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import streamlit as st
import pandas as pd
import geopandas as gpd
import requests
import json
import time
class DataModel:
def __init__(self,):
self.base_url = "https://infrasense-dashboard-aggregation-service-prod.delta.k8s-wdy.de"
self.crs_dist = 32630
self.crs_ll = 4326
self.sleep = 5
@st.cache_data(show_spinner='Daten werden geladen ...')
def get_data(_self, osm_id, radius=25):
"""
Method for getting and extracting data from backend
:param osm_id: id of the osm shape
:param radius: radius around shape for data selection
"""
# get data from backend
response = requests.get(f"{_self.base_url}/estimateShapeStatsAsync/{osm_id}/{radius}", headers={'X-API-KEY':st.secrets['api_key']})
loading_finished = False
# data is ready for processing
if response.status_code == 200:
loading_finished = True
# data are calculated, wait until finished
elif response.status_code == 202:
response, loading_finished = _self.__waiting_for_calculation(osm_id, radius)
# get error meassage if data loading failed
if not loading_finished:
st.error('Error while data loading')
st.stop()
# extract data from backend
return _self.extract_backend_data(response)
def __waiting_for_calculation(self, osm_id, radius):
"""
Method for asyncron requests for Biqe monitor endpoint
:param node_id: node id for calculation
:param radius: radius around node for more possible data points
:return data_json: json with response data
:return status: status of finished data loading
"""
# proof if data is loaded
time.sleep(self.sleep)
response = self.__check_request(osm_id, radius)
while response.status_code == 202:
time.sleep(self.sleep)
response = self.__check_request(osm_id, radius)
# if finished
if response.status_code == 200:
status = True
else:
status = False
return response, status
def __check_request(self, osm_id, radius):
"""
Method for looking if async calculation of node data is finished
:param node_id: node id for calculation
:param extension_radius: radius around node for more possible data points
:return req: response data from endpoint
"""
url = f'{self.base_url}/task_status/{osm_id}/{radius}/ShapeStats'
return requests.get(url, headers={'X-API-KEY':st.secrets['api_key']})
def extract_backend_data(self, response):
"""
Method for extracting and procrocess the data from backend json
:param response: request response from backend with data
:return df: dataframe with extracted quality data
:return geom: geometry of the shape
"""
# extraced data from response and parse to json
json_data = response.json()
json_data = json.loads(json_data['state'])
# extract geometry element
geom = json.loads(json_data['feature'])
geom = gpd.GeoDataFrame.from_features(geom["features"])
# extract data and set feature
df = pd.DataFrame(json_data['data'])
df['date'] = pd.to_datetime(df['int_date'].astype(str), format='%Y%m%d')
df['weekday'] = df['date'].dt.weekday
df.sort_values(by='date', ignore_index=True, inplace=True)
return df, geom |