%global _empty_manifest_terminate_build 0 Name: python-awswrangler Version: 2.20.1 Release: 1 Summary: Pandas on AWS. License: Apache-2.0 URL: https://aws-sdk-pandas.readthedocs.io/ Source0: https://mirrors.nju.edu.cn/pypi/web/packages/8b/72/f76290dffdf1a991277702d584dbfd913c1ddb0c4787b1d9e76890da8125/awswrangler-2.20.1.tar.gz BuildArch: noarch Requires: python3-boto3 Requires: python3-botocore Requires: python3-pandas Requires: python3-numpy Requires: python3-numpy Requires: python3-pyarrow Requires: python3-redshift-connector Requires: python3-pymysql Requires: python3-pg8000 Requires: python3-openpyxl Requires: python3-requests-aws4auth Requires: python3-jsonpath-ng Requires: python3-progressbar2 Requires: python3-opensearch-py Requires: python3-gremlinpython Requires: python3-backoff Requires: python3-SPARQLWrapper Requires: python3-pyodbc Requires: python3-oracledb Requires: python3-deltalake %description # AWS SDK for pandas (awswrangler) AWS Data Wrangler is now **AWS SDK for pandas (awswrangler)**. We’re changing the name we use when we talk about the library, but everything else will stay the same. You’ll still be able to install using `pip install awswrangler` and you won’t need to change any of your code. As part of this change, we’ve moved the library from AWS Labs to the main AWS GitHub organisation but, thanks to the GitHub’s redirect feature, you’ll still be able to access the project by its old URLs until you update your bookmarks. Our documentation has also moved to [aws-sdk-pandas.readthedocs.io](https://aws-sdk-pandas.readthedocs.io), but old bookmarks will redirect to the new site. *Pandas on AWS* Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL). ![AWS SDK for pandas](docs/source/_static/logo2.png?raw=true "AWS SDK for pandas") ![tracker](https://d3tiqpr4kkkomd.cloudfront.net/img/pixel.png?asset=GVOYN2BOOQ573LTVIHEW) > An [AWS Professional Service](https://aws.amazon.com/professional-services/) open source initiative | aws-proserve-opensource@amazon.com [![Release](https://img.shields.io/badge/release-2.20.1-brightgreen.svg)](https://pypi.org/project/awswrangler/) [![Python Version](https://img.shields.io/badge/python-3.7%20%7C%203.8%20%7C%203.9%20%7C%203.10-brightgreen.svg)](https://anaconda.org/conda-forge/awswrangler) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) [![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/) [![Coverage](https://img.shields.io/badge/coverage-91%25-brightgreen.svg)](https://pypi.org/project/awswrangler/) ![Static Checking](https://github.com/aws/aws-sdk-pandas/workflows/Static%20Checking/badge.svg?branch=main) [![Documentation Status](https://readthedocs.org/projects/aws-sdk-pandas/badge/?version=latest)](https://aws-sdk-pandas.readthedocs.io/?badge=latest) | Source | Downloads | Installation Command | |--------|-----------|----------------------| | **[PyPi](https://pypi.org/project/awswrangler/)** | [![PyPI Downloads](https://pepy.tech/badge/awswrangler)](https://pypi.org/project/awswrangler/) | `pip install awswrangler` | | **[Conda](https://anaconda.org/conda-forge/awswrangler)** | [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/awswrangler.svg)](https://anaconda.org/conda-forge/awswrangler) | `conda install -c conda-forge awswrangler` | > ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#emr-cluster), [Glue PySpark Job](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️ `pip install pyarrow==2 awswrangler` Powered By [](https://arrow.apache.org/powered_by/) ## Table of contents - [Quick Start](#quick-start) - [Read The Docs](#read-the-docs) - [Getting Help](#getting-help) - [Community Resources](#community-resources) - [Logging](#logging) - [Who uses AWS SDK for pandas?](#who-uses-aws-sdk-pandas) ## Quick Start Installation command: `pip install awswrangler` > ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#emr-cluster), [Glue PySpark Job](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️`pip install pyarrow==2 awswrangler` ```py3 import awswrangler as wr import pandas as pd from datetime import datetime df = pd.DataFrame({"id": [1, 2], "value": ["foo", "boo"]}) # Storing data on Data Lake wr.s3.to_parquet( df=df, path="s3://bucket/dataset/", dataset=True, database="my_db", table="my_table" ) # Retrieving the data directly from Amazon S3 df = wr.s3.read_parquet("s3://bucket/dataset/", dataset=True) # Retrieving the data from Amazon Athena df = wr.athena.read_sql_query("SELECT * FROM my_table", database="my_db") # Get a Redshift connection from Glue Catalog and retrieving data from Redshift Spectrum con = wr.redshift.connect("my-glue-connection") df = wr.redshift.read_sql_query("SELECT * FROM external_schema.my_table", con=con) con.close() # Amazon Timestream Write df = pd.DataFrame({ "time": [datetime.now(), datetime.now()], "my_dimension": ["foo", "boo"], "measure": [1.0, 1.1], }) rejected_records = wr.timestream.write(df, database="sampleDB", table="sampleTable", time_col="time", measure_col="measure", dimensions_cols=["my_dimension"], ) # Amazon Timestream Query wr.timestream.query(""" SELECT time, measure_value::double, my_dimension FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 """) ``` ## [Read The Docs](https://aws-sdk-pandas.readthedocs.io/) - [**What is AWS SDK for pandas?**](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/about.html) - [**Install**](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html) - [PyPi (pip)](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#pypi-pip) - [Conda](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#conda) - [AWS Lambda Layer](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-lambda-layer) - [AWS Glue Python Shell Jobs](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-python-shell-jobs) - [AWS Glue PySpark Jobs](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-pyspark-jobs) - [Amazon SageMaker Notebook](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#amazon-sagemaker-notebook) - [Amazon SageMaker Notebook Lifecycle](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#amazon-sagemaker-notebook-lifecycle) - [EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#emr) - [From source](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#from-source) - [**Tutorials**](https://github.com/aws/aws-sdk-pandas/tree/main/tutorials) - [001 - Introduction](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/001%20-%20Introduction.ipynb) - [002 - Sessions](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/002%20-%20Sessions.ipynb) - [003 - Amazon