semvec/pypi-packages huggingface dataset:
SQLiteCls 1.0.0
SQLite API wrapped into a class with automatic DB schema initialisation and PRAGMA execution upon connection
License: BSD
Requires Python: >=3
Keywords: sqlite,sqlite3,database,wrapper,class,with

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
----------------------------------------

```python
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.