Saravanan666/pypi-org huggingface dataset:
Package: predix
The Predix Python SDK has been crafted to help Python developers have quick
success writing applications using Predix Services.Install it from PyPI:pip install predixIf that isn’t working for you, we highly recommendThe Hitchiker’s Guide to
Properly Installing Pythonto learn about installingpython,pip, andvirtualenvfor your environment.  For industrial environments, you
may also need to learn how to set your proxies.See thePredix Volcano Appfor a full demonstration of the SDK
used in a Python Flask App.Getting StartedPlease see theGetting Started Guidefor a walkthrough and introduction to
basic usage of the Python SDK.[x]User Account and Authentication(UAA)[x]Predix Asset[x]Predix Time Series[x]Predix Access Control(ACS)[x]Predix Blob Store[x]Predix Cache(Redis)[x]Predix Database as a Service(PostgreSQL)[x]Predix Event Hub[x]Loggingmore…Getting HelpIf something doesn’t work as expected and you want help:Create aGitHub Issuein this projectAsk on thePredix Developer ForumSend email tovolcano@ge.comand we’ll respond as soon as we canContributorsSee theDeveloping PredixPy Guideif you want to contribute or
modify the SDK itself.If you send a PR it will be reviewed as soon as possible but contribution
guidelines and agreements for external parties have not been finalized.
Package: predixy
Predi-XYversion 1.2.0A command line program to predict NICS-XY scan results based on an additivity scheme.Requires Python 3.7 or newer. To check which version of Python is active:python --versionInstallationRecommended installation method:Predixy is available on PyPI, so simply install it usingpip:pip install predixyManual installation:Navigate to the top level folder of the downloaded/cloned repository. Then you can either run thesetup.pyscript or manually install requirements usingpip.Installation usingsetup.py:python setup.py installInstall dependencies usingpip:pip install -r requirements.txtRunning the programIf you installed the program from PyPI or using thesetup.py, you will have predixy in your PATH and can run it from anywhere. Just run:predixy INFILEIf you only installed the dependencies, you can need to navigate to the top level folder containingpredixy.pyand run:python predixy.py INFILEThe INFILE should be a.xyzor Gaussian.infile containing the xyz coordinates in Angstrom of the molecule you would like to analyze.HelpTo get the help and list all options, run (depending on your installation method):predixy --helpor:python predixy.py --helpEditing the configuration fileEdit theconfig.inifile using your favorite editor. Lines starting with#and;are comments. Do not delete lines as this will cause errors.
The location of the config file can be retrieved from the program by using the help.What's new in version 1.2.0Papers to cite were updated.
Scan distance was fixed (now starts at 0).
Data for building blocks was corrected.
Reading in xyz files was fixed.
Package: predocs
PreDoCS: Preliminary Design of Composite StructuresPreDoCS (Preliminary Design of Composite Structures) is a Python tool for fast evaluation of
wing structure concepts i.e. for a multi-disciplinary design optimization.Install PreDoCSCreate anAnacondaenvironment:conda create -n predocs python=3.9
conda activate predocsInstall the OpenCASCADE dependency (only available with conda)conda install -c dlr-sc "pythonocc-core<7.5"To install PreDoCS, use pip:pip install predocsAdditional dependenciesFor the export of the cross sections forBECAS(PreDoCS.CrossSectionAnalysis.Export.generate_BECAS_input), theBECAS shellexpandermust be installed.QuickstartFor a quickstart example, take a look at thePreDoCS examples.LicensePlease see the fileLICENSE.mdfor further information about how the content is licensed.DocumentationThe documentation is available athttps://dlr-sy.gitlab.io/predocs/.
Package: predpy
# predpyHere are the tools to automatically assess and test multiple workingmachine learning techniques.## InstallationA `setup.py` file is included. To install into a python environment run```bashpip install git+https://github.com/pgeurin/predpy.git```Included are two extra modules:##GalgraphsHere you will find graphing functions for numpy arrays and pandas dataframes.Graphs with ax take a axis from matplotlib.Use pattern matplotlib 'fig, ax = subplots(1,1)' for best effect.Graphs without an 'ax' input plot themselves.The code used here HEAVILY relies upon the foundational work of Matt Drury.This project just wouldn't be the same without it.Pandas and matplotlib. are also foundational tools to the work.How to use the documentation----------------------------Documentation in docstrings provided with the code.We recommend exploring the docstrings using`IPython <http://ipython.org/>`_, an advanced Python shell withTAB-completion and introspection capabilities.Use the built-in ``help`` function to view a function's docstring::Available graphs:---------------------'emperical_distribution','one_dim_scatterplot','plot_emperical_distribution','plot_many_predicteds_vs_actuals','plot_many_residuals','plot_one_univariate','plot_solution_paths','plot_univariate_smooth','predicteds_vs_actuals','residual_plot','simple_indicator_specification','simple_spline_specification','standardize_y','train_test_split'##CleandataCleans pandas dataframes using modern machine learning practices.Turn first to clean_df(). It's your friend in a world of darkness.It detects all manner of unmentionable values and replaces them with the mean ordistinguishing feature.## Versioning0.0.1 - Working graphs.0.0.2 - Documentation.0.0.3 - More graphs.0.0.4 - Cleaning. predpy.
Package: predstorm
