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Web Scraping is the method of collecting data using an automated script. Whereas, ChatGPT is a robust language model developed by OpenAI. It can quickly generate code for web scraping. In this blog, we will understand how ChatGPT is used to automate web scraping.
IMDb is the best source for information on movies, Tv shows, and several other forms of entertainment. It possesses a chart of the highly-rated movies along with the top 250 movies listed on The IMDb chart, including cast, title, ratings, and director of every movie.
So, we need to extract information via web scraping using Python and a beautiful soup library. Hence, we will use ChatGPT for this purpose.
ChatGPT is a powerful tool that helps us in creating code. Let’s implement the task using the following request:
Web Scrape https://www.imdb.com/chart/top/?ref_=nv_mv_250 with Python and BeautifulSoup.
ChatGPT is a response-specific implementation done step-by-step. The steps to web scrape the IMDb movies chart are as follows.
Although the above result looks good, it gives a complete understanding of the source code's performance. But we want the execution in a single file. So, we will copy and paste. We will ask ChatGPT to provide the Python web scripting in a single file.
“Please provide the code in one file.”
From the below image, you can see that ChatGPT is replying with a complete source code.
The complete Python code generated by Chat GPT is as follows:
To automate web scraping using ChatGPT, we must test whether the source code works as expected. For this, we need to create a new file.
Then, we will copy and paste the code into webscrape.py:
Next, write the following command on the Terminal line to start Python:
The script starts functioning, and a new file, imdb_top_movies.csv, generates after some time. It includes the scraped movie data in CSV format.
From the above result, ChatGPT is working nicely, and we don’t require to adapt the code manually.
If you remember, previously, we requested ChatGPT to extract data without any movie information. Hence, ChatGPT pulls the name and the year of publication. Now, we want to scrape data from IMDb for rating. For this, we will write the following within ChatGPT.
Also retrieve the IMDb rating for each film
After getting the instruction, ChatGPT will provide detailed instructions and code snippets to change the existing code and include and extract the rating information:
Now ask ChatGPT to inculcate these changes into the script:
Please give me the full code in one with, with the try-except block
The ChatGPT will generate the complete Python code again. It includes the changes for extracting additional information from the website:
Conclusion
Thus, ChatGPT is an effective tool for generating scripts for web scraping. By simply feeding essential input to ChatGPT, we obtained a ready-to-run Python script to make the web scraping process easier.
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