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Dictionary in Python
- Python Automation and Machine Learning for ICs -
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In Python, a dictionary is a mutable, unordered collection of key-value pairs. It is a data structure that allows us to store and retrieve values based on keys. Dictionaries are sometimes referred to as associative arrays or hash maps in other programming languages. Some key characteristics of dictionaries in Python are: 

  1. Key-Value Pairs: 

    Each element in a dictionary is a key-value pair. The key is a unique identifier, and the corresponding value is associated with that key.

  2.  Unordered: 

    The order of elements in a dictionary is not guaranteed. Starting from Python 3.7, dictionaries maintain the insertion order, meaning the order in which items are added to the dictionary is preserved. In Python 3.6 and earlier versions, dictionaries do not guarantee any specific order. 

  3. Mutable: 

    We can add, modify, and remove key-value pairs in a dictionary after its creation. 

  4. Keys are Unique: 

    Keys in a dictionary must be unique. If we try to add a key that already exists, the new value will overwrite the existing one. Dynamic: Dictionaries can grow or shrink in size as needed. 

Dictionaries are particularly useful in programming when we need to associate a set of values with unique keys. They provide a flexible and efficient way to store, retrieve, and manipulate data in various scenarios. 

Some cases ,where dictionaries are commonly used and why they might be preferred over other data structures like lists, sets, and tuples, are:

  1.  Mapping Keys to Values: 

    Dictionaries are designed for mapping unique keys to corresponding values. This makes them ideal for situations where we need to look up information quickly based on a known key. 

  2. Fast Lookups: 

    Retrieving a value from a dictionary by its key is generally faster than searching for an element in a list. Dictionaries use a hash table internally, allowing for constant-time average complexity for key lookups. 

  3. Data Retrieval by Identifier: 

    When we have a set of items that are uniquely identified by keys, dictionaries provide an efficient way to retrieve and update these items.

    # Example: Storing student 

    grades using student IDs as keys grades = {'123': 85, '456': 92, '789': 78} 

  4. Configurations and Settings: Dictionaries are commonly used to store configuration settings due to their key-value structure, making it easy to represent and access configuration parameters. 

    # Example: Configuration settings 

    config = {'debug_mode': True, 'max_attempts': 3, 'timeout': 10} 

  5. JSON-Like Data: When dealing with data that resembles JSON (JavaScript Object Notation), dictionaries provide a natural way to represent and manipulate hierarchical data structures. 

    # Example: Representing a person's information 

    person = {'name': 'John', 'age': 30, 'address': {'city': 'New York', 'zip': '10001'}}  

  6. Counting and Frequency: Dictionaries are useful for counting occurrences of elements. For example, counting the frequency of words in a text document. 

    # Example: Counting word frequency 

    text = "This is a sample text. Sample text is used for demonstration." 

    word_count = {} 

    for word in text.split(): 

    word_count[word] = word_count.get(word, 0) + 1  

  7. Dynamic Data Storage: Dictionaries allow dynamic addition and removal of key-value pairs, making them suitable for scenarios where the structure of the data can change during the program's execution.

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reliefs: code:          
          Switch from SUNKEN to FLAT after lelft-click
Output:         
          Switch from SUNKEN to FLAT after lelft-click

 

 

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