The latest articles on DEV Community by Ahmad Azeez (@ahmad_azeez). https://dev.to/ahmad_azeez https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F2525890%2F9bee54ff-2615-42da-a3a0-d3138ce226be.jpg https://dev.to/ahmad_azeez en Ahmad Azeez Wed, 14 May 2025 22:13:35 +0000 https://dev.to/ahmad_azeez/what-are-todays-top-movie-plots-i-wrote-a-python-scraper-to-find-out-2djn https://dev.to/ahmad_azeez/what-are-todays-top-movie-plots-i-wrote-a-python-scraper-to-find-out-2djn <p>The other day, YouTube recommended a trailer for the upcoming Superman movie. Naturally, instead of just watching it and moving on like a normal person, my brain went:<br> “What are the most common plots in today’s top movies?”</p> <p>Yeah…I do not understand how my brain works either.</p> <p>It struck me how many recent blockbusters seem to follow similar themes: superheroes (still going strong, somehow), explosive action flicks, and horror films (which I respectfully avoid because I enjoy sleeping at night). So rather than doing what a reasonable human might do, and just do a simple Google search, I built an entire Python scraper (which, to be honest, was done only because I really wanted to have a data-mining project, but let’s just pretend like it was an attempt at being bold, quirky, and different).</p> <p>My script pulls the current <strong>Top 25 movies</strong> from IMDb (technically <strong>Top 50</strong>, but I was only able to fetch the Top 25, more details in the repo), grabs each one’s plot summary, and then generates a <strong>word cloud</strong> from all that text. The result? A visual answer to the question: “What are audiences being served most often right now, plot-wise?” And as a bonus, I made it work for specific genres too, so you can visualize what “sells” in action, comedy, or even horror (if you're braver than me).</p> <h2> <strong>What I Learned:</strong> </h2> <p>This wasn’t just a fun little project that I worked on, my main goal was to learn a lot of new stuff along the way:</p> <ul> <li>Data cleaning &amp; preprocessing using tools like <strong>NLTK</strong> (stopwords, tokenization)</li> <li>Web scraping with <strong>requests</strong> and <strong>BeautifulSoup</strong> </li> <li>Visualizing data using <strong>WordCloud</strong> and <strong>matplotlib</strong> </li> <li>Handling website structure quirks and anti-bot headers</li> <li>Using <code>time.sleep()</code> to avoid hammering IMDb’s servers (being nice to websites)</li> </ul> <p><strong>Has This Been Done Before?</strong><br> Absolutely.<br> <strong>But was it worth building myself?</strong><br> 100%.<br> Because I didn’t just end up with a cool visual, I walked away with skills that go way beyond this one project. And that’s the power of learning by doing.</p> <p><a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Frmnmmbr51sgu2yoo6639.png" class="article-body-image-wrapper"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Frmnmmbr51sgu2yoo6639.png" alt=" " width="800" height="400"></a></p> <p>As a bonus, it also fetches the most common genres:<br> <a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fnhaxa1povblsydzsq6rq.png" class="article-body-image-wrapper"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fnhaxa1povblsydzsq6rq.png" alt=" " width="800" height="400"></a></p> <p>GitHub repo: <a href="https://github.com/AhmadAzeez999/IMDb-Python-Scraper" rel="noopener noreferrer">https://github.com/AhmadAzeez999/IMDb-Python-Scraper</a></p> python webscraping movies datascience