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"""
Generate 'Supported pandas APIs' documentation file
"""
import warnings
from enum import Enum, unique
from inspect import getmembers, isclass, isfunction, signature
from typing import Any, Dict, List, NamedTuple, Set, TextIO, Tuple
from types import FunctionType

import pyspark.pandas as ps
import pyspark.pandas.groupby as psg
import pyspark.pandas.window as psw
import pandas as pd
import pandas.core.groupby as pdg
import pandas.core.window as pdw

from pyspark.loose_version import LooseVersion
from pyspark.pandas.exceptions import PandasNotImplementedError

# Constants
MAX_MISSING_PARAMS_SIZE = 5
COMMON_PARAMETER_SET = {"kwargs", "args", "cls"}
MODULE_GROUP_MATCH = [(pd, ps), (pdw, psw), (pdg, psg)]
PANDAS_LATEST_VERSION = "2.3.3"

RST_HEADER = """
=====================
Supported pandas API
=====================

.. currentmodule:: pyspark.pandas

The following table shows the pandas APIs that implemented or non-implemented from pandas API on
Spark. Some pandas API do not implement full parameters, so the third column shows missing
parameters for each API.

* 'Y' in the second column means it's implemented including its whole parameter.
* 'N' means it's not implemented yet.
* 'P' means it's partially implemented with the missing of some parameters.

All API in the list below computes the data with distributed execution except the ones that require
the local execution by design. For example, `DataFrame.to_numpy() <https://spark.apache.org/docs/
latest/api/python/reference/pyspark.pandas/api/pyspark.pandas.DataFrame.to_numpy.html>`__
requires to collect the data to the driver side.

If there is non-implemented pandas API or parameter you want, you can create an `Apache Spark
JIRA <https://issues.apache.org/jira/projects/SPARK/summary>`__ to request or to contribute by
your own.

The API list is updated based on the `latest pandas official API reference
<https://pandas.pydata.org/docs/reference/index.html#>`__.

"""


@unique
class Implemented(Enum):
    """
    Enumeration of implementation statuses.
    """

    IMPLEMENTED = "Y"
    NOT_IMPLEMENTED = "N"
    PARTIALLY_IMPLEMENTED = "P"


class SupportedStatus(NamedTuple):
    """
    Defines a supported status for specific pandas API.
    """

    implemented: str
    missing: str


def generate_supported_api(output_rst_file_path: str) -> None:
    """
    Generate the supported APIs status dictionary and write it to an RST file.

    Parameters
    ----------
    output_rst_file_path : str
        The path to the document file in RST format.
    """
    _check_pandas_version()
    all_supported_status = _collect_supported_status()
    _write_rst(output_rst_file_path, all_supported_status)


def _check_pandas_version() -> None:
    """
    Check if the installed pandas version matches the expected version.
    """
    # Work around pandas version string issue,
    # see https://github.com/pandas-dev/pandas/issues/61579.
    if LooseVersion(pd.__version__.split("+")[0]) != LooseVersion(PANDAS_LATEST_VERSION):
        msg = (
            f"Warning: pandas {PANDAS_LATEST_VERSION} is required; your version is {pd.__version__}"
        )
        warnings.warn(msg, UserWarning)
        raise ImportError(msg)


def _collect_supported_status() -> Dict[Tuple[str, str], Dict[str, SupportedStatus]]:
    """
    Collect the supported status across multiple module paths.
    """
    all_supported_status: Dict[Tuple[str, str], Dict[str, SupportedStatus]] = {}
    for pd_module_group, ps_module_group in MODULE_GROUP_MATCH:
        pd_modules = _get_pd_modules(pd_module_group)
        _update_all_supported_status(
            all_supported_status, pd_modules, pd_module_group, ps_module_group
        )
    return all_supported_status


def _get_pd_modules(pd_module_group: Any) -> List[str]:
    """
    Get sorted list of pandas member names from a pandas module.

    Parameters
    ----------
    pd_module_group : Any
        Importable pandas module.

    Returns
    -------
    List[str]
        Sorted list of member names.
    """
    return sorted(m[0] for m in getmembers(pd_module_group, isclass) if not m[0].startswith("_"))


def _update_all_supported_status(
    all_supported_status: Dict[Tuple[str, str], Dict[str, SupportedStatus]],
    pd_modules: List[str],
    pd_module_group: Any,
    ps_module_group: Any,
) -> None:
    """
    Update the supported status dictionary with status from multiple modules.

