semvec/pypi-packages huggingface dataset:
geci-mimesis 0.5.0
A template Python module
Requires Python: >=3.9

<a href="https://www.islas.org.mx/"><img src="https://www.islas.org.mx/img/logo.svg" align="right" width="256" /></a>
# GECI Mimesis
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qolvoters 1.0
This library execute voter participation rate analysis for the Quality of Life Exporer variables
Keywords: urban institute, python, Mecklenburg County, quality of life explorer, voters, NPA


# Voter Participation Analysis for QOL

This package provides a Python class `voters` for analyzing voter participation rate for Urban Institute's Quality of Life (QOL) variables. It includes methods for spatial joining, summarizing voter data by NPA (Neighborhood Planning Area), and exporting the results to a CSV file.

# Installation

Install `voters` from PyPI using pip:


pip install qolvoters


# Usage
import pandas as pd 
import arcpy
import qolvoters as vt

# Example usage:
voter_analysis = vt.voters('GeocodedVoterPointAddresses', 'NPA_FeatureClass', 'SummaryTable')

# Summarize voter data by NPA
voter_analysis.summary('ActiveVoters', 'Join_Count')

# Export summarized results to a CSV file
voter_analysis.export('OutputDirectory', 'VoterParticipationSummary.csv')

# Methods 

`__init__(self, voterparticipation, NPA, SummaryTableName)`

Initialize the voters class with the following parameters:

* voterparticipation: Geocoded voter participation feature class.

* NPA: NPA feature class.

* SummaryTableName: Name of the summary table for voters in each NPA.

Assign NPA IDs to each voter by performing a spatial join between the voter participation feature class and the NPA feature class.

`summary(self, *FieldsToBeSummarized)`

Compute the summary of all voters within each NPA. Takes parameters for the fields to be summarized (e.g., active voters field and the 'Join_Count' field).

`export(self, OutputDirectory, FinalCSVName)`

Export the results of the voter participation analysis to a CSV file. Renames columns and computes additional fields before exporting the final CSV file.

# License

This project is licensed under the MIT License - see the LICENSE file for details.
cadquery-ocp-arm-test 7.7.2.1
OCP wheel with shared library dependencies bundled.

# ocp-build-system

This repository is used to build wheels for OCP, which is CadQuery's bindings to the OpenCASCADE CAD kernel. There are two GitHub Actions available as part of this repo.

* Build (Create Python wheel using Conda)
* Releases

The Build workflow is triggered manually by a developer, and sets up conda environments for each of the wheels to be built, builds the wheels, and then uploads them as artifacts to the GitHub Action. The Releases workflow is run when a tag is created, and takes the wheels attached to the latest build and uploads them to PyPi. Each time a new version of OCP is released these Actions, along with the setup.py file, need to be modified to build and release the new version.

# Building for Apple Silicon locally

Since there are no free Apple Silicon runners available for GitHub actions, a simple solution is to just run the build locally on an Apple Silicon Macbook. To that end, this repo contains a `local-build.sh` script which builds for whatever architecture the local machine is running on. On an M1 Macbook Pro it should take approx 25 minutes to build for all 4 Python versions.
casadi-fork 3.6.5
CasADi -- framework for algorithmic differentiation and numeric optimization

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Learn all about CasADi at the [homepage](http://casadi.org) or jump to [install instructions](http://install.casadi.org)...