Integrate the Data Stores API with the Python API

Setup the Data Stores API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Data Stores and Python remarkably fast. Free for developers.

Popular Data Stores and Python Actions#

Add or update a single record with the Data Stores API

Add or update a single record in your Pipedream Data Store.

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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Add or update multiple records with the Data Stores API

Add or update multiple records to your Pipedream Data Store.

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Append to record with the Data Stores API

Append to a record in your data store Pipedream Data Store. If the record does not exist, a new record will be created in an array format.

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Check for existence of key with the Data Stores API

Check if a key exists in your Pipedream Data Store or create one if it doesn't exist.

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Overview of Data Stores#

Data Stores are a key-value store that allow you to persist state and share data across workflows. You can perform CRUD operations, enabling dynamic data management within your serverless architecture. Use it to save results from API calls, user inputs, or interim data; then read, update, or enrich this data in subsequent steps or workflows. Data Stores simplify stateful logic and cross-workflow communication, making them ideal for tracking process statuses, aggregating metrics, or serving as a simple configuration store.

Connect Data Stores#

export default defineComponent({
  props: {
    myDataStore: {
      type: "data_store",
    },
  },
  async run({ steps, $ }) {
    await this.myDataStore.set("key_here","Any serializable JSON as the value")
    return await this.myDataStore.get("key_here")
  },
})

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}}