import requests

import json

import os

from datetime import datetime, timedelta

def scrape_electricity_prices():

# Official ESIOS (REE) API for PVPC (Spain)

# Archive 70 contains the aggregated PVPC prices (with taxes)

date_str = datetime.now().strftime("%Y-%m-%d")

url = f"https://api.esios.ree.es/archives/70/download_json?date={date_str}"

data = None

try:

print(f"Fetching data from official ESIOS API: {url}")

response = requests.get(url, timeout=15)

if response.status_code == 200:

raw_data = response.json()

pvpc_list = raw_data.get('PVPC', [])

if not pvpc_list:

raise ValueError("No data found in ESIOS response")

standardized = []

prices_list = []

for item in pvpc_list:

# Hour format from ESIOS is "HH-HH"

hour_start = int(item['Hora'].split('-')[0])

# Price is in €/MWh in the field "PCB" (Peninsula, Canarias, Baleares)

# We need to replace comma with dot for float conversion

price_str = item['PCB'].replace(',', '.')

price_mwh = float(price_str)

price_kwh = price_mwh / 1000

prices_list.append(price_kwh)

standardized.append({

"hour": hour_start,

"price": round(price_kwh, 5),

# We will calculate flags after getting min/max

"isLow": False,

"isMid": False,

"isHigh": False

})

# Calculate thresholds for aesthetics (matching tarifaluzhora.es feel)

min_p = min(prices_list)

max_p = max(prices_list)

range_p = max_p - min_p

# 33% chunks for low/mid/high

low_threshold = min_p + (range_p * 0.33)

high_threshold = min_p + (range_p * 0.66)

for item in standardized:

if item['price'] <= low_threshold:

item['isLow'] = True

elif item['price'] >= high_threshold:

item['isHigh'] = True

else:

item['isMid'] = True

# Sort by hour

standardized.sort(key=lambda x: x['hour'])

data = standardized

else:

print(f"ESIOS API failed with status {response.status_code}")

except Exception as e:

print(f"Error fetching from ESIOS: {e}")

# Fallback to a mock/old values only if everything fails completely

if not data:

print("Scraping failed. No data to save.")

return

# Metadata and Summary

result = {

"last_updated": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),

"prices": data,

"summary": {

"min": round(min(p['price'] for p in data), 5),

"max": round(max(p['price'] for p in data), 5),

"avg": round(sum(p['price'] for p in data) / len(data), 5)

}

}

# Ensure output directory exists

# If running in GitHub Actions, it might be docs/data

output_path = 'docs/data/luz.json'

if not os.path.exists('docs'):

# Fallback for different execution contexts

output_path = 'LuzMerida/docs/data/luz.json'

os.makedirs(os.path.dirname(output_path), exist_ok=True)

with open(output_path, 'w', encoding='utf-8') as f:

json.dump(result, f, indent=2, ensure_ascii=False)

print(f"Successfully updated {output_path}")

if __name__ == "__main__":

scrape_electricity_prices()