cumulus-message-adapter-python 1.0.8

A handler library for cumulus tasks written in python

# cumulus-message-adapter-python

[](https://circleci.com/gh/nasa/cumulus-message-adapter-python)
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## What is Cumulus?

Cumulus is a cloud-based data ingest, archive, distribution and management
prototype for NASA's future Earth science data streams.

Read the [Cumulus Documentation](https://cumulus-nasa.github.io/)

## What is the Cumulus Message Adapter?

The Cumulus Message Adapter is a library that adapts incoming messages in the
Cumulus protocol to a format more easily consumable by Cumulus tasks, invokes
the tasks, and then adapts their response back to the Cumulus message protocol
to be sent to the next task.

## Installation

```
$ pip install git+https://github.com/cumulus-nasa/cumulus-message-adapter-python.git
```

## Task definition

In order to use the Cumulus Message Adapter, you will need to create two
methods in your task module: a handler function and a business logic function.

The handler function is a standard Lambda handler function which takes two
parameters (as specified by AWS): `event` and `context`.

The business logic function is where the actual work of your task occurs. It
should take two parameters: `event` and `context`.

The `event` object contains two keys:

* `input` - the task's input, typically the `payload` of the message,
produced at runtime
* `config` - the task's configuration, with any templated variables
resolved

The `context` parameter is the standard Lambda context as passed by AWS.

The return value of the business logic function will be placed in the
`payload` of the resulting Cumulus message.

Expectations for input, config, and return values are all defined by the task,
and should be well documented. Tasks should thoughtfully consider their inputs
and return values, as breaking changes may have cascading effects on tasks
throughout a workflow. Configuration changes are slightly less impactful, but
must be communicated to those using the task.

## Cumulus Message Adapter interface

The Cumulus Message adapter for python provides one method:
`run_cumulus_task`. It takes four parameters:

* `task_function` - the function containing your business logic (as described
above)
* `cumulus_message` - the event passed by Lambda, and should be a Cumulus
Message
* `context` - the Lambda context
* `schemas` - optional: a dict with `input`, `config`, and `output` properties. Each should be a string set to the filepath of the corresponding JSON schema file. All three properties of this dict are optional. If ommitted, the message adapter will look in `/<task_root>/schemas/<schema_type>.json`, and if not found there, will be ignored.
* `taskargs` - Optional. Additional keyword arguments for the `task_function`

## Example

Simple example of using this package's `run_cumulus_task` function as a wrapper around another function:

```py
from run_cumulus_task import run_cumulus_task

# simple task that returns the event
def task(event, context):
return event

# handler that is provided to aws lambda
def handler(event, context):
return run_cumulus_task(task, event, context)
```

For a full example see the [example folder](./example).

## Creating a deployment package

Tasks that use this library are just standard AWS Lambda tasks. Information on
creating release packages is available [here](https://docs.aws.amazon.com/lambda/latest/dg/deployment-package-v2.html).

## Usage in a Cumulus Deployment

During deployment, Cumulus will automatically obtain and inject the [Cumulus Message Adapter](https://github.com/cumulus-nasa/cumulus-message-adapter) into the compiled code and create a zip file to be deployed to Lambda.

The example task in the [example folder](./example) of this repository would be configured in lambdas.yml as follows:

```yaml
PythonExample:
handler: task.handler
timeout: 300
source: './example'
useMessageAdapter: true
runtime: python2.7
memory: 256
```

## Development

### Dependency Installation

```
$ pip install -r requirements-dev.txt
$ pip install -r requirements.txt
```

### Logging with `CumulusLogger`

Included in this package is the `cumulus_logger` which contains a logging class `CumulusLogger` that standardizes the log format for Cumulus. Methods are provided to log error, fatal, warning, debug, info, and trace.

**Import the `CumulusLogger` class:**

```python
from cumulus_logger import CumulusLogger
```

**Instantiate the logger inside the task definition, name and level are optional:**

```python
logger = CumulusLogger(event, context)
```

**Use the logging methods for different levels:**

```python
logger.trace('<your message>')
logger.debug('<your message>')
logger.info('<your message>')
logger.warn('<your message>')
logger.error('<your message>')
logger.fatal('<your message>')
```

**It can also take additional non-keyworded and keyworded arguments as in Python Logger.**

The `msg` is the message format string, the `args` and `kwargs` are the arguments for string formatting.

If `exc_info` in `kwargs` is not false, the exception information in the `exc_info` or `sys.exc_info()` is added to the message.

```
logger.debug(msg, *args, **kwargs)
```

**Example usage:**

```python
import os
import sys

from run_cumulus_task import run_cumulus_task
from cumulus_logger import CumulusLogger

# instantiate CumulusLogger
logger = CumulusLogger()

def task(event, context):
logger.info('task executed')

# log error when an exception is caught
logger.error("task formatted message {} exc_info ", "bar", exc_info=True)

# return the output of the task
return { "example": "output" }

def handler(event, context):
# make sure event & context metadata is set in the logger
logger.setMetadata(event, context)
return run_cumulus_task(task, event, context)
```

### Running Tests

Running tests requires [localstack](https://github.com/localstack/localstack).

Tests only require localstack running S3, which can be initiated with the following command:

```
$ SERVICES=s3 localstack start
```

And then you can check tests pass with the following nosetests command:

```
$ CUMULUS_ENV=testing nosetests -v -s
```

### Linting

```
$ pylint run_cumulus_task.py
```

## Why?

This approach has a few major advantages:

1. It explicitly prevents tasks from making assumptions about data structures
like `meta` and `cumulus_meta` that are owned internally and may therefore
be broken in future updates. To gain access to fields in these structures,
tasks must be passed the data explicitly in the workflow configuration.
1. It provides clearer ownership of the various data structures. Operators own
`meta`. Cumulus owns `cumulus_meta`. Tasks define their own `config`,
`input`, and `output` formats.
1. The Cumulus Message Adapter greatly simplifies running Lambda functions not
explicitly created for Cumulus.
1. The approach greatly simplifies testing for tasks, as tasks don't need to
set up cumbersome structures to emulate the message protocol and can just
test their business function.

## License

[Apache 2.0](LICENSE)