PREDSTORMThis is Python3 code for space weather prediction research.The package is used for predicting the background solar wind, high speed solar wind streams and solar storm magnetic flux ropes based on data from solar wind monitors at the Sun-Earth L1 and L5 points, as well as from any spacecraft positioned east of the Sun-Earth line around or < 1 AU. We also derive predictions of the geomagnetic Dst index, Kp and auroral power.Status in 2019: work in progress.If you want to use parts of this code for generating results for peer-reviewed scientific publications, please contact us per email (see contributor biographies) or via twitter @chrisoutofspace (Christian Moestl).InstallationPREDSTORM is written in Python 3. Most dependencies (numpy, scipy, matplotlib) can be downloaded and used in an anaconda environment (https://www.anaconda.com/distribution/) and can be installed using the following lines:conda install scipy numpy matplotlib scikit-learn seaborn requests-ftp beautifulsoup4
  conda install -c conda-forge spiceypy cftime
  conda install -c numba numbaRemaining dependencies (particularly those for CDF handling) can be downloaded using pip:pip install cdflib spacepy astropyPREDSTORM also relies on the HelioSat package for all heliospheric data downloads and SPICE kernel handling. Currently it can be downloaded from GitHub:git clone https://github.com/IWF-helio/HelioSat.git
cd HelioSat
  python setup.py installHelioSat automatically downloads kernels and all required satellite files (e.g. STEREO, DSCOVR, ...). To set the path where these files are downloaded to, set the following environment variable (in .bashrc on Linux, .bash_profile on Mac):export HELIOSAT_DATAPATH="/path/to/data/heliosat"It's a good idea to import the package after first installation to handle first download of all required SPICE kernels.Running the codeIn the command line:python predstorm_l1.py
python predstorm_l5.pyUse the following option for the Agg backend in matplotlib:python predstorm_l5.py --serverNotesRunning the scripts creates the local folder /data. OMNI2 data, among other things, are automatically downloaded into this folder.Results are saved in the folder /results.Logs of the scripts are saved in predstorm.log.ContributorsIWF-Helio Group, Space Research Institute (ÖAW), Graz, Austria:Christian MöstlRachel L. Bailey
Package: preemo-worker-sdk
Preemo Worker SDKThis subrepo contains the python implementation of the Preemo Worker SDK.Installationpip install preemo-worker-sdkUsageRegister FunctionIn order to register a function with Preemo workers, you can useregisterto decorate your functions.frompreemo.workerimportregister@register(name="some_name",namespace="dev")defdo_something(params:bytes):...Both parameters,nameandnamespace, are optional. If the name isn't specified, it will default to the name of the function. If the namespace isn't specified, it will default to a global namespace.@registerdefdo_something(params:str):# registers with name do_something in the global namespace...At the moment, only functions that take 0 or 1bytesarguments will work. These functions should also either returnNoneorbytes.Resource RequirementsIf your function has particular resource requirements, you should specify those during registration.For example, if your function needs 4 cpu cores to run effectively, you can pass a configuration object.frompreemo.workerimportregister@register(name="some_name",namespace="dev",cpu_cores=4)defdo_something(params:bytes):...You can specify the memory and/or storage requirments in either Mebibytes (MiB) or Gibibytes (GiB).frompreemo.workerimportregister@register(name="some_name",namespace="dev",memory={"MiB":100},storage={"GiB":10})defdo_something(params:bytes):...If you need GPUs to effectively run your function, you may pass the specific model to use.frompreemo.workerimportregister@register(name="some_name",namespace="dev",gpu_model="nvidia-tesla-k80")defdo_something(params:bytes):...Along with a gpu model, you may pass a number of gpu devices needed.frompreemo.workerimportregister@register(name="some_name",namespace="dev",gpu_model="nvidia-tesla-k80",gpu_count=2)defdo_something(params:bytes):...Execute FunctionIn order to execute a function that you have previously registered with Preemo workers, you can useget_function.frompreemo.workerimportget_functiondo_something=get_function(name="some_name",namespace="dev")result=do_something(b"params")...The second parameter,namespace, is optional. If the namespace isn't specified, it will default to a global namespace.# gets the function named do_something in the global namespacedo_something=get_function("do_something")result=do_something(b"params")...Parallel Function ExecutionIn order to execute a function with multiple parameters at the same time, you can useparallel.frompreemo.workerimportget_function,paralleldo_something=get_function(name="some_name",namespace="dev")results=parallel(do_something,params=[b"params1",b"params2",...])...If your function doesn't take a parameter and you'd like to run multiple instances of it in parallel, you can use thecountparameter.do_something=get_function(name="some_name",namespace="dev")results=parallel(do_something,count=10)...ResultsIn order to view the result of an executed function, you can call.get().frompreemo.workerimportget_functiondo_something=get_function(name="some_name",namespace="dev")result=do_something(b"params")value=result.get()...ContributingContribution guidelines for this project
Package: preemptive-debugger
preemptive_debuggerA simple method to interactively preempt a running script to run a debuggerInstallingInstall:pip install preemptive_debuggerUsageIn one terminal, create a file calledtest.pywith the following:import preemptive_debugger

