Saravanan666/pypi-org huggingface dataset:
Package: edc-search
edc-searchAdd a slug field to models using the model mixinSearchSlugModelMixin. Specify the fields and/or properties to include in thesluginsearch_slug_fields:classTestModel(SearchSlugModelMixin,models.Model):search_slug_fields=['f1','f2','f3']f1=models.CharField(max_length=25,null=True)f2=models.DateTimeField(null=True)f3=models.IntegerField(null=True)f4=models.CharField(max_length=25,null=True)Fields in thesearch_slug_fieldsare converted to string in the slug:>>>obj=TestModel.objects.create(f1='run rabbit run!',f2=get_utcnow(),f3=12345)>>>obj.slug'run-rabbit-run!|2017-06-02 19:08:32.163520+00:00|12345'Fields not listed are not included:>>>obj=TestModel.objects.create(f1='slug me',f4='don\'t slug me')>>>obj.slug'slug-me||'Nullfields are converted to'':>>>obj=TestModel.objects.create()>>>obj.slug'||'You can use dotted syntax:classTestModel(SearchSlugModelMixin,models.Model):search_slug_fields=['f1','name.first','name.last']f1=models.CharField(max_length=25,null=True)defname(self):returnFullName(first='Gore',last='Vidal')>>>obj=TestModel.objects.create()>>>obj.slug'|Gore|Vidal'
Package: edc-sync
[![Build Status](https://travis-ci.org/botswana-harvard/edc-sync.svg?branch=develop)](https://travis-ci.org/botswana-harvard/edc-sync)
[![Coverage Status](https://coveralls.io/repos/botswana-harvard/edc-sync/badge.svg)](https://coveralls.io/r/botswana-harvard/edc-sync)
[![Code Health](https://landscape.io/github/botswana-harvard/edc-sync/develop/landscape.svg?style=flat)](https://landscape.io/github/botswana-harvard/edc-sync/develop)
[![PyPI version](https://badge.fury.io/py/edc-sync.svg)](http://badge.fury.io/py/edc-sync)# edc-syncDeploy a Django app as a client on laptop that is offline and sync the data with your server when you get back online.
Package: edc-vitals
edc-vitalsClasses for BP, weight, heart rate, respiratory rate, temperature etcSettings:# Blood pressure/severe hypertension
EDC_VITALS_SYS_UPPER: (default=180)
EDC_VITALS_DIA_UPPER: (default=110)

# Temperature/fever
EDC_VITALS_G3_FEVER_LOWER: (default=39.3)
EDC_VITALS_G4_FEVER_LOWER: (default=40.0)
Package: ed-design
IntroductionDesign package for the company Envidan A/S intended for use with matplotlib and seabornHardcoded palettes and colormaps with company design colorsEnvidan logo in print and web formGetting StartedInstallationYou can install this package usingpip install ed_designDependenciesSoftware dependencices are:matplotlib
seaborn
pandas
numpyUsePalettes and colormaps for matplotlib and seabornimport ed_design as edd

colors = edd.Colors()
colors.show_palette('all')

palette = colors.get_palette('blues')  # Use with categorical variabels
cmap = colors.get_cmap('BlGr')  # Use with continous variabels

my_own_camp = colors.create_cmap([color1, color2, color3], n_colors=256)Envidan logologo = edd.logo()Set styleedd.style()  # Sets envidan style with color prop cycle "normal" from edd.Colors()
edd.style('default')  # sets matplotlib default styleBuild and TestTODO:Nothing at the momementContributeOnly employees in Envidan has access to the repositoryAuthorMartin VidkjÃ¦r,mav@envidan.dk
Package: eddington
EddingtonEddingtonis a user-friendly data fitting platform for common uses, based on
open-source libraries such asnumpy,scipy, andmatplotlib.Eddingtoncan be integrated with python code as a library, can be used as a CLI and
has an easy to use GUI.InstallationIn order to install eddington use:pip install eddingtonDocumentationDocumentation for Eddington can be found onRead The Docs.CommunityYou can talk to the community through theEddLabs/developerschannel on Gitter.ContributingIf you experience problems with Eddington,log them on GitHub.If you want to contribute code, pleasefork the codeandsubmit a pull request.
