Step by Step Guide to Building a Runkeeper API Integration in Python

Aug 18, 2024 • 5 minute read

Introduction

Hey there, fellow code wrangler! Ready to dive into the world of fitness data? We're about to embark on a journey to integrate the Runkeeper API into your Python project. Whether you're building a fitness dashboard or just curious about your running stats, this guide will get you up and running (pun intended) in no time.

Prerequisites

Before we lace up our coding boots, make sure you've got:

Python 3.x installed (you're a pro, so I'm sure you do)
Your favorite Python environment set up (virtual env, anyone?)
requests and json libraries (pip install them if you haven't)
Runkeeper API credentials (grab them from the Runkeeper developer portal)

Authentication

First things first, let's get that access token:

import requests

def get_access_token(client_id, client_secret, authorization_code):
    url = "https://runkeeper.com/apps/token"
    data = {
        "grant_type": "authorization_code",
        "code": authorization_code,
        "client_id": client_id,
        "client_secret": client_secret,
        "redirect_uri": "YOUR_REDIRECT_URI"
    }
    response = requests.post(url, data=data)
    return response.json()["access_token"]

Pro tip: Store that token securely. You'll need it for every request!

Setting up the API Client

Let's create a sleek API client class:

class RunkeeperAPI:
    BASE_URL = "https://api.runkeeper.com"

    def __init__(self, access_token):
        self.access_token = access_token
        self.headers = {"Authorization": f"Bearer {access_token}"}

    def get(self, endpoint):
        return requests.get(f"{self.BASE_URL}{endpoint}", headers=self.headers)

    def post(self, endpoint, data):
        return requests.post(f"{self.BASE_URL}{endpoint}", headers=self.headers, json=data)

Implementing Core Functionalities

Now for the fun part. Let's fetch some data:

def get_user_profile(api):
    return api.get("/user").json()

def get_activities(api):
    return api.get("/fitnessActivities").json()

def post_activity(api, activity_data):
    return api.post("/fitnessActivities", activity_data)

Data Processing and Analysis

Time to make sense of all those numbers:

import pandas as pd

def analyze_activities(activities):
    df = pd.DataFrame(activities["items"])
    return df.groupby("type").agg({
        "duration": "mean",
        "total_distance": "sum"
    })

Error Handling and Rate Limiting

Let's play nice with the API:

from time import sleep

def api_call_with_retry(func, max_retries=3):
    for attempt in range(max_retries):
        try:
            response = func()
            if response.headers.get("X-RateLimit-Remaining") == "0":
                sleep(int(response.headers.get("X-RateLimit-Reset", 60)))
            return response
        except requests.RequestException:
            if attempt == max_retries - 1:
                raise
            sleep(2 ** attempt)

Testing the Integration

Don't forget to test! Here's a quick example:

import unittest

class TestRunkeeperAPI(unittest.TestCase):
    def setUp(self):
        self.api = RunkeeperAPI("YOUR_ACCESS_TOKEN")

    def test_get_user_profile(self):
        profile = get_user_profile(self.api)
        self.assertIn("name", profile)

if __name__ == "__main__":
    unittest.main()

Best Practices and Optimization

Cache frequently accessed data to reduce API calls
Use async requests for better performance when fetching multiple resources
Keep your access token safe and refresh it when needed

Conclusion

And there you have it! You've just built a solid foundation for your Runkeeper API integration. The possibilities are endless from here – create workout summaries, analyze your progress over time, or even build a custom fitness tracker.

Remember, the key to mastering any API is practice and exploration. So go ahead, run wild with your new Runkeeper integration!

Resources

Happy coding, and may your runs be as smooth as your Python scripts!