    Parameters
    ----------
    all_supported_status : Dict[Tuple[str, str], Dict[str, SupportedStatus]]
        The dictionary to update with supported statuses.
    pd_modules : List[str]
        List of module names in pandas.
    pd_module_group : Any
        Importable pandas module group.
    ps_module_group : Any
        Corresponding pyspark.pandas module group.
    """
    pd_modules.append("")  # Include General Function APIs
    for module_name in pd_modules:
        supported_status = _create_supported_by_module(
            module_name, pd_module_group, ps_module_group
        )
        if supported_status:
            all_supported_status[(module_name, ps_module_group.__name__)] = supported_status


def _create_supported_by_module(
    module_name: str, pd_module_group: Any, ps_module_group: Any
) -> Dict[str, SupportedStatus]:
    """
    Create a dictionary of supported status for a specific pandas module.

    Parameters
    ----------
    module_name : str
        Name of the module in pandas.
    pd_module_group : Any
        Importable pandas module.
    ps_module_group : Any
        Corresponding pyspark.pandas module.

    Returns
    -------
    Dict[str, SupportedStatus]
        Dictionary of supported status for the module.
    """
    pd_module = getattr(pd_module_group, module_name) if module_name else pd_module_group
    try:
        ps_module = getattr(ps_module_group, module_name) if module_name else ps_module_group
    except (AttributeError, PandasNotImplementedError):
        # module not implemented
        return {}

    pd_funcs = dict([m for m in getmembers(pd_module, isfunction) if not m[0].startswith("_")])
    if not pd_funcs:
        return {}

    ps_funcs = dict([m for m in getmembers(ps_module, isfunction) if not m[0].startswith("_")])

    return _organize_by_implementation_status(
        module_name, pd_funcs, ps_funcs, pd_module_group, ps_module_group
    )


def _organize_by_implementation_status(
    module_name: str,
    pd_funcs: Dict[str, FunctionType],
    ps_funcs: Dict[str, FunctionType],
    pd_module_group: Any,
    ps_module_group: Any,
) -> Dict[str, SupportedStatus]:
    """
    Organize functions by implementation status between pandas and pyspark.pandas.

    Parameters
    ----------
    module_name : str
        Class name that exists in the path of the module.
    pd_funcs: Dict[str, Callable]
        function name and function object mapping of pandas module.
    ps_funcs: Dict[str, Callable]
        function name and function object mapping of pyspark.pandas module.
    pd_module_group : Any
        Specific path of importable pandas module.
    ps_module_group: Any
        Specific path of importable pyspark.pandas module.

    Returns
    -------
    Dict[str, SupportedStatus]
        Dictionary of implementation status.
    """
    pd_dict = {}
    for pd_func_name, pd_func in pd_funcs.items():
        ps_func = ps_funcs.get(pd_func_name)
        if ps_func:
            missing_set = (
                set(signature(pd_func).parameters)
                - set(signature(ps_func).parameters)
                - COMMON_PARAMETER_SET
            )
            if missing_set:
                # partially implemented
                pd_dict[pd_func_name] = SupportedStatus(
                    implemented=Implemented.PARTIALLY_IMPLEMENTED.value,
                    missing=_transform_missing(
                        module_name,
                        pd_func_name,
                        missing_set,
                        pd_module_group.__name__,
                        ps_module_group.__name__,
                    ),
                )
            else:
                # implemented including it's whole parameter
                pd_dict[pd_func_name] = SupportedStatus(
                    implemented=Implemented.IMPLEMENTED.value, missing=""
                )
        else:
            # not implemented yet
            pd_dict[pd_func_name] = SupportedStatus(
                implemented=Implemented.NOT_IMPLEMENTED.value, missing=""
            )
    return pd_dict


def _transform_missing(
    module_name: str,
    pd_func_name: str,
    missing_set: Set[str],
    pd_module_path: str,
    ps_module_path: str,
) -> str:
    """
    Transform missing parameters into a formatted string for table display.

    Parameters
    ----------
    module_name : str
        Class name that exists in the path of the module.
    pd_func_name : str
        Name of pandas API.
    missing_set : Set[str]
        A set of parameters not yet implemented.
    pd_module_path : str
        Path string of pandas module.
    ps_module_path : str
        Path string of pyspark.pandas module.

