Abstract Syntax Trees in Python

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Well, it’s basically a tree-like representation of your code. It shows how each line breaks down into smaller parts and helps you understand how Python interprets your commands. Think of it as a map that tells you where all the cool stuff in your program is hiding!

Now Let’s get cracking with some examples, alright?

Example #1: Simple AST for “print(‘hello world’)”

# This script is an example of a simple Abstract Syntax Tree (AST) for the command "print('hello world')"

# Import the necessary module for creating an AST
import ast

# Create a Module node with a body attribute
module = ast.Module(body=[])

# Create an Expr node with a value attribute
expr = ast.Expr(value=None)

# Create a Call node with a func attribute and an empty list for keywords
call = ast.Call(func=None, args=[], keywords=[])

# Create a Name node with an id attribute and a ctx attribute set to Store
name = ast.Name(id='print', ctx=ast.Store())

# Add the Name node as the func attribute of the Call node
call.func = name

# Create a Str node with s, encoding, and errors attributes
string = ast.Str(s="hello world", encoding=None, errors="strict")

# Add the Str node as an argument to the Call node
call.args.append(string)

# Add the Call node as the value attribute of the Expr node
expr.value = call

# Add the Expr node as an element of the body attribute of the Module node
module.body.append(expr)

# Print the final AST
print(module)

# Output: Module(body=[Expr(value=Call(func=Name(id='print', ctx=Store()), args=[Str(s='hello world', encoding=None, errors='strict')], keywords=[]))])

# Explanation:
# - The ast module is imported to allow for the creation of AST nodes.
# - The Module node is created with an empty body attribute.
# - The Expr node is created with a value attribute set to None.
# - The Call node is created with a func attribute set to None and an empty list for keywords.
# - The Name node is created with an id attribute set to 'print' and a ctx attribute set to Store.
# - The Name node is added as the func attribute of the Call node.
# - The Str node is created with s, encoding, and errors attributes.
# - The Str node is added as an argument to the Call node.
# - The Call node is added as the value attribute of the Expr node.
# - The Expr node is added as an element of the body attribute of the Module node.
# - The final AST is printed, showing the structure of the AST for the command "print('hello world')".

Wow, that’s a mouthful! But don’t worry, let me break it down for you.

– `Module`: This represents the entire program (in this case, just one line).
– `body`: The body of the module is where all the action happens. In our example, we have an expression inside a list that makes up the body.
– `Expr(value=Call(func=Name(id=’print’, ctx=Store()), args=[Str(s=”hello world”, encoding=None, errors=”strict”)], keywords=[]))`: This is where things get interesting! Let’s break it down further:
`Call(func=Name(id=’print’, ctx=Store()), …)`: The `Call()` function represents a call to the built-in Python function called “print”. The `Name(id=’print’, ctx=Store())` part is where we specify that this is the print function.
`args=[Str(s=”hello world”, encoding=None, errors=”strict”)], keywords=[]`: This represents the arguments passed to the print function. In our case, it’s a string with the value “hello world”. The `encoding`, `errors`, and other keyword arguments are optional and not shown here for simplicity.
`value`: This is where we wrap everything up by assigning the entire expression as the value of the module body.

Example #2: AST for a function definition with multiple lines

# This script defines a function called "my_function" that takes in a parameter "x" and returns the value of "x" multiplied by 2.

def my_function(x): # Defines the function "my_function" with a parameter "x"
    y = x * 2 # Assigns the value of "x" multiplied by 2 to the variable "y"
    return y # Returns the value of "y" as the output of the function

Here’s what that looks like in AST form:

# This is a function definition with the name "my_function"
def my_function(x): # "x" is the argument passed into the function
    # This is a statement that assigns the result of the multiplication of "x" by 2 to the variable "y"
    y = x * 2
    # This is an expression that returns the value of "y"
    return y # "y" is the output of the function

# This is a decorator list, which is empty in this case
@decorator_list=[]

# This is a type comment, which is also empty in this case
@type_comment=None

Wow, that’s a lot of code! But don’t worry, let me break it down for you.

– `Module`: This represents the entire program (in this case, just one function).
– `body`: The body of the module is where all the action happens. In our example, we have a function inside a list that makes up the body.
– `FunctionDef(name=’my_function’, …)`: This represents the definition of our function called “my_function”. Let’s break it down further:
`args=arguments(…)`: Here we specify the arguments for our function, including their names and types (if any). In this case, we have one argument named “x” with no type annotation.
`body=stmt(…)`: This represents the body of our function, which consists of multiple statements. Let’s break it down further:
`Assign(targets=[Name(id=’y’, ctx=Store())], value=BinOp(left=Name(id=’x’, ctx=Load()), op=Mult(), right=Constant(value=2, kind=None)))`: This assigns the result of multiplying “x” by 2 to a variable called “y”.
`Expr(value=Return(value=Name(id=’y’, ctx=Load())))`: This returns the value stored in “y”, which is the final output of our function.
– `decorator_list=[], type_comment=None`: These are optional decorators and comments that can be added to a function definition, but we won’t cover them here for simplicity.

I hope this guide has helped you understand Abstract Syntax Trees in Python! Remember, they may seem overwhelming at first, but once you get the hang of it, they can provide valuable insights into how your code is interpreted by Python.

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