Apache Sedona extends pyspark functions which depends on libraries:

• pyspark
• shapely
• attrs

You need to install necessary packages if your system does not have them installed. Sedona now uses uv for Python dependency management. See the dependency definitions in our pyproject.toml.

Install sedona

• Installing from PyPI repositories. You can find the latest Sedona Python on PyPI. There is a known issue in Sedona v1.0.1 and earlier versions.

pip install apache-sedona

• Since Sedona v1.1.0, pyspark is an optional dependency of Sedona Python because spark comes pre-installed on many spark platforms. To install pyspark along with Sedona Python in one go, use the spark extra:

pip install apache-sedona[spark]

• Installing from Sedona Python source

Clone Sedona GitHub source code and run the following command

cd python
python3 -m pip install .

Prepare sedona-spark jar

Sedona Python needs one additional jar file called sedona-spark-shaded or sedona-spark to work properly. Please make sure you use the correct version for Spark and Scala.

Please use Spark major.minor version number in artifact names.

You can get it using one of the following methods:

1. If you run Sedona in Databricks, AWS EMR, or other cloud platform's notebook, use the shaded jar: Download sedona-spark-shaded jar and geotools-wrapper jar from Maven Central, and put them in SPARK_HOME/jars/ folder.
2. If you run Sedona in an IDE or a local Jupyter notebook, use the unshaded jar. Call the Maven Central coordinate in your python program. For example, ==Sedona >= 1.4.1==

from sedona.spark import *

config = (
    SedonaContext.builder()
    .config(
        "spark.jars.packages",
        "org.apache.sedona:sedona-spark-3.3_2.12:{{ sedona.current_version }},"
        "org.datasyslab:geotools-wrapper:{{ sedona.current_geotools }}",
    )
    .config(
        "spark.jars.repositories",
        "https://artifacts.unidata.ucar.edu/repository/unidata-all",
    )
    .getOrCreate()
)
sedona = SedonaContext.create(config)

==Sedona < 1.4.1==

SedonaRegistrator is deprecated in Sedona 1.4.1 and later versions. Please use the above method instead.

from pyspark.sql import SparkSession
from sedona.spark import SedonaRegistrator
from sedona.spark import SedonaKryoRegistrator, KryoSerializer

spark = (
    SparkSession.builder.appName("appName")
    .config("spark.serializer", KryoSerializer.getName)
    .config("spark.kryo.registrator", SedonaKryoRegistrator.getName)
    .config(
        "spark.jars.packages",
        "org.apache.sedona:sedona-spark-shaded-3.3_2.12:{{ sedona.current_version }},"
        "org.datasyslab:geotools-wrapper:{{ sedona.current_geotools }}",
    )
    .getOrCreate()
)
SedonaRegistrator.registerAll(spark)

Setup environment variables

If you manually copy the sedona-spark-shaded jar to SPARK_HOME/jars/ folder, you need to setup two environment variables

• SPARK_HOME. For example, run the command in your terminal

export SPARK_HOME=~/Downloads/spark-3.0.1-bin-hadoop2.7

• PYTHONPATH. For example, run the command in your terminal

export PYTHONPATH=$SPARK_HOME/python

You can then play with Sedona Python Jupyter notebook.