ts-dataweave 1.0.4

Python wrapper around MuleSoft DataWeave data transformation engine.

DataWeave Python Wrapper

Python wrapper around MuleSoft's DataWeave data transformation engine.

Installation

Add this package to your project using pip or pipenv:

# using pip
pip install ts-dataweave

# using pipenv
pipenv install ts-dataweave

The post-install script will download and extract the correct DataWeave command-line binary from MuleSoft's DataWeave CLI repository.

Usage

To use DataWeave, import ts_dataweave:

import ts_dataweave

ts_dataweave.run(payload, script, [timeout])

Runs a DataWeave script with the specified payloads. The input payloads and script are written to temporary files and then removed when the execution is complete.

The payload parameter should be a dictionary of ts_dataweave.Payload instances with string keys. The payloads will be added to DataWeave with the corresponding key as the name of the payload.

The script parameter should be a string, bytes, or file-like object containing the DataWeave script.

The timeout parameter is optional and should be the number of seconds that the script is allowed to run before an error is raised. The default timeout is 30 seconds.

The ts_dataweave.run() function returns a bytes object containing the output of the DataWeave script execution.

A bytes object can easily be converted to a UTF-8 string by using .decode("utf-8").

ts_dataweave.Payload

The dataweave.Payload object contains information about a DataWeave payload. Use the constructor:

ts_dataweave.Payload([payloadType], data)

The payloadType parameter should be either "json", "csv", or "xml". Alternatively, the members from the enumeration dataweave.PayloadType can also be used. Additional input types are not recognized at this time. If the payloadType parameter is omitted, the type will be guessed based on the first non-whitespace byte of data:

• b"{" ➡️ "json"
• b"[" ➡️ "json"
• b"<" ➡️ "xml"
• Else ➡️ "csv" If the payload is large or there is any chance of ambiguity, please specify payloadType.

The data parameter should be a string, bytes, dict, list, or file-like object containing the content of the payload. The payloadType parameter can be safely omitted if data is a dict or list.

Examples

Example with explicit payload types:

import ts_dataweave

print(ts_dataweave.run({
    "doc1": ts_dataweave.Payload(
        "xml", # can also use ts_dataweave.XML
        """<root>
            <firstname>Mike</firstname>
            <lastname>Foo</lastname>
        </root>"""
    ),
    "doc2": ts_dataweave.Payload(
        "json", # can also use ts_dataweave.JSON
        """{
            "birthday": "yesterday",
            "favoriteFood": "salami"
        }"""
    ),        
}, """contact: {
    firstname: doc1.root.firstname,
    lastname: doc1.root.lastname,
    food: doc2.favoriteFood,
    bday: doc2.birthday
}""").decode("utf-8"))

Payload data types can also be auto-detected:

import ts_dataweave

print(ts_dataweave.run({
    "doc1": ts_dataweave.Payload(
        """<root>
            <firstname>Mike</firstname>
            <lastname>Foo</lastname>
        </root>"""
    ),
    "doc2": ts_dataweave.Payload(
        """{
            "birthday": "yesterday",
            "favoriteFood": "salami"
        }"""
    ),        
}, """contact: {
    firstname: doc1.root.firstname,
    lastname: doc1.root.lastname,
    food: doc2.favoriteFood,
    bday: doc2.birthday
}""").decode("utf-8"))

Python dicts and lists can also be used for payload data with payload type safely omitted:

import ts_dataweave

print(ts_dataweave.run({
    "doc1": ts_dataweave.Payload(["Mike", "Foo"]),
    "doc2": ts_dataweave.Payload(
        {
            "birthday": "yesterday",
            "favoriteFood": "salami"
        }
    ),        
}, """contact: {
    firstname: doc1[0],
    lastname: doc1[1],
    food: doc2.favoriteFood,
    bday: doc2.birthday
}""").decode("utf-8"))

Tests

The repository includes a test suite.

python -m pytest

Compatibility

This package has been specifically developed and tested with Python 3.7 on Darwin (macOS) x86_64 and Linux x86_64 platforms.

Changelog

1.0.4

• Update DataWeave CLI to v1.0.16 for macOS and Linux.

1.0.3

• Optional auto-detection of payloadType in ts_dataweave.Payload constructor

1.0.2

• Fix wrapping of ts_dataweave.Error with another ts_dataweave.Error
• Sanitize payload IDs before executing DataWeave

1.0.1

• Use temporary file to capture DataWeave output instead of the standard output stream.

1.0.0

• Initial implementation.