swifter vs distributed-compute-on-aws-with-cross-regional-dask

swifter

A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner (by jmcarpenter2)

Source Code

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distributed-compute-on-aws-with-cross-regional-dask

Perform I/O intensive workloads on high-volume data sparsely located across multiple AWS regions through the use of Dask. (by aws-solutions-library-samples)

Dask dask-distributed dask-worker-pools

Source Code

aws.amazon.com

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swifter		distributed-compute-on-aws-with-cross-regional-dask
	Project
3	Mentions	2
2,464	Stars	14
-	Growth	-
5.5	Activity	3.1
about 1 month ago	Latest Commit	6 months ago
Python	Language	TypeScript
MIT License	License	MIT No Attribution

The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

swifter

Posts with mentions or reviews of swifter. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-12.

Tidyverse equivalent in Python?
4 projects | /r/datascience | 12 Sep 2021

With concat, merge, melt, and pivot_table, that may cover everything I have ever needed. There may be more efficient ways at times, but swifter promises to do that for you, maybe it is true.
[D] A hacky work-around for slow linear algebra operations on pyspark.
1 project | /r/MachineLearning | 2 Jul 2021

Since you already have a working python script, you can try swifter with minimal effort to see if it brings about a significant speedup before digging further.
What Is The Best Performance Fix You Ever
1 project | /r/datascience | 31 Dec 2020

With few lines of code? Swifter for quicker pandas apply and then there's numba. With concurrent.futures, it'll be a bit more lines of code.

distributed-compute-on-aws-with-cross-regional-dask

Posts with mentions or reviews of distributed-compute-on-aws-with-cross-regional-dask. We have used some of these posts to build our list of alternatives and similar projects.

Cross Regional Dask on AWS
1 project | /r/datascience | 17 Dec 2022

1 project | /r/Python | 17 Dec 2022

Check it out. Would you use this? https://github.com/aws-samples/distributed-compute-on-aws-with-cross-regional-dask

What are some alternatives?

When comparing swifter and distributed-compute-on-aws-with-cross-regional-dask you can also consider the following projects:

modin - Modin: Scale your Pandas workflows by changing a single line of code

ibis - the portable Python dataframe library

Dask - Parallel computing with task scheduling

xarray - N-D labeled arrays and datasets in Python

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

cudf - cuDF - GPU DataFrame Library

pandera - A light-weight, flexible, and expressive statistical data testing library

siuba - Python library for using dplyr like syntax with pandas and SQL

stumpy - STUMPY is a powerful and scalable Python library for modern time series analysis

mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.