Saravanan666/pypi-org huggingface dataset:
Package: gsd
GSDTheGSDfile format is the native file format forHOOMD-blue.GSDfiles store trajectories of theHOOMD-bluesystem state in a binary file with efficient random access to
frames.GSDallows all particle and topology properties to vary from one frame to the next. Use theGSDPython
API to specify the initial condition for aHOOMD-bluesimulation or analyze trajectory output with a script. Read aGSDtrajectory with a visualization tool to explore the behavior of the simulation.ResourcesGSD documentation: Tutorials, Python API, C API, usage information, and format
specification.Installation Guide: Instructions for installing and compilingGSD.HOOMD-blue: Simulation engine that reads and writesGSDfiles.GSD discussion board:
Ask theGSDcommunity for help.freud: A powerful set of tools for analyzing trajectories.OVITO: The Open Visualization Tool works withGSDfiles.gsd-vmd plugin: VMD plugin to supportGSDfiles.HOOMD examplesCreate a hoomd gsd file.>>>s=gsd.hoomd.Frame()>>>s.particles.N=4>>>s.particles.types=['A','B']>>>s.particles.typeid=[0,0,1,1]>>>s.particles.position=[[0,0,0],[1,1,1],[-1,-1,-1],[1,-1,-1]]>>>s.configuration.box=[3,3,3,0,0,0]>>>traj=gsd.hoomd.open(name='test.gsd',mode='w')>>>traj.append(s)Append frames to a gsd file:>>>defcreate_frame(i):...s=gsd.hoomd.Frame();...s.configuration.step=i;...s.particles.N=4+i;...s.particles.position=numpy.random.random(size=(4+i,3))...returns;>>>withgsd.hoomd.open('test.gsd','a')ast:...t.extend((create_frame(i)foriinrange(10)))...print(len(t))11Randomly index frames:>>>withgsd.hoomd.open('test.gsd','r')ast:...frame=t[5]...print(frame.configuration.step)4...print(frame.particles.N)8...print(frame.particles.position)[[0.569932820.422434810.5502916][0.368924860.381670360.27310368][0.047390230.136034860.196539][0.1202320.915911440.99463677][0.798063160.169914360.15228257][0.137243080.142535270.02505][0.392874390.825190540.01613089][0.231503230.951674340.7715748]]Slice frames:>>>withgsd.hoomd.open('test.gsd','r')ast:...forsint[5:-2]:...print(s.configuration.step,end=' ')4567File layer exampleswithgsd.fl.open(name='file.gsd',mode='w')asf:f.write_chunk(name='position',data=numpy.array([[1,2,3],[4,5,6]],dtype=numpy.float32));f.write_chunk(name='angle',data=numpy.array([0,1],dtype=numpy.float32));f.write_chunk(name='box',data=numpy.array([10,10,10],dtype=numpy.float32));f.end_frame()withgsd.fl.open(name='file.gsd',mode='r')asf:foriinrange(1,f.nframes):position=f.read_chunk(frame=i,name='position');do_something(position);
Package: gsdb-cli
GeoSpock DB CLIInstalling the CLI from pip$ python -m pip install gsdb-cliLogging in with your enterprise Identity ProviderTheconfigurecommand creates a configuration file with the endpoint for your deployment and saves your username
and password to your computer's secure keychain.Alternatively, if you do not want to save your details:all commands can be run withgsdb --user <value> --password <value> --endpoint <value> COMMAND.the CLI will also check for the environment variablesGEOSPOCK_USERandGEOSPOCK_PASSWORDand use these to
authenticate. An environment variableGEOSPOCK_ENDPOINTcan also be used to provide the request address.An optional--profile <value>argument can be used to set up configurations for multiple GeoSpock DB deployments.
All subsequentgsdbcommands can then use this profile flag to specify that deployment, e.g.gsdb --profile dev COMMAND.Running the CLIThe CLI can be activated at the command line usinggsdb [--profile <value>] COMMAND ...A list of commands can be shown by usinggsdb --help. Further information on the input types of each command can be
obtained by runninggsdb COMMAND --help.
Package: gs-dbs-client
GS DBS ClientThe GS-DBS-Client is a Python library interacting with the Glass Sphere DBS.CAUTIONVersion 0.2.0 introduces breaking changes due to introduction of the mission control client. Be aware of the changed
imports.InstallationUse the package managerpipto install the gs-dbs-client. Further information can be
foundhere.pipinstallgs-dbs-gsdbsUsageimportos#v0.1.xfromclient.gsdbsimportGSDBS#v0.2.xfromgsdbs.dbclientimportGSDBSfromgsdbs.missioncontrolimportMissionControl...gsdbs=GSDBS(os.path.dirname(os.path.realpath(__file__)))License(C) 2022 ENS - Freies Institut fuer Technische Informatik UG haftungsbeschraenktMIT
Package: gs-divergence
α-Geodesical Skew DivergenceOfficial PyTorch Implementation of "α-Geodesical Skew Divergence".[arXiv]The asymmetric skew divergence smooths one of the distributions by mixing it, to a degree determined by the parameter λ, with the other distribution. Such divergence is an approximation of the KL divergence that does not require the target distribution to be absolutely continuous with respect to the source distribution. In this paper, an information geometric generalization of  the skew divergence called the  α-geodesical skew divergence is proposed, and its properties are studied.InstallationFrom PyPi$pipinstallgs_divergenceFrom GitHub$gitclonehttps://github.com/nocotan/geodesical_skew_divergence
$pythonsetup.pyinstallUsageimporttorchfromgs_divergenceimportgs_diva=torch.Tensor([0.1,0.2,0.3,0.4])b=torch.Tensor([0.2,0.2,0.4,0.2])div=gs_div(a,b,alpha=-1,lmd=0.5)parameterdescriptioninputTensor of arbitrary shapetargetTensor of the same shape as inputalphaSpecifies the coordinate systems which equiped the geodesical skew divergence (default=-1)lmdSpecifies the position on the geodesic (default=0.5)reductionSpecifies the reduction to apply to the output:'none'|'batchmean'|'sum'|'mean'.'none': no reduction will be applied'batchmean': the sum of the output will be divided by the batchsize'sum': the output will be summed'mean': the output will be divided by the number of elements in the output             default='sum'Definition of α-Geodesical Skew DivergenceVisualizations of the α-Geodesical Skew DivergenceMonotonicity of the α-geodesical skew divergence with respect to αContinuity of the α-geodesical skew divergence with respect to α and λ.Citation@misc{kimura2021geodesical,title={$α$-Geodesical Skew Divergence},author={Masanari Kimura and Hideitsu Hino},year={2021},eprint={2103.17060},archivePrefix={arXiv},primaryClass={cs.IT}}
