dtale fastapi integration

[jv1522]

Is it possible to integrate dtale with fastapi and send the filters applied on UI back to the API to persist the filters?

[aschonfeld]

@jv1522 I can look into how hard it will be to convert the non-HTML based endpoints over to FastAPI. It will have to be customized to a point in order to support Python2.

You can currently save filters by hitting the following endpoints this way (this is to filter a string column on a set of values):

import requests
import json

requests.get(
  'http://<dtale_host>:<dtale_port>/dtale/save-column-filter/<dtale_data_id>',
  params={
    'col': '<column_name>',
    'cfg': json.dumps({'type': 'string', 'value': ['b']})
  }
)

To drop this filter you would do the following (the column name would need to match the one used above):

import requests

requests.get(
  'http://<dtale_host>:<dtale_port>/dtale/save-column-filter/<dtale_data_id>',
  params={'col': '<column_name>', 'cfg': None}
)

Here are some sample filter configs for different types of columns:

{"type": "string", "value": ["False"]}  # boolean column equal to False
{"type": "int", "missing": True}. # integer column whose values are NaN
{"type": "float", "missing": True}  # float column whose values are NaN
{"type": "date", "missing": True}  # date column whose values are NaN
{"type": "string", "missing": True}  # string column whose values are NaN

# all these integer filters also apply for float columns as well
{"type": "int", "operand": "=", "value": "5"}  # integer column with values equal to 5 (operands are "=", "<", ">", "<=", ">=", "ne")
{"type": "int", "operand": "=", "value": ["5", "4"]}  # integer column with values equal to 5 or 4
{"type": "int", "operand": "ne", "value": ["5", "4"]}  # integer column with values NOT equal to 5 or 4
{"type": "int", "operand": "[]", "min": "4", "max": "5"}  # integer column >= 4 and <= 5
{"type": "int", "operand": "()", "min": "4", "max": "5"}  # integer column > 4 and < 5
{"type": "int", "operand": "()", "min": "4", "max": None}  # integer column > 4

{"type": "date", "start": "20000101", "end": "20000101"}  # date column equal to 2000-01-01
{"type": "date", "start": "20000101", "end": "20000102"}  # date column between 2000-01-01 and 2000-01-02

{"type": "string", "action": "equals", "operand": "=", "value": ["a", "b"]}  # string column equal to 'a' or 'b'
{"type": "string", "action": "equals", "operand": "ne", "value": ["a", "b"]}  # string column NOT equal to 'a' or 'b'
{"type": "string", "action": "equals", "operand": "=", "value": ["a", "b"], "caseSensitive": True}  # string column equal to 'a' or 'b' w/ case-sensitivity on (this is turned off by default)
{"type": "string", "action": "startswith", "raw": "a"}  # string column starting with 'a' (can be used w/ case-sensitivity)
{"type": "string", "action": "endswith", "raw": "a"}  # string column ending with 'a' (can be used w/ case-sensitivity)
{"type": "string", "action": "contains", "raw": "a"}  # string column containing 'a' (can be used w/ case-sensitivity)
{"type": "string", "action": "regex", "raw": "a"}  # string column filtered by regex 'a' (can be used w/ case-sensitivity)
{"type": "string", "action": "length", "raw": "1,3"}  # string column with values of lengths between 1 and 3 (inclusive)

Hope this gives you enough to get started