Tag: RST

Converting a Python data into a ReStructured Text table

This probably exist but I couldn’t find it. I wanted to export a bunch of data from a Python/Django application into something a non-coder could understand. The data was not going to be a plain CSV, but a document, with various tables and explanations of what each table is. Because ReStructured Text seems to be the winning format in the Python world I decided to go with that.

Generating the text part was easy and straightforward. The question was how to export tables. I decided to represent tables as lists of dicts and thus, I ended up building this little module:

def dict_to_rst_table(data):
    field_names, column_widths = _get_fields(data)
    with StringIO() as output:
        output.write(_generate_header(field_names, column_widths))
        for row in data:
            output.write(_generate_row(row, field_names, column_widths))
        return output.getvalue()


def _generate_header(field_names, column_widths):
    with StringIO() as output:
        for field_name in field_names:
            output.write(f"+-{'-' * column_widths[field_name]}-")
        output.write("+\n")
        for field_name in field_names:
            output.write(
                f"| {field_name} {' ' * (column_widths[field_name] - len(field_name))}"
            )
        output.write("|\n")
        for field_name in field_names:
            output.write(f"+={'=' * column_widths[field_name]}=")
        output.write("+\n")
        return output.getvalue()


def _generate_row(row, field_names, column_widths):
    with StringIO() as output:
        for field_name in field_names:
            output.write(
                f"| {row[field_name]}{' ' * (column_widths[field_name] - len(str(row[field_name])))} "
            )
        output.write("|\n")
        for field_name in field_names:
            output.write(f"+-{'-' * column_widths[field_name]}-")
        output.write("+\n")
        return output.getvalue()


def _get_fields(data):
    field_names = []
    column_widths = defaultdict(lambda: 0)
    for row in data:
        for field_name in row:
            if field_name not in field_names:
                field_names.append(field_name)
            column_widths[field_name] = max(
                column_widths[field_name], len(field_name), len(str(row[field_name]))
            )
return field_names, column_widths

It’s straightforward and simple. It currently cannot deal very well with cases in which dicts have different set of columns.

Should this be turned into a reusable library?

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