Python Scripts

Python scripts run using Python 3 in a subprocess. The following packages are pre-installed system-wide:

Package	Version	Use case
pandas	Latest	Data manipulation, CSV/Excel processing
openpyxl	Latest	Excel file reading and writing

Standard library modules are fully available (json, urllib, datetime, os, re, etc.).

Injected variables

Auth headers and payload are passed via environment variables:

Env variable	Description
AUTH_HEADERS	JSON string of auth headers — parse with json.loads()
TASK_PAYLOAD	Webhook or MQTT payload string (if triggered by one)

Example: call a REST API

import json
import os
import urllib.request

auth_headers = json.loads(os.environ.get('AUTH_HEADERS', '{}'))

req = urllib.request.Request(
    'https://api.example.com/users',
    headers=auth_headers
)

with urllib.request.urlopen(req) as resp:
    users = json.loads(resp.read())

print(f"Found {len(users)} users")
active = [u for u in users if u.get('active')]
print(f"Active: {len(active)}")
print(json.dumps(active, indent=2))

Example: process CSV data with pandas

import json
import os
import pandas as pd
import urllib.request
import io

auth_headers = json.loads(os.environ.get('AUTH_HEADERS', '{}'))

# Download a CSV report
req = urllib.request.Request(
    'https://api.example.com/reports/daily.csv',
    headers=auth_headers
)

with urllib.request.urlopen(req) as resp:
    df = pd.read_csv(io.StringIO(resp.read().decode('utf-8')))

print(f"Rows: {len(df)}")
print(f"Columns: {list(df.columns)}")

summary = df.groupby('category')['amount'].sum()
print(summary.to_string())

Example: process Excel with openpyxl

import openpyxl
import urllib.request
import io
import json
import os

auth_headers = json.loads(os.environ.get('AUTH_HEADERS', '{}'))

req = urllib.request.Request(
    'https://api.example.com/export.xlsx',
    headers=auth_headers
)

with urllib.request.urlopen(req) as resp:
    wb = openpyxl.load_workbook(io.BytesIO(resp.read()))

ws = wb.active
print(f"Sheet: {ws.title}, rows: {ws.max_row}")

for row in ws.iter_rows(min_row=2, values_only=True):
    print(row)

Logging

Python scripts use print() for output — all stdout is captured and shown as INFO level in the run log. Write to stderr for ERROR level:

import sys

print("This is INFO level")
print("This is also INFO level")
print("This is ERROR level", file=sys.stderr)