Aws Sdk Pandas

pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Alternatives To Aws Sdk Pandas
Project NameStarsDownloadsRepos Using ThisPackages Using ThisMost Recent CommitTotal ReleasesLatest ReleaseOpen IssuesLicenseLanguage
Dbeaver31,197
9 hours ago1,751apache-2.0Java
Free universal database tool and SQL client
Redash22,844
a day ago2May 05, 2020777bsd-2-clausePython
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
Aws Sdk Pandas3,371349 hours ago125June 28, 202253apache-2.0Python
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Node Orm23,069700989 months ago100June 22, 2022224mitJavaScript
Object Relational Mapping
Sqlglot2,935210 hours ago161July 06, 2022mitPython
Python SQL Parser and Transpiler
Fluentmigrator2,91654813010 days ago52January 14, 2022221apache-2.0C#
Fluent migrations framework for .NET
Tbls2,228416 hours ago31May 28, 202226mitGo
tbls is a CI-Friendly tool for document a database, written in Go.
Jailer1,579
14 hours ago57July 04, 2022apache-2.0Java
Database Subsetting and Relational Data Browsing Tool.
Db.py1,2012613 years ago35March 31, 201732bsd-2-clausePython
db.py is an easier way to interact with your databases
Lucid846599574 months ago127June 23, 202221mitTypeScript
AdonisJS SQL ORM. Supports PostgreSQL, MySQL, MSSQL, Redshift, SQLite and many more
Alternatives To Aws Sdk Pandas
Select To Compare


Alternative Project Comparisons
Readme

AWS SDK for pandas (awswrangler)

AWS Data Wrangler is now AWS SDK for pandas (awswrangler). Were changing the name we use when we talk about the library, but everything else will stay the same. Youll still be able to install using pip install awswrangler and you wont need to change any of your code. As part of this change, weve moved the library from AWS Labs to the main AWS GitHub organisation but, thanks to the GitHubs redirect feature, youll 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, 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 tracker

An AWS Professional Service open source initiative | [email protected]

Release Python Version Code style: black License

Checked with mypy Coverage Static Checking Documentation Status

Source Downloads Installation Command
PyPi PyPI Downloads pip install awswrangler
Conda Conda Downloads conda install -c conda-forge awswrangler

For platforms without PyArrow 3 support (e.g. EMR, Glue PySpark Job, MWAA):
pip install pyarrow==2 awswrangler

Powered By

Table of contents

Quick Start

Installation command: pip install awswrangler

For platforms without PyArrow 3 support (e.g. EMR, Glue PySpark Job, MWAA):
pip install pyarrow==2 awswrangler

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

Getting Help

The best way to interact with our team is through GitHub. You can open an issue and choose from one of our templates for bug reports, feature requests... You may also find help on these community resources:

Community Resources

Please send a Pull Request with your resource reference and @githubhandle.

Logging

Enabling internal logging examples:

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:

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 companys 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 companys 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 companys name (and logo) for the limited purpose described here and you are confirming that you have authority to grant such permission.

Popular Mysql Projects
Popular Redshift Projects
Popular Data Storage Categories
Related Searches

Get A Weekly Email With Trending Projects For These Categories
No Spam. Unsubscribe easily at any time.
Python
Amazon Web Services
Mysql
Lambda Functions
Data Science
Pandas
Aws Lambda
Etl
Redshift
Data Engineering