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kestra

Kestra is an infinitely scalable orchestration and scheduling platform, creating, running, scheduling, and monitoring millions of complex pipelines.

  • 0.21.13
  • PyPI
  • Socket score

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Kestra Python Client

This Python client provides functionality to interact with the Kestra server for sending metrics, outputs, and logs, as well as executing/polling flows.

Installation

pip install kestra

Kestra Class

The Kestra class is responsible for sending metrics, outputs, and logs to the Kestra server.

Methods

  • send(map: dict): Sends a message to the Kestra server.
  • format(map_: dict) -> str: Formats a message to be sent to the Kestra server.
  • metrics(name: str, type: str, value: int, tags: dict | None = None): Sends a metric to the Kestra server.
  • outputs(map_: dict): Sends outputs to the Kestra server.
  • counter(name: str, value: int, tags: dict | None = None): Sends a counter to the Kestra server.
  • timer(name: str, duration: int | Callable, tags: dict | None = None): Sends a timer to the Kestra server.
  • logger() -> Logger: Retrieves the logger for the Kestra server.

Flow Class

The Flow class is used to execute a Kestra flow and optionally wait for its completion. It can also be used to get the status of an execution and the logs of an execution.

Initialization

flow = Flow(
  wait_for_completion=True, # default is True
  poll_interval=1, # seconds. default is 1  
  labels_from_inputs=False, # default is False
  tenant=None # default is None
)

You can also set the hostname and authentication credentials using environment variables:

export KESTRA_HOSTNAME=http://localhost:8080
export KESTRA_USER=admin
export KESTRA_PASSWORD=admin
export KESTRA_API_TOKEN=my_api_token

It is worth noting that the KESTRA_API_TOKEN or KESTRA_USER and KESTRA_PASSWORD need to be used, you do not need all at once. The possible Authentication patterns are:

  1. KESTRA_API_TOKEN
  2. KESTRA_USER and KESTRA_PASSWORD
  3. No Authentication (not recommended for production environments)

Methods

  • _make_request(method: str, url: str, **kwargs) -> requests.Response: Makes a request to the Kestra server with optional authentication and retries.
  • check_status(execution_id: str) -> requests.Response: Checks the status of an execution.
  • get_logs(execution_id: str) -> requests.Response: Retrieves the logs of an execution.
  • execute(namespace: str, flow: str, inputs: dict = None) -> namedtuple: Executes a Kestra flow and optionally waits for its completion. The namedtuple returned is a namedtuple with the following properties:
    • status: The status of the execution.
    • log: The log of the execution.
    • error: The error of the execution.

Usage Examples

  1. Trigger a flow and wait for its completion:

    from kestra import Flow
    flow = Flow()
    flow.execute('mynamespace', 'myflow', {'param': 'value'})
    
  2. Set labels from inputs:

    from kestra import Flow
    flow = Flow(labels_from_inputs=True)
    flow.execute('mynamespace', 'myflow', {'param': 'value'})
    
  3. Pass a text file to an input of type FILE named 'myfile':

    from kestra import Flow
    flow = Flow()
    with open('example.txt', 'rb') as fh:
        flow.execute('mynamespace', 'myflow', {'files': ('myfile', fh, 'text/plain')})
    
  4. Fire and forget:

    from kestra import Flow
    flow = Flow(wait_for_completion=False)
    flow.execute('mynamespace', 'myflow', {'param': 'value'})
    
  5. Overwrite the username and password:

    from kestra import Flow
    flow = Flow()
    flow.user = 'admin'
    flow.password = 'admin'
    flow.execute('mynamespace', 'myflow')
    
  6. Set the hostname, username, and password using environment variables:

    from kestra import Flow
    import os
    
    os.environ["KESTRA_HOSTNAME"] = "http://localhost:8080"
    os.environ["KESTRA_USER"] = "admin"
    os.environ["KESTRA_PASSWORD"] = "admin"
    flow = Flow()
    flow.execute('mynamespace', 'myflow', {'param': 'value'})
    

Error Handling

The client includes retry logic with exponential backoff for certain HTTP status codes, and raises a FailedExponentialBackoff exception if the request fails after multiple retries.

Kestra Class

Logging

The Kestra class provides a logger that formats logs in JSON format, making it easier to integrate with log management systems.

from kestra import Kestra

Kestra.logger().info("Hello, world!")

Outputs

The Kestra class provides a method to send key-value-based outputs to the Kestra server. If you want to output large objects, write them to a file and specify them within the outputFiles property of the Python script task.

Kestra.outputs({"my_output": "my_value"})

Counters

The Kestra class provides a method to send counter metrics to the Kestra server.

Kestra.counter("my_counter", 1)

Timers

The Kestra class provides a method to send timer metrics to the Kestra server.

Kestra.timer("my_timer", 1)

FAQs


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