蒐集極簡遞增資料

使用 Python 分析 IoT 資料

Matthias Voppichler

IT Developer

什麼是快取？

資料儲存

完成資料流蒐集後
一筆一筆寫入
- 對磁碟造成高負載
使用快取

快取

cache = []

def on_message(client, userdata, message):
    data = json.loads(message.payload)
    cache.append(data)

    if len(cache) > MAX_CACHE:

        with Path("data.txt").open("a") as f:
            f.writelines(cache)
        cache.clear()

# Connect function to mqtt datastream
subscribe.callback(on_message, 
                   topics="datacamp/energy", 
                   hostname=MQTT_HOST)

簡易資料流

C331,6020
M640,104
C331,6129
M640,180
C331,6205
M640,256

觀測時間戳

「payload 內的 timestamp」
message.timestamp
datetime.now()

觀測時間戳

def on_message(client, userdata, message):
    publishtime = message.timestamp

    consume_time = datetime.utcnow()

pd.to_datetime()

print(df.head())

   timestamp         device  val
0  1540535443083       C331  347069.305500
1  1540535460858       C331  347069.381205

import pandas as pd
df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms")

  timestamp                  device  val
0 2018-10-26 06:30:43.083      C331  347069.305500
1 2018-10-26 06:31:00.858      C331  347069.381205

一起來練習吧！

使用 Python 分析 IoT 資料