Saravanan666/pypi-org huggingface dataset:
Package: jet-django
Universal admin panel for DjangoDescriptionJet Admin:https://www.jetadmin.ioLive Demo:https://app.jetadmin.io/demoSupport:support@jetadmin.ioJetis a SaaS service that automatically generates back office for your Django Application through REST API ofJet Bridgepackage installed to your project.–Visual. Admin interface can be easily changed without need of development with the help of Visual Editor.–Secure. Jet does not access your data: its transferred directly from browser to your application.–Customizable. Flex functions allow you to solve your specific business tasks when standard functionality is not enough.This is a complete remake of popularDjango Jetadmin interface.FeaturesCRUD (create, read, update, delete):Create, view, update and delete data. Display it in an easy format, and then search and filter your data.Dashboard:Create reports and visualize KPIs. Monitor new data like new orders, comments, etc.Works with any technology:The interface is generated automatically based on an analysis of the data and data structure of your applications.Visual editor:Customize the admin area to make it easy for any manager to use. Allow managers to modify the interface, configure features, and set up analytics widgets without using any developers — just like WIX, Squarespace….Secure:Your data is safe. We do not have access to your information. We simply plug your information in to an easy-to-use interface for you to interact with it better.Works on any device:The interface is optimized for any device from phones to tablets to desktops.Quick installation:It takes only a few hours to integrate with your project.Available 24/7:Use it around the clock and don’t worry about updates — we take care of that.Manage users:Assign access rights to any data from within the panel.Activity log:Track the history of all changes and know who made them.RequirementsPython– 3.4, 3.5, 3.6, 3.7Django– 1.11, 2.0, 2.1Installation1. Download and install latest version of Jet Bridge:pipinstalljet-django2. Add ‘jet_django’ application to the INSTALLED_APPS setting of your Django project settings.py file:INSTALLED_APPS=(...'jet_django',...)3. Add URL-pattern to the urlpatterns of your Django project urls.py file:fromjet_django.urlsimportjet_urlsurlpatterns=[...url(r'^jet_api/',include(jet_urls)),...]4. Apply migrations:pythonmanage.pymigratejet_django5. Restart your project6. Open https://YOUR_PROJECT_URL/jet_api/register/ in browser to create a projectSupportFeel free to Email us –support@jetadmin.ioLicenseThis project isMITlicensed - see the LICENCE file for details.
Package: jeteloss
Data driven extraction of jet energy loss distributions in heavy ion collisionsCode Authors: Long-Gang Pang, Ya-Yun He and Xin-Nian WangIntroductionThis python package is a simple tool to extract the pt loss distribution
and the mean pt loss as a function of jet pt,
from the experimental single jet RAA for AA collisions at a specific beam energy
(with pt spectra in proton+proton collisions at the same beam energy) or the single hadron/gamma hadron
pt spectra (without pt spectra in proton+proton collisions).Example:fromjetelossimportPythiaPP,RAA2Elosspp_x,pp_y=PythiaPP(sqrts_in_gev=2760)raa_fname="RAA_2760.txt"eloss=RAA2Eloss(raa_fname,pp_x,pp_y)eloss.train()eloss.save_results()eloss.plot_mean_ptloss()eloss.plot_pt_loss_dist()The format of input data "RAA_2760.txt":
The first row is the comment row start with "#" and data description for the following columns,
"RAA_x, RAA_xerr, RAA_y, RAA_yerr" where RAA_x is the pt bins, RAA_xerr is the uncertainties of these pt bins, RAA_y is the RAA value in one A+A collisions, RAA_yerr is the uncertainties of RAA_y.ResultsCitationIf you have used this package to produce results for presentation/publications,
please cite the following two papers, from where one can find the detailed information of
the underlying physics.InstallationMethod 1: using pipStep 1:pip install jetelossStep 2:git clonegit@github.com:lgpang/jeteloss.gitStep 3:cd jeteloss/examplespython example1.pyMethod 2: install from local directoryStep 1: download the code from githubgit clonegit@github.com:lgpang/jeteloss.gitStep 2: install jeteloss and dependencescd jetelosspython setup.py installStep 3: run example codecd examplespython example1.pyMethod 3: using anacondaStep 1: To create one clean python virtual environmentconda create -n test_jeteloss python=3.6Step 2: To activate this environment, use:source activate test_jetelossStep 3: Install jeteloss module and its dependencespip install jetelossStep 4: Run the example code downloaded using:git clonegit@github.com:lgpang/jeteloss.gitcd jeteloss/examplespython example1.pyStep 5: To deactivate an active environment, use:source deactivateStep 6: Clean up