S3](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/003%20-%20Amazon%20S3.ipynb) - [004 - Parquet Datasets](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/004%20-%20Parquet%20Datasets.ipynb) - [005 - Glue Catalog](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/005%20-%20Glue%20Catalog.ipynb) - [006 - Amazon Athena](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/006%20-%20Amazon%20Athena.ipynb) - [007 - Databases (Redshift, MySQL, PostgreSQL, SQL Server and Oracle)](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/007%20-%20Redshift%2C%20MySQL%2C%20PostgreSQL%2C%20SQL%20Server%2C%20Oracle.ipynb) - [008 - Redshift - Copy & Unload.ipynb](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/008%20-%20Redshift%20-%20Copy%20%26%20Unload.ipynb) - [009 - Redshift - Append, Overwrite and Upsert](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/009%20-%20Redshift%20-%20Append%2C%20Overwrite%2C%20Upsert.ipynb) - [010 - Parquet Crawler](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/010%20-%20Parquet%20Crawler.ipynb) - [011 - CSV Datasets](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/011%20-%20CSV%20Datasets.ipynb) - [012 - CSV Crawler](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/012%20-%20CSV%20Crawler.ipynb) - [013 - Merging Datasets on S3](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/013%20-%20Merging%20Datasets%20on%20S3.ipynb) - [014 - Schema Evolution](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/014%20-%20Schema%20Evolution.ipynb) - [015 - EMR](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/015%20-%20EMR.ipynb) - [016 - EMR & Docker](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/016%20-%20EMR%20%26%20Docker.ipynb) - [017 - Partition Projection](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/017%20-%20Partition%20Projection.ipynb) - [018 - QuickSight](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/018%20-%20QuickSight.ipynb) - [019 - Athena Cache](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/019%20-%20Athena%20Cache.ipynb) - [020 - Spark Table Interoperability](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/020%20-%20Spark%20Table%20Interoperability.ipynb) - [021 - Global Configurations](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/021%20-%20Global%20Configurations.ipynb) - [022 - Writing Partitions Concurrently](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/022%20-%20Writing%20Partitions%20Concurrently.ipynb) - [023 - Flexible Partitions Filter](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/023%20-%20Flexible%20Partitions%20Filter.ipynb) - [024 - Athena Query Metadata](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/024%20-%20Athena%20Query%20Metadata.ipynb) - [025 - Redshift - Loading Parquet files with Spectrum](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/025%20-%20Redshift%20-%20Loading%20Parquet%20files%20with%20Spectrum.ipynb) - [026 - Amazon Timestream](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/026%20-%20Amazon%20Timestream.ipynb) - [027 - Amazon Timestream 2](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/027%20-%20Amazon%20Timestream%202.ipynb) - [028 - Amazon DynamoDB](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/028%20-%20DynamoDB.ipynb) - [029 - S3 Select](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/029%20-%20S3%20Select.ipynb) - [030 - Data Api](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/030%20-%20Data%20Api.ipynb) - [031 - OpenSearch](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/031%20-%20OpenSearch.ipynb) - [032 - Lake Formation Governed Tables](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/032%20-%20Lake%20Formation%20Governed%20Tables.ipynb) - [033 - Amazon Neptune](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/033%20-%20Amazon%20Neptune.ipynb) - [034 - Glue Data Quality](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/034%20-Glue%20%20Data%20Quality.ipynb) - [**API Reference**](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html) - [Amazon S3](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-s3) - [AWS Glue Catalog](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-glue-catalog) - [Amazon Athena](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-athena) - [AWS Lake Formation](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-lake-formation) - [Amazon Redshift](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-redshift) - [PostgreSQL](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#postgresql) - [MySQL](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#mysql) - [SQL Server](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#sqlserver) - [Oracle](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#oracle) - [Data API Redshift](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#data-api-redshift) - [Data API RDS](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#data-api-rds) - [OpenSearch](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#opensearch) - [Amazon Neptune](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-neptune) - [DynamoDB](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#dynamodb) - [Amazon Timestream](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-timestream) - [Amazon EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-emr) - [Amazon CloudWatch Logs](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-cloudwatch-logs) - [Amazon Chime](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-chime) - [Amazon QuickSight](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-quicksight) - [AWS STS](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-sts) - [AWS Secrets Manager](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-secrets-manager) - [Global Configurations](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#global-configurations) - [**License**](https://github.com/aws/aws-sdk-pandas/blob/main/LICENSE.txt) - [**Contributing**](https://github.com/aws/aws-sdk-pandas/blob/main/CONTRIBUTING.md) ## Getting Help The best way to interact with our team is through GitHub. You can open an [issue](https://github.com/aws/aws-sdk-pandas/issues/new/choose) and choose from one of our templates for bug reports, feature requests... You may also find help on these community resources: * The #aws-sdk-pandas Slack [channel](https://join.slack.com/t/aws-sdk-pandas/shared_invite/zt-sxdx38sl-E0coRfAds8WdpxXD2Nzfrg) * Ask a question on [Stack Overflow](https://stackoverflow.com/questions/tagged/awswrangler) and tag it with `awswrangler` ## Community Resources Please [send a Pull Request](https://github.com/aws/aws-sdk-pandas/edit/main/README.md) with your resource reference and @githubhandle. - [Optimize Python ETL by extending Pandas with AWS SDK for pandas](https://aws.amazon.com/blogs/big-data/optimize-python-etl-by-extending-pandas-with-aws-data-wrangler/) [[@igorborgest](https://github.com/igorborgest)] - [Reading Parquet Files With AWS Lambda](https://aprakash.wordpress.com/2020/04/14/reading-parquet-files-with-aws-lambda/) [[@anand086](https://github.com/anand086)] - [Transform AWS CloudTrail data using AWS SDK for pandas](https://aprakash.wordpress.com/2020/09/17/transform-aws-cloudtrail-data-using-aws-data-wrangler/) [[@anand086](https://github.com/anand086)] - [Rename Glue Tables using AWS SDK for pandas](https://ananddatastories.com/rename-glue-tables-using-aws-sdk-pandas/) [[@anand086](https://github.com/anand086)] - [Getting started on AWS SDK for pandas and Athena](https://medium.com/@dheerajsharmainampudi/getting-started-on-aws-sdk-pandas-and-athena-7b446c834076) [[@dheerajsharma21](https://github.com/dheerajsharma21)] - [Simplifying Pandas integration with AWS data related services](https://medium.com/@bv_subhash/aws-sdk-pandas-simplifying-pandas-integration-with-aws-data-related-services-2b3325c12188) [[@bvsubhash](https://github.com/bvsubhash)] - [Build an ETL pipeline using AWS S3, Glue and Athena](https://www.linkedin.com/pulse/build-etl-pipeline-using-aws-s3-glue-athena-data-wrangler-tom-reid/) [[@taupirho](https://github.com/taupirho)] ## Logging Enabling internal logging examples: ```py3 import logging logging.basicConfig(level=logging.INFO, format="[%(name)s][%(funcName)s] %(message)s") logging.getLogger("awswrangler").setLevel(logging.DEBUG) logging.getLogger("botocore.credentials").setLevel(logging.CRITICAL) ``` Into AWS lambda: ```py3 import logging logging.getLogger("awswrangler").setLevel(logging.DEBUG) ``` ## Who uses AWS SDK for pandas? Knowing which companies are using this library is important to help prioritize the project internally. If you would like us to include your company’s name and/or logo in the README file to indicate that your company is using the AWS SDK for pandas, please raise a "Support Us" issue. If you would like us to display your company’s logo, please raise a linked pull request to provide an image file for the logo. Note that by raising a Support Us issue (and related pull request), you are granting AWS permission to use your company’s name (and logo) for the limited purpose described here and you are confirming that you have authority to grant such permission. - [Amazon](https://www.amazon.com/) - [AWS](https://aws.amazon.com/) - [Cepsa](https://cepsa.com) [[@alvaropc](https://github.com/alvaropc)] - [Cognitivo](https://www.cognitivo.ai/) [[@msantino](https://github.com/msantino)] - [Digio](https://www.digio.com.br/) [[@afonsomy](https://github.com/afonsomy)] - [DNX](https://www.dnx.solutions/) [[@DNXLabs](https://github.com/DNXLabs)] - [Fortescue Future Industries](https://ffi.com.au/) [[@spencervoorend](https://github.com/spencervoorend)] - [Funcional Health Tech](https://www.funcionalcorp.com.br/) [[@webysther](https://github.com/webysther)] - [Funding Circle](https://www.fundingcircle.com/) [[@pfig](https://github.com/pfig)] - [Infomach](https://www.infomach.com.br/) - [Informa Markets](https://www.informamarkets.com/en/home.html) [[@mateusmorato]](http://github.com/mateusmorato) - [LINE TV](https://www.linetv.tw/) [[@bryanyang0528](https://github.com/bryanyang0528)] - [Magnataur](https://magnataur.com) [[@brianmingus2](https://github.com/brianmingus2)] - [M4U](https://www.m4u.com.br/) [[@Thiago-Dantas](https://github.com/Thiago-Dantas)] - [NBCUniversal](https://www.nbcuniversal.com/) [[@vibe](https://github.com/vibe)] - [nrd.io](https://nrd.io/) [[@mrtns](https://github.com/mrtns)] - [OKRA Technologies](https://okra.ai) [[@JPFrancoia](https://github.com/JPFrancoia), [@schot](https://github.com/schot)] - [Pier](https://www.pier.digital/) [[@flaviomax](https://github.com/flaviomax)] - [Pismo](https://www.pismo.io/) [[@msantino](https://github.com/msantino)] - [ringDNA](https://www.ringdna.com/) [[@msropp](https://github.com/msropp)] - [Serasa Experian](https://www.serasaexperian.com.br/) [[@andre-marcos-perez](https://github.com/andre-marcos-perez)] - [Shipwell](https://shipwell.com/) [[@zacharycarter](https://github.com/zacharycarter)] - [strongDM](https://www.strongdm.com/) [[@mrtns](https://github.com/mrtns)] - [Thinkbumblebee](https://www.thinkbumblebee.com/) [[@dheerajsharma21]](https://github.com/dheerajsharma21) - [VTEX](https://vtex.com/us-en/) [[@igorborgest]](https://github.com/igorborgest) - [Zillow](https://www.zillow.com/) [[@nicholas-miles]](https://github.com/nicholas-miles) %package -n python3-awswrangler Summary: Pandas on AWS. Provides: python-awswrangler BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-awswrangler # AWS SDK for pandas (awswrangler) AWS Data Wrangler is now **AWS SDK for pandas (awswrangler)**. We’re changing the name we use when we talk about the library, but everything else will stay the same. You’ll still be able to install using `pip install awswrangler` and you won’t need to change any of your code. As part of this change, we’ve moved the library from AWS Labs to the main AWS GitHub organisation but, thanks to the GitHub’s redirect feature, you’ll still be able to access the project by its old URLs until you update your bookmarks. Our documentation has also moved to [aws-sdk-pandas.readthedocs.io](https://aws-sdk-pandas.readthedocs.io), but old bookmarks will redirect to the new site. *Pandas on AWS* Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL). ![AWS SDK for pandas](docs/source/_static/logo2.png?raw=true "AWS SDK for pandas") ![tracker](https://d3tiqpr4kkkomd.cloudfront.net/img/pixel.png?asset=GVOYN2BOOQ573LTVIHEW) > An [AWS Professional Service](https://aws.amazon.com/professional-services/) open source initiative | aws-proserve-opensource@amazon.com [![Release](https://img.shields.io/badge/release-2.20.1-brightgreen.svg)](https://pypi.org/project/awswrangler/) [![Python Version](https://img.shields.io/badge/python-3.7%20%7C%203.8%20%7C%203.9%20%7C%203.10-brightgreen.svg)](https://anaconda.org/conda-forge/awswrangler) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) [![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/) [![Coverage](https://img.shields.io/badge/coverage-91%25-brightgreen.svg)](https://pypi.org/project/awswrangler/) ![Static