import time

for i in range(10_000):
    print(f"i = {i}")
    time.sleep(0.1)Run this code with:python3 test.pyIn another terminal, run:kill -SIGUSR1 $(pgrep -f "python3 test.py")This will preempt the running script and start a debugger in the original terminal, which can be used to analyze what is happening. This is very useful when you have a script that is stuck or doing strange things. Without this package, if you want to see what is going on in the script, you would typically need to stop the script, modify the code, and try your best to reproduce the result (or wait a long time to have the issue come back up). With this package, adding just one line (import preemptive_debugger), you can easily start a debugger whenever you want to look into what is happening in a python program.NotesI have tried some alternative methods to interactively choose when to start a debugger, but they didn't work well. Some pip packages I have tried:keyboard: Tried to start a debugger when a keyboard key was pressed, but I got this error which was very inconvenient:ImportError: You must be root to use this library on linux.pynput: Tried to start a debugger when a keyboard key was pressed, but I realized this starts a new thread to run the handler. This does not allow me to properly analyze the state of the program I am interested in.madbg: Tried attaching to the script withmadbg attach <pid>, but this only worked for very simple scripts. For any nontrivial script, I got this error:pyinjector.api.LinuxInjectorPermissionError: Injector failed with -8 calling injector_attach: PTRACE_ATTACH error : Operation not permitted
Failed attaching to process due to permission error.
This is most likely due to ptrace scope limitations applied to the kernel for security purposes.
Possible solutions:
 - Rerun as root
 - Temporarily remove ptrace scope limitations usin
`echo 0 | sudo tee /proc/sys/kernel/yama/ptrace_scope`
 - Persistently remove ptrace scope limitations by editing /etc/sysctl.d/10-ptrace.conf
More details can be found here: https://stackoverflow.com/q/19215177/2907819')Running withsudo, I got this error:pyinjector.api.InjectorError: Injector failed with -5 calling injector_inject: dlopen failed
Package: preerpost
[![Build Status](https://travis-ci.org/CSDTs/Django-pre-post.svg?branch=master)](https://travis-ci.org/CSDTs/Django-pre-post)[![Updates](https://pyup.io/repos/github/CSDTs/Django-pre-post/shield.svg)](https://pyup.io/repos/github/CSDTs/Django-pre-post/)# Django-pre-post
This Django app provides the ability to create pre-post questions and answers. It was developed by the CSDTs team at RPI to embed pre-post tests for students in their website and to ease data collection.# Installation & Integration## Download and install:
Either use pip in terminal:pip install django_pre_postOr add django_pre_post to your requirements / libraries file and runpip install -r requirements.txt## Add the application to your site:
Include it in settings.py` INSTALLED_APPS = ( ... your apps here ... 'django_pre_post', ) `Include it in URLS.py` urlpatterns = [ ... your pageshere...url(r'^questionnaire/',include('django_pre_post.urls')),] `# Testing## Prerequisites
* * VirtualBox
* Linux: sudo apt-get install virtualbox
* Windows & Mac:https://www.virtualbox.org/wiki/Downloads* * Vagrant
* Linux: sudo apt-get install vagrant
* Windows & Mac:https://www.vagrantup.com/downloads.html* * Git
* Linux: sudo apt-get install git
* Windows & Mac:https://git-scm.com/downloads* * * For windows Make sure C:Program FilesGitusrbin [is in your path variable](http://www.computerhope.com/issues/ch000549.htm)## Setup`shell git clonehttps://github.com/CSnap/Django-pre-post#get the code cdDjango-pre-postvagrant up #build the system in a virtual machine vagrant ssh #enter the virtual machine cd /vagrant python manage.py runserver 0.0.0.0:8000  #run the server `Navigate to localhost:8002/admin/
Package: pref
pref - a simple local preferences storePersistent storage ofattrsattributes or an ordered set (like a list, but no duplicates) to
a local SQLite database file.Examplefrom attr import attrib, attrs
from ismain import is_main

