example_bot

bot.py

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+import logging
+from aiogram import Bot, Dispatcher, types, executor
+import os
+from dotenv import load_dotenv
+from pathlib import Path
+from aiogram.types import InputFile
+from pydub import AudioSegment
+import matplotlib.pyplot as plt
+from scipy.io import wavfile
+from scipy.signal import spectrogram
+import numpy as np
+
+dotenv_path = Path('.env.txt')
+load_dotenv(dotenv_path=dotenv_path)
+
+# логирование, чтобы не пропустить важные сообщения
+logging.basicConfig(level=logging.INFO)
+bot_token = os.getenv("BOT_TOKEN")
+# объект бота
+bot = Bot(token=bot_token)
+# диспетчер
+dp = Dispatcher(bot)
+
+
+# хэндлер на команду /start
+@dp.message_handler(commands='start')
+async def cmd_start(message: types.Message):
+   await message.answer('Hello!')
+
+
+unique_id = ''
+@dp.message_handler(content_types=['audio', 'photo'])
+async def show_spectrogram(message: types.Message):
+    audio_id = message.audio.file_id
+    global unique_id
+    unique_id = message.audio.file_unique_id
+    file_info = await bot.get_file(audio_id)
+    path_to_file = f'D:\\PyCharm\\PyCharm 2022.3\\pythonProject\\{message.audio.file_unique_id}.mp3'
+    try:
+        await bot.download_file(file_info.file_path,
+                                destination=f'D:\\PyCharm\\PyCharm 2022.3\\pythonProject\\{message.audio.file_unique_id}.mp3')
+        await message.answer("Your audio is successfully downloaded")
+    except:
+        await message.answer("Error downloading")
+
+    input_file = f'{path_to_file}'
+    output_file = f'{path_to_file}.wav'
+
+    sound = AudioSegment.from_mp3(input_file)
+    sound.export(output_file, format='wav')
+
+    input_file2 = output_file
+    output_file_mono = f'{output_file}_mono.wav'
+
+    stereo_audio = AudioSegment.from_file(input_file2, format='wav')
+    mono_audios = stereo_audio.split_to_mono()
+    mono_left = mono_audios[0].export(output_file_mono, format='wav')
+
+    input_file_spectrogram = output_file_mono
+    samplerate, data = wavfile.read(input_file_spectrogram)
+    f, t, Sxx = spectrogram(data, samplerate)
+
+    plt.pcolormesh(1000 * t, f / 1000, 10 * np.log10(Sxx / Sxx.max()), vmin=-120, vmax=0, cmap='inferno')
+    plt.ylabel('Frequency [kHz]')
+    plt.xlabel('Time [ms]')
+    plt.colorbar()
+    img = f'{unique_id}.png'
+    plt.savefig(img)
+
+    try:
+        photo = open(f'{unique_id}.png', 'rb')
+        await message.answer_photo(photo, caption='Your spectrogram')
+    except:
+        await message.answer("Error showing")
+
+
+if __name__ == '__main__':
+    executor.start_polling(dp, skip_updates=True)