Saravanan666/pypi-org huggingface dataset:
Package: quintagroup.z3cform.captcha
Introductionquintagroup.z3cform.captcha is a package that allows to add captcha to the z3c.form.
As a result such forms are prevented from automatic submit.Captchas in a z3c formUsing quintagroup.z3cform.captcha in a z3c.form form is simple.
Just add a Captcha field to your schema, use CaptchaWidgetFactory
widget factory for this field and away you go:>>> from zope.interface import Interface
>>> from z3c.form import form, field
>>> from quintagroup.z3cform.captcha import Captcha
>>> from quintagroup.z3cform.captcha import CaptchaWidgetFactoryNow define form schema with Captch field>>> class ICaptchaSchema(Interface):
...     captcha = Captcha(
...         title=_(u'Type the code'),
...         description=_(u'Type the code from the picture shown below.'))And set proper widget factory for the captcha field>>>  class CaptchaForm(form.Form):
...      fields = field.Fields(ICaptchaSchema)
...      fields['captcha'].widgetFactory = CaptchaWidgetFactoryand z3c.form will take care of the rest. The widget associated with this field
will render the captcha and verify the use input automatically.Supported Plone versionsquintagroup.z3cform.captcha was tested with Plone 3.0.6, 3.1.7, 3.2.3, 3.3.4.AuthorsTaras MelnychukAndriy MylenkyiVitaliy StepanovCopyright (c) “Quintagroup”:http://quintagroup.com, 2004-2010Changelog1.0.3 (2013-07-17)Disabled handling in-line validation requests1.0.2 (2013-01-16)PPP fixesFixed Exception for python 2.4removed unused importUpdated classifiersfixed ViewPageTemplateFile import1.0.1 (2011-10-28)Fixed kss inline validation1.0 (2010-04-29)Initial release
Package: quinten-graph
The module quinten_graph provides tools to help:implement harmonized setting with respect to Quinten graphic chartexplore dataplot graphs for several variable at the same timeThe notebook sandbox.ipynb is here to let you play with the tool.Settings and variables used for the plots are managed through the class QuintenSettings defined in settings.py.
Plotting functions are defined in plotting.pyDoc for creating package:General procedure:https://packaging.python.org/en/latest/tutorials/packaging-projects/Example of pyproject.toml with dependencieshttps://setuptools.pypa.io/en/latest/userguide/pyproject_config.htmlInfo on file MANIFEST.in:https://packaging.python.org/en/latest/guides/distributing-packages-using-setuptools/#manifest-inProcedure for updating package:Make your changes in local repoPushIncrement version in pyproject.tomlin terminal pointing to folder where pyproject.toml is located, type:python -m build(if build is not installed,pip installit)You should get the following output "Successfully built quinten_graph-[VERSION].tar.gz and quinten_graph-[VERSION]-py3-none-any.whl"in same terminal, type :python -m twine upload --repository pypi dist/*(if twine is not installed, pip install it)You will be prompted for pypi credentials (@ get in touch withv.vincentelli@quinten-france.comidf needed). Then the upload should complete and you will get a link to the packageTasks:: Present the tool to Anna and Rami. Reminder: the objective is to have plots ready to copy and paste in presentations. skim over the plots and read through the following questions:Large color palette to defineFont Arial ok ?Other graphs to add to sandbox ,otebook ?Arrangement (titles, legend, xticks): before presenting add few graphs (prévison VS reel), check PBIs, pres projet DSN[x]: enlever fond gris seaborn[ ]: palette daltonien[x]: publier sur QF>packages_internes>  quinten_graph[ ]: étudier possibilité de d'étendre ce concept à PBI
Package: quintet
# Quintet_A Bootstrapped Markdown CMS powered by Django_[![Travis](http://img.shields.io/travis/quintet-cms/quintet.svg)](https://travis-ci.org/quintet-cms/quintet)[![Code Health](https://landscape.io/github/quintet-cms/quintet/master/landscape.png)](https://landscape.io/github/quintet-cms/quintet/master)[![pypi](http://img.shields.io/pypi/v/quintet.svg)](https://pypi.python.org/pypi/quintet/)![License](http://img.shields.io/pypi/l/quintet.svg)![Screenshot of edit post screen](http://thegoods.aj7may.com/content/images/2014/Sep/Screen_Shot_2014_09_29_at_11_23_26_PM.png)## Getting Started1. `pip install django`2. `pip install quintet --pre`3. `django-admin startproject myblog && cd myblog`4. Add the following to your `settings.py`INSTALLED_APPS = (...'django.contrib.humanize','django_forms_bootstrap','django_bootstrap_markdown','django_bootstrap_typeahead','django_password_strength','quintet',...)5. `./manage.py migrate`6. `./manage.py createsuperuser`7. `./manage.py runserver`8. Open <http://127.0.0.1:8000/quintet/>
Package: quintoandar-kafka
