64 lines
3.2 KiB
Python
64 lines
3.2 KiB
Python
import logging
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import constants
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import requests
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from PIL import Image, ImageDraw, ImageFont
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# Enable logging
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logging.basicConfig(
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', level=logging.INFO
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)
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logger = logging.getLogger(__name__)
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def create_image(product_id, price):
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width = 1280
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height = 800
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baseheight = int(height * 0.85)
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# límite de ancho para la parte izquierda (producto)
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wlimit = int(((width / 3) * 2) - 80)
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# límite de ancho para los logos (homelabers y amazon)
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wlogo = int(width * 0.2)
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# fuente y tamaño
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font = ImageFont.truetype("/app/data/fonts/Roboto-Bold.ttf", 90)
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# inicializamos canvas
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image = Image.new('RGBA', (width, height), (255, 255, 255))
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# logo homelabers, redimensionamos y ponemos en la parte derecha arriba
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logo_image = Image.open("/app/data/images/logo.png").convert("RGBA")
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lpercent = wlogo / float(logo_image.size[0])
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hlogo = int((float(logo_image.size[1]) * float(lpercent)))
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logo_image = logo_image.resize((wlogo, hlogo), Image.Resampling.LANCZOS)
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image.paste(logo_image, (int((width / 6) * 5 - logo_image.size[0] / 2), int(height * 0.1)), logo_image)
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# logo amazon, redimensionamos y ponemos en la parte derecha abajo
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amazon_logo = Image.open("/app/data/images/Amazon_logo.png").convert("RGBA")
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lpercent = wlogo / float(amazon_logo.size[0])
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hlogo = int((float(amazon_logo.size[1]) * float(lpercent)))
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amazon_logo = amazon_logo.resize((wlogo, hlogo), Image.Resampling.LANCZOS)
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image.paste(amazon_logo, (int((width / 6) * 5 - amazon_logo.size[0] / 2), int(height - height * 0.2)), amazon_logo)
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# dibujamos rectángulo verde externo, con un margen externo y ancho determinado
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draw = ImageDraw.Draw(image)
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wtext, htext = draw.textsize(price, font=font)
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draw.text(((width / 6) * 5 - wtext / 2, height / 2 - htext / 2), price, (0, 0, 0), font=font)
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draw.rectangle([15, 15, width - 15, height - 15], width = 15, outline="#20e163")
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# ponemos la imagen del producto en la parte izquierda y se redimensiona dependiendo de lo ancho
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product_image = Image.open(f"/app/data/images/products/{product_id}.jpg")
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hpercent = (baseheight / float(product_image.size[1]))
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wsize = int((float(product_image.size[0]) * float(hpercent)))
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if wsize < wlimit:
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product_image = product_image.resize((wsize, baseheight), Image.Resampling.LANCZOS)
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else:
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wpercent = wlimit / float(product_image.size[0])
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hsize = int((float(product_image.size[1]) * float(wpercent)))
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product_image = product_image.resize((wlimit, hsize), Image.Resampling.LANCZOS)
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image.paste(product_image, (int((width/3)-(product_image.size[0]/2)), int((height/2) - (product_image.size[1]/2))))
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# guardamos la imagen con otro nombre
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image.save(f"/app/data/images/products/{product_id}_composed.png", quality=95)
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def new_refer_url(pcode, extraparams=None):
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return constants.baseURL+pcode+"?tag="+constants.affiliate_tag+extraparams
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def unshort_url(url):
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session = requests.Session()
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#resp = session.head("https://"+url, allow_redirects=True)
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resp = session.get("https://"+url, allow_redirects=True)
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logging.info(f"Unshorted URL: {resp.url}")
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return resp.url |