To see how many environments do you have, use:conda env listTo remove one environment, use:conda remove --name test_jeteloss --all
Package: jetengine
JetEngineJetEngine is a no-nonsensePython 3.5+asyncioMongoDBODM based onMongoEngineandMotorEngine. This package
builds upon prior work byilexandBjörn
Friedrichsto introduce native
Asynchronous I/O capabilities to MotorEngine.InstallationYou can install this package usingpipor the includedsetup.pyscript:# Using pip
pip install jetengine

# Using setup.py
python setup.py installUsageimportasyncioimportjetenginefromjetengineimportDocument,StringFieldclassUser(Document):name=StringField(required=True)asyncdefoperations():chris=awaitUser(name='Chris').save()user=awaitUser.objects.get(chris._id)assertuser.name=='Chris'awaitUser.objects.create(name='Someone')users=awaitUser.objects.filter(name='Someone').find_all()assertlen(users)==1assertusers[0].name=='Someone'loop=asyncio.get_event_loop()jetengine.connect("example",host="localhost",port=27017,io_loop=loop)loop.run_until_complete(operations())LicenseBSD 3-Clause License

Copyright (c) 2019, Phil Demetriou
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

* Redistributions of source code must retain the above copyright notice, this
  list of conditions and the following disclaimer.

* Redistributions in binary form must reproduce the above copyright notice,
  this list of conditions and the following disclaimer in the documentation
  and/or other materials provided with the distribution.

* Neither the name of the copyright holder nor the names of its
  contributors may be used to endorse or promote products derived from
  this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Package: jetfactory
jetfactory: async web api frameworkJetfactory is a Python framework for creating structured, portable and high-performance
Web APIs. It's built on top ofSanicand uses the
blazing fastuvloopimplementation of the asyncio event loop.Features and limitations:Lightweight, delivers high performance and high concurrencyScales horizontallyComes with a REST API browserAsynchronous; code must be non-blockingBuilt-in support for Mysql and Postgres databasesProvides intuitive tools for object serializationWorks only with modern versions of Python (3.6+)Created with Docker/Kubernetes in mindGetting startedYou can read more about Jetfactory in theDocumentation,
or check out anExample.DevelopmentWhile Jetfactory does work, it's currently under heavy development; Expect some breakage, as well as lacking documentation and tests.
That being said - I would very much appreciate people testing out the software, and perhaps even contribute with code.TasksIf you're interested in helping out in any way, let me know by creating an Issue or contact me by email.
Below are various tasks that needs completion in a first stable release.Currently in progressAdmin UI/OpenAPIAPI documentationUnit TestsTodoCORS supportGraphQL supportUsers packageAuthentication packageProject WikiCommand-line interfaceModular coreAuthorRobert Wikman <rbw@vault13.org>
Package: jetfuel
Python Performance Profiling for Production~ It's About Time ~Jetfuel is a performance profiler that can monitor the performance of your production Python, and makes results easy to aggregate and search through.Jetfuel is designed forPurposeful Profiling. This means that you only use Jetfuel around code of interest, instead of dumping all code performance logs and mining it later.Useful for Profiling:🌎 API performance🚀 CI/CD stage / granular performance💡 ML training & inference jobs📀 Database queries📊 Data pipelines / compute jobsBad performance hasreal world consequences, and is often a result oflack of visibility,even if you are logging it, if it's not be easy to get to, it will be ignored.What gets measured gets managed!How does it work?Jetfuel is very simple. The client simply times sections of your code, and batches / aggregates them before committing to the Jetfuel server. Updates are aggregated based on a configurable resolution (default 5s). This batching / aggregating behavior allows us to time ms/ns code without introducing much overhead.Installationpipinstalljetfueldockerrun-it-p9000:9000-v${PWD}/data:/bin/jetfuel/datajetfuel/jetfuelDemoimportjetfueljetfuel.init(url="http://localhost:9000")jetfuel.demo()UsageStart / Stopp=jetfuel.start("Foobar")passp.stop()Profilerwithjetfuel.Profiler("Foobar"):passFunction Decorator@jetfuel.profiler("Foobar")defml_training():pass
