# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import logging
from typing import List

from fuzzywuzzy import fuzz

from DatabaseDriver.SqlClasses import PatchData
from Objects.PatchDiffs import PatchDiffs


def patch_matches(downstream_patches: List[PatchData], upstream: PatchData) -> bool:
    """Check if 'upstream' has an equivalent in 'downstream_patches'. """
    # Confidence weights
    author_weight = 0.2
    subject_weight = 0.48
    description_weight = 0.1
    filenames_weight = 0.2
    author_date_weight = (
        0.01  # This addresses some edge cases of identical other fields
    )
    commit_date_weight = (
        0.01  # This addresses some edge cases of identical other fields
    )

    # Threshold that we must hit to return a match
    threshold = 0.75

    # Preprocessing for matching filenames
    upstream_filepaths = upstream.affectedFilenames.split(" ")
    upstream_file_components = [
        _get_filepath_components(filepath) for filepath in upstream_filepaths
    ]

    logging.debug(f"Upstream missing patch {upstream.commitID}")
    for downstream in downstream_patches:
        # Calculate confidence that our upstream patch matches this downstream patch

        # Calculate filenames confidence, which is roughly the percent
        # of upstream filepaths present in downstream patch.
        if downstream.affectedFilenames == "" or upstream.affectedFilenames == "":
            filenames_confidence = (
                1.0
                if (downstream.affectedFilenames == upstream.affectedFilenames)
                else 0.0
            )
        else:
            total_filepaths_match = 0
            downstream_filepaths = downstream.affectedFilenames.split(" ")
            downstream_file_components = [
                _get_filepath_components(filepath) for filepath in downstream_filepaths
            ]

            for (upstream_path, upstream_name) in upstream_file_components:
                max_match = 0.0
                # Find best matching downstream filepath
                for (downstream_path, downstream_name,) in downstream_file_components:
                    if upstream_name == downstream_name:
                        # 0.5 for matching filename, the paths are
                        # fuzzymatched scaled 0.0-0.5 for remaining
                        # match
                        match = 0.5 + (
                            fuzz.partial_ratio(upstream_path, downstream_path) / 200.0
                        )
                    else:
                        match = 0.0

                    if match > max_match:
                        max_match = match
                total_filepaths_match += max_match

            filenames_confidence = float(total_filepaths_match) / len(
                upstream_filepaths
            )

        author_confidence = (
            fuzz.token_set_ratio(upstream.author, downstream.author) / 100.0
        )
        subject_confidence = (
            fuzz.partial_ratio(upstream.subject, downstream.subject) / 100.0
        )
        # Temporarily for description only checking exact string is in
        if upstream.description == "":
            description_confidence = 1.0 if downstream.description == "" else 0.0
        else:
            description_confidence = (
                1.0 if upstream.description in downstream.description else 0.0
            )
        author_date_confidence = (
            1.0 if upstream.authorTime == downstream.authorTime else 0.0
        )
        commit_date_confidence = (
            1.0 if upstream.commitTime == downstream.commitTime else 0.0
        )

        confidence = (
            author_weight * author_confidence
            + subject_weight * subject_confidence
            + description_weight * description_confidence
            + filenames_weight * filenames_confidence
            + author_date_confidence * author_date_weight
            + commit_date_confidence * commit_date_weight
        )
        if confidence >= threshold:
            return True

    # TODO just do this part?...
    # Check for code matching
    upstream_diffs = PatchDiffs(upstream.commitDiffs)
    for downstream in downstream_patches:
        downstream_diffs = PatchDiffs(downstream.commitDiffs)
        code_match_confidence = upstream_diffs.percent_present_in(downstream_diffs)
        if code_match_confidence > threshold:
            return True

    return False


def _get_filepath_components(filepath):
    """
    Splits filepath to return (path, filename)
    """
    components = filepath.rsplit("/", 1)
    if len(components) == 1:
        return (None, components[0])
    return (components[0], components[1])

# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import logging
from typing import List

from fuzzywuzzy import fuzz

from DatabaseDriver.SqlClasses import PatchData
from Objects.PatchDiffs import PatchDiffs


def patch_matches(downstream_patches: List[PatchData], upstream: PatchData) -> bool:
    """Check if 'upstream' has an equivalent in 'downstream_patches'. """
    # Confidence weights
    author_weight = 0.2
    subject_weight = 0.48
    description_weight = 0.1
    filenames_weight = 0.2
    author_date_weight = (
        0.01  # This addresses some edge cases of identical other fields
    )
    commit_date_weight = (
        0.01  # This addresses some edge cases of identical other fields
    )

