Dictionary Key-Value Operations: Tips for Adding, Removing, Modifying, and Querying in Python Dictionaries
Python dictionaries are a practical data structure for storing key-value pairs, where keys are immutable and unique types (such as strings, numbers), and values can be of any type. **Add/Modify**: Use `dict[key] = value` for assignment. If the key does not exist, it is added; if it exists, it is modified. **Delete**: `del` removes a specified key; `pop()` deletes and returns the value; `popitem()` (3.7+) deletes the last key-value pair; `clear()` empties the dictionary. **Retrieve**: Prefer `get(key, default)` for safe retrieval (to prevent KeyError); direct key access may cause errors; `keys()`, `values()`, and `items()` can be used to batch retrieve keys, values, and key-value pairs respectively. **Note**: Keys must be immutable and unique (lists cannot be used as keys). Use `get()` for retrieval, and assignment is used for both adding and modifying.
Read MoreBeginner's Guide: Python Dictionaries - Key-Value Pairs and Iteration Techniques
This article introduces Python Dictionaries, which store data as key-value pairs. Keys are unique and immutable types (e.g., strings, numbers), while values can be of any type, similar to an address book. Creation: Use `{}` with key-value pairs like `{"name": "Xiaoming", "age": 18}`. Access: Directly use `dict[key]` (raises an error if the key does not exist); the `get()` method is recommended for safety (returns None or a custom value by default). Modification/Addition: Assign a value; if the key exists, its value is updated; if not, a new key-value pair is added. Deletion: Use `del dict[key]` or `dict.pop(key)`. Iteration: Three methods: `for key in dict` (iterates over keys), `for value in dict.values()` (iterates over values), and `for key, value in dict.items()` (iterates over key-value pairs). Common techniques: Use `in` to check key existence, `len()` to get the length, and `update()` to merge dictionaries (overwriting duplicate keys). Dictionaries are flexible and efficient, ideal for storing relational data. Mastering core operations enables proficient application.
Read More