AWS Data Wrangler 2.0.0

Breaking changes

• sqlalchemy and psycopg2 dependencies replaced by redshift_connector and pg8000
• All wr.db.* functions was distributed into wr.redshift.*, wr.postgresql.* and wr.mysql.* (Tutorial)
• Redshift COPY and UNLOAD function was refactored into wr.redshift.* (Tutorial)
• wr.catalog.get_engine() was replaced by wr.redshift.connect(), wr.postgresql.connect(), wr.mysql.connect() (Tutorial)

New Functionalities

• Amazon Timestream support (Tutorial)

Enhancements

• General performance improved for s3 I/O removing eventual consistency guardrails (Reference)
• Add retry with decorrelated jitter for Athena and Glue Catalog calls to overcome throttling in high concurrency scenarios.

Docs

• Updates regarding all new functionalities
• Add Amazon Timestream tutorial
• Add Amazon Timestream tutorial 2

AWS re:Invent related news

• AWS Lambda now supports up to 10 GB of memory and 6 vCPU cores
• Amazon S3 now delivers strong read-after-write consistency
• AWS Lambda now supports container images as a packaging format
• Serverless Batch Scheduling with AWS Batch and AWS Fargate

Thanks

We thank the following contributors/users for their work on this release:

@Brooke-white, @danielwo, @sapientderek, @pmleveque, @igorborgest.

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P.S. Lambda Layer zip file and Glue wheel/egg files are available below. Just upload it and run!