Package: jetha-cli
Jetha-Bhai CLIJetha-Bhai CLI is a command-line interface that provides a fun and unique way to interact with your file system. It mimics some common shell commands, but with a twist. Each command is translated into the language of Jetha-Bhai, a popular character from Indian television.Installationpipinstalljetha-cliTest Cmdjetha-bhai--help
jetha-bhaiye-banadof1
jetha-bhailist-kardoTablecommandjetha-clipwdjetha-bhai babita-ji-kahalsjetha-bhai list-kardomkdir c1jetha-bdhai ye-banado c1mv f1 c2jetha-bhai move-on-karado f1 c2rm -rf f1jetha-bhai udado-isko f1cp -r f1 f2jetha-bhai copy-maro f1 f2Thank you
Package: jetkiller
Jet KillerJet Killer converts images using the "jet" colormap to a better
one (by default "viridis") by using directly the pixel values,
without any knowledge about the underlying data.It can be used as a tool to enhance data visualizations for which
the original dataset is unavailable. Use cases include:enhancing figures from sources who made an unfortunate
colormap choice,enhancing graphs for which the original data may be lost,enhancing visualizations without having to regenerate it from the
original dataset.InstallationTo install and use Jet Killer, Python 3 is required.The following command installs thejetkillercommand
and thejetkillerpackage:pip3 install jetkillerFor details and alternative installation methods,
read theuser guide.Basic UsageWith the GUITo launch the GUI, use the following command:jetkiller --guiFrom the Command LineUse the following command to convertinput_filetooutput_file:jetkiller input_file output_fileFor more details, read theuser guide.From PythonTo convert images, import thejetkillerpackage and
use thejetkiller.convert_filefunction:importjetkillerjetkiller.convert_file("input_image.png","output_image.png")For more details, read theuser guide.DocumentationThe reference documentation is theuser guide.Release HistoryAll releases of this project are listed on the tag page of this
repository.SeeCHANGES.mdfor more details on the content of each release.Development RoadmapThe standalone version of Jet Killer is considered as complete
and will not have any major new features.Here are a few ideas on how to further improve the user experience:develop an extension for GIMP (probably with Python-Fu)develop an extension for Inkscape (probably using Python)VersioningJet Killer attempts to follow theSemantic Versioning
Specificationfor its version
numbers.LicenseJet Killer is distributed under the MIT License. SeeLICENSE-MITfor more details.
Package: jetpack
# jetpack[![Build Status](https://travis-ci.org/bmweiner/jetpack.svg?branch=master)](https://travis-ci.org/bmweiner/jetpack)Jetpack is a package[templating](https://en.wikipedia.org/wiki/Template_processor)system based on the [mustache](http://mustache.github.io/) template syntax.A jetpack template (pack) is just a directory containing subdirectories andtemplate files. A pack might be a[python package](https://docs.python.org/2/tutorial/modules.html#packages),[R package](https://cran.r-project.org/manuals.html#R-exts),[Ruby gem](http://guides.rubygems.org/make-your-own-gem/),anything...Packs are stored in a [hanger](https://github.com/bmweiner/hanger) andrendered by the jetpack utility.## the HangerA simple hanger might look like this:hanger/pack1/profile.mdpack.jsonpack2/bio.txtpack.cfgpack.jsonEach pack has it's own directory in the hanger and contains all thesubdirectories and template files for that pack. Additionally `pack.cfg` and`pack.json` files may exist at the hanger and/or pack level.### Template FilesTemplates use the [mustache](http://mustache.github.io/) template syntax(implemented with [pystache](https://github.com/defunkt/pystache)).Partials are relative to the hanger directory.hanger/pack1/profile.md# {{team}}{{first}} {{last}}{{role}}## Bio{{> pack2/bio.txt}}Created: {{today}}hanger/pack2/bio.txtBelichick has extensive authority over the Patriots'...### Context FilesContext is stored in **pack.json** files.hanger/pack.json{"team": "New England Patriots"}hanger/pack1/pack.json{"first": "Bill","last": "Belichik","role": "coach"}#### Built-in ContextThe default context includes the following tags, which can be overwritten in acontext file, if desired.