Package: gs.dmarc
Author:Michael JasonSmithContact:Michael JasonSmith <mpj17@onlinegroups.net>Date:2015-06-25Organization:GroupServer.orgCopyright:This document is licensed under aCreative Commons Attribution-Share Alike 4.0 International LicensebyOnlineGroups.net.IntroductionThis product allows systems look up and report on the DMARC (RFC
7489: Domain-based Message Authentication, Reporting and
Conformance) status of a domain. DMARC allows the owner of a
domain to publish a key that is used to verify if an email
message actually originated from the domain, and to publish what
to do if the verification fails. It is an extension of DKIM (RFC
6376: DomainKeys Identified Mail) and SPF (RFC 4408: Sender
Policy Framework).Specifically this product suppliesgs.dmarc.ReceiverPolicyfor enumerating[1]the different DMARC policies, and thereceiver_policyfunction for querying the policy for a
given domain.ResourcesDocumentation:http://gsdmarc.readthedocs.io/Code repository:https://github.com/groupserver/gs.dmarcQuestions and comments tohttp://groupserver.org/groups/developmentReport bugs athttps://redmine.iopen.net/projects/groupserver[1]The enum34 packageis used to provideEnumsupport for releases of Python prior to 3.4.
Package: gsdr
gsdrGenerative Sparse Distributed Representations, a fast generative model
written in Python (Original C++ implementationhttps://github.com/222464/GSDR)DependenciesPython 3Python librariesnumpyInstallationpip install gsdror clone andpython setup.py installUsage(More extensive examples and IPython notebooks can be found in
examples/)With labeled data:data,labels=...num_labels=10# Data: (batches, num_features)# Labels: (batches,) (contains numbers from 0 to num_labels-1, eg. 10 for MNIST)# Build the GSDR network (only one layer for now)gsdr=GSDRStack()gsdr.add(input_count=data.shape[1],hidden_count=256,sparsity=0.1,forced_latent_count=num_labels)forced_latents=np.eye(num_labels)# Train once for each data pointforiinrange(data.shape[0]):gsdr.train(data[i],forced_latents={0:forced_latents[labels[i]]})# Generate one example for each labelforiinrange(num_labels):generated=gsdr.generate(forced_latents={0:forced_latents[i]})With unlabeled data:data=...# Data: (batches, num_features)# Build the GSDR network (only one layer for now)gsdr=GSDRStack()gsdr.add(input_count=data.shape[1],hidden_count=256,sparsity=0.1)# Train once for each data pointforiinrange(data.shape[0]):gsdr.train(data[i])states=np.eye(hidden_count)# Generate one example for each one-hot stateforiinrange(hidden_count):generated=gsdr.generate(states[i])
Package: gsea-incontext-notk
GSEA-InContext: Gene Set Enrichment Analysis In ContextNOTE: This is a stripped-down copy of the GSEA-InContext Python package. It has all graphics- and plot-related functionality removed so that it can be used on shinyapps.io, which cannot use packages that require access to the display (e.g., packages that require Tcl/Tk). The full package with plotting capability ishere.
Package: gsearch-nyaa
GSearch - A Python Package for Automated Google Searches and Scraping of Search ResultsIntroduction: gsearch is a Python package that allows users to perform automated Google searches and extract information from the search results using Python code. The package uses the Playwright and Selectolax libraries to scrape search results and provides a convenient way to automate and extract information from Google searches.InstallationTo install gsearch, you can use pip:pip install gsearch-nyaaUsageTo use gsearch, first import theGoogleclass from the package:from gsearch import GoogleThen, create a new instance of theGoogleclass and call thesearchmethod with the desired query:with Google() as google:     results = google.search("Python tutorial")Thesearchmethod returns a list ofGoogleSearchResultobjects, each containing the URL, title, and description of a search result.To print the search results, you can use the following code:for result in results:
    print(f"Title: {result.title}")
    print(f"URL: {result.url}")
    print(f"Description: {result.description}\n")Here is an example of using gsearch to perform a Google search for "how to use Python":from gsearch import Google
with Google() as google:
    results = google.search("how to use Python")
    for result in results:
        print(f"Title: {result.title}")
        print(f"URL: {result.url}")
        print(f"Description: {result.description}\n")This will perform a Google search for "how to use Python" and print the title, URL, and description of each search result.ContributingIf you find a bug or have an idea for a new feature, feel free to open an issue or submit a pull request on GitHub.Licensegsearch is released under the MIT License. SeeLICENSEfor more information.Conclusion: gsearch is a powerful Python package that makes it easy to automate Google searches and extract information from the search results. Whether you need to perform a one-time search or automate a search process, gsearch is a great tool to have in your Python toolbox.
Package: gsec
Git-SecretRequirementsgitgithub-cliSECRET_KEYenvironment variable or.keyfile in the root of the repositoryYou can generate a secret key automatically by leaving theSECRET_KEYenvironment variable empty. It will be stored in the.keyfile.InstallationPippipinstallgsecFrom sourcegitclonecdgit-secret
pipinstall-rrequirements.txt
pythonsrc/main.py--helpUsageUsage:main.py[OPTIONS]COMMAND[ARGS]...