QuintoAndar Kafka Python LibraryQuintoAndar's kafka-python lib wrapper with additional functionalities.KafkaIdempotentConsumerA simple wrapper for kafka-python lib that uses redis to check duplicate events.ConfigurationNameDescriptiongroup_idThe consumer group idbootstrap_serversThe bootstrap serversredis_hostThe topic to consume fromredis_portThe function that processes the eventidempotent_keyFunction which extract an unique identifier from the eventSeeexamplesDevelopmentEnvironmentAt the bare minimum you'll need the following for your development
environment:Python 3.6.8It is strongly recommended to also install and usepyenv:pyenv-installerThis tool eases the burden of dealing with virtualenvs and having to activate and
deactivate'em by hand. Once you runpyenv local my-project-venvthe directory you're
in will be bound to themy-project-venvvirtual environment and then you will have
never to bother again activating the correct venv.Getting Started1. Clone the project:gitclonegit@github.com:quintoandar/kafka-python.gitcdkafka-python2. Setup the python environment for the project:makeenvironment3. Install dependenciesYou can just the make recipe:makeinstall
Package: quippy
Quippy is a parser for quantum circuit descriptions produces byQuipper.
Specifically, Quipper can output an ASCII description of the circuit, which can then be parsed by Quippy.Quippy provides a default parser in quippy.parser that will parse given text as:import quippy
parsed:quippy.Start = quippy.parser().parse(text)The parsed format uses anquippy.Startobject to represent the Quipper circuit by default.
This is a nice Object representation of the circuit theAbstract Syntax Treeis
directly transformed to byquippy.transformer.QuipperTransformer.
The resulting parsed object will have as type a Start object which will make the structure of the parse tree much clearer.
If you do no wish to use the included transformer but would rather have a general AST then pass:quippy.parser(transformer=None)We use the optional static typing provided inPEP 484to provide types for the returned objects,
this was included in Python 3.5 or higher.
Python 3.6 or higher is recommended.
Package: quippy-cli
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 \__, |\__,_|_| .__/| .__/ \__, |
    |_|       |_|   |_|    |___/quip/kwip/A quick, witty remarkQuickly fetch code snippets, text and URLs from the CLI.RequirementsThis project makes use ofpyfzfwhich requiresfzfto be installed and available on the PATH.On a Mac, you can install it withbrew install fzf. For more installation instructions, please see the project page.Installationpip install quippy-cliUsageTypeqpto invoke quippy.Keys can be added to~/.quippy.yaml.On running, qp lists all the keys available throughfzf. Selecting a key will copy its associated value to your clipboard.LicenseMITThanksfzf
Package: quip-spreadsheet
Quip SpreadsheetAn opinionated client to search, retrieve, and parse Quip spreadsheets using theQuip Automation API.It provides a client to pull data from the Quip API as well as classes to interact with folders, spreadsheets, pages, and rows.Installpipinstallquip-spreadsheetUsage# Importfromquip_spreadsheet.quipimportQuipPage# Initialize Clientquip=QuipClient(QUIP_ACCESS_TOKEN,QUIP_BASE_URL)# Search by termthreads=quip.search_threads("My Spreadsheet",count=1)# Load the content of a spreadsheetspreadsheet=threads.spreadsheets[0]spreadsheet.load_content()# Get a specific page of a spreadsheetpage=spreadsheet.get_named_page("Sheet1")# Get a specific row from a pagerow=page.get_nth_row(pointer)# Get cells content from a rowcells=row.get_row_cells_content(include_index=False)LicenseMITContributing & DevelopingPRs are welcome as long as documented, accompained by passing unit tests and in scope with the project.To setup the development environment run:pipenvinstall--devor manually install all the development dependencies found in thePipfile.
