recognition Association of South Africa.[2] Thornton, C. (1998). Separability is a learner’s best friend. In 4th Neural Computation and Psychology Workshop, London, 9–11 April 1997 (pp. 40-46). Springer, London.InstallationRun the following to install:pipinstallgsindexUsageimportnumpyasnpfromgsindeximportgeometrical_separability_indexmatrix=np.array([[1,2],[3,4],[5,6],[7,8],[10,11],[12,13],[14,15],[16,17]])labels=np.array(['sample1','sample1','sample1','sample1','sample2','sample2','sample2','sample2'])gsi=geometrical_separability_index(matrix,labels)print(gsi)
Package: gs-jupyterlab
gs-jupyterlabA JupyterLab extension for GraphScopeRequirementsJupyterLab >= 3.0InstallTo install the extension, execute:pipinstallgs-jupyterlabUninstallTo remove the extension, execute:pipuninstallgs-jupyterlabContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the gs-jupyterlab directory# Install package in development modepipinstall-e.# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# Rebuild extension Typescript source after making changesjlpmbuildYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=FalseDevelopment uninstallpipuninstallgs-jupyterlabIn development mode, you will also need to remove the symlink created byjupyter labextension developcommand. To find its location, you can runjupyter labextension listto figure out where thelabextensionsfolder is located. Then you can remove the symlink namedgs-jupyterlabwithin that folder.Packaging the extensionSeeRELEASE
Package: gsk-geo-encryption
Note: Internet is mandatory for getting your current locationProject DescriptionThis program is to create a encryption password with a given Key and can get access when both the encryption  is at same location as
the password is created with the latitude and longitudeChange the ipinfo API Token (if needed):Code:gsk_geo_encryption.TOKEN="API_TOKEN"Getting the encrypted_password and timer with a class:Code:object1=gsk_geo_encryption.Keys()password,seconds=object1.password_encrypted()Classes:KeysInbuilt Functions(Unchangable):geo_lat_long_convertor()encryption()----------------------------------------------------------------Usable Functions(Changable):password_encrypterExceptions:ConnectionError
Package: gskrawler
gskrawler==============gskcrawler will enter your domain and scan every page of your website, extracting page titles, descriptions, keywords, and links etc..----Description: gskrawler==============gskcrawler will enter your domain and scan every page of your website, extracting page titles, descriptions, keywords, and links etc..Requirements============================BeautifulSoup4requestsurllib3 1.22Commands============================<head>------------gskrawler.head(url)<title>------------gskrawler.title(url)<body>------------gskrawler.body(url)response in html format------------gskrawler.html(url)links in a website------------gskrawler.links(url)class elements------------gskrawler.tagclass(url,tagname,classname)id elements------------gskrawler.tagid(url,tagname,idname)emails in a website------------gskrawler.emails(url)images in a website------------gskrawler.images(url)----Example Code------------Open Python Interpreter::>>> import gskrawler>>> gskrawler.emails('https://www.fisglobal.com/')>>> gskrawler.images('https://www.fisglobal.com/')>>> gskrawler.head('https://www.fisglobal.com/')>>> gskrawler.tagclass('https://www.naukri.com/','ul','set')
Package: gslconsts
It may be convenient for python users to have available physical
constants from theGNU Scientific Librarywithout installing GSL itself.  This package makes those constants
available directly.InstallationInstall fromPyPIwith pip by
typing in your favorite terminal:$ pip install gslconstsUsageTo learn how to use the package, follow thetutorials.AuthorsBradley S. Meyer <mbradle@g.clemson.edu>ContributeIssue Tracker:https://github.com/mbradle/gslconsts/issues/Source Code:https://github.com/mbradle/gslconsts/LicenseThe project is licensed under the GNU Public License v3 (or later).DocumentationThe project documentation is available athttps://gslconsts.readthedocs.io.
Package: gslibutils
gslibutilsPython utilities for GSLIB parameter, input and output filesGSLIB executables use parameter, input and output files in a specific format.
gslibutils comes with the modules for importing/exporting those files and with
CLI commands for pipeline executions.Installpython-mpipinstallgslibutilsUsage as Python packageFor the use of gslibutils as a Python package, a simple example is:fromgslibutils.parserimportload_input_dftitle,df=load_input_df("data/simple.gslib")print(df["var1"])01.0110.02100.0Name:var1,dtype:float64Usage as CLIgslibutils can run as CLI to facilitate pipelines.
