`datestartswith` requires stringified date instead of just a date

I’d like to write {Date received} datestartswith 2015 but instead I have to write {Date received} datestartswith "2015"

Example:

import dash
from dash.dependencies import Input, Output
import dash_html_components as html
import dash_core_components as dcc
from dash_table import DataTable
import json
import pandas as pd
import textwrap


url = ("https://github.com/plotly/datasets/raw/master/"
       "26k-consumer-complaints.csv")

types = {
    'id': 'numeric',
    'ZIP code': 'text',
    'Date received': 'datetime',
    'Date sent to company': 'datetime',
}

df = pd.read_csv(url)
df['id'] = df['Unnamed: 0']
df = df.drop(['Unnamed: 0'], axis=1)
df = df.reindex(columns=['id']+df.columns[:-1].tolist())

app = dash.Dash(__name__)
app.scripts.config.serve_locally = True

app.layout = ddk.App([

    dcc.Textarea(
        id='filter-input',
        style={'width': '100%', 'height': '150px'},
        value='{id} > 5'
        # value=textwrap.dedent(
        # '''
        # {id} > 100 and
        # ({State} = TX or {State} = NJ) and
        # {Date received} = {Date sent to company} and
        # {Product} contains Debt and
        # {Date received} datestartswith "2015-02"
        # ''')
    ),

    dcc.RadioItems(
        id='output-type',
        options=[
            {'label': i, 'value': i} for i in ['Filter', 'Highlight']
        ],
        value='Highlight'
    ),

    html.Div(
        children=DataTable(
            id='demo-table',
            data=df.to_dict('rows'),
            columns=[{ 'id': i, 'name': i, 'type': types.get(i, 'any') } for i in df.columns],
            filtering=True,
            pagination_mode=False,
            virtualization=True,
            style_data={
                'width': '200px'
            },
            style_table={
                'height': 'calc(100vh - 200px)'
            }
        ),
    )
])

@app.callback(
    [Output('demo-table', 'filter'),
     Output('demo-table', 'style_data_conditional')],
    [Input('output-type', 'value'),
     Input('filter-input', 'value')])
def update_filter(output_type, value):
    value = value.strip()

    if output_type == 'Filter':
        return [value, []]
    else:
        return ['', [{
            'if': {
                'filter': value,
            },
            'backgroundColor': 'hotpink'
        }]]



if __name__ == "__main__":
    app.run_server(port=8080, debug=True)

[chriddyp]

Right yeah, {temperature} * 9 / 5 - 32 > 0 or w/e

[alexcjohnson]

Not so useful in that exact case (arithmetic with literals) but if one part of the expression is a field you could do lots of cool things