import copy
import os
import re
from pprint import pprint
from typing import Dict, List, Tuple

from obsidian.py_models import Approach, Exercise, Training

current_directory = os.path.dirname(os.path.abspath(__file__))


def get_current_path():
    return current_directory


def get_obsidian_examples_file(example_file_name: str):
    return os.path.join(get_current_path(), f"examples/{example_file_name}")


def read_example_file(example_file_name: str):
    path_to_example: str = get_obsidian_examples_file(example_file_name)
    with open(path_to_example, "r") as f:
        content = f.read()
    return content


def serialize_exercise(reps: str, weight: str, name: str) -> Exercise:
    # Split reps into array of int's
    reps: List[int] = [int(rep) for rep in reps.split("-")]
    weight_splitted: bool = False
    if weight:
        weight: List[str] = [weight for weight in weight.split("-")]
        # Check if weight is splitted
        if any(split_anchor in weight[0] for split_anchor in ["x", "х"]):
            weight_splitted = True
            splitter = "x" if "x" in weight[0] else "х"
            weight: List[float] = [xweight.split(splitter)[0] for xweight in weight]
    approaches = []
    if not weight:
        for rep_index in range(0, len(reps)):
            approach = Approach(weight=0, reps=reps[rep_index])
            approaches.append(approach)
    else:
        weight_pointer = 0
        for rep_index in range(0, len(reps)):
            print(reps[rep_index])
            approach = Approach(weight=weight[weight_pointer], reps=reps[rep_index])
            if rep_index < len(weight) - 1:
                weight_pointer += 1
            approaches.append(approach)
    exercise = Exercise(
        name=name, approaches=approaches, splitted_weight=weight_splitted
    )
    print(exercise)
    return exercise


def parse_training_exercises(exercise_line: str) -> Exercise:
    stripped: List[str] = [entry.strip() for entry in exercise_line.split("|")][1:-1]
    for entry in stripped:
        if entry in ["Упражнение", "Вес", "Подходы"]:
            raise ValueError
    if stripped:
        if "---" in stripped[0]:
            raise ValueError
        if len(stripped) != 3:
            raise ValueError
        # return {
        #     "name": stripped[0],
        #     "weight": stripped[1],
        #     "reps": stripped[2],
        # }
        return serialize_exercise(
            name=stripped[0], weight=stripped[1], reps=stripped[2]
        )


def parse_training_header(training_data_line: str) -> Tuple[bool, str, str, str]:
    pattern: str = r"#\s(?P<date>\d+.\d+.\d+)\s\((?P<trainer>.+)-(?P<year_counter>.+)\)"
    match = re.search(pattern, training_data_line)
    if match:
        date = match.group("date").strip()
        trainer = match.group("trainer").strip()
        year_count = match.group("year_counter").strip()
        return True, date, trainer, year_count
    return False, None, None, None


def filter_training_data(training_data: str):
    cleaned_text = re.sub(r"^\s*?\n", "", training_data, flags=re.MULTILINE)
    return cleaned_text


def parse_training_data():
    training_data: str = filter_training_data(read_example_file("notes.txt"))
    training_template: Dict = {
        "date": None,
        "trainer": None,
        "year_count": None,
        "exercises": [],
    }
    parsed_trainings: List[List[str]] = []
    current_training: Dict = {}
    lines = training_data.splitlines()
    for index, line in enumerate(lines):
        # Check for last line
        if index == len(lines) - 1:
            current_training["exercises"] = current_training["exercises"][1:]
            parsed_trainings.append(current_training)
            break
        header_parsed, date, trainer, year_count = parse_training_header(line)
        if header_parsed:
            if not current_training:
                pass
            else:
                current_training["exercises"] = current_training["exercises"][1:]
            parsed_trainings.append(current_training)
            current_training = copy.deepcopy(training_template)
            current_training["date"] = date
            current_training["trainer"] = trainer
            current_training["year_count"] = year_count
        try:
            exr = parse_training_exercises(line)
            current_training["exercises"].append(exr)
        except ValueError:
            pass
    trainings: List[Training] = []
    for training in parsed_trainings:
        if not training:
            continue
        pprint(training)
        print("-" * 10)
        train = Training(date=training.get("date"), exercises=training.get("exercises"))

    return trainings


pprint(parse_training_data()[1:])