Python Input and Output: A Practical Tutorial on print() and input() Functions
This article introduces basic input and output operations in Python, with the core being the `print()` and `input()` functions. The `print()` function is used to output content, supporting text, numbers, variables, or expressions. It allows customizing the separator (e.g., using `-` to separate elements) via the `sep` parameter and controlling the ending (default is a newline; setting it to an empty string enables multi-line content to be printed on the same line) through the `end` parameter. The `input()` function retrieves user input and returns it as a string, which needs to be converted to numeric types (e.g., `int()`/`float()`) for numerical operations. For multiple inputs, the `split()` method can be used to separate values by spaces or commas, etc. Taking a "Personal Information Collection Program" as an example, the article demonstrates combining these functions: obtaining name, age, and height, outputting formatted information, and calculating next year's age and height. The summary emphasizes that `print()` enables flexible output, `input()` requires type conversion, `f-strings` facilitate convenient variable and expression concatenation, and proficiency can be achieved through more practice.
Read MoreFunction Definition and Call: How to Create Your First Function in Python?
Functions are a core tool for code reuse in Python, designed to solve the problem of repetitive code. By "packaging" functional modules, they save time and ensure consistency. The definition syntax uses the `def` keyword, including the function name, parameters (to receive external data), an indented function body, and `return` (to return a result, defaulting to `None`). When calling, parameters must be passed (either positional or keyword arguments), and the return value should be received. Key points to note include indentation requirements, parameter quantity matching, and unique function names. Mastering the basics of functions (parameters, return values) is crucial for advanced usage, as they allow breaking down complex logic and improving code simplicity and maintainability.
Read MoreMust-Know for Beginners: A Detailed Explanation of Python Data Types (Integers, Strings, Booleans)
This article introduces Python's basic data types, using the analogy of "data boxes" with labels to help understand the operations of different data. There are three core types: 1. **Integer (int)**: Handles numbers (positive/negative/0), supporting addition, subtraction, multiplication, division, modulo operation (%), and integer division (//). It can be converted using int() (e.g., converting a string to an integer) and has no size limit. 2. **String (str)**: Text enclosed in quotes (single/double quotes, requiring matching pairs), supporting concatenation (+), length calculation (len()), and indexing (0-based). It can be converted using str() (e.g., converting an integer to a string). 3. **Boolean (bool)**: Only True/False, used for logical judgments, and supports the not operator for negation (e.g., in conditional statements). These three types are fundamental to programming. Subsequent learning will involve complex types like lists and dictionaries, making basic data types a crucial prerequisite.
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