from pref import Pref, PrefOrderedSet

application_name = "myapp"
author = "me"


@attrs
class MyPref(Pref):
    first_name: str = attrib(default=None)
    last_name: str = attrib(default=None)
    has_subscription: bool = attrib(default=False)  # start off with no subscription


def get_pref() -> MyPref:
    return MyPref(application_name, author)


def get_ordered_set() -> PrefOrderedSet:
    return PrefOrderedSet(application_name, author, "mylist")


if is_main():

    # set a variable
    preferences = get_pref()
    preferences.first_name = "James"
    preferences.last_name = "Abel"

    # read it back
    preferences = get_pref()
    print(preferences.first_name)  # James
    print(preferences.last_name)  # Abel
    print(preferences.has_subscription)  # evaluates as False (is actually int of 0)

    # set an ordered set (list-like, but no duplicates)
    my_list = get_ordered_set()
    my_list.set(["a", "b", "c"])

    # read the ordered set back in
    my_list = get_ordered_set()
    print(my_list.get())  # ['a', 'b', 'c']
Package: prefab
PreFabPreFableveragesdeep learningto model fabrication-induced structural variations in integrated photonic devices. Through thisvirtual nanofabrication environment, we uncover valuable insights into nanofabrication processes and enhance device design accuracy.PredictionPreFabaccurately predicts process-induced structural alterations such as corner rounding, washing away of small lines and islands, and filling of narrow holes in planar photonic devices. This enables designers to quickly prototype expected performance and rectify designs prior to nanofabrication.CorrectionPreFabautomates corrections to device designs, ensuring the fabricated outcome aligns with the original design. This results in reduced structural variation and performance disparity from simulation to experiment.ModelsPreFabaccommodates uniquepredictorandcorrectormodels for each photonic foundry, regularly updated based on recent fabrication data. Current models include (see full list ondocs/models.md):FoundryProcessLatest VersionLatest DatasetModel NameModel TagStatusANTNanoSOIv6 (Nov 24 2023)d8 (Feb 6 2023)ANT_NanoSOIv6-d8BetaANTSiN (Upper Edge)v5 (Jun 3 2023)d0 (Jun 1 2023)ANT_SiNv5-d0-upperAlphaANTSiN (Lower Edge)v5 (Jun 3 2023)d0 (Jun 1 2023)ANT_SiNv5-d0-lowerAlphaSiEPICfabSOIv5 (Jun 3 2023)d0 (Jun 14 2023)SiEPICfab_SOIv5-d0AlphaNew models and foundries are to be added. Usage may change. For additional foundry and process models, feel free to contact us or raise an issue.InstallationLocalInstallPreFabvia pip:pipinstallprefabOr clone the repository and install in development mode:gitclonehttps://github.com/PreFab-Photonics/PreFab.gitcdPreFab
pipinstall-e.OnlineUsePreFabonline through GitHub Codespaces:Getting StartedAccount setupBefore you can make PreFab requests, you will need tocreate an account.To link your account, you will need a token. You can do this by running the following command in your terminal. This will open a browser window where you can log in and authenticate your token.python3-mprefabsetupGuidesVisit/examplesor ourGuidesto get started with your first predictions.Performance and UsagePreFabmodels are served via a serverless cloud platform. Please note:🐢 CPU inference may result in slower performance. Future updates will introduce GPU inference.🥶 The first prediction may take longer due to cold start server loading. Subsequent predictions will be faster.😊 Be considerate of usage. Start small and limit usage during the initial stages. Thank you!LicenseThis project is licensed under the LGPL-2.1 license. © 2024 PreFab Photonics.