Package: quipu
Evaluate simple Python mathmatical and logical expressionshttp://en.wikipedia.org/wiki/QuipuAn attempt to make a safe evaluator of a subset of Python expressions.This is mostly a proof-of-concept for getting feedback, it has not been
thoroughly checked for safety, use at your own risk :)It uses the Python ast module to parse the expression, but all evaluation is
done by walking the ast, it is not directly executed by the Python runtime.Nosetests are provided below including coverage of supported and unsupported
operations.Known security considerations:The variables are expected to be simple primitive types. Providing functions
with unsafe effects, or variables where the operator implementations can have
unsafe effects is obviously unsafe.Some operations may also take a lot of time or memory and DOS the process.Usage:import quipu
result = quipu.evaluate('2 + 2')See the list of “supported_expressions” intest_asteval.pyfor an example of
what operations are implemented.
Package: quiq
quiqquiq is a simple and lightweight unit testing framework for for exploratory and
prototyping coding. quiq allows unit tests to be written right before functions
are declared in order to make a much more natural test/develop workflow in the
spirit of TDD.Example:@TestCase(F(6,5).isin(list(range(2,50))),F(6,5)==11,F(1,2)==51,F(1,2).throws())defadd(x,y):ifx==1:raiseValueError("No 1s!")returnx+yTest Case: add
✅  Original: add(6, 5) isin [2, 3, 4, 5...47, 48, 49]
    Expanded:        11 isin [2, 3, 4, 5...47, 48, 49]

✅  Original: add(6, 5) == 11
    Expanded:        11 == 11

❌  Original: add(1, 2) == 51
    Expanded: ValueError('No 1s!')

✅  Original: add(1, 2) throws Exception
    Expanded: ValueError('No 1s!')
Package: quirtylog
⚡ quirtylog ⚡Quick & dirty logging in python.The filerequirements.txtcontains the packages needed for the installation.
The code requirespython3.11+.InstallationTo install the package the simplest procedure is:pipinstallquirtylogNow you can test the installation... In a python shell:importquirtylogquirtylog.__version__Installation from sourceOnce you have cloned the repositorypipinstall.To use the develop mode just writepip install -e ..ExamplesThe package creates custom loggers object.importquirtyloglog_path="/path/to/logs"logger=quirtylog.create_logger(log_path=log_path)It is also possible to create decorators to be
used in a user-defined function.importquirtylog@quirtylog.measure_time(logger)deff(x):"""A function that do nothing"""returnx@quirtylog.measure_time(logger)defg(x):"""A function that raise an exception"""returnx/0.For further examples see the folderexamples.ContributingIf you want to contribute to this project, please follow the guidelines in theCONTRIBUTING.md.Official soundtrackJhonny Cash - The Frozen Logger
Package: quisby
Quisby(Unoffical name) Quisby: An idler; one who does not or will not work. (noun)Quisby is a tool to provide first view into the results from various benchmarks such as linpack, streams, fio etc. It doesn't aim to replace existing data viz tool but rather to provide a simplified view to the data with basic metric to understand the benchmark results from a higher level view. For detailed view, there are other tools such as pbench-dashboard, js-charts etc at hand.Bechmarks currently supported:BenchmarkSource datalinpackBenchmark resultstreamsSummary resultuperfSummary csv resultspecjbbBenchmark resultpigBenchmark  resulthammerDBBenchmark  resultfiopbench resultautohplSummary  resultaimBenchmark  resultetcdpbench  resultrebootBenchmark  resultspeccpuBenchmark  resultWhat it doesIt extracts data from benchmark results file or summary results produced by wrapper benchmark programs and move that results to Google Sheet via sheets API V4.Development#Clone the repogitclonegit@github.com:sourabhtk37/data-to-sheet.git# Installationsource./install.sh(optional,forconfiguringawsand/orazurecli)source./install-aws-azureconfig.pyconfig.pyis the only file you need to edit. Sample example have been provided in the file.quisby.pyThis is the main driver program that will be called once you have editedconfig.pyfile accordingly. It takes in an input file with list of location to the test results.The location file will look like:test: results_linpack
</path/to/results>
...
