Python

Beta features are available to users before official release. Your testing and feedback are an enormous help, please leave any feedback or bug reports you have at [e-mail]. Note that beta features are subject to change.

LogicLoop offers a Python script execution environment to enhance your data analysis capabilities.

Accessing the Python Data Source

For security, the Python data source is disabled by default. To enable it, please reach out to [e-mail]. Once enabled, you can create a Python data source from Settings > Data Sources.

Generating Results in LogicLoop

In LogicLoop, you can build result tables by inspecting the final state of your script execution for a variable named result. This variable should follow a specific format, as demonstrated in the example 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"
    }
  ]
}

When you execute the above snippet in LogicLoop, it will return a table like this:

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

If you require additional Python libraries to support your queries in LogicLoop, please reach out at [e-mail]. We will be happy to assist you in adding the necessary libraries to enhance your scripting capabilities.