Checking](https://github.com/aws/aws-sdk-pandas/workflows/Static%20Checking/badge.svg?branch=main) [![Documentation Status](https://readthedocs.org/projects/aws-sdk-pandas/badge/?version=latest)](https://aws-sdk-pandas.readthedocs.io/?badge=latest) | Source | Downloads | Installation Command | |--------|-----------|----------------------| | **[PyPi](https://pypi.org/project/awswrangler/)** | [![PyPI Downloads](https://pepy.tech/badge/awswrangler)](https://pypi.org/project/awswrangler/) | `pip install awswrangler` | | **[Conda](https://anaconda.org/conda-forge/awswrangler)** | [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/awswrangler.svg)](https://anaconda.org/conda-forge/awswrangler) | `conda install -c conda-forge awswrangler` | > ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#emr-cluster), [Glue PySpark Job](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️ `pip install pyarrow==2 awswrangler` Powered By [](https://arrow.apache.org/powered_by/) ## Table of contents - [Quick Start](#quick-start) - [Read The Docs](#read-the-docs) - [Getting Help](#getting-help) - [Community Resources](#community-resources) - [Logging](#logging) - [Who uses AWS SDK for pandas?](#who-uses-aws-sdk-pandas) ## Quick Start Installation command: `pip install awswrangler` > ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#emr-cluster), [Glue PySpark Job](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️`pip install pyarrow==2 awswrangler` ```py3 import awswrangler as wr import pandas as pd from datetime import datetime df = pd.DataFrame({"id": [1, 2], "value": ["foo", "boo"]}) # Storing data on Data Lake wr.s3.to_parquet( df=df, path="s3://bucket/dataset/", dataset=True, database="my_db", table="my_table" ) # Retrieving the data directly from Amazon S3 df = wr.s3.read_parquet("s3://bucket/dataset/", dataset=True) # Retrieving the data from Amazon Athena df = wr.athena.read_sql_query("SELECT * FROM my_table", database="my_db") # Get a Redshift connection from Glue Catalog and retrieving data from Redshift Spectrum con = wr.redshift.connect("my-glue-connection") df = wr.redshift.read_sql_query("SELECT * FROM external_schema.my_table", con=con) con.close() # Amazon Timestream Write df = pd.DataFrame({ "time": [datetime.now(), datetime.now()], "my_dimension": ["foo", "boo"], "measure": [1.0, 1.1], }) rejected_records = wr.timestream.write(df, database="sampleDB", table="sampleTable", time_col="time", measure_col="measure", dimensions_cols=["my_dimension"], ) # Amazon Timestream Query wr.timestream.query(""" SELECT time, measure_value::double, my_dimension FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 """) ``` ## [Read The Docs](https://aws-sdk-pandas.readthedocs.io/) - [**What is AWS SDK for pandas?**](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/about.html) - [**Install**](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html) - [PyPi (pip)](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#pypi-pip) - [Conda](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#conda) - [AWS Lambda Layer](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-lambda-layer) - [AWS Glue Python Shell Jobs](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-python-shell-jobs) - [AWS Glue PySpark Jobs](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-pyspark-jobs) - [Amazon SageMaker Notebook](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#amazon-sagemaker-notebook) - [Amazon SageMaker Notebook Lifecycle](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#amazon-sagemaker-notebook-lifecycle) - [EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#emr) - [From source](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#from-source) - [**Tutorials**](https://github.com/aws/aws-sdk-pandas/tree/main/tutorials) - [001 - Introduction](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/001%20-%20Introduction.ipynb) - [002 - Sessions](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/002%20-%20Sessions.ipynb) - [003 - Amazon S3](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/003%20-%20Amazon%20S3.ipynb) - [004 - Parquet Datasets](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/004%20-%20Parquet%20Datasets.ipynb) - [005 - Glue Catalog](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/005%20-%20Glue%20Catalog.ipynb) - [006 - Amazon Athena](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/006%20-%20Amazon%20Athena.ipynb) - [007 - Databases (Redshift, MySQL, PostgreSQL, SQL Server and Oracle)](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/007%20-%20Redshift%2C%20MySQL%2C%20PostgreSQL%2C%20SQL%20Server%2C%20Oracle.ipynb) - [008 - Redshift - Copy & Unload.ipynb](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/008%20-%20Redshift%20-%20Copy%20%26%20Unload.ipynb) - [009 - Redshift - Append, Overwrite and Upsert](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/009%20-%20Redshift%20-%20Append%2C%20Overwrite%2C%20Upsert.ipynb) - [010 - Parquet Crawler](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/010%20-%20Parquet%20Crawler.ipynb) - [011 - CSV Datasets](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/011%20-%20CSV%20Datasets.ipynb) - [012 - CSV Crawler](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/012%20-%20CSV%20Crawler.ipynb) - [013 - Merging Datasets on S3](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/013%20-%20Merging%20Datasets%20on%20S3.ipynb) - [014 - Schema Evolution](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/014%20-%20Schema%20Evolution.ipynb) - [015 - EMR](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/015%20-%20EMR.ipynb) - [016 - EMR & Docker](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/016%20-%20EMR%20%26%20Docker.ipynb) - [017 - Partition Projection](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/017%20-%20Partition%20Projection.ipynb) - [018 - QuickSight](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/018%20-%20QuickSight.ipynb) - [019 - Athena Cache](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/019%20-%20Athena%20Cache.ipynb) - [020 - Spark Table Interoperability](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/020%20-%20Spark%20Table%20Interoperability.ipynb) - [021 - Global Configurations](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/021%20-%20Global%20Configurations.ipynb) - [022 - Writing Partitions Concurrently](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/022%20-%20Writing%20Partitions%20Concurrently.ipynb) - [023 - Flexible Partitions