"""
This module provides functionality to generate currency rate charts
based on historical data retrieved from the database.
"""

from datetime import datetime

from matplotlib import pyplot as plt
from scipy.interpolate import make_interp_spline
import numpy as np

from function.gen_unique_name import generate_unique_name
from database.server import create_pool

async def create_chart(
		from_currency: str,
		conv_currency: str,
		start_date: str,
		end_date: str
) -> (str, None):
	"""
	Generates a line chart of currency rates for a given date range.

	The chart shows the exchange rate trend between `from_currency` and
	`conv_currency` within the specified `start_date` and `end_date` range.
	The generated chart is saved as a PNG file, and the function returns the
	file name. If data is invalid or insufficient, the function returns `None`.

	Args:
		from_currency (str): The base currency (e.g., "USD").
		conv_currency (str): The target currency (e.g., "EUR").
		start_date (str): The start date in the format 'YYYY-MM-DD'.
		end_date (str): The end date in the format 'YYYY-MM-DD'.

	Returns:
		str | None: The name of the saved chart file, or `None` if the operation fails.
	"""
	pool = await create_pool()

	if not validate_date(start_date) or not validate_date(end_date):
		return None

	start_date_obj = datetime.strptime(start_date, '%Y-%m-%d').date()
	end_date_obj = datetime.strptime(end_date, '%Y-%m-%d').date()

	async with pool.acquire() as conn:
		data = await conn.fetch(
			'SELECT date, rate FROM currency '
			'WHERE (date BETWEEN $1 AND $2) ' +
			'AND from_currency = $3 AND conv_currency = $4 ORDER BY date',
			start_date_obj,
			end_date_obj,
			from_currency.upper(),
			conv_currency.upper()
		)

	if not data or len(data) <= 1:
		return None

	date, rate = [], []

	for row in data:
		date.append(row[0])
		rate.append(row[1])

	spline = make_interp_spline(range(len(date)), rate, k=2)
	x = np.arange(len(date))

	newx_2 = np.linspace(0, len(date) - 1, 200)
	newy_2 = spline(newx_2)
	fig, ax = plt.subplots(figsize=(15, 6))

	for label in (ax.get_xticklabels() + ax.get_yticklabels()):
		label.set_fontsize(10)

	ax.set_xticks(np.linspace(0, len(date) - 1, 10))
	ax.set_xticklabels(
		[
			date[int(i)].strftime('%Y-%m-%d') 
			for i in np.linspace(0, len(date) - 1, 10).astype(int)
		]
		)

	name = await generate_unique_name(
		f'{from_currency.upper()}_{conv_currency.upper()}',
		datetime.now()
	)

	
	if rate[0] < rate[-1]:
		plt.plot(newx_2, newy_2, color='green')
	elif rate[0] > rate[-1]:
		plt.plot(newx_2, newy_2, color='red', marker='o')
	else:
		plt.plot(newx_2, newy_2, color='grey')

	plt.savefig(f'../charts/{name}.png')
	fig.clear()

	return name


def validate_date(date_str: str) -> bool:
	"""
	Validates whether the provided string is a valid date in the format 'YYYY-MM-DD'.

	Args:
		date_str (str): The date string to validate.

	Returns:
		bool: `True` if the string is a valid date, `False` otherwise.
	"""
	try:
		datetime.strptime(date_str, '%Y-%m-%d')
		return True
	except ValueError:
		return False