107 lines
4.3 KiB
Python
107 lines
4.3 KiB
Python
import datetime
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import json
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now = datetime.datetime.now().strftime("%Y-%m-%d")
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def createDateList(start_date, end_date):
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start = datetime.datetime.strptime(start_date, "%Y-%m-%d")
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end = datetime.datetime.strptime(end_date, "%Y-%m-%d")
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# add a day to the end date to include it in the list
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end += datetime.timedelta(days=1)
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# remove a day from the start date to include it in the list
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start -= datetime.timedelta(days=1)
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date_generated = [
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start + datetime.timedelta(days=x) for x in range(0, (end - start).days)
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]
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date_generated = [date.strftime("%Y-%m-%d") for date in date_generated]
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return date_generated
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class Transform:
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"""Takes the raw json data and creates a dictionary containing a dictionary per sensor. The inner dictionary contains the date as x and the number of activations as y.
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"""
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def __init__(self, data_source):
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self.data_source = data_source
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self.data = None
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def load_data(self)->"Transform":
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"""loads the data from the data source and stores it in the data attribute
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Returns:
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self: The instance of the class
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"""
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with open(self.data_source, "r") as file:
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self.data = json.load(file)
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return self
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def transform_data(
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self, addMissing=False, start_date="2024-04-05", end_date=now, split=False
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):
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"""Take the raw data and transform it into a format that can be used by the diagram generator.
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There should be one entry per sensor, where x is represented by date and y is represented by the number of activations. If the activations are equal or less than 1 in the on-state, set the sensor data to 0 for that day
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"""
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sensors = []
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for key, value in self.data.items():
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sensors.append({"id": key, "value": value})
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temp = {}
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s_data = {}
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start_date = start_date
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end_date = end_date
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# create a list of all dates between the start and end date
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all_dates = createDateList(start_date, end_date)
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for sensor in sensors:
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tmp = {}
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sensor_values = {}
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name = sensor["id"]
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sensor_values[name] = sensor["value"]
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tmp[name] = {"x": [], "y": []}
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sensor_data = sensor["value"]
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sensor_dates = list(sensor_data.keys())
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sum_activations = 0
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for date in all_dates:
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if date not in sensor_dates:
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# print("Date not in sensor data", name, date)
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if addMissing:
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tmp[name]["x"].append(date)
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tmp[name]["y"].append(0)
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else:
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on_state = len(sensor_data[date]["on"])
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off_state = len(sensor_data[date]["off"])
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activations = (on_state + off_state) / 2
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if activations == 1:
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activations = 0
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else:
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activations = on_state
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sum_activations += activations
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# add the date to the tmp dictionary as x and the number of activations as y
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tmp[name]["x"].append(date)
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tmp[name]["y"].append(activations)
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# if on_state != off_state:
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# tmp[name]["x"].append(date)
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# tmp[name]["y"].append(activations)
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# else:
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# # add the date to the tmp dictionary as x and the number of activations, divided by two as y
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# tmp[name]["x"].append(date)
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# tmp[name]["y"].append(activations if activations > 1 else 0)
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temp.update(tmp)
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#create new entry in s_data for sensor, add key "total_activations" and the sum of all activations, as well as the usage, which is activation divided by the number of days
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s_data[name] = {"total_activations": sum_activations, "usage": round(sum_activations / 2)}
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return temp, s_data
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if __name__ == "__main__":
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transform = Transform("data.json")
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transform.load_data()
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result = transform.transform_data(True, end_date="2024-04-10", split=True)
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print(result)
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# print(createDateList("2024-01-01", "2024-03-04"))
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