Filter](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/023%20-%20Flexible%20Partitions%20Filter.ipynb) - [024 - Athena Query Metadata](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/024%20-%20Athena%20Query%20Metadata.ipynb) - [025 - Redshift - Loading Parquet files with Spectrum](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/025%20-%20Redshift%20-%20Loading%20Parquet%20files%20with%20Spectrum.ipynb) - [026 - Amazon Timestream](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/026%20-%20Amazon%20Timestream.ipynb) - [027 - Amazon Timestream 2](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/027%20-%20Amazon%20Timestream%202.ipynb) - [028 - Amazon DynamoDB](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/028%20-%20DynamoDB.ipynb) - [029 - S3 Select](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/029%20-%20S3%20Select.ipynb) - [030 - Data Api](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/030%20-%20Data%20Api.ipynb) - [031 - OpenSearch](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/031%20-%20OpenSearch.ipynb) - [032 - Lake Formation Governed Tables](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/032%20-%20Lake%20Formation%20Governed%20Tables.ipynb) - [033 - Amazon Neptune](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/033%20-%20Amazon%20Neptune.ipynb) - [034 - Glue Data Quality](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/034%20-Glue%20%20Data%20Quality.ipynb) - [**API Reference**](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html) - [Amazon S3](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-s3) - [AWS Glue Catalog](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-glue-catalog) - [Amazon Athena](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-athena) - [AWS Lake Formation](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-lake-formation) - [Amazon Redshift](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-redshift) - [PostgreSQL](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#postgresql) - [MySQL](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#mysql) - [SQL Server](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#sqlserver) - [Oracle](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#oracle) - [Data API Redshift](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#data-api-redshift) - [Data API RDS](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#data-api-rds) - [OpenSearch](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#opensearch) - [Amazon Neptune](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-neptune) - [DynamoDB](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#dynamodb) - [Amazon Timestream](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-timestream) - [Amazon EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-emr) - [Amazon CloudWatch Logs](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-cloudwatch-logs) - [Amazon Chime](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-chime) - [Amazon QuickSight](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-quicksight) - [AWS STS](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-sts) - [AWS Secrets Manager](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-secrets-manager) - [Global Configurations](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#global-configurations) - [**License**](https://github.com/aws/aws-sdk-pandas/blob/main/LICENSE.txt) - [**Contributing**](https://github.com/aws/aws-sdk-pandas/blob/main/CONTRIBUTING.md) ## Getting Help The best way to interact with our team is through GitHub. You can open an [issue](https://github.com/aws/aws-sdk-pandas/issues/new/choose) and choose from one of our templates for bug reports, feature requests... You may also find help on these community resources: * The #aws-sdk-pandas Slack [channel](https://join.slack.com/t/aws-sdk-pandas/shared_invite/zt-sxdx38sl-E0coRfAds8WdpxXD2Nzfrg) * Ask a question on [Stack Overflow](https://stackoverflow.com/questions/tagged/awswrangler) and tag it with `awswrangler` ## Community Resources Please [send a Pull Request](https://github.com/aws/aws-sdk-pandas/edit/main/README.md) with your resource reference and @githubhandle. - [Optimize Python ETL by extending Pandas with AWS SDK for pandas](https://aws.amazon.com/blogs/big-data/optimize-python-etl-by-extending-pandas-with-aws-data-wrangler/) [[@igorborgest](https://github.com/igorborgest)] - [Reading Parquet Files With AWS Lambda](https://aprakash.wordpress.com/2020/04/14/reading-parquet-files-with-aws-lambda/) [[@anand086](https://github.com/anand086)] - [Transform AWS CloudTrail data using AWS SDK for pandas](https://aprakash.wordpress.com/2020/09/17/transform-aws-cloudtrail-data-using-aws-data-wrangler/) [[@anand086](https://github.com/anand086)] - [Rename Glue Tables using AWS SDK for pandas](https://ananddatastories.com/rename-glue-tables-using-aws-sdk-pandas/) [[@anand086](https://github.com/anand086)] - [Getting started on AWS SDK for pandas and Athena](https://medium.com/@dheerajsharmainampudi/getting-started-on-aws-sdk-pandas-and-athena-7b446c834076) [[@dheerajsharma21](https://github.com/dheerajsharma21)] - [Simplifying Pandas integration with AWS data related services](https://medium.com/@bv_subhash/aws-sdk-pandas-simplifying-pandas-integration-with-aws-data-related-services-2b3325c12188) [[@bvsubhash](https://github.com/bvsubhash)] - [Build an ETL pipeline using AWS S3, Glue and Athena](https://www.linkedin.com/pulse/build-etl-pipeline-using-aws-s3-glue-athena-data-wrangler-tom-reid/) [[@taupirho](https://github.com/taupirho)] ## Logging Enabling internal logging examples: ```py3 import logging logging.basicConfig(level=logging.INFO, format="[%(name)s][%(funcName)s] %(message)s") logging.getLogger("awswrangler").setLevel(logging.DEBUG) logging.getLogger("botocore.credentials").setLevel(logging.CRITICAL) ``` Into AWS lambda: ```py3 import logging logging.getLogger("awswrangler").setLevel(logging.DEBUG) ``` ## Who uses AWS SDK for pandas? Knowing which companies are using this library is important to help prioritize the project internally. If you would like us to include your company’s name and/or logo in the README file to indicate that your company is using the AWS SDK for pandas, please raise a "Support Us" issue. If you would like us to display your company’s logo, please raise a linked pull request to provide an image file for the logo. Note that by raising a Support Us issue (and related pull request), you are granting AWS permission to use your company’s name (and logo) for