Using Python

This book uses Python as its implementation language. Python supports functional, imperative, and object-oriented programming. Plus, it is cross-platform, beginner-friendly, and has many libraries you could use in projects that build on this book. One downside is that Python is quite slow, and for this reason every real web browser is written in C++. For teaching, that isn’t a problem.

This section will feature a quick discussion of installing Python and point to some Python resources for students who aren’t familiar with the language.

Python comes in two major versions: Python 2 and Python 3. All of the examples in this book use Python 3, and if you try to follow along in Python 2 you will get pretty confused. In a few places, I show Python command lines, and when I do I call the Python binary python3. Your system might be different (but probably won’t be).

Debugging Tips

As you’re following along with the text, or implementing exercises, you’ll frequently want to test or debug your web browser. Here are a few tips on doing that.

Testing against browsers: Except where explicitly noted, the web browser developed in this book is intended to match the behavior of real web browsers. That means you can always see the correct behavior by firing up your favorite web browser on the same pages that you’re testing your web browser on. Use this any time you’re unsure what the correct behavior in some situation is. Often there’s no rhyme or reason to what browsers do in some edge case. Looking at the real thing is the best way to find out.

Simple HTTP Server: You’ll frequently want to test your web browser by running it on custom web pages. To do so, you’ll need to start a web server that your browser could connect to. Luckily, Python ships with one. Go to a directory an run:

python3 -m http.server

This will start a web server at the address http://localhost:8000/ serving the contents of index.html in the current directory. You can view other files in the directory as well.

Printable Forms: The Python print function is the most flexible method of debugging, but it relies on things having a printable form. For a custom object, that doesn’t come for free. In Python, you can define the printable form of an object by defining its __repr__ method, like this:

class Tag:
    def __repr__(self):
        return "Tag(" + self.tag + ")"

The book doesn’t show code for these methods, but for your own sanity you should probably implement them for each custom object you define.

Handling Crashes: Crashes in the HTML and CSS parser can be frustrating to debug. Luckily, we don’t end up making many modifications to either component once it’s written. Still, if you find an error in either component, the best way to proceed is to print the state of the parser (the current element and current token for the HTML parser, and the current parsing function and current input position for the CSS parser) at every parsing step, and then walking through the output by hand until you see the mistake. This is a slow but a sure process.

Crashes in the JavaScript component, on the other hand, are fairly frustrating because backtraces that involve both JavaScript and Python frames aren’t supported by DukPy. I recommend wrapping Python registered functions like so to print any backtraces they produce:

    # ...
    import traceback

For JavaScript functions called by Python, you can do the same like this:

try {
    # ...
} catch(e) {

Most other crashes or errors are best fixed starting from the backtrace.