How to read group info in Python with the Wapito WhatsApp API

Before you start

• pip install requests
• os.environ["WAPITO_TOKEN"]
• A channel with a WhatsApp number linked to it, and its API token. Create one in the dashboard — the authentication guide shows where the token goes.

The whole script

Every step above in one runnable file. Save it as group-info.py, put your token in the environment, and run it.

"""Group Info with the Wapito WhatsApp API.

List the groups, read one in detail, rename or re-describe it when your own data changes, and follow edits on the webhook.

Run it with:
    export WAPITO_TOKEN="wpt_..."
    python group-info.py
"""
import os

import requests

BASE_URL = "https://api.wapito.com/v1"
TOKEN = os.environ["WAPITO_TOKEN"]

# --- List the groups this number is in ---
url = BASE_URL + "/groups"

querystring = {"count":"50","offset":"0"}

headers = {"Authorization": "Bearer " + TOKEN}

response = requests.get(url, headers=headers, params=querystring)

print(response.json())

# --- Read one group in detail ---
url = BASE_URL + "/groups/120363041234567890@g.us"

headers = {"Authorization": "Bearer " + TOKEN}

response = requests.get(url, headers=headers)

print(response.json())

# --- Rename or re-describe the group ---
url = BASE_URL + "/groups/120363041234567890@g.us"

payload = {
    "subject": "Acme Launch Team",
    "description": "Launch week: daily standup at 09:30."
}
headers = {
    "Authorization": "Bearer " + TOKEN,
    "Content-Type": "application/json"
}

response = requests.patch(url, json=payload, headers=headers)

print(response.json())

Receive the webhook

FastAPI receiver for groups — it verifies the signature, answers immediately and does the work after. Install it with pip install fastapi uvicorn and save it as webhook.py.

import hashlib
import hmac
import os
import time

from fastapi import FastAPI, Header, HTTPException, Request

app = FastAPI()
SECRET = os.environ["WAPITO_WEBHOOK_SECRET"].encode()
EVENTS = ["groups"]


def verify(raw: bytes, header: str | None) -> bool:
    """Checks the X-Wapito-Signature header: t=<ms>,v1=<hex hmac-sha256>."""
    if not header:
        return False
    parts = dict(p.split("=", 1) for p in header.split(",") if "=" in p)
    ts, sig = parts.get("t"), parts.get("v1")
    if not ts or not sig:
        return False
    if abs(time.time() * 1000 - int(ts)) > 300_000:  # 5 minute clock skew
        return False
    expected = hmac.new(SECRET, ts.encode() + b"." + raw, hashlib.sha256).hexdigest()
    return hmac.compare_digest(expected, sig)


@app.post("/wapito")
async def wapito(request: Request, signature: str | None = Header(default=None, alias="X-Wapito-Signature")):
    raw = await request.body()
    if not verify(raw, signature):
        raise HTTPException(status_code=401, detail="bad signature")
    payload = await request.json()
    if payload["event"] in EVENTS:
        print(payload["event"], payload["data"])
    return {"ok": True}  # answer 2xx fast; do the real work in a queue

Errors you may hit

• not_found (404)
• token_revoked (401)
• rate_limited (429)

Gotchas

• requests does not raise on a 4xx by itself. Call response.raise_for_status() or check response.ok, otherwise a 429 send_rate_limited silently looks like a successful send and your loop keeps hammering the queue.
• json= and data= are not interchangeable. Pass json={...} so requests sets Content-Type: application/json and encodes UTF-8 for you; data= with a dict sends form encoding and the API answers 400 invalid_request.
• The default requests timeout is None, which means a stalled connection hangs your worker forever. Always pass timeout=(5, 30) and treat a read timeout as "maybe delivered" - re-check with the message id before you send again.
• A group id such as 120363000000000000@g.us is a string, not a number. Building it with an f-string from an int drops the precision and you get 404 not_found.
• Emoji and accented text need no extra work in Python 3, but reading a CSV of numbers with the default encoding on Windows will mangle them - open files with encoding="utf-8".

Where to run it

• Google Cloud Run (container, scale to zero, one revision per deploy)
• Render background worker for the sender, Render web service for the webhook receiver
• A 1 GB VPS with systemd for the worker and Caddy in front of the FastAPI receiver
• AWS Lambda + API Gateway for the webhook receiver only (the sender needs a long-lived process for queue spacing)

Pitfalls in Python

• A pandas DataFrame with the ids in a numeric column rounds them; read the list into a column of dtype str, or better, keep the ids in a plain Python list of strings.
• A PATCH sent on every run without comparing first produces a system message in the group each time, and members mute the group; compare the subject and description to the read-back and skip when equal.
• requests.get with no timeout can hang the generator on one page forever; pass timeout=(5, 30) and let a Timeout exception end the run so cron retries it later.

Frequently asked questions

Related