Messy input in.
Tidy rows out.

1 · The webhook, and what happens when Whisper is unavailable

A voice note needs transcription. If that call fails — say the API key runs out of credit — the bot should tell him, not silently swallow the message. Failure has to be visible to the person in the field.

# Telegram calls this endpoint every time he sends a message.
@app.route("/webhook", methods=["POST"])
def webhook():
    # VOICE needs OpenAI Whisper. If that's down (e.g. no credit),
    # we DON'T crash — we tell him to type it instead.
    ...

2 · Turning a spoken sentence into fields

The date is the subtle part. "Yesterday" has to become a real date, and it has to be written YYYY-MM-DD — because that is the format that sorts chronologically when the sheet re-sorts itself.

def extract_fields(text, today_iso):
    """Pull task type, time spent and date out of natural speech.

    The date is returned as a YYYY-MM-DD string — that format sorts
    chronologically when the sheet is sorted.
    """
    ...
    response = openai_client.chat.completions.create(...)

3 · Appending without disturbing what's already there

A logbook people trust is one that never rewrites itself. New rows are added and the sheet is re-sorted by date, but existing rows are never edited or moved.

# Existing rows are never edited, moved, or re-sorted.
gc = gspread.authorize(credentials)

1 · Searching in both languages

This is the part that matters most and is easiest to skip. An Icelandic supplier describes itself in Icelandic — search only in English and you miss the local market, which is exactly the market in question.

SEARCH_QUERIES = [
    "biodegradable paper cups distributor Iceland",
    "compostable paper cups supplier Iceland",
    "eco-friendly disposable cups Iceland",
    "sustainable packaging cups Iceland supplier",
    "environmentally friendly paper cups Iceland buy",
    "umhverfisvænar pappírsbikara Ísland",
    "lífrænar einnota bíkara Ísland dreifingaraðili",
    "pappírsbikar lógó prentun Ísland",
    "custom printed paper cups Iceland supplier",
    "wholesale paper cups Iceland",
]

2 · One row per company, not one per search hit

Ten overlapping queries return the same supplier repeatedly. De-duplicating by URL as results arrive is what makes the output a comparison table rather than a pile of links. The pause between searches is courtesy to the search engine.

def search_distributors():
    seen_urls = set()
    results   = []

    with DDGS() as ddgs:
        for query in SEARCH_QUERIES:
            hits = ddgs.text(query, max_results=6)
            for hit in hits:
                url = hit.get("href", "")
                if url and url not in seen_urls:
                    seen_urls.add(url)
                    results.append(hit)
            time.sleep(1.5)

3 · Reading each site and classifying it

A search snippet is often marketing filler. Opening the page and reading its meta description gives a truer one-line summary, which then gets scanned for pricing and logo-printing signals so the columns are comparable across suppliers.

PRICE_KEYWORDS = ["price", "cost", "isk", "kr.",
                  "per unit", "per case", ...]
LOGO_KEYWORDS  = ["logo", "print", "custom print",
                  "branded", "branding", ...]

def scrape_meta_description(url: str) -> str:
    resp = requests.get(url, headers={...}, timeout=10)
    if resp.status_code == 200:
        soup = BeautifulSoup(resp.text, "html.parser")
        tag  = soup.find("meta", attrs={"name": "description"})

4 · Keeping the key out of the repository

Writing to a Google Sheet needs a service-account key. It's resolved at runtime from a folder that's git-ignored, never hard-coded — so the script can be shown to anyone without showing them the credentials.

_CREDENTIAL_CANDIDATES = [
    os.environ.get("GOOGLE_APPLICATION_CREDENTIALS"),
    os.path.join(PROJECT_DIR, "secrets", CREDENTIALS_FILENAME),
    ...
]