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117 lines
3 KiB
Python
117 lines
3 KiB
Python
"""
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This module provides functionality to generate currency rate charts
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based on historical data retrieved from the database.
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"""
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from datetime import datetime
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from matplotlib import pyplot as plt
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from scipy.interpolate import make_interp_spline
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import numpy as np
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from function.gen_unique_name import generate_unique_name
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from database.server import create_pool
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async def create_chart(
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from_currency: str,
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conv_currency: str,
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start_date: str,
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end_date: str
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) -> (str, None):
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"""
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Generates a line chart of currency rates for a given date range.
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The chart shows the exchange rate trend between `from_currency` and
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`conv_currency` within the specified `start_date` and `end_date` range.
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The generated chart is saved as a PNG file, and the function returns the
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file name. If data is invalid or insufficient, the function returns `None`.
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Args:
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from_currency (str): The base currency (e.g., "USD").
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conv_currency (str): The target currency (e.g., "EUR").
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start_date (str): The start date in the format 'YYYY-MM-DD'.
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end_date (str): The end date in the format 'YYYY-MM-DD'.
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Returns:
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str | None: The name of the saved chart file, or `None` if the operation fails.
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"""
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pool = await create_pool()
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if not validate_date(start_date) or not validate_date(end_date):
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return None
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start_date_obj = datetime.strptime(start_date, '%Y-%m-%d').date()
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end_date_obj = datetime.strptime(end_date, '%Y-%m-%d').date()
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async with pool.acquire() as conn:
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data = await conn.fetch(
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'SELECT date, rate FROM currency '
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'WHERE (date BETWEEN $1 AND $2) ' +
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'AND from_currency = $3 AND conv_currency = $4 ORDER BY date',
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start_date_obj,
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end_date_obj,
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from_currency.upper(),
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conv_currency.upper()
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)
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if not data or len(data) <= 1:
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return None
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date, rate = [], []
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for row in data:
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date.append(row[0])
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rate.append(row[1])
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spline = make_interp_spline(range(len(date)), rate, k=2)
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x = np.arange(len(date))
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newx_2 = np.linspace(0, len(date) - 1, 200)
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newy_2 = spline(newx_2)
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fig, ax = plt.subplots(figsize=(15, 6))
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for label in (ax.get_xticklabels() + ax.get_yticklabels()):
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label.set_fontsize(10)
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ax.set_xticks(np.linspace(0, len(date) - 1, 10))
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ax.set_xticklabels(
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[
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date[int(i)].strftime('%Y-%m-%d')
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for i in np.linspace(0, len(date) - 1, 10).astype(int)
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]
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)
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name = await generate_unique_name(
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f'{from_currency.upper()}_{conv_currency.upper()}',
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datetime.now()
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)
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if rate[0] < rate[-1]:
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plt.plot(newx_2, newy_2, color='green')
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elif rate[0] > rate[-1]:
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plt.plot(newx_2, newy_2, color='red')
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else:
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plt.plot(newx_2, newy_2, color='grey')
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plt.savefig(f'../charts/{name}.png')
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fig.clear()
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return name
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def validate_date(date_str: str) -> bool:
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"""
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Validates whether the provided string is a valid date in the format 'YYYY-MM-DD'.
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Args:
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date_str (str): The date string to validate.
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Returns:
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bool: `True` if the string is a valid date, `False` otherwise.
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"""
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try:
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datetime.strptime(date_str, '%Y-%m-%d')
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return True
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except ValueError:
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return False
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