Package: prefab-cloud-django
prefab-cloud-djangoThis project provides custom template tags for usingprefab-cloud-pythonin Django applicationsUsageAdd this project to your Django application's dependenciesAddprefab_cloud_djangoto the list ofINSTALLED_APPSin your app'ssettings.pyConfigure your Prefab client insettings.pyoptions=prefab.Options(api_key="...",...log_boundary=BASE_DIR,)PREFAB=prefab.Client(options)LOGGER=PREFAB.loggerIn your templates, add{% load prefab_tags %}Use these tags{%prefab_get"name-of-config"%}{%prefab_enabled"name-of-flag"%}# with default{%prefab_get"name-of-config"default="default"%}# with context{%prefab_get"name-of-config"context=context%}
Package: prefab-cloud-python
prefab-cloud-pythonPython client for prefab.cloud, providing Config, FeatureFlags as a ServiceNote: This library is under active developmentSign up to be notified about updatesExample usagefromprefab_cloud_pythonimportClient,Optionsimportprefab_cloud_pythonoptions=Options(prefab_api_key="your-prefab-api-key")context={"user":{"team_id":432,"id":123,"subscription_level":'pro',"email":"alice@example.com"}}prefab_cloud_python.set_options(options)result=prefab_cloud_python.get_client().enabled("my-first-feature-flag",context=context)print("my-first-feature-flag is:",result)See full documentationhttps://docs.prefab.cloud/docs/sdks/pythonDevelopmentEnsure thatpoetryis installed:https://python-poetry.org/docs/#installationFrom the root of this directory, runpoetry installto ensure dependencies are installedpoetry run pythonto open a Python REPL with access to the project dependenciesRunning testsTo run all tests, including integration testspoetryrunpytesttestsTo run only local tests and skip integration testspoetryrunpytesttests-k"not integration"To run only one specific test filepoetryrunpytesttests/name_of_test_file.pyExamplesThere are examples inexamplesReleasingRun pre-commit hooks to check and fix formatting, other rule enforcement.poetry run pre-commit run --show-diff-on-failure --color=always --all-filesOn a branchUpdate the version inpyproject.tomlUpdateCHANGELOG.mdMerge the branchgit tag <version> && git push --tagspoetry release --buildTo do this you will need anpypi.orgaccount, and to be added to this project (ask Michael for an invitation)
Package: preface
prefaceis a set of basic utility functions that I’d like to be global in Python, and some utility types.
Stuff like getting any element from a set, flattening a list, etc.These functions should be appropriately named but also not conflict with other names in the global space.The name is a joke based on Haskell’s prelude.There is also a SumType that’s useful for defining Python enums is an easier manner.
Package: prefai
PrefAI Python LibraryThe PrefAI Python Library enables applications coded in Python to interface with the PrefAI API.InstallationInstall with:pipinstallprefaiUsageThe library needs an API key, which you get on yourpref.ai developer account.exportPREFAI_API_KEY=<YOUR_SECRET_KEY>We can now add a user record like this:importosfromprefaiimportprefai_clientprefai_client.api_key=os.getenv("PREFAI_API_KEY")test_user_email=os.getenv("PREFAI_TEST_USER_EMAIL")# Add recordprefai_client.add_record(user_email="test@pref.ai",user_action="What's a spicy appetizer you'd recommend for a BBQ with 6 people?",)For more information and next steps, read thequickstart.