airflow/contrib/operators/databricks_operator.py
def _deep_string_coerce(content, json_path='json'):
    """
    Coerces content or all values of content if it is a dict to a string. The
    function will throw if content contains non-string or non-numeric types.

    The reason why we have this function is because the ``self.json`` field must be a
    dict with only string values. This is because ``render_template`` will fail
    for numerical values.
    """
    c = _deep_string_coerce
    if isinstance(content, six.string_types):
        return content
    elif isinstance(content, six.integer_types + (float,)):
        # Databricks can tolerate either numeric or string types in the API backend.
        return str(content)
    elif isinstance(content, (list, tuple)):
        return [c(e, '{0}[{1}]'.format(json_path, i)) for i, e in enumerate(content)]
    elif isinstance(content, dict):
        return {k: c(v, '{0}[{1}]'.format(json_path, k))
                for k, v in list(content.items())}
    else:
        param_type = type(content)
        msg = 'Type {0} used for parameter {1} is not a number or a string' \
            .format(param_type, json_path)
        raise AirflowException(msg)
def _deep_string_coerce(content, json_path='json'):
    """
    Coerces content or all values of content if it is a dict to a string. The
    function will throw if content contains non-string or non-numeric types.

    The reason why we have this function is because the ``self.json`` field must be a
    dict with only string values. This is because ``render_template`` will fail
    for numerical values.
    """
    c = _deep_string_coerce
    if isinstance(content, six.string_types):
        return content
    elif isinstance(content, six.integer_types + (float,)):
        # Databricks can tolerate either numeric or string types in the API backend.
        return str(content)
    elif isinstance(content, (list, tuple)):
        return [c(e, '{0}[{1}]'.format(json_path, i)) for i, e in enumerate(content)]
    elif isinstance(content, dict):
        return {k: c(v, '{0}[{1}]'.format(json_path, k))
                for k, v in list(content.items())}
    else:
        param_type = type(content)
        msg = 'Type {0} used for parameter {1} is not a number or a string' \
            .format(param_type, json_path)
        raise AirflowException(msg)
def _deep_string_coerce ( content , json_path = 'json' ) : c = _deep_string_coerce if isinstance ( content , six . string_types ) : return content elif isinstance ( content , six . integer_types + ( float , ) ) : # Databricks can tolerate either numeric or string types in the API backend. return str ( content ) elif isinstance ( content , ( list , tuple ) ) : return [ c ( e , '{0}[{1}]' . format ( json_path , i ) ) for i , e in enumerate ( content ) ] elif isinstance ( content , dict ) : return { k : c ( v , '{0}[{1}]' . format ( json_path , k ) ) for k , v in list ( content . items ( ) ) } else : param_type = type ( content ) msg = 'Type {0} used for parameter {1} is not a number or a string' . format ( param_type , json_path ) raise AirflowException ( msg )
Coerces content or all values of content if it is a dict to a string. The
    function will throw if content contains non-string or non-numeric types.

    The reason why we have this function is because the ``self.json`` field must be a
    dict with only string values. This is because ``render_template`` will fail
    for numerical values.
Coerces content or all values of content if it is a dict to a string . The function will throw if content contains non - string or non - numeric types .