**datetime*** today: %c* year: %Y* month: %m* day: %d* hour: %H* minute: %M* second: %S### Configuration FilesConfiguration is stored in **pack.cfg** files. The following options areavailable:A pack object can inherit the templates, contexts, and configurations of otherpacks. Base classes are separated by a comma.[class]base: python,generic#### InheritanceWhen base classes are specified, templates, contexts, and configurations areinherited in the following order:* pack* pack bases (recursive)* hangerCircular imports are not permitted.Set the format of built-in context tags by using the datetime[directives](https://docs.python.org/2/library/time.html#time.strftime).[datetime]today: %cyear: %Ymonth: %mday: %dhour: %Hminute: %Msecond: %S## Installation$ git clone https://github.com/bmweiner/jetpack.git$ python setup.py installor$ pip install jetpack## Usagejetpack provides a terminal command `jetpack`:$ jetpack python -s /path/to/hangername: my_packagedescription: The best package!try `jetpack --help` for additional details on usage.and a python module for interaction:import jetpackjetpack.launch(hanger='/path/to/hanger', pack='python', name='my_package',description='The best package!')## ExampleFork my [hanger](https://github.com/bmweiner/hanger) to get started. Thisexample demonstrates using...* partials to create .gitignore and LICENSE* subclasses to render python-flask pack from python pack* built-in datetime context
Package: jetpay-sdk
Jetpay payment page SDKThis is a set of libraries in the Python language to ease integration of your service
with the Jetpay Payment Page.Please note that for correct SDK operating you must have at least Python 3.5.Payment flowInstallationInstall with pippipinstalljetpay-sdkGet URL for paymentfrompayment_page_sdk.gateimportGatefrompayment_page_sdk.paymentimportPaymentgate=Gate('secret')payment=Payment('402')payment.payment_id='some payment id'payment.payment_amount=1001payment.payment_currency='USD'payment_url=gate.get_purchase_payment_page_url(payment)payment_urlhere is the signed URL.Handle callback from JetpayYou'll need to autoload this code in order to handle notifications:frompayment_page_sdk.gateimportGategate=Gate('secret')callback=gate.handle_callback(data)datais the JSON data received from payment system;callbackis the Callback object describing properties received from payment system;callbackimplements these methods:callback.get_payment_status()Get payment status.callback.get_payment()Get all payment data.callback.get_payment_id()Get payment ID in your system.
Package: jetplot
# Jetplot![build](https://github.com/nirum/jetplot/workflows/build/badge.svg)
[![codecov](https://codecov.io/gh/nirum/jetplot/branch/master/graph/badge.svg)](https://codecov.io/gh/nirum/jetplot)## Aboutjetplotis collection of miscellaneous utils for Matplotlib.## Installation`bash pip install jetplot `## DocumentationComing soon.## ChangelogVersion | Release Date | Description                                                                                                                                                                                                     |——: | :———-: | :————————————————————————————————————————————————————————————————————– |0.5.3   | Aug 30 2022  | Stops jetplot from updating Matplotlib rcParams on import.                                                                                                                                                     |0.5.0   | Jul 15 2022  | Updates default color palettes, adds new Palette class, adds ridgeline plot.                                                                                                                                                     |0.4.0   | Oct 20 2021  | Name change! Renamed package fromjetpacktojetplot.                                                                                                                                                       |0.3.0   | Oct 13 2021  | Drops animation module and themoviepydependency                                                                                                                                                             |0.0.0   | Jan 19 2015  | Initial commit                                                                                                                                                                                                  |## LicenseMIT. See [LICENSE.md](./LICENSE.md)
Package: jet-python