Package: edds-process
edds_processPython Package to handle EGOS Data Dissemination System (EDDS) Data.QuickstartTo install package usingpip:pip install edds_process --extra-index-url https://__token__:<your_personal_token>@gitlab.obspm.fr/api/v4/projects/2052/packages/pypi/simple --trusted-host gitlab.obspm.frTo install package from source files:git clone https://gitlab.obspm.fr/rpw/edds_process.gitThen install usingpip:cd edds_proces
pip install .or usingpoetry:cd edds_process
pip install poetry
poetry installUser guidePackage modules can be then imported into codes with lineimport edds_process.Especially,edds_process.responsemodule contains methods to parse/create TmRaw/TcReport EDDS XML files.Authorsxavier dot bonnin at obspm dot fr
Package: edd-utils
EDD UtilsThis package is a utility for downloadingExperiment Data Depotstudy instances through python or the commandline. It was coded and is to be used in Python 3.6+. The package can be installed on your system through pip via the commandpip install edd-utilsThe package has two entry points, either as a commandline utility or as a python module. The commandline utility is used as below:$export_edd_studymy_edd_study_slug--usernamemy_edd_username--servermy.edd.server.orgFor an example of how to use the python module see the jupyter notebook in the notebooks directory.Note: The progressbar functionality will run correctly on JupyterLab v0.35.6 with enabled jupyterlab-manager labextension, which can be installed byjupyter labextension install @jupyter-widgets/jupyterlab-managerLogin credentials can also be provided in a configuration file,~/.eddrc:[edd.server1.org]
username: my_user_name1
password: my_password1

[edd.server2.org]
username: my_user_name2
password: my_password2Licenseedd-utilsis available under theBSD-3-Clause-LBNL license.
Package: eddy-bot
Eddy BotEddy Bot is a command line interface to interact with social media. Currently supports Twitter, TikTok and Instagram.Free software: Apache Software License 2.0Documentation:https://eddy-bot.readthedocs.io.ConfiguringBefore using Eddy Bot make sure you export all the needed environment variables for the social media you intend to interact with.
If you intend to interact with Tiktok and Instagram, you won’t need any further configuration.
The Tiktok crawler is implemented usingxdotooland the Instagram crawler is implemented usingSeleniumso you’ll just need to set your credentials according to the file .env.example.
If you intend to interact with Twitter as well, you’ll need first to apply for api usage onTwitter Developer Platformand then you’ll get all the keys you need to export, according to the file .env.example.Create a file named .env inside the root folder your repository, then copy the content from the file .env.example and paste it into file .env.Replace the values “xxx” with your credentials inside .env file.Installing packageMake sure you’ve created aPython Virtual Environmentand you’re using it.Install this package using command line:` pip installeddy-bot`FeaturesTwitterTweet message:` eddy_bot--tweet"Your message" `Tweet message with media:` eddy_bot--tweet"Your message"--mediapath/path/to/file.jpg `Follow profile:` eddy_bot twitter--follow"profile1,profile2" `Unfollow profile:` eddy_bot twitter--unfollow"profile1,profile2" `Update self profile description:` eddy_bot twitter--bio-update"My new profile description" `TiktokFollow profiles:` eddy_bot tiktok--follow"profile1,profile2" `Unfollow profiles:` eddy_bot tiktok--unfollow"profile1,profile2" `InstagramComment profile post:` eddy_bot instagram comment "Profile to comment on post" `Follow profiles:` eddy_bot instagram "profile1,profile2" `History0.1.0 (2021-05-08)First release on PyPI.
Package: eddy-footprint
eddy-footprint: Eddy covariance footprint modelingA Python library for creating eddy covariance flux footprints using multiple analytical models.Installationeddy-footprint can be installed from PyPI as:python -m pip install eddy_footprintOr from source as:python -m pip install git+https://github.com/arctic-carbon/eddy-footprint.gitNote:
The required dependencies installed with eddy-footprint areXarray,SciPy, andNumPy.DocumentationDocumentation is hosted on ReadTheDocs:https://eddy-footprint.readthedocs.io/en/latestlicenseAll the code in this repository isMITlicensed.
Package: eddy-mc
Eddy is a HTML output generator for MCNP and SCALE, it imports an MCNP or SCALE output file, extracts the important
data, and writes it to a user-friendly HTML file.This repository contains the source code version of Eddy, however Eddy is also available asa pre-compiled executable.Source Code CLI UsageEddy can be run from the command line with the output file and any applicable scaling factor as optional arguments; if
no such arguments are supplied a GUI will appear to request them.General CLI usage:python3eddy.py[-ooutputfile][-sfscaling_factor]PyPI Package UsageEddy is also available on the PyPI Python Package index as eddy-mc, in order to allow easier integration into other
programs. It can be installed using pip:pipinstalleddy-mcand accessed using:fromeddymcimporteddyeddy.main()whereeddy.main()can take the same two optional arguments; the filepath for the MCNP output and a scaling factor.