To covert a gslib file into a CSV:gslib2csvdata/simple.gslib
gslib2csvdata/simple.gslib--delimiter" "gslib2csvdata/simple.gslib--delimiter",">my.csv
gslib2csvdata/simple.gslib--delimiter","--outputmy.csv
Package: gslides
gslidesis a Python package that helps analysts turnpandasdataframes into Google slides & sheets charts by configuring and executing Google API calls.The package provides a set of classes that enable the user full control over the creation of new visualizations through configurable parameters while eliminating the complexity of working directly with the Google API.Quick InstallationpipinstallgslidesUsageBelow is an example that only showcases a simple workflow. Full discussion around features can be found in the docs.1. Initialize package and connectionimportgslidesfromgslidesimport(Frame,Presentation,Spreadsheet,Table,Series,Chart)fromsklearnimportdatasetsgslides.initialize_credentials(creds)#BringYourOwnCredentials2. Create a presentationprs=Presentation.create(name='demo pres')3. Create a spreadsheetspr=Spreadsheet.create(title='demo spreadsheet',sheet_names=['demo sheet'])4. Load the data to the spreadsheetplt_df=#Iris dataframe=Frame.create(df=plt_df,spreadsheet_id=spr.spreadsheet_id,sheet_id=spr.sheet_names['demo sheet'],sheet_name='demo sheet',overwrite_data=True)5. Create a scatterplotsc=Series.scatter(series_columns=target_names)ch=Chart(data=frame.data,x_axis_column='sepal length (cm)',series=[sc],title=f'Demo Chart',x_axis_label='Sepal Length',y_axis_label='Petal Width',legend_position='RIGHT_LEGEND',)6. Create a tabletbl=Table(data=plt_df.head())7. Create a slide with the scatterplotprs.add_slide(objects=[ch,tbl],layout=(1,2),title="Investigation into Fischer's Iris dataset",notes="Data from 1936")8. Preview the slide you have just created in your notebookprs.show_slide(prs.slide_ids[-1])gslidesalso supports basic templating functionality. See thisnotebookfor an example.Advanced UsageFind thisJupyter notebookdetailing advanced usage ofgslides.Developer InstructionsTo install the package with development dependencies run the commandpipinstall-e.[dev]This will enable the followingUnit testing usingpytest- Runpytestin root package directoryPre commit hooks ensuring codes style usingblackandisortSphinx documentation
- To create sphinx runmake htmlin package docs folder
- To view locally runpython-mhttp.server
Package: gsm0338
Python Codec for 3GPP TS 23.038 / ETSI GSM 03.38ExamplesDecode GSM 03.38 encoded bytes:>>> import gsm0338
>>> b'\x1b(\x1b)'.decode('gsm03.38')
u'{}'Encode bytes in GSM 03.38:>>> import gsm0338
>>> u'{}'.encode('gsm03.38')
b'\x1b(\x1b)'How it worksThe codec implements the encoding and decoding methods in the stateless codecs.Codec class.
With loading the module the codec get’s automatically registered.Mapping source3GPP TS 23.038 version 13.0.0 Release 133GPP TS 23.038 Rel-13: Alphabets and language-specific informationhttp://www.3gpp.org/dynareport/23038.htm
Package: gs_media_bot
Bot for posting media to GNU Social.Installationpip install gs_media_botorpython3 setup.py installYou can also installgs-media-botpackage from AUR.Basic usageSet the configuration parameters in the default location ($XDG_CONFIG_HOME/gs_media_bot/config.json) or supply it to the script with-c.Configuration example:{
    "credentials": {
        "server_url": "https://gnusocial.server",
        "username": "username",
        "password": "password",
    },
    "patterns": {
        "~/My_Cool_Photos/my_photo.jpg": "Yet another photo!",
        "~/Directory/With/subdirs/**": "random pic"
    }
}
Package: gsmirror
A Python module and script, which is able to download content from Google Sites (via Sites Data API) and create a mirror of the original web sites, but with a custom design (via Cheetah template) - for hosting on a traditional webserver.Google Sites then become just an editing interface for the content, which is displayed somewhere else - with the possibility to completely customize the design of the websites.The complete Sites structure is preserved, including the attachments. The script creates directories and files emulating the original Sites on the local disk. To publish such mirror of the Google Sites, it is enough to copy this directories via FTP to any webserver. We plan to support also direct hosting on the Google App Engine.
Package: gsmtpd
SMTP servers impletement base on GeventInstallpip install gsmtpdUsageBasically gsmtpd is ported from Python standard libsmtpd,
you can it check fromDochowever there is only one difference, you should add monkey patch of geventfromgeventimportmonkeymonkey.patch_all()Examplefromgeventimportmonkeymonkey.patch_all()fromgsmtpd.serverimportSMTPServerclassDebuggingServer(SMTPServer):# Do something with the gathered messagedefprocess_message(self,peer,mailfrom,rcpttos,data):inheaders=1lines=data.split('\n')print'---------- MESSAGE FOLLOWS ----------'forlineinlines:# headers firstifinheadersandnotline:print'X-Peer:',peer[0]inheaders=0printlineprint'------------ END MESSAGE ------------'if__name__=="__main__":server=DebuggingServer()server.serve_forever()PerformanceThe charts below shows gsmtpd vs asyncore based smtpd in Python standrary lib.NoteResponse per second = 0 means the program is crashed or refuse to connect
Package: gsmvi
GSM-VICode for Variational Inference (VI) with Gaussian Score Matching (GSM).This repo implements code for paperhttps://arxiv.org/abs/2307.07849.GSM-VI fits a multivariate Gasussian distribution with dense covaraince matrix to the target distribution
by score matching. It only requires access to the score function i.e. the gradient of the target log-probability
distribution and implements analytic updates for the variational parameters (mean and covariance matrix).Installation:The code is available onPyPIpip install gsmviUsageThe simplest version of the algorithm is written in numpy.