test: pbench_fio
<http url with results>
...quisbyprocess--os-type<add-here>--os-release<add-here>--cloud-type<add-here>location_file`For more information on options, run:`quisby -h`That's it. It will return a google sheet. Visit the google sheet page and you will see a newly created spreadsheet with the data populated and graphed.ComparisonIf you want to compare two different OS release of similar system type then there are scripts that will help you to create a spreadsheet for the same.and then run:quisbycompare--test-name<benchmark-name-(optional)>--spreadsheets<spreadsheet1,spreadsheet2>and it would return a newly created spreadsheet with the comparison data.ContributingCreate issues and create a seperate feature branch to work on it. Push the changes to your clone repo and then create a pull request to the master branch of the origin repo.
Package: quisca
QuiScA - Quizizz Score AggregatorA tool to compile and analyze multiple Quizizz reports to get statistics and rankings of KITS students.Features :Merges data from multiple Quizizz reportsDisplay all or top 10 scoresOption to save aggregated data in an Excel fileInstallationInstall it from pypi using :pip install quiscaUsageThe tool can be run from the command line using the following syntax:quisca -f [file1.xlsx] [file2.xlsx] ... [-a] [-o [output.xlsx]] [-v]-f, --files: List of Quizizz report files to process (required)-a, --all: Show/print all data (default option shows top 10 rankers)-o, --output: Save output into a .xlsx file-v, --verbose: Activate verbose output-h, --help: View helpDependenciespandastabulate
Package: quisk
QUISK is a Software Defined Radio (SDR) transceiver.
You supply radio hardware that converts signals at the antenna to complex (I/Q) data at an
intermediate frequency (IF). Data can come from a sound card, Ethernet or USB. Quisk then filters and
demodulates the data and sends the audio to your speakers or headphones. For transmit, Quisk takes
the microphone signal, converts it to I/Q data and sends it to the hardware.Quisk can be used with SoftRock, Hermes Lite 2, HiQSDR, Odyssey and many radios that use the Hermes protocol.
Quisk can connect to digital programs like Fldigi and WSJT-X. Quisk can be connected to other software like
N1MM+ and software that uses Hamlib.
Package: quisp
quisp.pyA Jupyter Widget Library for Running QuISPInstallationYou can install usingpip:pipinstallquispIf you are using Jupyter Notebook 5.2 or earlier, you may also need to enable
the nbextension:jupyternbextensionenable--py[--sys-prefix|--user|--system]quispDevelopment InstallationCreate a dev environment:condacreate-nquisp-dev-cconda-forgenodejsyarnpythonjupyterlab
condaactivatequisp-devInstall the python. This will also build the TS package.pipinstall-e".[test, examples]"When developing your extensions, you need to manually enable your extensions with the
notebook / lab frontend. For lab, this is done by the command:jupyter labextension develop --overwrite .
