84 lines
2.7 KiB
Python
84 lines
2.7 KiB
Python
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from datetime import datetime, timedelta
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import json
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import MySQLdb #Version 2.2.4
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import pandas as pd #Version 2.2.2
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import plotly.express as px #Version 5.22.0
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db = MySQLdb.connect(host="localhost",user="root",passwd="admin",db="heiraterei")
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cur = db.cursor()
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cur.execute("SELECT JSON_EXTRACT(header, '$.Date') "
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"FROM extractions "
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"WHERE type='calendar' AND property_id = 200;")
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dateoutput = cur.fetchall()
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cur.execute("SELECT JSON_EXTRACT(body, '$.content.days') "
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"FROM extractions "
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"WHERE type='calendar' AND property_id = 200;")
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output = cur.fetchall()
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db.close()
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#createScrapedate Liste
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ytickVals = list(range(0, 30, 5))
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scrapeDates = []
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#print(dateoutput)
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for row in dateoutput:
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date = datetime.strptime(json.loads(row[0])[0], '%a, %d %b %Y %H:%M:%S %Z').date()
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str = date.strftime('%d/%m/%Y')
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scrapeDates.append(str)
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#minimales und maximales Datum ermitteln
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fullDateList = []
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for row in output:
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tempJson = json.loads(row[0]).keys()
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for key in tempJson:
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#print(key)
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fullDateList.append(datetime.strptime(key, '%Y-%m-%d').date())
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end_dt = max(fullDateList)
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start_dt = min(fullDateList)
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delta = timedelta(days=1)
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HeaderDates = []
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while start_dt <= end_dt:
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HeaderDates.append(start_dt)
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start_dt += delta
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#Create data-Matrix
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data = []
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for row in output:
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tempList = [-1] * len(HeaderDates)
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tempJson = json.loads(row[0])
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for key in tempJson:
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date = datetime.strptime(key, '%Y-%m-%d').date()
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content = tempJson[key]
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index = [i for i, x in enumerate(HeaderDates) if x == date]
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tempList[index[0]] = content
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data.append(tempList)
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#Transform to Dataframe for Plotly
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df = pd.DataFrame(data, columns=HeaderDates)
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#Generate Plotly Diagramm
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colScale = [[0, 'rgb(0, 0, 0)'], [0.33, 'rgb(204, 16, 16)'], [0.66, 'rgb(10, 102, 15)'], [1, 'rgb(17, 184, 26)']]
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fig = px.imshow(df, color_continuous_scale= colScale)
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lines = list(range(0,30,1))
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for i in lines:
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#fig.add_hline(y=i+0.5, line_color="white")
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fig.add_hline(y=i+0.5)
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fig.update_layout(yaxis = dict(tickfont = dict(size=50))),
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fig.update_layout(xaxis = dict(tickfont = dict(size=50)))
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fig.update_layout(xaxis_title="Verfügbarkeitsdaten Mietobjekt", yaxis_title="Scrapingvorgang")
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fig.update_xaxes(title_font_size=100, title_font_weight="bold")
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fig.update_yaxes(title_font_size=100, title_font_weight="bold")
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fig.update_layout(yaxis = dict(tickmode = 'array',tickvals = ytickVals, ticktext = scrapeDates))
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fig.update_xaxes(title_standoff = 80)
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fig.update_yaxes(title_standoff = 80)
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fig.update_layout(xaxis={'side': 'top'})
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fig.show()
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