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Python API for Pathling

This is the Python API for Pathling. It currently supports encoding of FHIR JSON bundles and NDJSON into Apache Spark dataframes.

Installation

Prerequisites:

  • Python 3.8+ with pip
  • PySpark 3.1+

To install, run this command:

pip install pathling  

Usage

The code below shows an example of using the Pathling API to encode Patient resources from FHIR JSON bundles:

from pyspark.sql import SparkSession
from pathling import PathlingContext
from pathling.etc import find_jar

spark = SparkSession.builder
.appName('pathling-test')
.master('local[*]')
.config('spark.jars', find_jar())
.getOrCreate()

ptl = PathlingContext.create(spark)

json_bundles = spark.read.text('examples/data/bundles/', wholetext=True)

patients_df = ptl.encode_bundle(json_bundles, 'Patient')
patients_df.show()

More usage examples can be found in the examples directory.

Development setup

Create an isolated python environment with Miniconda, e.g:

conda create -n pathling-dev python=3.8
conda activate pathling-dev

Prerequisites:

  • maven (Ubuntu 20.04: apt install maven)
  • java (Ubuntu 20.04: apt install default-jdk)
  • make (Ubuntu 20.04: apt install make)

To run the tests and install the package, run this command from the project root:

mvn install -pl lib/python -am

Pathling is copyright © 2018-2022, Commonwealth Scientific and Industrial Research Organisation (CSIRO) ABN 41 687 119 230. Licensed under the CSIRO Open Source Software Licence Agreement.

Release files for pathling 5.3.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pathling 5.3.1
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pathling-5.3.1.tar.gz 29.4 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for pathling 5.3.1
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pathling-5.3.1-py2.py3-none-any.whl Python 3, Python 2 none any Details

Total release size: 58.7 MB

Release files / pathling-5.3.1.tar.gz

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