Python Jet.com API ClientInstallationpip install jet-pythonUsageGet an authenticated jet clientfromjetimportJetjet=Jet(user='0CXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX',secret='NXXXXXXXXXXXXXXXXXXXXXXXXj+',merchant_id='d4fe23456789876545678656787652',)Fetch 10 products at a timeskus=jet.products.get_skus(page=1)Find ready to ship ordersorder_ids=jet.orders.get_recent_order_ids(status='ready')Acknowledge an orderjet.orders.acknowledge(order_id)Mark an order as shippedThis involved a nested data structure. To make this easier
this module provides a convenient higher level data
structure calledjet.ShipmentfromjetimportShipmentshipment=Shipment(shipment_id='CS1234',tracking_number='1Z12324X12342435',ship_from_zip_code='91789',shipment_date=date.today(),carrier='UPS',shipment_method='Other')foriteminitems:shipment.add_item(sku='iphone-xs',quantity=2,)jet.orders.ship(order_id,[shipment])FeaturesTODOIntegration Approval API callsfromjetimportJetjet=Jet('XXX','XXX','XXXX')jet.products.update_price('IPHONE-8',79.99)# Fulfillment node id prodived by approval workflowjet.products.update_inventory('IPHONE-8',{'998bb45c821d4d5a84e73d68004f898b':5})# Get ordersorder_ids=jet.orders.get_recent_order_ids('ready')# Acknowledge an orderjet.orders.acknowledge('6b07db3d2e5643479242527332782dee',{'a35bd1f8a8ab4481a0cccda6e2012e13':'fulfillable'})# Acknowledge orderjet.orders.acknowledge('e0d9e28d650d44daaa55f297847c0ab2',order_items={'69585063be2a46ccb5dbf75823a3e7c1':'fulfillable'})# Cancelling an ordershipment=Shipment(shipment_id='CS1234')shipment.add_item("RBE750-GOL",quantity=0,cancel_quantity=1)jet.orders.ship('e0d9e28d650d44daaa55f297847c0ab2',[shipment])DocumentationThe full documentation is athttp://jet-python.rtfd.org.History0.1.0 (2019-04-01)First release on PyPI.
Package: jetsam
JetsamTrue daemonizer using native C callsCurrently only compatible with*nixfile systemsExtra Paranoid Edition uses thatdouble fork magic!jetsam definition: floating debris ejected from a shipC ExtensionTo showcase a C library being used as anative python moduleExampleimporttimeimportloggingimportjetsamfromjetsamimportdaemon# jetsam will log pids and errors from daemons# to a single log file. It will also update the file# with the current status of the daemon##   function_name:pid:status#jetsam.set_logfile("user_daemon.log")# defaults to /tmp/jetsam.log@daemondeffunc():logging.basicConfig(filename="func.log",level=logging.DEBUG,filemode="w")whileTrue:time.sleep(1)logging.debug("I am running in my own interpreter!")func()# detachs from current interpreter each function immediately returnsprint("simulate long running process...")time.sleep(3)jetsam.end_daemon(func)print("Eject and forget with jetsam!")
Package: jetset
JetSeT is  an open source  C/Python   framework  to reproduce radiative and accelerative processes acting in relativistic jets,allowing to fit the numerical models to observed data. The main features of this framework are:handling observed data: re-binning, definition of data sets, bindings to astropy tables and quantities
definition of complex numerical radiative scenarios: Synchrotron Self-Compton (SSC), external Compton (EC) and EC
against the CMBConstraining of the model in the pre-fitting stage, based on accurate  and already published phenomenological trends.
In particular, starting from phenomenological parameters, such as spectral indices, peak fluxes and frequencies, and
spectral  curvatures, that the code evaluates automatically, the pre-fitting algorithm is able to provide a good
starting model,following the phenomenological trends that I have implemented. fitting of multiwavelength SEDs usingboth frequentist approach (iminuit) and bayesian MCMC sampling (emcee)Self-consistent temporal evolution of the plasma under the effect of radiative and accelerative processes, both firstorder and second order (stochastic acceleration) processes.AcknowledgementsIf you use this code in any kind of scientific publication please cite the following papers:Tramacere A. 2020https://ui.adsabs.harvard.edu/abs/2020ascl.soft09001T/abstractTramacere A. et al. 2011http://adsabs.harvard.edu/abs/2011ApJ...739...66TTramacere A. et al. 2009http://adsabs.harvard.edu/abs/2009A%26A...501..879TMassaro E. et. al 2006http://adsabs.harvard.edu/abs/2006A%26A...448..861MLicenceJetSeT is released under a 3-clause BSD  license,  for deatils seeLicensefileDocumentationvisit:https://jetset.readthedocs.io/en/latest/visit:https://github.com/andreatramacere/jetset