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License: MIT PyPI package version Downloads

LiteDBC

Lightweight Database Connector

This library is a streamlined wrapper for Python's sqlite3 module, built to provide a user-friendly and thread-safe bridge between Jinbase and SQLite.

Connecting to an embedded database:

from litedbc import LiteDBC

dbc = LiteDBC("/path/to/file.db")

# manually initialize the database with a SQL script
if dbc.is_new:
    with dbc.transaction() as cursor:
        cursor.execute_script("-- <Initialization SQL Script> --")
# ...
dbc.close()
# the line above is optional, as the connection 
# closes automatically when the program exits

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Providing SQL script for automatic initialization:

from litedbc import LiteDBC

INIT_SCRIPT = """BEGIN TRANSACTION;
-- Create the USER table
CREATE TABLE user (
    name TEXT PRIMARY KEY,
    age INTEGER NOT NULL);
COMMIT;"""

with LiteDBC("/path/to/file.db", init_script=INIT_SCRIPT) as dbc:
    pass

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Interacting with a database:

from litedbc import LiteDBC

with LiteDBC("/path/to/file.db") as dbc:
    with dbc.cursor() as cur:
        # execute a SQL statement
        statement = "INSERT INTO user (id, name) VALUES (?, ?)"
        cur.execute(statement, (42, "alex"))  # returns the 'rowcount'
        
        # query data
        cur.execute("SELECT id, name FROM user")
        
        # get the rows iteratively
        for row in cur.fetch():
            print(row)
        
        # execute a SQL script in a single transaction
        cur.executescript("-- SQL Script --")

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Creating a transaction context to run complex logic:

from litedbc import LiteDBC

dbc = LiteDBC("/path/to/file.db")

# creating a transaction context
with dbc.transaction() as cur:  # accepts an optional transaction mode
    # from here, everything will be executed within a single transaction
    cur.execute("SELECT COUNT(*) FROM user")
    for row in cur.fetch():
        if row[0] >= 256:
            cur.execute("DELETE FROM user WHERE id=?", (1,))

dbc.close()

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Miscelleaneous:

from litedbc import LiteDBC

# the constructor also accepts conn_kwargs, on_create_db, on_create_conn
dbc = LiteDBC("/path/to/file.db")  # not filename provided -> in-memory db !

# return a tuple of tables present in the database
tables = dbc.list_tables()

# return a list of ColumnInfo instances that provide rich info
# about each column, such as whether it's a primary key column or not
table_info = dbc.inspect(table)

# export the database as a SQL script
sql_script = dbc.dump(dst=None)

# safely create a backup
dbc.backup("/path/to/file.backup")

# create a new instance of Dbc for the same database file
new_dbc = dbc.copy()

# Note that the Dbc class also exposes these properties:
# .new, .conn, .in_memory, .filename, .conn_kwargs, .closed, .deleted

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Testing and contributing

Feel free to open an issue to report a bug, suggest some changes, show some useful code snippets, or discuss anything related to this project. You can also directly email me.

Setup your development environment

Following are instructions to setup your development environment

# create and activate a virtual environment
python -m venv venv
source venv/bin/activate

# clone the project then change into its directory
git clone https://github.com/pyrustic/litedbc.git
cd litedbc

# install the package locally (editable mode)
pip install -e .

# run tests
python -m tests

# deactivate the virtual environment
deactivate

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Installation

LiteDBC is cross-platform. It is built on Ubuntu and should work on Python 3.8 or newer.

Create and activate a virtual environment

python -m venv venv
source venv/bin/activate

Install for the first time

pip install litedbc

Upgrade the package

pip install litedbc --upgrade --upgrade-strategy eager

Deactivate the virtual environment

deactivate

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About the author

Hello world, I'm Alex, a tech enthusiast ! Feel free to get in touch with me !




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