SQLiteFrame 0.3.1

A lightweight, zero-dependency ORM for SQLite in Python

A lightweight, zero-dependency ORM for SQLite in Python
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About the Project · Getting Started · Basic Usage · Documentation · License

About the Project

SQLiteFrame is an SQLite ORM for python, designed to be as lightweight, intuitive, and simple to use as possible.
It is designed to closely mimic SQL syntax whilst remaining as pythonic as possible to save developers valuable time (and brain cells) when interacting with SQLite databases, by building reusable SQLite query objects using method-chaining, and abstracting away SQLite's connection and cursor system with a single context manager.

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Getting Started

SQLiteFrame is available on PyPI. Simply install the package into your project environment with PIP:

pip install SQLiteFrame

To install specific previous versions, take a look at the version history, locate the version tag (vX.Y.Z), and run:

pip install SQLiteFrame==X.Y.Z

SQLiteFrame has ZERO external dependencies - it uses only the standard library's sqlite3 to execute SQLite commands.

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Basic Usage

Creating a table

To create a table, use the template below. This will automatically run the CreateTable SQLite command for you:

from sqliteframe import Database, table, String, Integer, Boolean
from pathlib import Path


database = Database(Path("<database_path>.db"), output=False)  # When the output parameter is True, the formed SQL query will be outputted into the console as a string every time a query is executed


@table(database)
class TableName:
    primary_key_field = String(primary_key=True)  # The primary key parameter is False by default
    second_column = Integer  # If only the default options are required, no brackets are necessary either
    third_column = Boolean(nullable=True)  # The nullable parameter is False by default
    fourth_column = String(default="This is a default value.")  # You can also opt-in to giving columns default values like this

Managing Connections

Before you can interact with the tables you create, you must first connect to the database:

with database.connection(commit=True)  # When the commit parameter is False, changes to the database will not be committed at the end of the context block
    ...  # Execute any statements while a connection is open

Inserting Data

To insert data into an existing table, use the following query template:

insert_statement = TableName.insert_into({
    TableName.primary_key_field: "PrimaryKey1",
    TableName.second_column: 1_000,
    TableName.third_column: True
})

with database.connection():
    insert_statement.execute()

Fetching / Selecting Data

Fetching / selecting data from an existing table with pre-inserted data is done as below:

select_statement = TableName.select(TableName.second_column, TableName.third_column)
with database.connection():
    select_statement.execute()

Linking Tables (Foreign Keys)

Linking tables can be done with Foreign Keys in SQLiteFrame:

from sqliteframe import Database, table, String, Integer, Boolean, ForeignKey
from pathlib import Path


database = Database(Path("<database_path>.db"), output=False)


@table(database)
class FirstTableName:
    primary_key_field = String(primary_key=True)
    second_column = Integer
    third_column = Boolean(nullable=True)


@table(database)
class SecondTableName:
    primary_key_field = Integer(primary_key=True)
    second_column = Boolean(nullable=True)
    third_column = String
    foreign_key_column = ForeignKey(FirstTableName)  # This column now references the primary key of the FirstTableName entity, and will infer its type

Complex Data Fetching / Selection

To build more complex select queries, you can use join, where, and order by:

from sqliteframe import JoinTypes, OrderTypes


select_statement = FirstTableName.select(SecondTableName.second_column, FirstTableName.third_column).join(
    SecondTableName, SecondTableName.foreign_key_column == FirstTableName.primary_key_field, join_type=JoinTypes.LEFT
).where(
    SecondTableName.third_column == "Criteria"
).order_by(
    FirstTableName.second_column, (OrderTypes.DESCENDING, OrderTypes.NULLS_FIRST)
)
with database.connection():
    select_statement.execute()

Editing Data

To edit pre-inserted data, a set query can be used:

set_statement = FirstTableName.set({
    TableName.second_column: 10_000,
    TableName.third_column: None  # This column is nullable, and so this is acceptable
}).where(
    (Person.primary_key_column == "PrimaryKey1") & (Person.second_column > 500)  # Brackets are ESSENTIAL with complex where clauses, as these statements use bitwise operators, which often have unexpected operator precedence
)
with database.connection():
    set_statement.execute()

NOTE: The where clause can be emitted from this statement, but this would update every record in the target table.

Deleting Data

To delete pre-inserted table data, use the delete_from query:

delete_statement = TableName.delete_from().where(
    (TableName.second_column <= 250)
)
with database.connection():
    delete_statement.execute()

NOTE: The where clause can be emitted from this statement, but this would delete every record in the target table.

Dropping Tables

Dropping tables does not delete the table reference from python - just in the SQL. Tables which others tables depend on / reference cannot be deleted by default to maintain referential integrity. This behaviour can be changed when defining the referencing foreign key column.

To entirely drop (delete) an existing table, use the drop_table statement:

with database.connection():
    SecondTableName.drop_table().execute()  # This entity is dropped first as it depends on the FirstTableName entity
    FirstTableName.drop_table().execute()  # Cannot drop this entity until the SecondTableName entity is dropped

For more examples and specific detail, please refer to the Documentation

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License

Distributed under the MIT License. See LICENSE for more information.

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