the limited purpose described here and you are confirming that you have authority to grant such permission. - [Amazon](https://www.amazon.com/) - [AWS](https://aws.amazon.com/) - [Cepsa](https://cepsa.com) [[@alvaropc](https://github.com/alvaropc)] - [Cognitivo](https://www.cognitivo.ai/) [[@msantino](https://github.com/msantino)] - [Digio](https://www.digio.com.br/) [[@afonsomy](https://github.com/afonsomy)] - [DNX](https://www.dnx.solutions/) [[@DNXLabs](https://github.com/DNXLabs)] - [Fortescue Future Industries](https://ffi.com.au/) [[@spencervoorend](https://github.com/spencervoorend)] - [Funcional Health Tech](https://www.funcionalcorp.com.br/) [[@webysther](https://github.com/webysther)] - [Funding Circle](https://www.fundingcircle.com/) [[@pfig](https://github.com/pfig)] - [Infomach](https://www.infomach.com.br/) - [Informa Markets](https://www.informamarkets.com/en/home.html) [[@mateusmorato]](http://github.com/mateusmorato) - [LINE TV](https://www.linetv.tw/) [[@bryanyang0528](https://github.com/bryanyang0528)] - [Magnataur](https://magnataur.com) [[@brianmingus2](https://github.com/brianmingus2)] - [M4U](https://www.m4u.com.br/) [[@Thiago-Dantas](https://github.com/Thiago-Dantas)] - [NBCUniversal](https://www.nbcuniversal.com/) [[@vibe](https://github.com/vibe)] - [nrd.io](https://nrd.io/) [[@mrtns](https://github.com/mrtns)] - [OKRA Technologies](https://okra.ai) [[@JPFrancoia](https://github.com/JPFrancoia), [@schot](https://github.com/schot)] - [Pier](https://www.pier.digital/) [[@flaviomax](https://github.com/flaviomax)] - [Pismo](https://www.pismo.io/) [[@msantino](https://github.com/msantino)] - [ringDNA](https://www.ringdna.com/) [[@msropp](https://github.com/msropp)] - [Serasa Experian](https://www.serasaexperian.com.br/) [[@andre-marcos-perez](https://github.com/andre-marcos-perez)] - [Shipwell](https://shipwell.com/) [[@zacharycarter](https://github.com/zacharycarter)] - [strongDM](https://www.strongdm.com/) [[@mrtns](https://github.com/mrtns)] - [Thinkbumblebee](https://www.thinkbumblebee.com/) [[@dheerajsharma21]](https://github.com/dheerajsharma21) - [VTEX](https://vtex.com/us-en/) [[@igorborgest]](https://github.com/igorborgest) - [Zillow](https://www.zillow.com/) [[@nicholas-miles]](https://github.com/nicholas-miles) %package help Summary: Development documents and examples for awswrangler Provides: python3-awswrangler-doc %description help # AWS SDK for pandas (awswrangler) AWS Data Wrangler is now **AWS SDK for pandas (awswrangler)**. We’re changing the name we use when we talk about the library, but everything else will stay the same. You’ll still be able to install using `pip install awswrangler` and you won’t need to change any of your code. As part of this change, we’ve moved the library from AWS Labs to the main AWS GitHub organisation but, thanks to the GitHub’s redirect feature, you’ll still be able to access the project by its old URLs until you update your bookmarks. Our documentation has also moved to [aws-sdk-pandas.readthedocs.io](https://aws-sdk-pandas.readthedocs.io), but old bookmarks will redirect to the new site. *Pandas on AWS* Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL). ![AWS SDK for pandas](docs/source/_static/logo2.png?raw=true "AWS SDK for pandas") ![tracker](https://d3tiqpr4kkkomd.cloudfront.net/img/pixel.png?asset=GVOYN2BOOQ573LTVIHEW) > An [AWS Professional Service](https://aws.amazon.com/professional-services/) open source initiative | aws-proserve-opensource@amazon.com [![Release](https://img.shields.io/badge/release-2.20.1-brightgreen.svg)](https://pypi.org/project/awswrangler/) [![Python Version](https://img.shields.io/badge/python-3.7%20%7C%203.8%20%7C%203.9%20%7C%203.10-brightgreen.svg)](https://anaconda.org/conda-forge/awswrangler) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) [![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/) [![Coverage](https://img.shields.io/badge/coverage-91%25-brightgreen.svg)](https://pypi.org/project/awswrangler/) ![Static Checking](https://github.com/aws/aws-sdk-pandas/workflows/Static%20Checking/badge.svg?branch=main) [![Documentation Status](https://readthedocs.org/projects/aws-sdk-pandas/badge/?version=latest)](https://aws-sdk-pandas.readthedocs.io/?badge=latest) | Source | Downloads | Installation Command | |--------|-----------|----------------------| | **[PyPi](https://pypi.org/project/awswrangler/)** | [![PyPI Downloads](https://pepy.tech/badge/awswrangler)](https://pypi.org/project/awswrangler/) | `pip install awswrangler` | | **[Conda](https://anaconda.org/conda-forge/awswrangler)** | [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/awswrangler.svg)](https://anaconda.org/conda-forge/awswrangler) | `conda install -c conda-forge awswrangler` | > ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#emr-cluster), [Glue PySpark Job](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️ `pip install pyarrow==2 awswrangler` Powered By [](https://arrow.apache.org/powered_by/) ## Table of contents - [Quick Start](#quick-start) - [Read The Docs](#read-the-docs) - [Getting Help](#getting-help) - [Community Resources](#community-resources) - [Logging](#logging) - [Who uses AWS SDK for pandas?](#who-uses-aws-sdk-pandas) ## Quick Start Installation command: `pip install awswrangler` > ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#emr-cluster), [Glue PySpark Job](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️`pip install pyarrow==2 awswrangler` ```py3 import awswrangler as wr import pandas as pd from datetime import datetime df = pd.DataFrame({"id": [1, 2], "value": ["foo", "boo"]}) # Storing data on Data Lake wr.s3.to_parquet( df=df, path="s3://bucket/dataset/", dataset=True, database="my_db", table="my_table" ) # Retrieving the data directly from Amazon S3 df = wr.s3.read_parquet("s3://bucket/dataset/", dataset=True) # Retrieving the data from Amazon Athena df = wr.athena.read_sql_query("SELECT * FROM my_table", database="my_db") # Get a Redshift connection from Glue Catalog and retrieving data from Redshift Spectrum con = wr.redshift.connect("my-glue-connection") df = wr.redshift.read_sql_query("SELECT * FROM external_schema.my_table", con=con) con.close() # Amazon Timestream Write df = pd.DataFrame({ "time": [datetime.now(), datetime.now()], "my_dimension": ["foo", "boo"], "measure": [1.0, 1.1], }) rejected_records = wr.timestream.write(df, database="sampleDB", table="sampleTable", time_col="time", measure_col="measure", dimensions_cols=["my_dimension"], ) # Amazon Timestream Query wr.timestream.query(""" SELECT time, measure_value::double, my_dimension FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 """) ``` ## [Read The Docs](https://aws-sdk-pandas.readthedocs.io/) - [**What is AWS SDK for pandas?