aiolago
Unofficial Asyncronous Python Client for Lago
Latest Version:
Official Client
Features
- Unified Asyncronous and Syncronous Python Client for Lago
- Supports Python 3.6+
- Strongly Typed with Pydantic
- Includes Function Wrappers to quickly add to existing projects
- Utilizes Environment Variables for Configuration
Installation
pip install aiolago
pip install git+https://github.com/GrowthEngineAI/aiolago.git
Usage
WIP - Simple Usage Example
import asyncio
from aiolago import Lago
from aiolago.utils import logger
"""
Environment Vars that map to Lago.configure:
all vars are prefixed with LAGO_
LAGO_API_KEY (apikey): str
LAGO_URL (url): str takes precedence over LAGO_SCHEME | LAGO_HOST | LAGO_PORT
LAGO_SCHEME (scheme): str - defaults to 'http://'
LAGO_HOST (host): str - defaults to None
LAGO_PORT (port): int - defaults to 3000
LAGO_API_PATH (api_path): str - defaults to '/api/v1'
LAGO_TIMEOUT (timeout): int - defaults to 10
LAGO_IGNORE_ERRORS (ignore_errors): bool = defaults to False
"""
Lago.configure(
api_key = '...',
url = '',
)
customer_id = "gexai_demo"
metric_name = "Demo API Requests"
metric_id = "demo_requests"
plan_name = "Demo Plan"
plan_id = "demo_plan"
async def create_demo_customer():
customer = await Lago.customers.async_create(
external_id = customer_id,
email = f"{customer_id}@growthengineai.com",
billing_configuration = {
"tax_rate": 8.25,
},
)
logger.info(f'Created Customer: {customer}')
return customer
flat_rate = 0.021
volume_rate = 0.025
base_rate = 0.023
rates = {
'volume': [
{
'from_value': 0,
'to_value': 2500,
'flat_amount': '0',
'per_unit_amount': str(round(volume_rate, 5)),
},
{
'from_value': 2501,
'to_value': 10000,
'flat_amount': '0',
'per_unit_amount': str(round(volume_rate * .8, 5)),
},
{
'from_value': 10001,
'flat_amount': '0',
'per_unit_amount': str(round(volume_rate * .5, 5)),
},
],
'graduated': [
{
'to_value': 2500,
'from_value': 0,
'flat_amount': '0',
'per_unit_amount': str(round(base_rate, 5)),
},
{
'from_value': 2501,
'flat_amount': '0',
'per_unit_amount': str(round(base_rate * .75, 5)),
},
],
}
def create_charge(
metric_id: str,
name: str = 'volume'
) -> Charge:
if name in {'volume', 'graduated'}:
return Charge(
billable_metric_id = metric_id,
charge_model = name,
amount_currency = 'USD',
properties = {
f'{name}_ranges': rates[name],
}
)
return Charge(
billable_metric_id = metric_id,
charge_model = name,
amount_currency = 'USD',
properties = {
'amount': rates[name]
},
)
async def create_metric() -> BillableMetricResponse:
"""
The upsert logic creates a new metric if it doesn't exist.
"""
return await Lago.billable_metrics.async_upsert(
resource_id = metric_id,
name = metric_name,
code = metric_id,
description = 'Demo API Requests',
aggregation_type = "sum_agg",
field_name = "consumption"
)
async def create_plan() -> Plan:
plan = await Lago.plans.async_exists(
resource_id = plan_id,
)
if not plan:
metric = await create_metric()
plan_obj = Plan(
name = plan_name,
amount_cents = 0,
amount_currency = 'USD',
code = plan_id,
interval = "monthly",
description = "Demo API Plan",
pay_in_advance = False
)
for rate in rates:
charge = create_charge(
name = rate,
metric_id = metric.resource_id,
)
plan_obj.add_charge_to_plan(charge)
plan = await Lago.plans.async_create(plan_obj)
logger.info(f'Created Plan: {plan}')
return plan
async def run_test():
plan = await create_plan()
asyncio.run(run_test())