yarn run buildFor classic notebook, you need to run:jupyter nbextension install --sys-prefix --symlink --overwrite --py quisp
jupyter nbextension enable --sys-prefix --py quispNote that the--symlinkflag doesn't work on Windows, so you will here have to run
theinstallcommand every time that you rebuild your extension. For certain installations
you might also need another flag instead of--sys-prefix, but we won't cover the meaning
of those flags here.How to see your changesTypescript:If you use JupyterLab to develop then you 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 widget.# Watch the source directory in one terminal, automatically rebuilding when neededyarnrunwatch# Run JupyterLab in another terminaljupyterlabAfter a change wait for the build to finish and then refresh your browser and the changes should take effect.Python:If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.Updating the versionTo update the version, install tbump and use it to bump the version.
By default it will also create a tag.pipinstalltbump
tbump<new-version>
Package: quisp-widget
jupyter-quisp-widgetA Jupyter Widget Library for Running QuISPInstallationYou can install usingpip:pipinstallquisp_widgetIf you are using Jupyter Notebook 5.2 or earlier, you may also need to enable
the nbextension:jupyternbextensionenable--py[--sys-prefix|--user|--system]quisp_widgetDevelopment InstallationCreate a dev environment:condacreate-nquisp_widget-dev-cconda-forgenodejsyarnpythonjupyterlab
condaactivatequisp_widget-devInstall the python. This will also build the TS package.pipinstall-e".[test, examples]"When developing your extensions, you need to manually enable your extensions with the
notebook / lab frontend. For lab, this is done by the command:jupyter labextension develop --overwrite .
yarn run buildFor classic notebook, you need to run:jupyter nbextension install --sys-prefix --symlink --overwrite --py quisp_widget
jupyter nbextension enable --sys-prefix --py quisp_widgetNote that the--symlinkflag doesn't work on Windows, so you will here have to run
theinstallcommand every time that you rebuild your extension. For certain installations
you might also need another flag instead of--sys-prefix, but we won't cover the meaning
of those flags here.How to see your changesTypescript:If you use JupyterLab to develop then you 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 widget.# Watch the source directory in one terminal, automatically rebuilding when neededyarnrunwatch# Run JupyterLab in another terminaljupyterlabAfter a change wait for the build to finish and then refresh your browser and the changes should take effect.Python:If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.Updating the versionTo update the version, install tbump and use it to bump the version.
By default it will also create a tag.pipinstalltbump
tbump<new-version>
Package: quite
Featurespowerful signal-slotuser friendly widget classesUser Friendly Widget ClassesUniform wrapper on frequently-used widget, including:container widget:WidgetDialogMainWindowGroupBoxDockWidgetvalue widget:LabelLineEditComboBoxListWidgetSpinBoxDoubleSpinBoxbehavior widget:InputDialogActionShortcutPushButtonContainer WidgetExample 1:create widgetimportquitew=quite.Widget()w.exec()Simple WidgetExample 2:nested widgetimportquiteclassCustomWidget(quite.Widget):defpaint(self,painter:quite.Painter):painter.setFont(quite.QFont("Courier New",14.0))painter.draw_text_bottom_right(quite.PointF(0,0),"Custom Widget")painter.end()main_window=quite.MainWindow()custom_widget=CustomWidget(parent=main_window)main_window.set_central_widget(custom_widget)main_window.exec()Nested WidgetExample 3:widget from ui
fileimportosfromquiteimport*classCustomWidget(Widget):defpaint(self,painter:Painter):w,_=self.sizepainter.setFont(QFont("Courier New",14.0))painter.draw_text_bottom_right(PointF(0,0),"So Cool!")painter.draw_text_bottom_left(PointF(w,0),"From Custom Widget")painter.end()main_window=load_ui(filename=os.path.join(os.path.dirname(__file__),'main_window.ui'))main_window.set_central_widget(CustomWidget(parent=main_window))main_window.exec()Use QtDesigner to create a ui file:UI Design
Package: quit-store
Quads in Git - Distributed Version Control for RDF Knowledge BasesThe Quit Store (stands for Quads in Git) provides a workspace for distributed
collaborative Linked Data knowledge engineering. You are able to read and write
RDF datasets (aka. multiple Named Graphs) through a standard SPARQL 1.1 Query
and Update interface. To collaborate you can create multiple branches of the
dataset and share your repository with your collaborators as you know it from
Git.