    # Threshold that we must hit to return a match
    threshold = 0.75

    # Preprocessing for matching filenames
    upstream_filepaths = upstream.affectedFilenames.split(" ")
    upstream_file_components = [
        _get_filepath_components(filepath) for filepath in upstream_filepaths
    ]

    logging.debug(f"Upstream missing patch {upstream.commitID}")
    for downstream in downstream_patches:
        # Calculate confidence that our upstream patch matches this downstream patch

        # Calculate filenames confidence, which is roughly the percent
        # of upstream filepaths present in downstream patch.
        if downstream.affectedFilenames == "" or upstream.affectedFilenames == "":
            filenames_confidence = (
                1.0
                if (downstream.affectedFilenames == upstream.affectedFilenames)
                else 0.0
            )
        else:
            total_filepaths_match = 0
            downstream_filepaths = downstream.affectedFilenames.split(" ")
            downstream_file_components = [
                _get_filepath_components(filepath) for filepath in downstream_filepaths
            ]

            for (upstream_path, upstream_name) in upstream_file_components:
                max_match = 0.0
                # Find best matching downstream filepath
                for (downstream_path, downstream_name,) in downstream_file_components:
                    if upstream_name == downstream_name:
                        # 0.5 for matching filename, the paths are
                        # fuzzymatched scaled 0.0-0.5 for remaining
                        # match
                        match = 0.5 + (
                            fuzz.partial_ratio(upstream_path, downstream_path) / 200.0
                        )
                    else:
                        match = 0.0

                    if match > max_match:
                        max_match = match
                total_filepaths_match += max_match

            filenames_confidence = float(total_filepaths_match) / len(
                upstream_filepaths
            )

        author_confidence = (
            fuzz.token_set_ratio(upstream.author, downstream.author) / 100.0
        )
        subject_confidence = (
            fuzz.partial_ratio(upstream.subject, downstream.subject) / 100.0
        )
        # Temporarily for description only checking exact string is in
        if upstream.description == "":
            description_confidence = 1.0 if downstream.description == "" else 0.0
        else:
            description_confidence = (
                1.0 if upstream.description in downstream.description else 0.0
            )
        author_date_confidence = (
            1.0 if upstream.authorTime == downstream.authorTime else 0.0
        )
        commit_date_confidence = (
            1.0 if upstream.commitTime == downstream.commitTime else 0.0
        )

        confidence = (
            author_weight * author_confidence
            + subject_weight * subject_confidence
            + description_weight * description_confidence
            + filenames_weight * filenames_confidence
            + author_date_confidence * author_date_weight
            + commit_date_confidence * commit_date_weight
        )
        if confidence >= threshold:
            return True

    # TODO just do this part?...
    # Check for code matching
    upstream_diffs = PatchDiffs(upstream.commitDiffs)
    for downstream in downstream_patches:
        downstream_diffs = PatchDiffs(downstream.commitDiffs)
        code_match_confidence = upstream_diffs.percent_present_in(downstream_diffs)
        if code_match_confidence > threshold:
            return True

    return False


def _get_filepath_components(filepath):
    """
    Splits filepath to return (path, filename)
    """
    components = filepath.rsplit("/", 1)
    if len(components) == 1:
        return (None, components[0])
    return (components[0], components[1])

# Copyright (c) Microsoft Corporation. # Licensed under the MIT License. Check if 'upstream' has an equivalent in 'downstream_patches'. # Confidence weights # This addresses some edge cases of identical other fields # This addresses some edge cases of identical other fields # Threshold that we must hit to return a match # Preprocessing for matching filenames # Calculate confidence that our upstream patch matches this downstream patch # Calculate filenames confidence, which is roughly the percent # of upstream filepaths present in downstream patch. # Find best matching downstream filepath # 0.5 for matching filename, the paths are # fuzzymatched scaled 0.0-0.5 for remaining # match # Temporarily for description only checking exact string is in # TODO just do this part?... # Check for code matching Splits filepath to return (path, filename)