diff --git a/main_backup.py b/main_backup.py
deleted file mode 100644
index d7738d8..0000000
--- a/main_backup.py
+++ /dev/null
@@ -1,190 +0,0 @@
-import asyncio
-from collections import defaultdict
-from pprint import pprint
-import os
-from typing import Dict, List
-from sqlalchemy import Table, create_engine, text, insert
-from dotenv import load_dotenv
-from sqlalchemy.ext.asyncio import create_async_engine
-from dbapi.migrator import FitnessDatabseMigrator
-from dbapi.repositories.approach_repo import ApproachRepository
-from dbapi.repositories.exercise_repo import ExerciseRepository
-from dbapi.repositories.training_repo import TrainingRepository
-from dbapi.tables import metadata_obj, training, exercise, approach
-from obsidian.notes_parser import parse_training_data, remap_unique_exercises
-from apple.notes_parser import parse_training_data as apple_parse_training_data
-from apple.notes_parser import remap_unique_exercises as apple_remaper
-from obsidian.py_models import Training
-
-# LOADING DATA
-
-load_dotenv()
-
-DB_USERNAME = os.getenv("POSTGRES_USER")
-DB_PASS = os.getenv("POSTGRES_PASSWORD")
-
-engine = create_engine(
-    f"postgresql+psycopg2://{DB_USERNAME}:{DB_PASS}@localhost:5433/fitness_database",
-    echo=True,
-)
-#
-# # Creating async engine for Database connection
-# async_engine = create_async_engine(
-#     f"postgresql+asyncpg://{DB_USERNAME}:{DB_PASS}@localhost:5433/fitness_database",
-#     echo=True,
-# )
-
-
-# NOTE: "Begin once" style - using `.begin` as context creator for SQLAlchemy
-# with engine.begin() as conn:
-#     result = conn.execute(text("select 'hello world'"))
-#     print(result.all())
-#     conn.execute(
-#         text("INSERT INTO some_table(x, y) VALUES (:x, :y)"),
-#         [{"x": 6, "y": 7}, {"x": 9, "y": 10}],
-#     )
-
-# NOTE: "Commit as you go" style - after managing transactions we need to call Connection.commit(). Otherwise ROLLBACK
-# will be executed
-# with engine.connect() as conn:
-#     result = conn.execute(text("SELECT x, y FROM some_table"))
-#     for row in result:
-#         print(f"x: {row.x} -- y: {row.y}")
-
-# NOTE : Create all tables from metadata object
-# metadata_obj.create_all(engine)
-# TODO: Check how psycopg2 handles duplication of tables
-# TODO: Check how migrations are done
-
-# NOTE: Drop all Tables from database
-# metadata_obj.drop_all(engine)
-# metadata_obj.create_all(engine)
-
-# NOTE: Table reflection - generating table object from existing tables (only tables, that are stored in metadata)
-# some_table = Table("some_table", metadata_obj, autoload_with=engine)
-# print(some_table.c)
-
-# -----
-
-# Inserting training values into database
-
-trainings: List[Training] = parse_training_data()
-for train in trainings:
-    if not train or not train.exercises:
-        continue
-    else:
-        print(train)
-        new_training_pk: int = TrainingRepository(engine).create_training(train.date)
-        for exr in train.exercises:
-            approach_statements: List[str] = []
-            new_exercise_pk: int = ExerciseRepository(engine).create_exercise(
-                training_pk=new_training_pk, exercise_name=exr.name
-            )
-            for appr in exr.approaches:
-                new_approach_pk: int = ApproachRepository(engine).create_approach(
-                    exercise_pk=new_exercise_pk, weight=appr.weight, reps=appr.reps
-                )
-
-
-print("-------------------------\n" * 2)
-print("-------------------------\n" * 2)
-# -----
-
-# Calculating unique exercises for obsidian
-
-# trainings: List[Training] = parse_training_data()
-#
-#
-# unique_exercise_names = defaultdict(int)
-# counter = 0
-#
-# for train in trainings:
-#     if not train:
-#         continue
-#     if train.exercises:
-#         for exr in train.exercises:
-#             counter += 1
-#             unique_exercise_names[exr.name] += 1
-#
-# pprint(unique_exercise_names)
-# print(counter)
-# parsed_trainings = remap_unique_exercises(trainings)
-#
-# print("\n" * 3)
-#
-# unique_exercise_parsed_names = defaultdict(int)
-# p_counter = 0
-# for train in parsed_trainings:
-#     if not train:
-#         continue
-#     if train.exercises:
-#         for exr in train.exercises:
-#             p_counter += 1
-#             unique_exercise_parsed_names[exr.name] += 1
-# pprint(unique_exercise_parsed_names)
-# print(p_counter)
-
-# Apple notes playground
-
-# trainings: List[Training] = apple_parse_training_data()
-#
-#
-# unique_exercise_names = defaultdict(int)
-# counter = 0
-#
-# for train in trainings:
-#     if not train:
-#         continue
-#     if train.exercises:
-#         for exr in train.exercises:
-#             if exr:
-#                 counter += 1
-#                 unique_exercise_names[exr.name] += 1
-#
-# pprint(unique_exercise_names)
-# print(counter)
-#
-# parsed_trainings = apple_remaper(trainings)
-#
-# print("\n" * 3)
-#
-# unique_exercise_parsed_names = defaultdict(int)
-# p_counter = 0
-# for train in parsed_trainings:
-#     if not train:
-#         continue
-#     if train.exercises:
-#         for exr in train.exercises:
-#             if exr:
-#                 p_counter += 1
-#                 unique_exercise_parsed_names[exr.name] += 1
-# pprint(unique_exercise_parsed_names)
-# print(p_counter)
-
-# Combined trainings
-
-
-# obsidian_trainings: List[Training] = parse_training_data()
-# obsidian_parsed_trainings = remap_unique_exercises(obsidian_trainings)
-#
-# apple_trainings: List[Training] = apple_parse_training_data()
-# apple_parsed_trainings = apple_remaper(apple_trainings)
-#
-#
-# combined_trainings = obsidian_trainings + apple_trainings
-# unique_exercise_parsed_names = defaultdict(int)
-# for train in combined_trainings:
-#     if not train:
-#         continue
-#     if train.exercises:
-#         for exr in train.exercises:
-#             if exr:
-#                 unique_exercise_parsed_names[exr.name] += 1
-# pprint(unique_exercise_parsed_names)
-# print(len(combined_trainings))
-
-# Async engine playground
-
-# fbm = FitnessDatabseMigrator(async_engine=async_engine)
-#
-# asyncio.run(fbm.reset_database())