**](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/about.html) - [**Install**](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html) - [PyPi (pip)](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#pypi-pip) - [Conda](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#conda) - [AWS Lambda Layer](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-lambda-layer) - [AWS Glue Python Shell Jobs](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-python-shell-jobs) - [AWS Glue PySpark Jobs](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#aws-glue-pyspark-jobs) - [Amazon SageMaker Notebook](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#amazon-sagemaker-notebook) - [Amazon SageMaker Notebook Lifecycle](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#amazon-sagemaker-notebook-lifecycle) - [EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#emr) - [From source](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/install.html#from-source) - [**Tutorials**](https://github.com/aws/aws-sdk-pandas/tree/main/tutorials) - [001 - Introduction](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/001%20-%20Introduction.ipynb) - [002 - Sessions](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/002%20-%20Sessions.ipynb) - [003 - Amazon S3](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/003%20-%20Amazon%20S3.ipynb) - [004 - Parquet Datasets](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/004%20-%20Parquet%20Datasets.ipynb) - [005 - Glue Catalog](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/005%20-%20Glue%20Catalog.ipynb) - [006 - Amazon Athena](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/006%20-%20Amazon%20Athena.ipynb) - [007 - Databases (Redshift, MySQL, PostgreSQL, SQL Server and Oracle)](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/007%20-%20Redshift%2C%20MySQL%2C%20PostgreSQL%2C%20SQL%20Server%2C%20Oracle.ipynb) - [008 - Redshift - Copy & Unload.ipynb](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/008%20-%20Redshift%20-%20Copy%20%26%20Unload.ipynb) - [009 - Redshift - Append, Overwrite and Upsert](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/009%20-%20Redshift%20-%20Append%2C%20Overwrite%2C%20Upsert.ipynb) - [010 - Parquet Crawler](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/010%20-%20Parquet%20Crawler.ipynb) - [011 - CSV Datasets](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/011%20-%20CSV%20Datasets.ipynb) - [012 - CSV Crawler](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/012%20-%20CSV%20Crawler.ipynb) - [013 - Merging Datasets on S3](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/013%20-%20Merging%20Datasets%20on%20S3.ipynb) - [014 - Schema Evolution](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/014%20-%20Schema%20Evolution.ipynb) - [015 - EMR](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/015%20-%20EMR.ipynb) - [016 - EMR & Docker](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/016%20-%20EMR%20%26%20Docker.ipynb) - [017 - Partition Projection](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/017%20-%20Partition%20Projection.ipynb) - [018 - QuickSight](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/018%20-%20QuickSight.ipynb) - [019 - Athena Cache](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/019%20-%20Athena%20Cache.ipynb) - [020 - Spark Table Interoperability](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/020%20-%20Spark%20Table%20Interoperability.ipynb) - [021 - Global Configurations](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/021%20-%20Global%20Configurations.ipynb) - [022 - Writing Partitions Concurrently](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/022%20-%20Writing%20Partitions%20Concurrently.ipynb) - [023 - Flexible Partitions Filter](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/023%20-%20Flexible%20Partitions%20Filter.ipynb) - [024 - Athena Query Metadata](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/024%20-%20Athena%20Query%20Metadata.ipynb) - [025 - Redshift - Loading Parquet files with Spectrum](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/025%20-%20Redshift%20-%20Loading%20Parquet%20files%20with%20Spectrum.ipynb) - [026 - Amazon Timestream](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/026%20-%20Amazon%20Timestream.ipynb) - [027 - Amazon Timestream 2](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/027%20-%20Amazon%20Timestream%202.ipynb) - [028 - Amazon DynamoDB](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/028%20-%20DynamoDB.ipynb) - [029 - S3 Select](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/029%20-%20S3%20Select.ipynb) - [030 - Data Api](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/030%20-%20Data%20Api.ipynb) - [031 - OpenSearch](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/031%20-%20OpenSearch.ipynb) - [032 - Lake Formation Governed Tables](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/032%20-%20Lake%20Formation%20Governed%20Tables.ipynb) - [033 - Amazon Neptune](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/033%20-%20Amazon%20Neptune.ipynb) - [034 - Glue Data Quality](https://github.com/aws/aws-sdk-pandas/blob/main/tutorials/034%20-Glue%20%20Data%20Quality.ipynb) - [**API Reference**](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html) - [Amazon S3](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-s3) - [AWS Glue Catalog](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-glue-catalog) - [Amazon Athena](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-athena) - [AWS Lake Formation](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-lake-formation) - [Amazon Redshift](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-redshift) - [PostgreSQL](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#postgresql) - [MySQL](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#mysql) - [SQL Server](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#sqlserver) - [Oracle](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#oracle) - [Data API Redshift](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#data-api-redshift) - [Data API RDS](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#data-api-rds) - [OpenSearch](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#opensearch) - [Amazon