Automating Crypto Website API Pull Using Python

A Python script that automates cryptocurrency price data extraction from CoinMarketCap API, stores it in a CSV file, and continuously updates the data at regular intervals.

Overview

This project fetches real-time cryptocurrency data using the CoinMarketCap API. It retrieves the latest listings, normalizes the data into a structured format using pandas, and saves it into a CSV file for further analysis. The script runs in a loop, appending new data at fixed time intervals.

Features

• Uses CoinMarketCap API to fetch real-time cryptocurrency prices.
• Extracts and normalizes data into a pandas DataFrame.
• Saves data to a CSV file and appends new data at regular intervals.
• Handles API connection errors gracefully.
• Automates data collection for further analysis.

Technologies Used

• Python
• Requests (for API calls)
• Pandas (for data manipulation)
• JSON (for parsing API response)
• OS (for file handling)
• Time (for scheduling requests)

Installation & Setup

Prerequisites

Ensure you have the following installed:

• Python 3.x
• pip (Python package manager)

Installation Steps

1. Clone this repository:

   git clone https://github.com/yourusername/Automating-Crypto-API.git
   cd Automating-Crypto-API

2. Install dependencies:

   pip install requests pandas

3. Obtain a CoinMarketCap API key from CoinMarketCap Developer Portal.

4. Replace 'X-CMC_PRO_API_KEY' with your actual API key in the script.

Usage

Run the script to start collecting data:

python crypto_api_runner.py

The script will continuously fetch and store cryptocurrency data every 60 seconds.

Code Explanation

API Request & Data Processing

from requests import Request, Session
from requests.exceptions import ConnectionError, Timeout, TooManyRedirects
import json
import pandas as pd

url = 'https://pro-api.coinmarketcap.com/v1/cryptocurrency/listings/latest'
parameters = {
    'start': '1',
    'limit': '15',
    'convert': 'USD'
}
headers = {
    'Accepts': 'application/json',
    'X-CMC_PRO_API_KEY': 'your_api_key_here',
}

session = Session()
session.headers.update(headers)

try:
    response = session.get(url, params=parameters)
    data = json.loads(response.text)
except (ConnectionError, Timeout, TooManyRedirects) as e:
    print(e)

df = pd.json_normalize(data['data'])
df['timestamp'] = pd.to_datetime('now')

• Establishes a session with the API.
• Retrieves and processes cryptocurrency data.
• Converts JSON response into a pandas DataFrame.

Automating API Calls & Data Storage

import os
from time import sleep

def api_runner():
    global df
    try:
        response = session.get(url, params=parameters)
        data = json.loads(response.text)
        df = pd.json_normalize(data['data'])
        df['timestamp'] = pd.to_datetime('now')

        # Save to CSV
        file_path = r'C:\Users\HP\Desktop\API Script\API.csv'
        if not os.path.isfile(file_path):
            df.to_csv(file_path, header=True)
        else:
            df.to_csv(file_path, mode='a', header=False)
    except Exception as e:
        print(e)

for i in range(333):
    api_runner()
    print('API Runner completed')
    sleep(60)  # Fetch data every 1 minute

• Calls the API every 60 seconds to fetch new data.
• Stores data in a CSV file, appending new records.
• Runs for 333 iterations (~5.5 hours of continuous data collection).