abarorm

abarorm

	abarorm is a lightweight and easy-to-use Object-Relational Mapping (ORM) library for SQLite and PostgreSQL databases in Python. It provides a simple and intuitive interface for managing database models and interactions.

Features

• Define models using Python classes.
• Automatically handle database schema creation and management.
• Support for basic CRUD (Create, Read, Update, Delete) operations.
• Manage foreign key relationships effortlessly.
• Custom field types with validation and constraints.
• New in v1.0.0: Automatic table creation and updates without needing explicit create_table() calls.
• New in v2.0.0: Added support for PostgreSQL databases.
• New in v2.0.0: Ordering by fields in the all() method.
• New in v3.0.0: Fixed table naming bugs to ensure consistent naming conventions.
• New in v3.0.0: Updated return values for methods to improve clarity and usability.
• New in v3.0.0: Enhanced filter method now supports order_by functionality for result ordering.
• New in v3.2.0: Added __gte and __lte functionality in the filter section.
• New in v4.0.0: Added __repr__, count, and to_dict methods.
• New in v4.2.3: Added first(), last(), exists(), and paginate() methods to the QuerySet class.
• New in v5.0.0: Fix PostgreSQL Bugs and structure.
• New in v5.1.0: Enhanced functionality for better usability for delete and contains methods.
• New in v5.2.0: Introduced bulk_create for efficient batch insertions.

Installation

You can install abarorm from PyPI using pip:

pip install abarorm

For PostgreSQL support, you need to install psycopg2-binary:

pip install psycopg2-binary

Documentation

For detailed documentation, examples, and advanced usage, please visit the official abarorm documentation website.

Database Configuration

Before defining models, you need to set up your database configuration. This involves specifying connection parameters for the database you are using (SQLite and PostgreSQL). Here’s an example of how to configure the database:

# Database configuration
DATABASE_CONFIG = {
    'sqlite': {
        'db_name': 'example.db',  # Name of the SQLite database file
    },
    'postgresql': {
        'host': 'localhost',
        'user': 'hoopad',
        'password': 'db_password',
        'database': 'example_db',  # Ensure this matches everywhere
        'port': 5432,
    }
}

Model Definition

After setting up the database configuration, you can define your models. A model is a representation of a database table. Here’s how to create a model using abarorm:

from abarorm import SQLiteModel, PostgreSQLModel
from abarorm.fields.sqlite import CharField, DateTimeField, ForeignKey
from abarorm.fields import psql

# Define the Category model for SQLite
class Category(SQLiteModel):
    class Meta:
        db_config = DATABASE_CONFIG['sqlite']
        table_name = 'categories'  # Name of the table for storing the Category model data

    title = CharField(max_length=200, null=False)  # Title of the category, must be unique and not null
    create_time = DateTimeField(auto_now=True, auto_now_add=True)  # Automatically set to current datetime
    update_time = DateTimeField(auto_now=True)  # Automatically set to current datetime


# Define the Post model for Postgresql
class Post(PostgreSQLModel):
    class Meta:
        db_config = DATABASE_CONFIG['postgresql']

    title = psql.CharField(max_length=100, null=False)  # Title of the post, must be unique and not null
    create_time = psql.DateTimeField(auto_now=True)  # Automatically set to current datetime
    category = psql.ForeignKey(to=Category)  # Foreign key referring to the Category model

CRUD Operations

Now that you have defined your models, you can perform CRUD operations. Here’s a breakdown of each operation:

Create

To create new records in the database, use the create() method or Bulk Create: bulk_create. For example:

# Create a new category
Category.create(title='Movies')

# Create a new post
category = Category.get(id=1)  # Fetch the category with ID 1
if category:
    Post.create(title='Godfather', category=category.id)  # Create a new post associated with the fetched category

# Bulk Create Post
records = [
    {"title": "Godfather Part II", "category": 1},
    {"title": "Godfather Part III", "category": 1},
]
Post.bulk_create(records)

Read

To read records from the database, use the all() or get() methods:

# Retrieve all posts
all_posts = Post.all()

# Retrieve a specific post by ID
post_data = Post.get(id=1)

Filtering Records

The filter() method allows you to retrieve records based on specified criteria. You can use keyword arguments to filter by field values and sort the results using order_by.

# Filter posts by category ID and order by creation time
filtered_posts = Post.filter(category=category.id, order_by='-create_time')

Advanced Filtering

You can also use special lookup expressions like __gte (greater than or equal to) and __lte (less than or equal to) for more complex queries:

# Retrieve posts created after a specific date
filtered_posts = Post.filter(create_time__gte='2024-01-01 00:00:00')

Update

To update existing records, fetch the record, modify its attributes, and then save it:

if post_data:
    post_data.title = "The Godfather"
    post_data.save()  # Save the updated post data

Or:

Post.update(1, title='Updated Godfather')  # Update the title of the post with ID 1 to 'Updated Godfather'

Delete

To delete a record from the database, use the delete() method:

Post.delete(id=1)  # Delete the post with ID 1
# or Removal based on a sometimes repeated argument
Post.delete(title='Godfather')

Converting to Dictionary, Counting Records, and Other Query Methods

This section covers how to convert records to dictionaries, count records, and use various query methods like first(), last(), exists(), order_by(), paginate(), and contains(). These methods are essential for data manipulation, debugging, and optimizing query performance.

to_dict() Method

The to_dict() method converts a model instance (or a collection of instances) into a dictionary, which is particularly useful for data manipulation and serialization. It makes it easier to work with the data in Python or send it over an API.

Example:

# Retrieve all posts
posts = Post.all()

# Convert the collection of posts to a list of dictionaries
posts_dict = posts.to_dict()
print(posts_dict)
# Output: [{'id': 1, 'title': 'Godfather', 'create_time': '2024-01-01 12:00:00', ...}, {...}]

count Method

The count() method returns the number of records that match the query. It’s an efficient way to find the size of a dataset without retrieving the actual data.

Example:

# Count the number of posts in the database
num_posts = Post.count()
print(num_posts)  # Output: 10 (if there are 10 posts in the database)

The count() method can also be used after applying filters to count specific records:

# Count the number of posts with a specific title
num_posts_with_title = Post.filter(title='Godfather').count()
print(num_posts_with_title)  # Output: 3 (if there are 3 posts with the title 'Godfather')

first(), last(), exists(), order_by(), paginate() and contains()

• first(): Returns the first result or None if no results are present.
• last(): Returns the last result or None if no results are present.
• exists(): Checks if any records exist in the QuerySet.
• paginate(): Handles pagination of results, allowing you to retrieve subsets of data based on page and page size.
• contains(): Performs a case-insensitive search to check if a field contains a specific substring.

Example:

# Check if any posts exist
exists = Post.all().exists()

# Get the first post
first_post = Post.all().first()

# Get the last post
last_post = Post.all().last()

# Paginate the results
paginated_posts = Post.all().paginate(1, 5)  # Page 1, 5 results per page

# Using multiple querysets in one query
posts = Post.all().contains(title='god').order_by('create_time').paginate(1, 4).to_dict()

These methods are particularly useful for data manipulation and debugging, as they provide a simple way to view and interact with your database records.

Contributing

Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request on GitHub.

License

This project is licensed under the Apache-2.0 License - see the LICENSE file for details.

Acknowledgements

• Python: The language used for this project.
• SQLite and Postgresql: The databases supported by this project.
• setuptools: The tool used for packaging and distributing the library.
• psycopg2-binary: The PostgreSQL adapter used for connecting to PostgreSQL databases.