Skip to main content

Netflix Conductor Python SDK

Project description

Netflix Conductor SDK - Python

The conductor-python repository provides the client SDKs to build task workers in Python.

Building the task workers in Python mainly consists of the following steps:

  1. Setup conductor-python package
  2. Create and run task workers
  3. Create workflows using code

Setup Conductor Python Package​

  • Create a virtual environment to build your package
virtualenv conductor
source conductor/bin/activate
  • Get Conductor Python SDK
python3 -m pip install conductor-python

Server Settings

Everything related to server settings should be done within the Configuration class by setting the required parameter (when initializing an object) like this:

configuration = Configuration(
    server_api_url='https://play.orkes.io/api',
    debug=True
)
  • server_api_url : Conductor server address. For example, if you are running locally, it would look like; http://localhost:8000/api.
  • debug: It can take the values true/false. true for verbose logging false to display only the errors

Authentication Settings (Optional)

Configure the authentication settings if your Conductor server requires authentication.

Access Control Setup

See Access Control for more details on role-based access control with Conductor and generating API keys for your environment.

configuration = Configuration(
    authentication_settings=AuthenticationSettings(
        key_id='key',
        key_secret='secret'
    )
)

Metrics Settings (Optional)

Conductor uses Prometheus to collect metrics.

metrics_settings = MetricsSettings(
    directory='/path/to/folder',
    file_name='metrics_file_name.extension',
    update_interval=0.1,
)
  • directory: Directory to store the metrics.
    • Ensure that you have already created this folder, or the program should have permission to create it for you.
  • file_name: File where the metrics are stored.
    • example: metrics.log
  • update_interval: Time interval in seconds to refresh metrics into the file.
    • example: 0.1 means metrics are updated every 0.1s or 100ms.

Create and Run Task Workers

The next step is to create and run task workers.

Create Workflows using Code

Finally, you can create workflows using code.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

conductor-python-1.0.70.tar.gz (82.3 kB view details)

Uploaded Source

Built Distribution

conductor_python-1.0.70-py3-none-any.whl (159.8 kB view details)

Uploaded Python 3

File details

Details for the file conductor-python-1.0.70.tar.gz.

File metadata

  • Download URL: conductor-python-1.0.70.tar.gz
  • Upload date:
  • Size: 82.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.3

File hashes

Hashes for conductor-python-1.0.70.tar.gz
Algorithm Hash digest
SHA256 9faac23cd05a94a501014f7e69171b799d1f3ca2245af1e6270b9ec7bf3c9702
MD5 2e6c44e908778f2b80b7330ad6a6a130
BLAKE2b-256 1163ac561bdc9cbceb2fbfdac60acb3cc5ca2827457ab2b942a1395f5fbd8481

See more details on using hashes here.

File details

Details for the file conductor_python-1.0.70-py3-none-any.whl.

File metadata

File hashes

Hashes for conductor_python-1.0.70-py3-none-any.whl
Algorithm Hash digest
SHA256 ba05d2f51f620506becdf8708d8cc3fd6fc381cdbaa597bb7ae6d55350271986
MD5 7a5cbc4d5967e8b081adc82e6261fe37
BLAKE2b-256 1b131b29a37c99f5057dde845d2235cee451fd99c54ab8c348c3de8706048531

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page