If these are not supplied, the GUI will appear to request them wheneddy.main()is called.Additionally, for Linux installs the wrapper script inbin/eddywill be placed in the/usr/local/bindirectory, placing it into the user'sPATHand allowing eddy to be called directly from any command line with
the following command:eddy outputfile [-h] [-sf SCALING_FACTOR]This method is intended for pure command-line use, so when eddy is called in this way, the filename argument is
non-optional, and if no scaling factor is supplied a default
of 1.0 will be assumed; this CLI interface will prevent the GUI window from appearing to request these values.FeaturesFeatures include:Eddy can convert F2, F4, F5, F6 and F6+ talliesEddy can accept average tallies, given in the formF4:N (4 5)Eddy can take an MCNP criticality output and show k-effective for the
first half, second half and total calculation.Eddy will present a warning if an MCNP case was halted due to lost particlesEddy will clearly present any FATAL ERROR messages in the MCNP outputEddy currentlydoes notaccept multi-particle tallies of the formF4:N,PFor F2, F4 and F5 tallies, the units are presented as microSieverts per hour.
The actual result from MCNP is typically multiplied by some conversion factor, so the
tally output could be in any unit. The uSv/h units have been left in for now as this
seems to be by far the most common conversion factor used for shielding calculations.Any valid HTML tags found in the MCNP output file will be escaped, preventing any unwanted
HTML or javascript injected into the MCNP output from making its way into the HTML output file.RequirementsPython 3.6 or laterJinja2 Python package is required (will be included automatically if Eddy is installed via pip)importlib_resources may be required for versions of python < 3.9pytest and pytest-mock Python packages are required to run the unit testsExample HTML outputs
Package: eddy-mc-core
Eddy is an HTML output generator for MCNP and SCALE, it imports an MCNP or SCALE output file, extracts the important
data, and writes it to a user-friendly HTML file.This repository contains the core source code version of Eddy. It is intended to be accessed via PIP and used as a
python module.
A stand-alone version of Eddy is also availablehere(it has this
package as one of its requirements), and Eddy is also available
asa pre-compiled executable.This package is available on the PyPI Python Package index as eddy-mc-core, in order to allow easier integration
into other programs. It can be installed using pip:pipinstalleddy-mc-coreand accessed using:fromeddymc_coreimporteddyeddy.main()whereeddy.main()has one non-optional argument; the filepath for the MCNP output, and one optional argument; a scaling factor to multiply any tally results by.
Features include:Eddy can convert F2, F4, F5, F5a, F6 and F6+ talliesEddy can accept average tallies, given in the formF4:N (4 5)Eddy can take an MCNP criticality output and show k-effective for the
first half, second half and total calculation.Eddy will present a warning if an MCNP case was halted due to lost particlesEddy will clearly present any FATAL ERROR messages in the MCNP outputEddy currentlydoes notaccept multi-particle tallies of the formF4:N,PFor F2, F4 and F5 tallies, the units are presented as microSieverts per hour.
The actual result from MCNP is typically multiplied by some conversion factor, so the
tally output could be in any unit. The uSv/h units have been left in for now as this
seems to be by far the most common conversion factor used for shielding calculations.RequirementsPython 3.6 or laterJinja2 Python package is required (will be included automatically if Eddy is installed via pip)importlib_resources may be required for versions of python < 3.9pytest and pytest-mock Python packages are required to run the unit testsExample HTML outputs
Package: eddy-mc-wrapper
Eddy is a HTML output generator for MCNP and SCALE, it imports an MCNP or SCALE output file, extracts the important
data, and writes it to a user-friendly HTML file.This repository contains the source code version of Eddy-Wrapper. It is a wrapper program for Eddy-Core, which contains
the core functionality of the Eddy Project. Eddy-Core is designed to work with a display-less remote server and as
such cannot handle parts of Eddy's User Interface, which have been extracted to this package; when Eddy-Wrapper is run,
it will call Eddy-Core to do the back-end work.Eddy is also available asa pre-compiled executable.PyPI Package UsageEddy is available on the PyPI Python Package index as eddymc-wrapper, in order to allow easier integration into other
programs. It can be installed using pip:pipinstalleddy-mc-wrapperand accessed using:fromeddymc_wrapperimporteddy_wrappereddy_wrapper.main()whereeddy_wrapper.main()can take the same two optional arguments; the filepath for the MCNP output and a scaling factor.