Options:--helpShowthismessageandexit.

Commands:addAddanewsecretdeleteDeleteasecretbyIDeditEditasecretbyIDlistListallsecretsshowShowasecretbyIDTODOAdd configuration file (json)Change repo pathChange secret keyCreate packagesPyPIAURCOPRAdd testsChange the wayshowdisplays the secrets
Package: gsee-redux
GSEE Redux: Global Solar Energy EstimatorThis is a fork ofGSEE.GSEEis a solar energy simulation library designed for rapid calculations and ease of use.Renewables.ninjausesGSEE.The development ofGSEEpredates the existence ofpvlib-pythonbut builds on its functionality as of v0.4.0. UseGSEEif you want fast simulations with sensible defaults and solar energy technologies other than PV, andpvlib-pythonif you need control over the nuts and bolts of simulating PV systems.Installationpip install gsee-reduxCurrently pip is the only supported installation method.The original GSEE library was intended to be installed through Conda,
but this is not yet possible for this version.DocumentationSee theoriginal documentationfor more information onGSEE's functionality and for examples.LicenseBSD-3-Clause
Package: gsem
gsemgsem- Command line extension manager for Gnome-Shellusage: gsem [-h]
            {ls,enabled,disabled,outdated,info,install,reinstall,uninstall,update,search,enable,disable}
            ...

