A Complete Tutorial: Using RabbitMQ + Celery with Multiple Django Projects

In this post, we’ll walk through how to set up RabbitMQ on one server and run Celery across multiple Django projects, with clean project isolation, scalable architecture, and best practices. ✅ Step 1: Install RabbitMQ (Server A) ➡️ On Ubuntu (Server A): sudo apt update sudo apt install rabbitmq-server -y sudo systemctl enable rabbitmq-server sudo systemctl start rabbitmq-server ➡️ Enable RabbitMQ Management UI: sudo rabbitmq-plugins enable rabbitmq_management Visit: http://server-a-ip:15672 (default guest/guest). ➡️ Create RabbitMQ User: sudo rabbitmqctl add_user admin strongpasswordhere sudo rabbitmqctl set_user_tags admin administrator sudo rabbitmqctl set_permissions -p / admin ".*" ".*" ".*" sudo rabbitmqctl delete_user guest # For security ➡️ Open Ports: 5672 (for Celery workers) 15672 (for admin UI, restricted IPs recommended) ✅ Step 2: Project Structure (Multiple Django Projects Example) /var/www/ ├── project_...
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Differences Between List, Dictionary, and Tuple in Python

In Python, lists, dictionaries, and tuples are all built-in data structures that store collections of items. While they share similarities, each has its distinct characteristics and use cases. This post provides a comprehensive comparison.

Comparison Table

Aspect List Dictionary Tuple
Definition An ordered collection of elements. A collection of key-value pairs. An ordered and immutable collection of elements.
Access Method Index-based access (my_list[0]). Key-based access (my_dict['key']). Index-based access (my_tuple[0]).
Mutability Mutable: Elements can be added, removed, or changed. Mutable (for values): Keys/values can be added, modified, or removed, but keys must be immutable. Immutable: Elements cannot be changed once assigned.
Order Guarantee Maintains the order of elements. Maintains insertion order (Python 3.7+). Maintains the order of elements.
Duplicates Allows duplicate elements. Allows duplicate values but not duplicate keys. Allows duplicate elements.
Heterogeneous Data Can contain elements of different types. Can contain keys and values of different types. Can contain elements of different types.
Syntax Square brackets ([]). Curly braces ({}) with key-value pairs (key: value). Parentheses (()), or without them if clear (e.g., 1, 2).
Use Case Suitable for ordered collections or sequences where position matters. Suitable for key-value lookups or associative arrays where you need quick access by key. Suitable for fixed, ordered collections that should not change.
Memory Efficiency Dynamic arrays; resizing may involve reallocation. Uses hash tables; more memory overhead but fast access. More memory-efficient than lists, as they are fixed and immutable.
Performance Access: O(1); Insertion/Deletion: O(n). Access by key: O(1); Insertion/Deletion: O(1). Access: O(1); No insertion/deletion allowed.
Hashable Not hashable; cannot be used as keys in dictionaries. Keys must be hashable (immutable types like strings, numbers, or tuples). Hashable if it contains only immutable elements; can be used as dictionary keys.
Methods Available Extensive (e.g., append(), extend(), pop()). Extensive (e.g., keys(), values(), items()). Limited (e.g., count(), index()).

Deeper Concepts Interviewers Might Explore

1. Mutability and Immutability

Tuples are immutable, providing data integrity, making them suitable for use as dictionary keys. Lists are mutable, allowing flexibility but affecting performance.

2. Hashability and Usage as Dictionary Keys

Tuples, being immutable, are hashable and stable enough to serve as dictionary keys, while lists are not.

3. Performance and Memory Overheads

Dictionaries use hash tables, offering O(1) access time, while lists may require O(n) time for searching when the index is not known.

4. Use Cases

  • List: Use for ordered collections, such as a sequence of steps.
  • Dictionary: Use for key-value pairs, like user profiles where keys are IDs.
  • Tuple: Use for fixed data, such as coordinates (x, y).

5. Python-Specific Details

Dictionaries maintain insertion order in Python 3.7+, combining the flexibility of key-value pairs with the order guarantee of lists.

Conclusion

Understanding the core differences between lists, dictionaries, and tuples is essential for writing efficient and Pythonic code. Use lists for sequences, dictionaries for associative arrays, and tuples for fixed collections.

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