A utility for functional piping in Python that allows you to access any function in any scope as a partial.

Overview

WithPartial

Introduction

WithPartial is a simple utility for functional piping in Python. The package exposes a context manager (used with with) called PipeContext, that allows you to access any function in any scope as a partial, meaning that it's naturally pipeable. Here's a contrived example from the test suite:

import numpy as np
from with_partial import PartialContext
from pipetools import pipe

with PartialContext() as _:
    ret = (
            10 > pipe |
            _.np.ones() |
            _.np.reshape(newshape=(5, 2)) |
            _.np.mean() |
            _.int()
    )
    assert ret == 1

As you can see, we were able to call both numpy and built-in functions on the _ object, and it executed the pipeline similarly to say R's magrittr package.

Installation

pip install with_partial

Usage

Actually WithPartial doesn't provide an actual piping mechanism, but it does add a useful syntax for use with pipes. For the actual piping mechanism, I suggest that you try pipetools, which this package is actually tested against.

WithPartial provides a single class: PipeContext. The way you use PipeContext is by first using it as a context manager:

with PipeContext() as _:

Then, using the return value of the context manager, which we have named _ (but you could call it anything), you access attributes and items (using .attr or ["key"] or [0]) to locate the function you want and then you finally call it (), which will create the partial. You can use positional and keyword arguments at this point if you need

For more usage information, refer to the test suite.

Tests

Note: you will need poetry installed.

git clone https://github.com/multimeric/WithPartial.git
cd WithPartial
poetry install --extras pipetools
poetry run pytest test/
Owner
Michael Milton
Michael Milton
An ETL Pipeline of a large data set from a fictitious music streaming service named Sparkify.

An ETL Pipeline of a large data set from a fictitious music streaming service named Sparkify. The ETL process flows from AWS's S3 into staging tables in AWS Redshift.

1 Feb 11, 2022
My solution to the book A Collection of Data Science Take-Home Challenges

DS-Take-Home Solution to the book "A Collection of Data Science Take-Home Challenges". Note: Please don't contact me for the dataset. This repository

Jifu Zhao 1.5k Jan 03, 2023
Demonstrate a Dataflow pipeline that saves data from an API into BigQuery table

Overview dataflow-mvp provides a basic example pipeline that pulls data from an API and writes it to a BigQuery table using GCP's Dataflow (i.e., Apac

Chris Carbonell 1 Dec 03, 2021
Data Competition: automated systems that can detect whether people are not wearing masks or are wearing masks incorrectly

Table of contents Introduction Dataset Model & Metrics How to Run Quickstart Install Training Evaluation Detection DATA COMPETITION The COVID-19 pande

Thanh Dat Vu 1 Feb 27, 2022
A real-time financial data streaming pipeline and visualization platform using Apache Kafka, Cassandra, and Bokeh.

Realtime Financial Market Data Visualization and Analysis Introduction This repo shows my project about real-time stock data pipeline. All the code is

6 Sep 07, 2022
Demonstrate the breadth and depth of your data science skills by earning all of the Databricks Data Scientist credentials

Data Scientist Learning Plan Demonstrate the breadth and depth of your data science skills by earning all of the Databricks Data Scientist credentials

Trung-Duy Nguyen 27 Nov 01, 2022
Data Analytics on Genomes and Genetics

Data Analytics performed on On genomes and Genetics dataset to predict genetic disorder and disorder subclass. DONE by TEAM SIGMA!

1 Jan 12, 2022
In this project, ETL pipeline is build on data warehouse hosted on AWS Redshift.

ETL Pipeline for AWS Project Description In this project, ETL pipeline is build on data warehouse hosted on AWS Redshift. The data is loaded from S3 t

Mobeen Ahmed 1 Nov 01, 2021
PLStream: A Framework for Fast Polarity Labelling of Massive Data Streams

PLStream: A Framework for Fast Polarity Labelling of Massive Data Streams Motivation When dataset freshness is critical, the annotating of high speed

4 Aug 02, 2022
Two phase pipeline + StreamlitTwo phase pipeline + Streamlit

Two phase pipeline + Streamlit This is an example project that demonstrates how to create a pipeline that consists of two phases of execution. In betw

Rick Lamers 1 Nov 17, 2021
Creating a statistical model to predict 10 year treasury yields

Predicting 10-Year Treasury Yields Intitially, I wanted to see if the volatility in the stock market, represented by the VIX index (data source), had

10 Oct 27, 2021
NumPy and Pandas interface to Big Data

Blaze translates a subset of modified NumPy and Pandas-like syntax to databases and other computing systems. Blaze allows Python users a familiar inte

Blaze 3.1k Jan 05, 2023
This is an example of how to automate Ridit Analysis for a dataset with large amount of questions and many item attributes

This is an example of how to automate Ridit Analysis for a dataset with large amount of questions and many item attributes

Ishan Hegde 1 Nov 17, 2021
Numerical Analysis toolkit centred around PDEs, for demonstration and understanding purposes not production

Numerics Numerical Analysis toolkit centred around PDEs, for demonstration and understanding purposes not production Use procedure: Initialise a new i

George Whittle 1 Nov 13, 2021
Spectacular AI SDK fuses data from cameras and IMU sensors and outputs an accurate 6-degree-of-freedom pose of a device.

Spectacular AI SDK examples Spectacular AI SDK fuses data from cameras and IMU sensors (accelerometer and gyroscope) and outputs an accurate 6-degree-

Spectacular AI 94 Jan 04, 2023
Tools for analyzing data collected with a custom unity-based VR for insects.

unityvr Tools for analyzing data collected with a custom unity-based VR for insects. Organization: The unityvr package contains the following submodul

Hannah Haberkern 1 Dec 14, 2022
A Python Tools to imaging the shallow seismic structure

ShallowSeismicImaging Tools to imaging the shallow seismic structure, above 10 km, based on the ZH ratio measured from the ambient seismic noise, and

Xiao Xiao 9 Aug 09, 2022
Pipeline to convert a haploid assembly into diploid

HapDup (haplotype duplicator) is a pipeline to convert a haploid long read assembly into a dual diploid assembly. The reconstructed haplotypes

Mikhail Kolmogorov 50 Jan 05, 2023
Stitch together Nanopore tiled amplicon data without polishing a reference

Stitch together Nanopore tiled amplicon data using a reference guided approach Tiled amplicon data, like those produced from primers designed with pri

Amanda Warr 14 Aug 30, 2022
Flenser is a simple, minimal, automated exploratory data analysis tool.

Flenser Have you ever been handed a dataset you've never seen before? Flenser is a simple, minimal, automated exploratory data analysis tool. It runs

John McCambridge 79 Sep 20, 2022