FTrack
ftrack, a Backlight business, is the creator of Emmy and Academy Award-winning team collaboration and media review platforms for the creative industries.
Integrate the FTrack API with the Python API
Setup the FTrack API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate FTrack and Python remarkably fast. Free for developers.
Popular FTrack and Python Triggers#
Triggered when the status of an item is changed. See the documentation
Popular FTrack and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of FTrack#
The FTrack API is a powerhouse for creative project management, enabling users to automate and integrate a wide array of tasks related to project tracking, asset management, and team collaboration. With Pipedream, you can harness this API to create custom workflows that trigger actions within FTrack or connect it with other apps to streamline your creative operations. It's a toolset for improving efficiency by automating repetitive tasks, syncing data across applications, and orchestrating complex project management activities.
Connect FTrack#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
ftrack: {
type: "app",
app: "ftrack",
}
},
async run({steps, $}) {
return await axios($, {
method: "POST",
url: `https://${this.ftrack.$auth.subdomain}.ftrackapp.com/api`,
headers: {
"Content-Type": `application/json`,
"ftrack-user": `${this.ftrack.$auth.username}`,
"ftrack-api-key": `${this.ftrack.$auth.api_key}`,
},
data: []
})
},
})
Overview of Python#
Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.
This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.
Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:
Connect Python#
def handler(pd: "pipedream"):
# Reference data from previous steps
print(pd.steps["trigger"]["context"]["id"])
# Return data for use in future steps
return {"foo": {"test":True}}