SQLiteCls 1.0.0

SQLite API wrapped into a class with automatic DB schema initialisation and PRAGMA execution upon connection

SQLite Class wrapper with auto-initialisation of empty DB and PRAGMAs

SQLiteDb class wrapping the operations from the sqlite3 module, providing better support for the with operator and automatic initialisation of an empty DB upon first creation of the DB and setting of the per-connection pragmas.

Additional wrappers are available as a utility, including extraction of a list of tables, extraction of the list of columns of a SELECT query, commit, rollback, start of a transaction, check if the DB is in memory and if it's empty. Executions of SQL script files is also made easy.

Example usage

import sqlitecls

with sqlitecls.SqliteDb('mydata.db', 'mydbschema.sql', 'mypragmas.sql') as db:
    # Now the DB connection is established. If the DB did not exist before,
    # its schema is initialised by running the 'mydbschema.sql' script,
    # preparing it for whatever your application has to do.
    #
    # The 'mypragmas.sql' script is also run EVERY time a connection is
    # opened or re-opened, to ensure each connection to the same file has
    # the correct per-connection PRAGMA settings.
    # For example, imagine we have `PRAGMA synchronous = 3;` in the script
    assert db.pragma('synchronous') == 3

    # You can easily check which tables are available
    tables = db.tables_names()
    # and what columns they have
    columns = db.columns_names('some_table')
    # Otherwise use as any other DB API from now on
    cursor = db.execute('SELECT * FROM mytable')
    # Simplified extraction of the column names from the SELECT query
    columns = sqlitecls.cursor_column_names(cursor)
    # Use as any other DB API from now on
    for row in cursor:
        pass  # Do something with each row
    db.connection, db.cursor  # Accessible for custom operations
    # More utility functions!
    db.start_transaction()
    db.commit()
    db.rollback()
    db.vacuum()
    db.size_bytes()
    db.is_in_memory()
    # Have existing SQL script files? Just run them as they are!
    db.execute_sql_file('myotherfile.sql')  # Load WHOLE file in memory
# Connection automatically closed now

Installation

pip install SQLteCls

or just include the sqlitecls.py file in your project (copy-paste). It's self-contained and has no dependencies other than the standard Python library.