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Adding 1.0.0 warning
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README.md

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![AWS Data Wrangler](docs/source/_static/logo.png?raw=true "AWS Data Wrangler")
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> DataFrames on AWS
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> Pandas on AWS
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## IMPORTANT NOTE: Version 1.0.0 coming soon with several breaking changes.
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Please, pin the version you are using on your environment.
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AWS Data Wrangler is completing 1 year, and the team is working to collect feedbacks and features requests to put in our 1.0.0 version. By now we have 3 major changes listed:
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- API redesign
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- Nested data types support
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- Deprecation of PySpark support
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- PySpark support takes considerable part of the development time and it has not been reflected in user adoption. Only 2 of our 66 issues on GitHub are related to Spark.
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- In addition, the integration between PySpark and PyArrow/Pandas remains in experimental stage and we have been experiencing tough times to keep it stable.
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---
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[![Release](https://img.shields.io/badge/release-0.3.2-brightgreen.svg)](https://pypi.org/project/awswrangler/)
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[![Python Version](https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8-brightgreen.svg)](https://anaconda.org/conda-forge/awswrangler)

awswrangler/__version__.py

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"""Metadata Module."""
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__title__ = "awswrangler"
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__description__ = "DataFrames on AWS."
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__description__ = "Pandas on AWS."
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__version__ = "0.3.2"
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__license__ = "Apache License 2.0"

docs/source/examples.rst

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.. warning:: Version 1.0.0 coming soon with several breaking changes. Please, pin the version you are using on your environment.
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AWS Data Wrangler is completing 1 year, and the team is working to collect feedbacks and features requests to put in our 1.0.0 version. By now we have 3 major changes listed:
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- API redesign
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- Nested data types support
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- Deprecation of PySpark support
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- PySpark support takes considerable part of the development time and it has not been reflected in user adoption. Only 2 of our 66 issues on GitHub are related to Spark.
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- In addition, the integration between PySpark and PyArrow/Pandas remains in experimental stage and we have been experiencing tough times to keep it stable.
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Examples
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========
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docs/source/index.rst

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:width: 38%
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:alt: AWS Data Wrangler
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*DataFrames on AWS*
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*Pandas on AWS*
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---------------------
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.. warning:: Version 1.0.0 coming soon with several breaking changes. Please, pin the version you are using on your environment.
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AWS Data Wrangler is completing 1 year, and the team is working to collect feedbacks and features requests to put in our 1.0.0 version. By now we have 3 major changes listed:
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- API redesign
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- Nested data types support
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- Deprecation of PySpark support
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- PySpark support takes considerable part of the development time and it has not been reflected in user adoption. Only 2 of our 66 issues on GitHub are related to Spark.
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- In addition, the integration between PySpark and PyArrow/Pandas remains in experimental stage and we have been experiencing tough times to keep it stable.
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.. toctree::
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:maxdepth: 4
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docs/source/install.rst

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.. warning:: Version 1.0.0 coming soon with several breaking changes. Please, pin the version you are using on your environment.
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AWS Data Wrangler is completing 1 year, and the team is working to collect feedbacks and features requests to put in our 1.0.0 version. By now we have 3 major changes listed:
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- API redesign
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- Nested data types support
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- Deprecation of PySpark support
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- PySpark support takes considerable part of the development time and it has not been reflected in user adoption. Only 2 of our 66 issues on GitHub are related to Spark.
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- In addition, the integration between PySpark and PyArrow/Pandas remains in experimental stage and we have been experiencing tough times to keep it stable.
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Install
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============
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docs/source/tutorials.rst

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.. warning:: Version 1.0.0 coming soon with several breaking changes. Please, pin the version you are using on your environment.
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AWS Data Wrangler is completing 1 year, and the team is working to collect feedbacks and features requests to put in our 1.0.0 version. By now we have 3 major changes listed:
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- API redesign
6+
- Nested data types support
7+
- Deprecation of PySpark support
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- PySpark support takes considerable part of the development time and it has not been reflected in user adoption. Only 2 of our 66 issues on GitHub are related to Spark.
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- In addition, the integration between PySpark and PyArrow/Pandas remains in experimental stage and we have been experiencing tough times to keep it stable.
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Read the Tutorials
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==================
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