If these are not supplied, the GUI will appear to request them wheneddy.main()is called.Alternatively, Eddy-Wrapper can be run from the command line with the output file and any applicable scaling factor as
optional arguments; if no such arguments are supplied a GUI will appear to request them. It should be noted that if
Eddy-Wrapper has been downloaded directly (such as from GitHub) rather than via PIP, eddy-core will also have to be installed.General CLI usage:python3eddy_wrapper.py[-ooutputfile][-sfscaling_factor]However, users wishing to incorporate Eddy into their own software projects may find it easier just to use Eddy-Core;
information on how to include this module can be found inthe Eddy-Core repository.FeaturesFeatures include:Eddy can convert F2, F4, F5, F6 and F6+ talliesEddy can accept average tallies, given in the formF4:N (4 5)Eddy can take an MCNP criticality output and show k-effective for the
first half, second half and total calculation.Eddy will present a warning if an MCNP case was halted due to lost particlesEddy will clearly present any FATAL ERROR messages in the MCNP outputEddy currentlydoes notaccept multi-particle tallies of the formF4:N,PFor F2, F4 and F5 tallies, the units are presented as microSieverts per hour.
The actual result from MCNP is typically multiplied by some conversion factor, so the
tally output could be in any unit. The uSv/h units have been left in for now as this
seems to be by far the most common conversion factor used for shielding calculations.Any valid HTML tags found in the MCNP output file will be escaped, preventing any unwanted
HTML or javascript injected into the MCNP output from making its way into the HTML output file.RequirementsPython 3.6 or laterJinja2 Python package is required (will be included automatically if Eddy is installed via pip)importlib_resources may be required for versions of python < 3.9pytest and pytest-mock Python packages are required to run the unit testsExample HTML outputs
Package: eddysearch
EddySearchEddy is a collection of artificial function landscapes and search strategies to find their extrema points.
Most artificial landscapes are in euclidean space and can simply be seen as a landscape of hills and valleys and the goal is to find the lowest or highest point within a given evaluation budget.
This gives the possibility to compare optimization methods -- or often also known as search strategies -- in artificial settings:
either for the curious mind, for pedagogical purpose or for fair experimental comparison.
You can simply extend it with your own search strategy and see how well it works in these landscapes (objective functions).Jump to ..InstallationIntroduction / OverviewInstallationInstall from PyPi via poetry:poetry install eddysearchInstall with pip:pip install eddysearchInstall latest development version:poetry add git+https://github.com/innvariant/eddysearch.git#masterIntroTo make visualizations (e.g. 3D Plots or Manim-Videos) easy, objectives define much more information than just the pure function definition.
For example, they contain information about suggested visualization boundaries or their analytical or empirical known extrema.
Search strategies on the other hand provide capabilities to track their search path through space.
So it is easy to follow their search principles.
The main intent is to provide insights into the differences of various search strategies and how they behave in different artifcial landscapes.Artificial Landscapes.. also calledtest functions for optimization on Wikipedia.Himmelblau FunctionAlso seeWikipedia: Himmelblau's function.$f(x,y) = (x^2+y-11(x+ y^2-7)^2)$fromeddysearch.objectiveimportHimmelblauObjectiveobj=HimmelblauObjective()RastriginObjectivefromeddysearch.objectiveimportRastriginObjectiveobj=RastriginObjective()RosenbrockObjectivefromeddysearch.objectiveimportRosenbrockObjectiveobj=RosenbrockObjective()LeviN13Objectivefromeddysearch.objectiveimportLeviN13Objectiveobj=LeviN13Objective()CrossInTrayObjectivefromeddysearch.objectiveimportCrossInTrayObjectiveobj=CrossInTrayObjective()EggholderObjectivefromeddysearch.objectiveimportEggholderObjectiveobj=EggholderObjective()Under DevelopmentStier2020A1Objectivefromeddysearch.objectiveimportStier2020A1Objectiveobj=Stier2020A1Objective()Stier2020A2Objectivefromeddysearch.objectiveimportStier2020A2Objectiveobj=Stier2020A2Objective()Stier2020BObjectivefromeddysearch.objectiveimportStier2020BObjectiveobj=Stier2020BObjective()
Package: edea_ms