The following is the minimal code to use GSM to fit the parametersxof amodelgiven itslog_probandlog_prob_gradfunctions.
Seeexample/example_gsm_numpy.pyfor a full example.dimensions = D
def log_prob(x):
  # return log_prbability at sample x
  ...

def log_prob_grad(x):
  # return the score fuction i.e. the gradient of log_prbability at sample x
  ...

from gsmvi.gsm_numpy import GSM
gsm = GSM(D=D, lp=log_prob, lp_g=log_prob_grad)
random_seed = 99
number_of_iterations = 500
mean_fit, cov_fit = gsm.fit(key=random_seed, niter=number_of_iterations)A more efficient version of the algorithm is implemented in Jax where it can benefit from jit compilation. The basic signature stays the same.
Seeexample/example_gsm.pyfor a full example.dimensions = D
model =  setup_model(D=D)     # Ths example sets up a numpyro model which has log_prob attribute implemented
lp = jit(lambda x: jnp.sum(model.log_prob(x)))
lp_g = jit(grad(lp, argnums=0))

from gsmvi.gsm import GSM
gsm = GSM(D=D, lp=lp, lp_g=lp_g)
mean_fit, cov_fit = gsm.fit(key=random.PRNGKey(99), niter=500)Other utilities:For comaprison, we also provide implementation of ADVI algorithm (https://arxiv.org/abs/1603.00788),
another common approach to fit a multivariate Gaussian variational distribution which maximizes ELBO.We provide LBFGS initilization for the variational distribution which can be used with GSM and ADVI.We also provide a Monitor class to monitor the KL divergence over iterations as the algorithms progress.Code DependenciesThe vanilla code is written in python3 and does not have any dependencies.Optional dependenciesThese will not be installed with the package and should be installed by user depending on the use-case.The Jax version of the code requiresjaxandjaxlib.The target distributions in example files other than example_gsm_numpy.py are implemented innumpyro.ADVI algorithm usesoptaxfor maximizing ELBO.LBFGS initialization for initializing variational distributions usesscipy.Starting pointWe provide simple examples inexamples/folder to fit a target multivariate Gaussian distribution with GSM and ADVI.cd examples
python3 example_gsm_numpy.py  # vanilla example in numpy, no dependencies
python3 example_gsm.py        # jax version, requires jax and numpyro
python3 example_advi.py       # jax version, requires jax, numpyro and optaxAn example on how to use the Monitor class and LBFGS initialization is inexamples/example_initializers.pycd examples
python3 example_initializers.py   # jax version, requires jax, numpyro, optax and scipy
Package: gsn
===============================Python wrapper for the Global Sensor Networks API===============================.. contents:: **Table of Contents**-------------------------Installation-------------------------> pip install gsn-------------------------Usage-------------------------The wrapper uses the `sanction`_ Oauth2 library to authenticate against GSN services.Before starting you must create a "client" on GSN services and get the client_id, client_secret and redirect_uri.As we will be using client_credentials, the client must be linked to the user from which it will inherit the access rights.The value of redirect uri is not used, but must nevertheless match.Then in your python code, you can use it this way::> import gsn> a = gsn.API(service_url="http://localhost:9000/ws", client_id="client", client_secret="secret", redirect_uri="http://localhost")> s = a.get_latest_values("push")> s.values = [[1469959498000, 18]]> r = a.push_values(s).. _sanction: https://github.com/demianbrecht/sanctionSensor object===============================This object abstract the json representation used by GSN for the stream elements.  It has the following fields:* fields: list of triples representing the name, type and units* name: name of the sensor* values: list of lists. The inner lists must have the same size as the fields list and represent the data of a stream element.* location: (optional) a triple representing the location of the sensor as latitude, longitude, altitude.=======CHANGES=======v0.2.0-------* adding refresh token support* automatically tracking the expiration of access token and refreshing if necessaryv0.1.0-------* initial release* supports querying the latest values and pushing data* compatible with GSN v2.0.0
Package: gsnake
gsnakeNokia's classic snake gameTechnologies usedPyGameRequiresPython 3PyGame 2.5.2InstallingInstall via pippython3-mpipinstallgsnakeDownload it from thePyPI LinkRun the game using Pythonpython3-mgsnakeGame controlsControl the snake with arrow keysTo speed up, presswTo speed down, presssTo pause, pressSpacebarTo continue, press arrow keysTo exit, pressESCDeveloped byRushikesh Kundkar