    Returns
    -------
    str
        Formatted string representing missing parameters.

    Examples
    --------
    >>> _transform_missing("DataFrame", "add", {"axis", "fill_value", "level"},
    ...                     "pandas.DataFrame", "pyspark.pandas.DataFrame")
    '``axis`` , ``fill_value`` , ``level``'
    """
    missing_str = " , ".join("``%s``" % x for x in sorted(missing_set)[:MAX_MISSING_PARAMS_SIZE])
    if len(missing_set) > MAX_MISSING_PARAMS_SIZE:
        module_dot_func = "%s.%s" % (module_name, pd_func_name) if module_name else pd_func_name
        additional_str = (
            " and more. See the "
            + "`%s.%s " % (pd_module_path, module_dot_func)
            + "<https://pandas.pydata.org/docs/reference/api/"
            + "%s.%s.html>`__ and " % (pd_module_path, module_dot_func)
            + "`%s.%s " % (ps_module_path, module_dot_func)
            + "<https://spark.apache.org/docs/latest/api/python/reference/pyspark.pandas/api/"
            + "%s.%s.html>`__ for detail." % (ps_module_path, module_dot_func)
        )
        missing_str += additional_str
    return missing_str


def _write_table(
    module_name: str,
    module_path: str,
    supported_status: Dict[str, SupportedStatus],
    w_fd: TextIO,
) -> None:
    """
    Write the support status in a table format using Sphinx list-table directive.

    Parameters
    ----------
    module_name : str
        The name of the module whose support status is being documented.
    module_path : str
        The import path of the module in the documentation.
    supported_status : Dict[str, SupportedStatus]
        A dictionary mapping each function name to its support status.
    w_fd : TextIO
        An open file descriptor where the table will be written.
    """
    lines = []
    if module_name:
        lines.append(module_name)
    else:
        lines.append("General Function")
    lines.append(" API\n")
    lines.append("-" * 100)
    lines.append("\n")
    lines.append(".. currentmodule:: %s" % module_path)
    if module_name:
        lines.append(".%s\n" % module_name)
    else:
        lines.append("\n")
    lines.append("\n")
    lines.append(".. list-table::\n")
    lines.append("    :header-rows: 1\n")
    lines.append("\n")
    lines.append("    * - API\n")
    lines.append("      - Implemented\n")
    lines.append("      - Missing parameters\n")
    for func_str, status in supported_status.items():
        func_str = _escape_func_str(func_str)
        if status.implemented == Implemented.NOT_IMPLEMENTED.value:
            lines.append("    * - %s\n" % func_str)
        else:
            lines.append("    * - :func:`%s`\n" % func_str)
        lines.append("      - %s\n" % status.implemented)
        lines.append("      - \n") if not status.missing else lines.append(
            "      - %s\n" % status.missing
        )
    w_fd.writelines(lines)


def _escape_func_str(func_str: str) -> str:
    """
    Escape function names to conform to RST format.

    Parameters
    ----------
    func_str : str
        Function name to escape.

    Returns
    -------
    str
        Escaped function name.
    """
    # TODO: Take into account that this function can create links incorrectly
    # We can create alias links or links to parent methods
    if func_str.endswith("_"):
        return func_str[:-1] + "\_"  # noqa: W605
    else:
        return func_str


def _write_rst(
    output_rst_file_path: str,
    all_supported_status: Dict[Tuple[str, str], Dict[str, SupportedStatus]],
) -> None:
    """
    Write the final RST file with the collected support status.

    Parameters
    ----------
    output_rst_file_path : str
        Path to the output RST file.
    all_supported_status : Dict
        Collected support status data.
    """
    with open(output_rst_file_path, "w") as w_fd:
        w_fd.write(RST_HEADER)
        for module_info, supported_status in all_supported_status.items():
            module, module_path = module_info
            if supported_status:
                _write_table(module, module_path, supported_status, w_fd)
                w_fd.write("\n")


def _test() -> None:
    import doctest
    import sys

    import pyspark.pandas.supported_api_gen

    globs = pyspark.pandas.supported_api_gen.__dict__.copy()
    (failure_count, test_count) = doctest.testmod(pyspark.pandas.supported_api_gen, globs=globs)
    if failure_count:
        sys.exit(-1)


if __name__ == "__main__":
    _test()