Package: quittance
QuittanceGénère des quittances de loyers, au format PDF.Installationpip install quittanceConfigurationIl faut d’abord configurer quelques informations (addresses, noms…),
le plus simple est d’exécuter :quittance configqui vous génèrera un fichier de configuration et vous proposera de
l’éditer.Il est possible d’éditer la configuration en ligne de commande :quittance config --bailleur-city Lyon --bailleur-country FranceC’est pratique pour de petites corrections, mais pour tout configurer
préférez éditer le fichiertoml.UtilisationPour générer une nouvelle quittance, exécutez :quittanceUne nouvelle quittance sera générée au format PDF.
Package: quiverquant
Quiver Quantitative Alternative DataThis package allows you to access several alternative data sources which are updated daily and mapped to tickers. These include:Trading by US congressmenCorporate LobbyingGovernment ContractsPatentsOff-exchange short volumeCompanies' Wikipedia page viewsDiscussion on Reddit's r/wallstreetbetsDiscussion on Reddit's r/SPACsCompanies' Twitter followingsFlights by corporate private jetsPolitical BetaInsider TransactionsThis data can be used for backtesting and implementing trading strategies.Receiving API TokenYou can sign up for a Quiver API tokenhere.The pricing starts at $10/month, pleasee-mail meif that is an issue and I may be able to help cover.Getting StartedPrerequisitesPython version 3 installed locallyPip installed locallyInstallationThe package can easily be installed in your terminal by enteringpipinstallquiverquantUsage#Import the packageimportquiverquant#Connect to the API using your token#Replace <TOKEN> with your tokenquiver=quiverquant.quiver("<TOKEN>")#Get data on WallStreetBets discussiondfWSB=quiver.wallstreetbets()#Get data on WallStreetBets discussion of GameStopdfWSB_GameStop=quiver.wallstreetbets("GME")#Get recent trades by members of U.S. CongressdfCongress=quiver.congress_trading()#Get trades of a Tesla by members of congressdfCongress_Tesla=quiver.congress_trading("TSLA")#Get trades made by U.S. Senator Richard BurrdfCongress_Burr=quiver.congress_trading("Richard Burr",politician=True)#Get recent corporate lobbyingdfLobbying=quiver.lobbying()#Get corporate lobbying by AppledfLobbying_Apple=quiver.lobbying("AAPL")#Get data on government contractsdfContracts=quiver.gov_contracts()#Get data on government contracts to Lockheed MartindfContracts_Lockheed=quiver.gov_contracts("LMT")#Get data on off-exchange short volumedfOTC=quiver.offexchange()#Get data on off-exchange short volume for AMCdfOTC_AMC=quiver.offexchange("AMC")#Get data on Wikipedia page viewsdfWiki=quiver.wikipedia()#Get data on Wikipedia page views of MicrosoftdfWiki_Microsoft=quiver.wikipedia("MSFT")#Get data on companies' Twitter followingdfTwitter=quiver.twitter()#Get data on GE's Twitter followingdfTwitter_GE=quiver.twitter("GE")#Get data on r/SPACs discussiondfSPACs=quiver.spacs()#Get data on r/SPACs discussion of CCIVdfSPACs_CCIV=quiver.spacs("CCIV")#Get data on recent corporate private jet flightsdfFlights=quiver.flights()#Get data on private jet flights by TargetdfFlights_Target=quiver.flights("TGT")#Get data on patents by AppledfPatents_Apple=quiver.patents("AAPL")#Get data on recent insider transactionsdfInsiders=quiver.insiders()#Get data on recent insider transactions by Tesla insidersdfInsiders_Tesla=quiver.insiders("TSLA")