Python

Security warning: The Python sandbox is not safe, and we do not consider it a security boundary. We do not recommend using the Python data source with untrusted users. This is why the Python data source is disabled by default.

Setup

The Python query runner lets you run arbitrary Python 3 scripts and visualize the contents of a result variable declared in the script. To enable it add this to your environment:

REDASH_ADDITIONAL_QUERY_RUNNERS: "redash.query_runner.python"

Now you can create a Python data source from Settings > Data Sources.

• Modules to import prior to running the script lets you define which modules that were installed by pip on the host server may be import in Redash queries.
• AdditionalModulesPaths is a comma-separated list of absolute paths on the Redash server to Python modules that should be available when querying from Redash. This is useful for private modules that are not available from pip.
• AdditionalBuiltins Redash allows twenty-five of Python’s built-in functions by default. You can specify additional built-ins here.

These are the default built-ins: abs, all, any, bool, complex, dict, divmod, enumerate, filter, float, int, len, list, map, max, min, next, reversed, round, set, slice, sorted, str, sum, tuple

Writing Queries

Redash builds the result table by inspecting the final state of your script execution for a variable named result.

result is a dictionary with two keys: columns and rows.

• The columns key should expose a list of dictionaries describing the columns to be included in your data set. Each dictionary will include three keys:

  • name
  • type
  • friendly_name

• rows key should expose a list of dictionaries representing each row of data. The keys for each dictionary should match the name keys described in your columns dictionary.

The following data types are supported for columns:

• text
• integer
• float
• boolean
• string
• datetime
• date

An example of returned data appears below:

result = {
  "columns": [
    {
      "name": "date",
      "type": "date",
      "friendly_name": "date"
    },
    {
      "name": "day_number",
      "type": "integer",
      "friendly_name": "day_number"
    },
    {
      "name": "value",
      "type": "integer",
      "friendly_name": "value"
    },
    {
      "name": "total",
      "type": "integer",
      "friendly_name": "total"
    }
  ],
  "rows": [
    {
      "value": 40832,
      "total": 53141,
      "day_number": 0,
      "date": "2014-01-30"
    },
    {
      "value": 27296,
      "total": 53141,
      "day_number": 1,
      "date": "2014-01-30"
    },
    {
      "value": 22982,
      "total": 53141,
      "day_number": 2,
      "date": "2014-01-30"
    }
  ]
}

If you execute the above snippet in Redash it will return this table:

date	day_number	value	total
2014-01-30	0	40832	53141
2014-01-30	1	27296	53141
2014-01-30	2	22982	53141