Complete the code to compress the payload using a common algorithm.
compressed_payload = zlib.[1](original_payload)The compress function reduces the payload size by encoding it efficiently.
Complete the code to encode the payload in a compact binary format.
encoded_payload = cbor2.[1](data)The dumps function converts data into CBOR binary format, which is compact.
Fix the error in the code to correctly remove unnecessary fields from the payload dictionary.
optimized_payload = {k: v for k, v in payload.items() if k != [1]The key must be a string literal, so it needs quotes like 'timestamp'.
Fill both blanks to create a dictionary with keys as sensor IDs in uppercase and values filtered by threshold.
filtered_data = {sensor[1]: value for sensor, value in data.items() if value [2] threshold}Use .upper() to convert keys to uppercase and > to filter values above threshold.
Fill all three blanks to build a dictionary comprehension that includes only keys starting with 'temp' and values less than max_val.
result = {k[1]: v for k, v in readings.items() if k.[2]('temp') and v [3] max_val}Convert keys to lowercase with .lower(), check if they startswith 'temp', and filter values less than max_val.