Tale Distributed Transactions
What?
Tale is a small library to help write a "distributed transaction like" object across a number of services. It's loosely based on the saga pattern. A good intro is available on the couchbase blog: https://blog.couchbase.com/saga-pattern-implement-business-transactions-using-microservices-part/
Installation
pipenv install talepyExample Usage
An example use case of this would be some holiday booking software broken down into a few services.
Assuming we have the following services: Flight booking API, Hotel booking API, and a Customer API.
We'd write the following steps:
from talepy.steps import Step
class DebitCustomerBalance(Step):
def __init__(self):
self.payment_client= {}
def execute(self, state):
state['payment_id'] = self.payment_client.bill(state.customer_id, state.payment_amount)
return state
def compensate(self, state):
self.payment_client.refund(state['payment_id'])
and so on for any of the steps needed. Then in whatever is handling the user's request a distributed transaction can be built:
from talepy import run_transaction
run_transaction(
steps=[
DebitCustomerBalance(),
BookFlight(),
BookHotel(),
EmailCustomerDetailsOfBooking()
],
starting_state={}
)If any step along the way fails then the compensate method on each step is called in reverse order until everything is undone.
Steps as Lambdas
For some cases you may not want to create a class for the step. Lambdas can be used directly instead. Extending the previous example:
from talepy import run_transaction
run_transaction(
steps=[
DebitCustomerBalance(),
BookFlight(),
lambda _: print("LOG -- The flight has been booked"),
BookHotel(),
EmailCustomerDetailsOfBooking()
],
starting_state={}
)This new print statement will now execute following a success in BookFlight.
It's also possible to implement compensations by adding another lambda as a tuple pair:
from talepy import run_transaction
run_transaction(
steps=[
DebitCustomerBalance(),
BookFlight(),
(
lambda _: print("LOG -- The flight has been booked"),
lambda _: print("LOG -- ┌[ ಠ ▃ ಠ ]┐ something went wrong")
),
BookHotel(),
EmailCustomerDetailsOfBooking()
],
starting_state={}
)Automatic retries
You may also want to try a step a few times before giving up. A convinence function is provided to help out with this. Starting with the initial example. If the hotel booking step is a bit unreliable and we want to try it 3 times:
from talepy import run_transaction
from talepy.retries import attempt_retries
run_transaction(
steps=[
DebitCustomerBalance(),
BookFlight(),
attempt_retries(BookHotel(), times=2),
EmailCustomerDetailsOfBooking()
],
starting_state={}
)The book hotel step will now be executed 3 times before the transaction is aborted. Once all these attempts fail the normal compensation logic will be applied.
Async
If you want to make use of async in your steps you will need to import run_transaction
from talepy.async_transactions. This can be awaited on and allows async steps and
compensations. In addition you can also run_concurrent_transaction where all
steps will be executed concurrently. The downside here is that the ordering
of the steps isn't guaranteed. This means all steps receive the same starting state.
example
from talepy.async_transactions import run_transaction
from talepy.steps import Step
class AsyncBookFlight(Step):
async def execute(self, state):
# do something
return state
async def compensate(self, state):
# revert something
pass
await run_transaction(
step_defs=[
DebitCustomerBalance(),
AsyncBookFlight(),
EmailCustomerDetailsOfBooking()
],
starting_state={}
)Concurrent example
from talepy.async_transactions import run_concurrent_transaction
from talepy.steps import Step
class AsyncBookFlight(Step):
async def execute(self, state):
# do something
return state
async def compensate(self, state):
# revert something
pass
await run_concurrent_transaction(
steps=[
DebitCustomerBalance(),
AsyncBookFlight(),
EmailCustomerDetailsOfBooking()
],
starting_state={}
)Testing / Development
TODO