Gnome-Shell extension manager

positional arguments:
  {ls,enabled,disabled,outdated,info,install,reinstall,uninstall,update,search,enable,disable}
    ls                  list installed extensions
    enabled             list enabled extensions
    disabled            list disabled extensions
    outdated            list outdated extensions
    info                show extension information
    install             install extension
    reinstall           reinstall extension
    uninstall           uninstall extension
    update              update extensions
    search              search extensions
    enable              enable extension
    disable             disable extension

optional arguments:
  -h, --help            show this help message and exitInstallationUser installation (recommended)Runpip install --user gsemMake sure you have"$HOME/.local/bin"in your$PATH.Global installationRunsudo pip install gsemUpdating the packageRunpip install -U --user gsemfor user installation orsudo pip install -U gsemfor global installation.Features:list installedlist enabled/disabledlist outdatedextension infosearchenable/disableinstall/uninstall/reinstallupdateContributingDevelopment on latest python version is preferred, as of now it's 3.9.
To start you'll need the following setup:Example uses pyenv to install latest python and manage virtualenv. Run the following commands from the root of the repository.pyenvinstall3.9.2# install latest python versionpyenvvirtualenv3.9.2gsem# create gsem virtual environmentpyenvactivategsem# activate the venvpyenvlocalgsem# set local python version for the repopoetryinstall# install all dependencies inside the virtual environmentpre-commitinstall# install pre-commit hooksRun all the linters:pre-commitrun-aTODO:pin
Package: gsender
galarm一个消息发送合集，有以下模块EmailSender：邮件发送DingTalkSender：钉钉群聊机器人EmailSender有以下参数receiver：接收者（可以是列表）content_text：邮件内容content_html：邮件内容（html 形式）files：文件路径（可以是列表）【示例】sender = EmailSender(user='xxx', pwd='xxx')
sender.send(receiver='', content_text='这是一封测试邮件')DingTalkSender支持钉钉所有消息类型消息发送了解链接：https://open.dingtalk.com/document/group/message-types-and-data-format#topic-2098229【示例】d = DingTalkSender(secret=DING_TALK_SECRET, access_token=DING_TALK_ACCESS_TOKEN)

d.send_text(content='测试消息', at_all=True)

d.send_text(content='测试消息', at_mobiles='xxx')

d.send_markdown(title='test', text='测试消息')

d.send_link(title='test', text='测试消息', message_url="https://www.baidu.com/")

d.send_feed_card(links=[
    {
        "title": "时代的火车向前开1",
        "messageURL": "https://www.dingtalk.com/",
        "picURL": "https://img.alicdn.com/tfs/TB1NwmBEL9TBuNjy1zbXXXpepXa-2400-1218.png"
    },
    {
        "title": "时代的火车向前开2",
        "messageURL": "https://www.dingtalk.com/",
        "picURL": "https://img.alicdn.com/tfs/TB1NwmBEL9TBuNjy1zbXXXpepXa-2400-1218.png"
    }
])

