mirror of
https://github.com/flobz/psa_car_controller.git
synced 2026-08-22 01:16:14 +00:00
91 lines
3.0 KiB
Python
91 lines
3.0 KiB
Python
from datetime import datetime, timedelta
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import dash_bootstrap_components as dbc
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from dash import html
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from dash.development.base_component import Component
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from pandas import DataFrame
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from pytz import UTC
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def unix_time_millis(date):
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return int(date.timestamp())
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def get_marks_from_start_end(start, end):
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nb_marks = 10
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result = []
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time_delta = int((end - start).total_seconds() / nb_marks)
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current = start
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if time_delta > 0:
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while current <= end:
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result.append(current)
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current += timedelta(seconds=time_delta)
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result[-1] = end
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if time_delta < 3600 * 24:
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if time_delta > 3600:
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date_f = '%x %Hh'
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else:
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date_f = '%x %Hh%M'
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else:
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date_f = '%x'
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marks = {}
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for date in result:
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marks[unix_time_millis(date)] = str(date.strftime(date_f))
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return marks
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return None
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def card_value_div(card_id, unit, value="-"):
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return html.Div([html.Div(value, id=card_id, className="mr-2"), html.Div(unit)],
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className="d-flex flex-row justify-content-center")
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def dash_date_to_datetime(st):
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return datetime.strptime(st, "%Y-%m-%dT%H:%M:%S.000Z").replace(tzinfo=UTC)
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def create_card(card: dict):
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res = []
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for tile, value in card.items():
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rows = value["text"]
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# if isinstance(text, str):
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# text = html.H3(text)
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html_text = []
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for row in rows:
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html_text.append(html.Div(row, className="d-flex flex-row justify-content-center"))
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res.append(html.Div(
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dbc.Card([
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html.H4(tile, className="card-title text-center"),
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dbc.Row([
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dbc.Col(dbc.CardBody(html_text, style={"whiteSpace": "nowrap", "fontSize": "160%"}),
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className="text-center"),
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dbc.Col(dbc.CardImg(src=value.get("src", Component.UNDEFINED), style={"maxHeight": "7rem"}))
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],
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className="align-items-center flex-nowrap")
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], className="h-100 p-2"),
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className="col-sm-12 col-md-6 col-lg-3 py-2"
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))
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return res
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def diff_dashtable(data, data_previous, row_id_name="row_id"):
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df, df_previous = DataFrame(data=data), DataFrame(data_previous)
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for _df in [df, df_previous]:
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assert row_id_name in _df.columns
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_df = _df.set_index(row_id_name)
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mask = df.ne(df_previous)
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df_diff = df[mask].dropna(how="all", axis="columns").dropna(how="all", axis="rows")
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changes = []
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for idx, row in df_diff.iterrows():
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row.dropna(inplace=True)
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for change in row.iteritems():
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changes.append(
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{
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row_id_name: data[idx][row_id_name],
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"column_name": change[0],
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"current_value": change[1],
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"previous_value": df_previous.at[idx, change[0]],
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}
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)
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return changes
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