stouputils.io.csv module#

csv_dump(
data: Any,
file: IO[Any] | str | None = None,
delimiter: str = ',',
has_header: bool = True,
index: bool = False,
*args: Any,
**kwargs: Any,
) → str[source]#

Writes data to a CSV file with customizable options and returns the CSV content as a string.

Parameters:

  • data (list[list[Any]] | list[dict[str, Any]] | pd.DataFrame | pl.DataFrame) – The data to write, either a list of lists, list of dicts, pandas DataFrame, or Polars DataFrame

  • file (IO[Any] | str) – The file object or path to dump the data to

  • delimiter (str) – The delimiter to use (default: ‘,’)

  • has_header (bool) – Whether to include headers (default: True, applies to dict and DataFrame data)

  • index (bool) – Whether to include the index (default: False, only applies to pandas DataFrame)

  • *args (Any) – Additional positional arguments to pass to the underlying CSV writer or DataFrame method

  • **kwargs (Any) – Additional keyword arguments to pass to the underlying CSV writer or DataFrame method

Returns:

The CSV content as a string

Return type:

str

Examples

>>> csv_dump([["a", "b", "c"], [1, 2, 3], [4, 5, 6]])
'a,b,c\r\n1,2,3\r\n4,5,6\r\n'

>>> csv_dump([{"name": "Alice", "age": 30}, {"name": "Bob", "age": 25}])
'name,age\r\nAlice,30\r\nBob,25\r\n'
csv_load(
file_path: str,
delimiter: str = ',',
has_header: bool = True,
as_dict: bool = False,
as_dataframe: bool = False,
use_polars: bool = False,
*args: Any,
**kwargs: Any,
) → list[list[str]][source]#
csv_load(
file_path: str,
delimiter: str = ',',
has_header: bool = True,
*,
as_dict: Literal[True],
as_dataframe: bool = False,
use_polars: bool = False,
**kwargs: Any,
) → list[dict[str, str]]
csv_load(
file_path: str,
delimiter: str = ',',
has_header: bool = True,
as_dict: bool = False,
*,
as_dataframe: Literal[True],
use_polars: Literal[False] = False,
**kwargs: Any,
) → pd.DataFrame
csv_load(
file_path: str,
delimiter: str = ',',
has_header: bool = True,
as_dict: bool = False,
*,
as_dataframe: Literal[True],
use_polars: Literal[True],
**kwargs: Any,
) → pl.DataFrame

Load a CSV file from the given path

Parameters:

  • file_path (str) – The path to the CSV file

  • delimiter (str) – The delimiter used in the CSV (default: ‘,’)

  • has_header (bool) – Whether the CSV has a header row (default: True)

  • as_dict (bool) – Whether to return data as list of dicts (default: False)

  • as_dataframe (bool) – Whether to return data as a DataFrame (default: False)

  • use_polars (bool) – Whether to use Polars instead of pandas for DataFrame (default: False, requires polars)

  • *args – Additional positional arguments to pass to the underlying CSV reader or DataFrame method

  • **kwargs – Additional keyword arguments to pass to the underlying CSV reader or DataFrame method

Returns:

The content of the CSV file

Return type:

list[list[str]] | list[dict[str, str]] | pd.DataFrame | pl.DataFrame

Examples

> Assuming "test.csv" contains: a,b,c\n1,2,3\n4,5,6
> csv_load("test.csv")
[['1', '2', '3'], ['4', '5', '6']]

> csv_load("test.csv", as_dict=True)
[{'a': '1', 'b': '2', 'c': '3'}, {'a': '4', 'b': '5', 'c': '6'}]

> csv_load("test.csv", as_dataframe=True)
   a  b  c
0  1  2  3
1  4  5  6

> csv_load("test.csv", as_dataframe=True, use_polars=True)
shape: (2, 3)
┌─────┬─────┬─────┐
│ a   ┆ b   ┆ c   │
│ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ i64 │
╞═════╪═════╪═════╡
│ 1   ┆ 2   ┆ 3   │
│ 4   ┆ 5   ┆ 6   │
└─────┴─────┴─────┘