d.send_action_card_only(**{
    "title": "乔布斯 20 年前想打造一间苹果咖啡厅，而它正是 Apple Store 的前身",
    "text": "![screenshot](https://img.alicdn.com/tfs/TB1NwmBEL9TBuNjy1zbXXXpepXa-2400-1218.png) \n\n #### 乔布斯 20 年前想打造的苹果咖啡厅 \n\n Apple Store 的设计正从原来满满的科技感走向生活化，而其生活化的走向其实可以追溯到 20 年前苹果一个建立咖啡馆的计划",
    "btn_orientation": 0,
    "btns": [
        {
            "title": "内容不错",
            "actionURL": "https://www.dingtalk.com/"
        },
        {
            "title": "不感兴趣",
            "actionURL": "https://www.dingtalk.com/"
        }
    ]
})
Package: gserver
gserver 0.2.0Simple wrapper aroundgeventthat provides a basic routing engine
and JSON/JSONP handling.Here’s a simple usage example:from gevent.monkey import patch_all; patch_all()
from gevent import queue

from gserver.routes import Routes
from gserver.request import parse_vals
from gserver.wsgi import WSGIServer

routes = Routes()
route = routes.route
route_json = routes.route_json

@route("^/example/$")
def example(req):
    return "hello"

@route("^/poll/$")
def poll(request):
    yield ' ' * 1000
    yield "hello"
    sleep(5)
    yield "goodbye" # connection is closed at this point

@route("^/queue/$")
def q(request):
    def process(b):
        b.put("<div>1</div>")
        sleep(1)
        b.put("<div>2</div>")
        sleep(1)
        b.put("<div>3</div>")

    body = queue.Queue()
    body.put(' ' * 1000)
    body.put("<!doctype html><html><head><title>hola</title><head><body>\n")
    gevent.spawn(process, body)
    return body

@route_json("^/example/(?P<name>\w+)/$", method="GET,POST")
def example_name(request, name=None):
    data = request.query_data
    if request.method == "POST":
        data = request.form_data
    query_age, query_height = parse_vals(data, "age", "height")

    return { "name": name,
             "age": query_age,
             "height": query_height }

