Serving sensor data as JSON API in Raspberry Pi - Time & Space Complexity

Time Complexity: Serving sensor data as JSON API

O(n)

Understanding Time Complexity

When serving sensor data as a JSON API on a Raspberry Pi, it is important to understand how the time to respond grows as more data or requests come in.

We want to know how the program's work changes when the amount of sensor data or number of requests increases.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

from flask import Flask, jsonify
import random

app = Flask(__name__)

@app.route('/sensor')
def sensor_data():
    data = {"temperature": random.uniform(20, 30), "humidity": random.uniform(30, 50)}
    return jsonify(data)

if __name__ == '__main__':
    app.run(host='0.0.0.0')

This code creates a simple web server that returns current sensor data as JSON when a user visits the /sensor URL.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Generating sensor data and creating JSON response each time the /sensor URL is requested.
• How many times: Once per request, no loops inside the handler.

How Execution Grows With Input

Each request triggers a fixed amount of work: reading sensor values and packaging them into JSON.

Input Size (n)	Approx. Operations
10 requests	About 10 times the fixed work
100 requests	About 100 times the fixed work
1000 requests	About 1000 times the fixed work

Pattern observation: The work grows directly with the number of requests, but each request takes the same small amount of time.

Final Time Complexity

Time Complexity: O(n)

This means the total work grows linearly with the number of requests, but each request is handled quickly and independently.

Common Mistake

[X] Wrong: "The server does a lot more work as more requests come in at the same time."

[OK] Correct: Each request is handled separately and quickly; the server does not do extra work just because many requests exist, it just repeats the same small work for each.

Interview Connect

Understanding how your code handles repeated requests helps you write efficient APIs and shows you can think about performance in real projects.

Self-Check

What if the sensor_data function collected data from 100 sensors instead of 2? How would the time complexity change?

Practice

1.

What is the main purpose of serving sensor data as a JSON API on a Raspberry Pi?

easy

A. To allow other devices to easily access sensor information in a standard format

B. To store sensor data only on the Raspberry Pi without sharing

C. To convert sensor data into images for display

D. To run heavy calculations on sensor data locally

Solution

1. Step 1: Understand JSON API purpose

   A JSON API provides data in a simple, standard format that other devices can read easily.

2. Step 2: Relate to sensor data sharing

   Serving sensor data as JSON means sharing sensor readings so other devices or apps can use them.

3. Final Answer:

   To allow other devices to easily access sensor information in a standard format -> Option A

4. Quick Check:

   JSON API shares sensor data easily [OK]

Hint: JSON API means sharing data in a simple format [OK]

Common Mistakes:

• Thinking JSON API stores data only locally
• Confusing JSON API with image or video output
• Assuming JSON API does heavy local processing

2.

Which of the following is the correct way to import Flask in a Python script on Raspberry Pi?

?

easy

A. import flask

B. import Flask

C. from Flask import flask

D. from flask import Flask

Solution

1. Step 1: Recall Flask import syntax

   The Flask class is imported from the flask module using: from flask import Flask

2. Step 2: Check options for correct case and syntax

   from flask import Flask matches correct syntax and case; others have wrong case or structure.

3. Final Answer:

   from flask import Flask -> Option D

4. Quick Check:

   Correct Flask import uses 'from flask import Flask' [OK]

Hint: Flask class is imported with 'from flask import Flask' [OK]

Common Mistakes:

• Using wrong capitalization like 'import Flask'
• Importing the whole module without accessing Flask class
• Mixing module and class names incorrectly

3.

What will be the output of this Flask route when accessed?

from flask import Flask, jsonify
app = Flask(__name__)

@app.route('/sensor')
def sensor_data():
    data = {'temperature': 22.5, 'humidity': 60}
    return jsonify(data)

# Assume app is running

medium

A. Error: jsonify not defined

B. {temperature: 22.5, humidity: 60}

C. {"temperature": 22.5, "humidity": 60}

D. ['temperature', 22.5, 'humidity', 60]

Solution

1. Step 1: Understand jsonify output

   jsonify converts Python dict to JSON string with keys in quotes and proper JSON format.

2. Step 2: Match output format

   {"temperature": 22.5, "humidity": 60} shows correct JSON string with keys and values properly formatted.

3. Final Answer:

   {"temperature": 22.5, "humidity": 60} -> Option C

4. Quick Check:

   jsonify returns JSON string with quoted keys [OK]

Hint: jsonify outputs JSON with quoted keys and values [OK]

Common Mistakes:

• Forgetting quotes around keys in JSON output
• Confusing Python dict print with JSON string
• Assuming jsonify returns Python list

4.

Identify the error in this Flask code snippet that serves sensor data as JSON:

from flask import Flask, jsonify
app = Flask(__name__)

@app.route('/data')
def data():
    sensor = {'temp': 25}
    return json.dumps(sensor)

app.run()

medium

A. json.dumps is used instead of jsonify

B. Flask app is not created correctly

C. Route decorator syntax is wrong

D. Missing import for Flask

Solution

1. Step 1: Check JSON response method

   Flask expects jsonify to create proper response with correct headers, not json.dumps.

2. Step 2: Identify error cause

   Using json.dumps returns a string without correct content-type, causing client issues.

3. Final Answer:

   json.dumps is used instead of jsonify -> Option A

4. Quick Check:

   Use jsonify, not json.dumps, for Flask JSON responses [OK]

Hint: Use jsonify for Flask JSON responses, not json.dumps [OK]

Common Mistakes:

• Returning json.dumps output directly in Flask
• Not importing jsonify
• Assuming json.dumps sets response headers

5.

You want to serve live temperature sensor data from a Raspberry Pi using Flask. Which approach correctly updates the JSON response with real sensor readings each time the API is called?

from flask import Flask, jsonify
app = Flask(__name__)

def read_temp_sensor():
    # Returns current temperature reading
    return 24.7

@app.route('/temp')
def temp():
    # Fill in here

app.run()

hard

A. temp = 24.7
return jsonify({'temperature': temp})

B. temp = read_temp_sensor()
return jsonify({'temperature': temp})

C. return jsonify({'temperature': read_temp_sensor})

D. return {'temperature': read_temp_sensor()} # Flask auto converts

Solution

1. Step 1: Call sensor function inside route

   We must call read_temp_sensor() to get current value each time the route is accessed.

2. Step 2: Return JSON response with current value

   Assign the value to a variable and pass it to jsonify to return proper JSON response.

3. Final Answer:

   temp = read_temp_sensor() return jsonify({'temperature': temp}) -> Option B

4. Quick Check:

   Call sensor function and jsonify result each request [OK]

Hint: Call sensor function inside route, then jsonify result [OK]

Common Mistakes:

• Returning function object instead of calling it
• Using fixed value instead of live sensor reading
• Returning dict without jsonify in Flask