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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 suppo[email protected]. Note that beta features are subject to change.
LogicLoop offers a Python script execution environment to enhance your data analysis capabilities.
For security, the Python data source is disabled by default. To enable it, please reach out to [email protected]. Once enabled, you can create a Python data source from Settings > Data Sources.
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 [email protected]. We will be happy to assist you in adding the necessary libraries to enhance your scripting capabilities.
Last modified 2mo ago