if __name__ == "__main__":
    server = WSGIServer(('', 9191), routes, log=None)
    server.serve_forever()get gserverInstallgevent, and it’s dependenciesgreenletandlibevent:sudo easy_install gserverDownload the latest release fromPython Package Indexor clonethe repositoryMore documentation is on it’s way(check thesitefor updates)Provide any feedback and issues on thebug tracker, that should be coming soon.
Package: gsExport
gsExportis a utility designed to help educators simplify and
streamline the process of grading student notebooks. Designed to
alleviate the struggles realized in UC Berkeley’sData 8, the system
allows students to easily export Jupyter notebooks as PDFs which are
segmented to allow for easy grading through the Gradescope interface.FeaturesThe system is easy to use, once installed on the client computer.In order to generate the PDF file for a notebook, students simply run the following
commandsimport gsExport
gsExport.generateSubmission("hw01a.ipynb")The exporting tool does the following:We diff the student’s notebook with the default “beginning” notebook,
to see what regions students actually contributed to. By doing so, we
eliminate a lot of the text/in-place code which doesn’t need to be
gradedUsing a custom LaTex template, we export to PDF (with pagebreaks as necessary)Structure RequirementsHow to work with gsExportIn your notebook, add the followingadd the text#newpagein the Markdown cells before which you’d like to pagebreak (for example, the beginning of a question)add ‘#student’ on all cells in which you expect the student to write informationTo generate the new notebook, run the following commands in the shelljupyter nbconvert hw01a.ipynb --NotebookExporter.preprocessors="['gsExport.gsExportPreprocessor']" --to notebookwhich will generate a notebook with all the appropriate structure in hw01a.nbconvert.ipynb. The following structure inside the IPython notebook is addedThe number of ‘#newpages’ in nb[‘metadata’][‘number_of_pages’]All cells with ‘#student’ set cell[‘metadata’][‘#student’] = True, and the line with ‘#student’ is removedWe save a list of MD5 checksums of each cell  in the notebook metadata: nb[‘metadata][‘checksums’]Installationpip install gsExport
pip install git+git://github.com/dibyaghosh/gsExport # alternativelyDevelopmentexporter.py- contains the main logic for the exporterutils.py- contains utilities for importing and exporting
notebooksok_grading.py- contains the OK autograder and export logicFor those interested in bundling filesSeesetup.pyfor the commands required to install bundled files Seeutils.pyfor the commands required to fetch the bundled files (this
is actually quite jank right now, because of a weird bug withJupyter
nbConvert)
Package: gs_export
GS ExportGS Export is a little helper that dumps your GenericSetup profile
to a given directory, and sends you a mail, if anything has changed
since it was last run.GS Export uses git to store the change history, it simply sends the result
of agit status-qif there are any changes.
It is your responsabilility to commit the changes, else you will get the
same notification on the next run.GS Export always sends a passwort with each request, it is POST encoded
but it is still there. This also means, it needs basic auth working on your
plone site. You might want to run GS Export only on the same machine
as the zope client.GS Export needs to be configured, and it needs a lot of options.
Since GS Export might be needed for many sites on one host, it does not
look for a configuration file with a fixed name, but you must provide
a configuration file as the first argument to the script.
This is a sample configuration. All arguments are required:[gs_export]
base_url = http://yoursite:8080/Plone/portal_setup
user = youruser
password = yourpass
path = /absolute_path_to_dump_diretory_of_git
mail_server = your.mailserver
mail_port = 587
mail_user = your_mail_user
mail_password= your_mail_pass
mail_from = your_email_adress
mail_mode = TLS
mail_recipient=your_receiving_email_adress
ignore = structure
    workflowbase_url must point to portal_setupthe path must existmail_mode accepts an empty string, TLS and SSLThis tool only accepts one mail recipient. This could easily by changed thoughignore accepts multiple parameters. Ignore means, after dumping the
configuration, the ignore parts are deleted! It is a good idea to ignore
structure. Multiple values can be added by adding one for each line
and indenting the elementsGS Export is intended to be run by a cron job.TodoAllow for multiple recipients.Changes0.1.2 (2012-12-05)Work around missing subprocess.check_output() in python 2.6
[pgerken]0.1.1 (2012-12-03)Make email-message more verbose
[pbauer]0.1.0 (2012-09-06)Nothing changed yet.0.0.5 (2012-09-06)Nothing changed yet.0.0.4 (2012-09-06)Nothing changed yet.0.0.3 (2012-09-06)Corrected the classifiers.0.0.2 (2012-09-06)Adding missing meta information.The egg has correct classifiers, but the egg tagged as 0.0.2
has not!0.0.1 (2012-09-06)Initial release
Package: gs.form
Author:Michael JasonSmithContact:Michael JasonSmith <mpj17@onlinegroups.net>Date:2014-05-05Organization:GroupServer.orgCopyright:This document is licensed under aCreative Commons Attribution-Share Alike 4.0 International LicensebyOnlineGroups.Net.IntroductionThis product contains the core functions and classes for making
HTTPPOSTrequests to send data to forms. For the most part
it consists of thepost_multipartutility, for posting data to
a form.While originally written forGroupServer, there is nothing
specific to GroupServer in this product.post_multipartThegs.form.post_multipartfunction is used to post data to a
form:post_multipart(host, selector, fields, files=[], usessl=False)See the documentation for more on how to use this function.AcknowledgementsThepost_multipartcode was based ona Python recipe by Wade
Leftwich. It was changed to useemail.multipartto create
the multipart document that is sent using aPOST.The Python standard library currently lacks a module for making aPOSTto a Web server.Issue 3244tracks the inclusion of a
module into the standard library.ResourcesDocumentation:http://gsform.readthedocs.org/Code repository:https://source.iopen.net/groupserver/gs.formQuestions and comments tohttp://groupserver.org/groups/developmentReport bugs athttps://redmine.iopen.net/projects/groupserver