Neptune](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-neptune) - [DynamoDB](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#dynamodb) - [Amazon Timestream](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-timestream) - [Amazon EMR](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-emr) - [Amazon CloudWatch Logs](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-cloudwatch-logs) - [Amazon Chime](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-chime) - [Amazon QuickSight](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#amazon-quicksight) - [AWS STS](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-sts) - [AWS Secrets Manager](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#aws-secrets-manager) - [Global Configurations](https://aws-sdk-pandas.readthedocs.io/en/2.20.1/api.html#global-configurations) - [**License**](https://github.com/aws/aws-sdk-pandas/blob/main/LICENSE.txt) - [**Contributing**](https://github.com/aws/aws-sdk-pandas/blob/main/CONTRIBUTING.md) ## Getting Help The best way to interact with our team is through GitHub. You can open an [issue](https://github.com/aws/aws-sdk-pandas/issues/new/choose) and choose from one of our templates for bug reports, feature requests... You may also find help on these community resources: * The #aws-sdk-pandas Slack [channel](https://join.slack.com/t/aws-sdk-pandas/shared_invite/zt-sxdx38sl-E0coRfAds8WdpxXD2Nzfrg) * Ask a question on [Stack Overflow](https://stackoverflow.com/questions/tagged/awswrangler) and tag it with `awswrangler` ## Community Resources Please [send a Pull Request](https://github.com/aws/aws-sdk-pandas/edit/main/README.md) with your resource reference and @githubhandle. - [Optimize Python ETL by extending Pandas with AWS SDK for pandas](https://aws.amazon.com/blogs/big-data/optimize-python-etl-by-extending-pandas-with-aws-data-wrangler/) [[@igorborgest](https://github.com/igorborgest)] - [Reading Parquet Files With AWS Lambda](https://aprakash.wordpress.com/2020/04/14/reading-parquet-files-with-aws-lambda/) [[@anand086](https://github.com/anand086)] - [Transform AWS CloudTrail data using AWS SDK for pandas](https://aprakash.wordpress.com/2020/09/17/transform-aws-cloudtrail-data-using-aws-data-wrangler/) [[@anand086](https://github.com/anand086)] - [Rename Glue Tables using AWS SDK for pandas](https://ananddatastories.com/rename-glue-tables-using-aws-sdk-pandas/) [[@anand086](https://github.com/anand086)] - [Getting started on AWS SDK for pandas and Athena](https://medium.com/@dheerajsharmainampudi/getting-started-on-aws-sdk-pandas-and-athena-7b446c834076) [[@dheerajsharma21](https://github.com/dheerajsharma21)] - [Simplifying Pandas integration with AWS data related services](https://medium.com/@bv_subhash/aws-sdk-pandas-simplifying-pandas-integration-with-aws-data-related-services-2b3325c12188) [[@bvsubhash](https://github.com/bvsubhash)] - [Build an ETL pipeline using AWS S3, Glue and Athena](https://www.linkedin.com/pulse/build-etl-pipeline-using-aws-s3-glue-athena-data-wrangler-tom-reid/) [[@taupirho](https://github.com/taupirho)] ## Logging Enabling internal logging examples: ```py3 import logging logging.basicConfig(level=logging.INFO, format="[%(name)s][%(funcName)s] %(message)s") logging.getLogger("awswrangler").setLevel(logging.DEBUG) logging.getLogger("botocore.credentials").setLevel(logging.CRITICAL) ``` Into AWS lambda: ```py3 import logging logging.getLogger("awswrangler").setLevel(logging.DEBUG) ``` ## Who uses AWS SDK for pandas? Knowing which companies are using this library is important to help prioritize the project internally. If you would like us to include your company’s name and/or logo in the README file to indicate that your company is using the AWS SDK for pandas, please raise a "Support Us" issue. If you would like us to display your company’s logo, please raise a linked pull request to provide an image file for the logo. Note that by raising a Support Us issue (and related pull request), you are granting AWS permission to use your company’s name (and logo) for the limited purpose described here and you are confirming that you have authority to grant such permission. - [Amazon](https://www.amazon.com/) - [AWS](https://aws.amazon.com/) - [Cepsa](https://cepsa.com) [[@alvaropc](https://github.com/alvaropc)] - [Cognitivo](https://www.cognitivo.ai/) [[@msantino](https://github.com/msantino)] - [Digio](https://www.digio.com.br/) [[@afonsomy](https://github.com/afonsomy)] - [DNX](https://www.dnx.solutions/) [[@DNXLabs](https://github.com/DNXLabs)] - [Fortescue Future Industries](https://ffi.com.au/) [[@spencervoorend](https://github.com/spencervoorend)] - [Funcional Health Tech](https://www.funcionalcorp.com.br/) [[@webysther](https://github.com/webysther)] - [Funding Circle](https://www.fundingcircle.com/) [[@pfig](https://github.com/pfig)] - [Infomach](https://www.infomach.com.br/) - [Informa Markets](https://www.informamarkets.com/en/home.html) [[@mateusmorato]](http://github.com/mateusmorato) - [LINE TV](https://www.linetv.tw/) [[@bryanyang0528](https://github.com/bryanyang0528)] - [Magnataur](https://magnataur.com) [[@brianmingus2](https://github.com/brianmingus2)] - [M4U](https://www.m4u.com.br/) [[@Thiago-Dantas](https://github.com/Thiago-Dantas)] - [NBCUniversal](https://www.nbcuniversal.com/) [[@vibe](https://github.com/vibe)] - [nrd.io](https://nrd.io/) [[@mrtns](https://github.com/mrtns)] - [OKRA Technologies](https://okra.ai) [[@JPFrancoia](https://github.com/JPFrancoia), [@schot](https://github.com/schot)] - [Pier](https://www.pier.digital/) [[@flaviomax](https://github.com/flaviomax)] - [Pismo](https://www.pismo.io/) [[@msantino](https://github.com/msantino)] - [ringDNA](https://www.ringdna.com/) [[@msropp](https://github.com/msropp)] - [Serasa Experian](https://www.serasaexperian.com.br/) [[@andre-marcos-perez](https://github.com/andre-marcos-perez)] - [Shipwell](https://shipwell.com/) [[@zacharycarter](https://github.com/zacharycarter)] - [strongDM](https://www.strongdm.com/) [[@mrtns](https://github.com/mrtns)] - [Thinkbumblebee](https://www.thinkbumblebee.com/) [[@dheerajsharma21]](https://github.com/dheerajsharma21) - [VTEX](https://vtex.com/us-en/) [[@igorborgest]](https://github.com/igorborgest) - [Zillow](https://www.zillow.com/) [[@nicholas-miles]](https://github.com/nicholas-miles) %prep %autosetup -n awswrangler-2.20.1 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-awswrangler -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Mon Apr 10 2023 Python_Bot - 2.20.1-1 - Package Spec generated