Removing build-egg.sh

aws · Jan 9, 2021 · 13e71a0 · 13e71a0
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diff --git a/building/build-egg.sh b/building/build-egg.sh
diff --git a/docs/source/install.rst b/docs/source/install.rst
@@ -61,7 +61,7 @@ Go to your Glue PySpark job and create a new *Job parameters* key/value:
 
 To install a specific version, set the value for above Job parameter as follows:
 
-* Value: ``awswrangler==1.10.0``
+* Value: ``awswrangler==2.3.0``
 
 `Official Glue PySpark Reference <https://docs.aws.amazon.com/glue/latest/dg/reduced-start-times-spark-etl-jobs.html#reduced-start-times-new-features>`_
 

diff --git a/docs/source/what.rst b/docs/source/what.rst
@@ -3,7 +3,8 @@ What is AWS Data Wrangler?
 
 An `AWS Professional Service <https://aws.amazon.com/professional-services>`_ `open source <https://github.com/awslabs/aws-data-wrangler>`_ python initiative that extends the power of `Pandas <https://github.com/pandas-dev/pandas>`_ library to AWS connecting **DataFrames** and AWS data related services.
 
-Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
+Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR,
+SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
 
 Built on top of other open-source projects like `Pandas <https://github.com/pandas-dev/pandas>`_, `Apache Arrow <https://github.com/apache/arrow>`_ and `Boto3 <https://github.com/boto/boto3>`_, it offers abstracted functions to execute usual ETL tasks like load/unload data from **Data Lakes**, **Data Warehouses** and **Databases**.