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Suave Bajaj
Suave Bajaj

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🚀 My First Flask API – Lightweight Monitoring Data Server (with Deep Dive)

#python #flask #api #tutorial

Hey folks! 👋

I recently built my first API using Flask and wanted to share the experience — not just the code, but also how it works, what each part does, and how you can run it yourself. If you're learning Flask or curious about simple data-serving APIs, this might help!

🧠 What This API Does

This Flask API serves precomputed monitoring data for various backend services (like Kafka, RabbitMQ, etc.) using .json files. Here's what it can do:

✅ 1. Returns JSON Files Containing Health Data

  • Data for each service is stored as JSON files in a structured directory.
  • You can query the API with parameters like stackname, service, and time to get specific metrics.
  • Example:

/getdata?stackname=retail&service=kafka&time=20240708

This returns the contents of:

/data-files/retail/kafka_20240708.json

✅ 2. Compares Two Time Periods for the Same Service

  • You can compare a service's performance between two timestamps:

/getdata/comparison?stackname=retail&service=kafka&start_time=20240701&end_time=20240707

This returns:

/data-files/retail/comparisons/kafka_20240701_vs_20240707.json

Useful for catching trends, regressions, or improvements.

✅ 3. Displays a Landing Page with All Available Endpoints

  • Visit the root / to get a helpful summary: 
{ "message": "👋 Welcome to the API!", "available_endpoints": { "/getdata/comparison": "GET with params: stackname, service, start_time, end_time", "/getdata": "GET with params: stackname, service, time" }, "available_services": [ "elasticsearch", "rabbitmq", "pods", "responsetime", "logsearch", "kafka", "database", "asciapp", "consul" ], "status": "running" }
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🔍 Code Walkthrough

app.py

from flask import Flask from datahandler import DataHandler handler = DataHandler() app = Flask(__name__) app.add_url_rule('/getdata/comparison', 'getcomparisondata', handler.get_comparison_data) app.add_url_rule('/getdata', 'stackdata', handler.get_stack_data) app.add_url_rule('/', 'landingpage', handler.get_landing_page) if __name__ == '__main__': app.run(debug=True, port=8080)
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datahandler.py

from flask import request, send_file, abort, Response, json import os BASE_DIR = os.path.dirname(os.path.abspath(__file__)) files_file_path = os.path.abspath(os.path.join(BASE_DIR, "..", "data-files")) config_path = os.path.abspath(os.path.join(BASE_DIR, "..", "config", "data_config.json")) with open(config_path) as f: config = json.load(f) class DataHandler: valid_data_paths = config.get("valid_data_paths", []) def get_comparison_data(self): stackname = request.args.get('stackname') service = request.args.get('service') start_time = request.args.get('start_time') end_time = request.args.get('end_time') file_name = f"{stackname}_{service}_{start_time}_vs_{end_time}.json" path = os.path.join(files_file_path, stackname, "comparisons", file_name) return send_file(path, mimetype='application/json') def get_stack_data(self): stackname = request.args.get('stackname') service = request.args.get('service') time = request.args.get('time') if service in self.valid_data_paths: file_name = f"{stackname}_{service}_{time}.json" path = os.path.join(files_file_path, stackname, file_name) return send_file(path, mimetype='application/json') return abort(400, description="Invalid data type") def get_landing_page(self): data = { "message": "Welcome to the API!", "available_endpoints": { "/getdata/comparison": "GET with params: stackname, service, start_time, end_time", "/getdata": "GET with params: stackname, service, time" }, "available_services": self.valid_data_paths, "status": "running" } return Response(json.dumps(data, indent=2), mimetype='application/json')
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▶️ How to Run It

Install Flask:

pip install flask
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Run the python code

python app.py
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Open your browser and visit or use the POSTMAN tool to get the details

http://localhost:8080/
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💡 What Does Each Line in app.run() Do? 

app.run(debug=True, port=8080)
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Argument What It Does
debug=True Auto-reloads the app on code changes and shows detailed error messages. Great for dev, not for prod.
port=8080 Runs the app on port 8080 instead of the default 5000.
host='0.0.0.0' (optional) Allows access from any IP address (e.g., Docker or public cloud). 
app.run(host='0.0.0.0', port=8080, debug=True)
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🔗 Query Parameters in Flask

You pass arguments like this:

/getdata?stackname=prod&service=pods&time=0708
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And extract them in code:

request.args.get('stackname') request.args.get('service') request.args.get('time')
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You can also give default values:

request.args.get('service', 'default_service')
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🛠️ Lessons I Learned

  • How to use Flask routing and send_file() for static JSON
  • The importance of modular design (datahandler.py)
  • Building an API without needing a full DB
  • Making endpoints self-documenting for easy testing and consumption

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