Klayers
AWS Data Wrangler
Klayers | AWS Data Wrangler | |
---|---|---|
4 | 9 | |
1,969 | 3,804 | |
- | 0.7% | |
8.0 | 9.4 | |
5 days ago | 3 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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.
Klayers
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Lambda with Python libraries
Use public layers maintained by others. For example Klayers which are produced with CI in GitHub Actions. This way you don't have any layers lying around in your Lambda UI. You can point to new layer versions whenever you wish. You can interact with the layer data via an API : https://github.com/keithrozario/Klayers/#api
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AWS Serverless Menu - Small to Big
If I want to do something more data heavy or complex, I'll sometimes instead go for Python. Having a mixture of languages is one of the big advantages of micro services. Packaging dependencies is a bit tricker for Python, for simple packages I'll usually include in my build script something to copy the relevant directories from my venv's site-packages. However one neat alternative is to use a publicly available precompiled lambda layer from Klayers. These slot neatly in one line of code into my terraform config and enable me to use popular Python packages like numpy and pandas without troubling myself about C extensions, build environment or having to mess with Amazon Linux.
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Serverless ETL using AWS Lambda, Pandas, PostgreSQL, AWS CDK
Before anything, Huge shoutout to Keith Rozario for providing us with this awesome Repo. where he defined layers for lambda functions to add libraries that doesn't exist by default in the lambda runtime without you having to create them yourself. I used his repo to add the requests, pandas and psycopg2 libraries to the project.
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Can a lambda use a layer which is stored in S3
I like to use this guy’s layers as an arn: https://github.com/keithrozario/Klayers
AWS Data Wrangler
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Read files from s3 using Pandas/s3fs or AWS Data Wrangler?
I had no problem with awswrangler (https://github.com/aws/aws-sdk-pandas) and it supports reading and writing partitions which was really helpful and a few other optimizations that made it a great tool
- I agree that Arrow Tables are great, but we decided to keep the library focused on the Pandas interface. [wont implement]
- Automate some wrangling and data visualization in Python
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Redshift API vs. other ways to connect?
awslabs has developed their own package for this and given it's for their product, seem likely to maintain it. https://github.com/awslabs/aws-data-wrangler
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Parquet files
AWS data wrangler works well. it's a wrapper on pandas: https://github.com/awslabs/aws-data-wrangler
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Reading s3 file data with Python lambda function
you'll find pre-made zips here: https://github.com/awslabs/aws-data-wrangler/releases
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A guide to load (almost) anything into a DataFrame
Don't forget about https://aws-data-wrangler.readthedocs.io/
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Go+: Go designed for data science
Yep, agreed. Go is a great language for AWS Lambda type workflows.
Python isn't as great (Python Lambda Layers built on Macs don't always work). AWS Data Wrangler (https://github.com/awslabs/aws-data-wrangler) provides pre-built layers, which is a work around, but something that's as portable as Go would be the best solution.
- Best way to install pandas and bumpy to AWS Lanbda
What are some alternatives?
mangum - AWS Lambda support for ASGI applications
PyAthena - PyAthena is a Python DB API 2.0 (PEP 249) client for Amazon Athena.
configure-aws-credentials - Configure AWS credential environment variables for use in other GitHub Actions.
Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
python-lambdarest - Flask like web framework for AWS Lambda
ga-extractor - Tool for extracting Google Analytics data suitable for migrating to other platforms/databases
covid-19-data - A repository of data on coronavirus cases and deaths in the U.S.
python-mysql-replication - Pure Python Implementation of MySQL replication protocol build on top of PyMYSQL
Zappa - Serverless Python
gonum - Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more
serverless-etl-cdk - Deploy python code for ETL using the AWS CDK
zef - Toolkit for graph-relational data across space and time