code: def connect(url=None, schema=None, reflect_metadata=True, engine_kwargs=None,
              reflect_views=True, ensure_schema=True, row_type=row_type):
      
      if url is None:
          url = os.environ.get('DATABASE_URL', 'sqlite://')
  
      return Database(url, schema=schema, reflect_metadata=reflect_metadata,
                      engine_kwargs=engine_kwargs, reflect_views=reflect_views,
                      ensure_schema=ensure_schema, row_type=row_type)
docs: Opens a new connection to a database.
  
      *url* can be any valid `SQLAlchemy engine URL`_.  If *url* is not defined
      it will try to use *DATABASE_URL* from environment variable.  Returns an
      instance of :py:class:`Database <dataset.Database>`. Set *reflect_metadata*
      to False if you don't want the entire database schema to be pre-loaded.
      This significantly speeds up connecting to large databases with lots of
      tables. *reflect_views* can be set to False if you don't want views to be
      loaded.  Additionally, *engine_kwargs* will be directly passed to
      SQLAlchemy, e.g.  set *engine_kwargs={'pool_recycle': 3600}* will avoid `DB
      connection timeout`_. Set *row_type* to an alternate dict-like class to
      change the type of container rows are stored in.::
  
          db = dataset.connect('sqlite:///factbook.db')
  
      .. _SQLAlchemy Engine URL: http://docs.sqlalchemy.org/en/latest/core/engines.html#sqlalchemy.create_engine
      .. _DB connection timeout: http://docs.sqlalchemy.org/en/latest/core/pooling.html#setting-pool-recycle