How to Read Documentation? - Python Resources

1. Understand the Structure of Documentation¶

Function Name and Syntax:
- The function name, followed by parentheses (()), lists the parameters it can take.
- Example: function(param1, param2="default", *args, **kwargs)
  - param1: Required parameter.
  - param2="default": Optional with a default value.
  - *args: Accepts a variable-length tuple of positional arguments.
  - **kwargs: Accepts a variable-length dictionary of named arguments.
Description:
- Provides a brief explanation of what the function does.
Parameters:
- Lists all the inputs the function accepts:
  - Name: The parameter name.
  - Type: Expected data type (e.g., str, int, list).
  - Description: Purpose or behavior of the parameter.
  - Default Value: (if applicable) Indicates an optional parameter.
Returns:
- Explains what the function outputs (type and description).
Examples (if included):
- Shows how the function is applied in practice.

2. Key Symbols and Conventions¶

Optional Parameters:
- Optional parameters may sometimes be indicated with square brackets ([]) in informal examples.
- Example: function(param1[, param2]) → param2 is optional.
- Official Python documentation does not use this format but instead lists default values explicitly.
Default Values:
- Parameters with default values make the parameter optional.
- Example: param="value" → If no argument is passed, the default value is used.
*args and **kwargs:
- *args: Allows a variable number of positional arguments.
- **kwargs: Allows a variable number of named arguments (key-value pairs).
Placeholders:
- Placeholders like <value> or <required_value> in examples indicate required inputs.
- Note: These are not part of actual Python syntax but used in tutorials or examples.

3. Tips for Reading Documentation¶

Start with the Overview:
- Read the summary to understand the purpose of the function or library.
Focus on Parameters and Returns:
- Identify what inputs the function expects and what it outputs.
Look for Examples:
- Examples, if available, provide insights into how the function is applied.
Check Edge Cases:
- Review limitations or special cases described in the documentation.
Take Note of Data Types:
- Match your inputs with the expected types to avoid errors.

4. Example Walkthrough¶

Documentation for sorted():

def sorted(iterable, *, key=None, reverse=False):
    """
    Return a new sorted list from the elements of an iterable.

    Parameters:
        iterable (list, tuple, etc.): The data to sort.
        key (function, optional): A function to customize the sort order.
        reverse (bool, optional): If True, sorts in descending order (default: False).

    Returns:
        list: A sorted list.
    """

Steps to Read:

Purpose: Sorts an iterable (e.g., a list or tuple) into the desired order.
Parameters:
- iterable: Required; the data to sort.
- key: Optional; a function to customize the sort order.
- reverse: Optional; sorts descending if True.
Return Value: Outputs a new sorted list.
Example Usage:

data = [3, 1, 2]
print(sorted(data))  # [1, 2, 3]
print(sorted(data, reverse=True))  # [3, 2, 1]

None
None

5. Practice¶

Start with small examples to test how a function behaves.
Experiment with variations to understand how parameters influence the outcome.
Combine reading documentation with hands-on coding to solidify understanding.