EDeA Measurement Serveredea-ms provides an API and user interface for planning, executing and analyzing measurement data for electronics engineering purposes. It allows engineering teams or collaborating individuals to automate tests and share results in a unified way, be it for board bringup, silicon evaluation or other test and measurement tasks.This project is based on the original EDeA Project proposal and takes further inspiration from theTestOps Manifesto by Keysight.Current StatusWe're using and developing this at Fully Automated for our OSHW and consulting projects. It's in a usable state, but currently only used internally. If you intend to use this, please contact us so we can understand the usecase of other engineering teams better.Running itTo make it as easy as possible to use, we've published a package on pypi which can just be installed like this:pipinstalledea_ms# or with optional dependencies for rendering charts server-sidepipinstall"edea_ms[optional]"And it can be run locally like this:python-medea_ms--localThis starts a webserver which is only reachable on the local machine without any user authentication to keep it simple for single user installs or just trying it out. To set up authentication to collaborate with others in a team see the docs onAuthentication.DevelopmentTo run the server from the repository, it needs both the backend and the frontend like this:# run the serverpdmrunuvicornedea_ms.main:app--reload# run the frontendnpmrundevBuilding the packageIn case you want to bundle a modified frontend into your own package, simply run:npmrunbuild# this will compile the frontend to static filespdmbuild# to build the final wheel with the frontend embedded in itMeasurement ClientSee theEDeA TMCproject for a library with which one can write test programs with.LicensesThe server code is licensed under theEUPL-1.2 licenseand the frontend code is licensed under theMIT license.
Images and artwork are licensed under CC BY-ND 4.0.Linking the server code (e.g. using it as a library) is allowed under the EUPL-1.2, even for commercial use. Modifications should be shared but the server code is structured in a way that it can easily be integrated in other systems (internal or otherwise) without modifying the core.If you want to host a modified frontend internally or externally, please replace the logos so that it's clear that it is a modified distribution.
Package: edeklaracje-client
E-Deklaracje clientHow toZnajdź interaktywny formularz PDF nastronie ministerstwadla PITu, który chcesz złożyć.Wypełnij formularz.Przygotuj plik XML na podstawieprzykładu. Wpisz wartości z interaktywnego formularza, który właśnie wypełniłeś.Zainstaluj klient edeklaracji:pip install edeklaracje_clientWyślij deklarację z pliku XML:edeklaracje send_document twoj_plik.xmlWięcej informacji o działaniu klienta można uzyskać.
Package: edelweiss-data-cli
Edelweiss Data CLIA CLI tool forEdelweiss Data:
Convenient publishing of scientific data with proper versioning, rich metadata support and a powerful APIInstallationInstall globally fromPyPiusingpip:pipinstalledelweiss-data-cliUsageRunedelweiss --helpto see a list of available commands.By default, the tool uses the public edelweiss api athttps://api.edelweissdata.com.
The--urlflag lets you use an alternative edelweiss api:edelweiss--urlhttps://${MY_DOMAIN}<command>For each command, use the--helpflag for more information:edelweiss<command>--helpCommandsAuthenticateUse theauthenticatecommand to generate access tokens and refresh tokens.edelweissauthenticateThe CLI responds with:Visit this url in your web browser to sign into edelweiss:
https://edelweiss.eu.auth0.com/activate?user_code=XXXX-XXXX

Your authorization token is XXXX-XXXX
Waiting for authentication.....Open the url in your web browser and follow the instructions to sign up or sign in. After you have signed in via the web browser, the CLI will print out the result:access_token- this is the bearer token for you to attach to all http requests.expires_in- the number of seconds until your access token expires; by default 86400 seconds.Use the--helpflag to see what options are available with the authenticate command:yarnrunauthenticate----helpCaution: If you sign up with a new email/password then you will receive an email to let you validate your address.  Access tokens generated by the CLI tool are not valid until you have validated your email address.Other commandsWe have lots of ideas for other Edelweiss commands, but they are not implemented yet. For example:Create a datasetFetch a datasetSearch for datasetsManage read/write permissionsPleasecreate an issueto lend your support to any of these suggested features.
Package: edendb
- clean API- flexible usage- good performance- 100% of unit tests pass- 100% code coverage (currently, only 75 lines of code)- each wrapper function can optionally have straight sql passed to it- wrapper functions use the same ordering of arguments as sql does- so it is easy for those who know sql to use the wrappers (thus savingkeystrokes!)- runs on any platform python2.5 runs (it would be trivial to port to earlierversions of python)Each sql command can be run in one line of code.