from typing import Any

from ee.kicad.read_schematic import read_schematic, read_schematics
from ee.kicad.to_bom import to_bom, to_bom_xml
from .model import *
from .._utils import run_filters

__all__ = [
    "Component",
    "ComponentField",
    "Position",
    "read_schematic",
    "read_schematics",
    "Schematic",
    "to_bom",
    "to_bom_xml",
    "to_pandas",
]


def parse_ref(ref):
    m = parse_ref.r.match(ref)
    if not m:
        return
    g = m.groups()
    return g[0], None if g[1] == "?" else int(g[1])


parse_ref.r = re.compile("([^0-9]+)([0-9]+|\?)$")


def to_pandas(obj: Any, **kwarg):
    import pandas

    def to_pandas_schematics(ss: Schematics):
        dfs = [to_pandas_schematic(schematic) for schematic in ss.schematics]

        df = pandas.concat(dfs). \
            sort_values(["ref_type", "ref_num"]). \
            applymap(lambda s: s if isinstance(s, str) else None)

        return df

    def to_pandas_schematic(sch: Schematic):
        # These fields will always be put first.
        special_fields = ["ref", "ref_type", "ref_num", "value", "footprint"]

        def make_dict(c: Component):
            fields = {
                "ref": c.ref,
                "ref_type": c.ref_type,
                "value": c.value,
                "footprint": c.footprint,
            }
            if c.has_ref_num:
                fields["ref_num"] = c.ref_num
            fields.update({f.name: f.value for f in c.fields if f.is_custom})
            return fields

        components = sch.components

        filters = []

        include_pwr = kwarg.get("include_pwr", False)
        if not include_pwr:
            filters.append(lambda c: not c.is_pwr)

        include_flg = kwarg.get("include_flg", False)
        if not include_flg:
            filters.append(lambda c: c.ref_type != "#FLG")

        data = [make_dict(c) for c in components if run_filters(filters, c)]
        columns = set([key for row in data for key in list(row)]) - set(special_fields)
        columns = special_fields + list(columns)

        df = pandas.DataFrame(data=data, columns=columns). \
            set_index("ref"). \
            sort_values(["ref_type", "ref_num"]). \
            applymap(lambda s: s if isinstance(s, str) else None)
        return df

    if isinstance(obj, Schematic):
        return to_pandas_schematic(obj)
    elif isinstance(obj, Schematics):
        return to_pandas_schematics(obj)
    else:
        raise EeException("Unsupported type: {}".format(type(obj)))