You can access the code for fetching data from an API at this GitHub repository: Link to GitHub Repository

API (Application Programming Interface) serves as a means for software components to communicate with each other.

Fetching Data from API Explanation:

We are trying to retrieve data from the TMDB API for analysis.

Code:

# We use pandas to manipulate data and requests to access data
import pandas as pd
import requests

# Request to get data from the TMDB API for page=1
response = requests.get('https://api.themoviedb.org/3/movie/top_ratedapi_key=8265bd1679663a7ea12ac168da84d2e8&language=en-US&page=1')

# After fetching data from the API, it is converted into a tabular form (dataframe)
temp_df = pd.DataFrame(response.json()['results'][['id', 'title', 'overview', 'release_date', 'popularity', 'vote_average', 'vote_count']])

# To display the first 5 elements
df.head()

df = pd.DataFrame()

df

# It accesses all the data from page=1 to 428
for i in range(1, 429):
    response = requests.get('https://api.themoviedb.org/3/movie/top_rated?api_key=8265bd1679663a7ea12ac168da84d2e8&language=en-US&page={}'.format(i))
    temp_df = pd.DataFrame(response.json()['results'][['id', 'title', 'overview', 'release_date', 'popularity', 'vote_average', 'vote_count']])
    df = df.append(temp_df, ignore_index=True)

# Show the shape of the dataframe
df.shape

# Convert the dataframe into a CSV file
df.to_csv('movies.csv')

This code demonstrates how to fetch data from the TMDB API, format it into a dataframe, and save it as a CSV file for further analysis.

Web Scraping Through API: A Summary

How It Works:
Web scraping through APIs (Application Programming Interfaces) is a method of programmatically extracting data from websites or online services. Unlike traditional web scraping, which involves parsing HTML pages, APIs provide a structured way to access and retrieve data in a more organized and efficient manner.

  1. Access Point: APIs are provided by websites or online platforms as an access point to their data or services. These APIs have predefined endpoints, which are URLs that accept specific requests.
  2. HTTP Requests: To retrieve data through an API, you send HTTP requests to these endpoints. Common HTTP methods used are GET (retrieve data), POST (submit data), PUT (update data), and DELETE (remove data).
  3. Data Format: APIs typically return data in a structured format, commonly in JSON (JavaScript Object Notation) or XML (eXtensible Markup Language). JSON is more popular due to its simplicity and ease of use in programming.
  4. Authentication: Many APIs require authentication using API keys or tokens to ensure security and control access to their data. You often need to include these keys in your API requests.

When to Use It:
Web scraping through APIs is preferable in several scenarios:

  1. Structured Data: When the data you need is available through an API, it’s usually more structured and organized compared to scraping HTML pages.
  2. Real-Time Data: APIs often provide real-time or up-to-date data, making them suitable for applications requiring the latest information.
  3. Legitimate Access: When you have permission to access the data through an API, it’s a legal and ethical way to retrieve information.
  4. Efficiency: APIs are efficient for large-scale data extraction since they are designed for this purpose.

What to Do:
To perform web scraping through APIs:

  1. Identify the API: Find the API that provides the data you need. Review its documentation to understand the available endpoints, request parameters, and authentication requirements.
  2. Compose API Requests: Use a programming language like Python to compose HTTP requests to the API’s endpoints. Include any required headers or authentication tokens.
  3. Parse the Response: Once you receive the API response, parse the data (usually in JSON format) to extract the specific information you’re interested in.
  4. Store or Process Data: Depending on your needs, you can store the extracted data in a database, analyze it, or perform any necessary post-processing.
  5. Respect Rate Limits: Many APIs have rate limits to prevent excessive requests. Ensure you comply with these limits to avoid being blocked.
  6. Error Handling: Implement error handling to deal with potential issues, such as network errors or API changes.

Web scraping through APIs offers a structured and efficient way to access online data for various purposes, including data analysis, research, and integration into applications. It’s essential to understand the API’s documentation and follow best practices to ensure successful data retrieval.

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