fdk 0.0.33

Function Developer Kit for Python

FN development kit for Python
=============================

Purpose of this library to provide simple interface to parse HTTP 1.1 requests represented as string

Following examples are showing how to use API of this library to work with streaming HTTP requests from Fn service.

Handling Hot JSON Functions
---------------------------

A main loop is supplied that can repeatedly call a user function with a series of HTTP requests.
In order to utilise this, you can write your `app.py` as follows:

```python
import fdk


def handler(context, data=None, loop=None):
return data


if __name__ == "__main__":
fdk.handle(handler)

```

Unittest your functions
--------------------------

As you may be aware [Fn CLI](https://github.com/fnproject/cli) offers a very first compatibility barrier between your code and Fn server
by allowing developers to perform black-box testing using the following CLI call with a function's folder:
```bash
fn test
```

This CLI call depends on `test.json` file that contains an input and the output data for the black-box testing.

Starting v0.0.33 FDK-Python provides a testing framework that allows performing unit tests of your function's code.
The framework is an extension to [testtools](https://testtools.readthedocs.io/en/latest/) testing framework, coding style remain the same, so, write your tests as you've got used to.
Here's the example of the test suite:
```python
import fdk
import ujson

from fdk import fixtures


def handler(ctx, data=None, loop=None):
name = "World"
if data and len(data) > 0:
body = ujson.loads(data)
name = body.get("name")
return {"message": "Hello {0}".format(name)}


class TestFuncWithData(fixtures.FunctionTestCase):
content = ujson.dumps({"name": "John"})

def setUp(self):
super(TestFuncWithData, self).setUp(
self.content, handler, fn_format="json")

def tearDown(self):
super(TestFuncWithData, self).tearDown()

def test_response_with_data(self):
def assert_data(data):
return {"message": "Hello John"} == data

self.assertResponseConsistent(
assert_data,
message="content must be equal to '{0}'"
.format({"message": "Hello John"})
)


class TestFuncWithoutData(fixtures.FunctionTestCase):
content = ""

def setUp(self):
super(TestFuncWithoutData, self).setUp(
self.content, handler, fn_format="cloudevent")

def tearDown(self):
super(TestFuncWithoutData, self).tearDown()

def test_response_without_data(self):

def assert_data(data):
return {"message": "Hello World"} == data

self.assertResponseConsistent(
assert_data,
message="content must be equal to '{0}'"
.format({"message": "Hello World"})
)


if __name__ == "__main__":
fdk.handle(handler)

```

As you may see, the framework provides new assertion methods like:

* assertInHeaders - allows asserting header(s) presence in response
* assertInTime - allows asserting the time necessary for a function to finish
* assertNotInTime - allows asserting the time within a function was not able to finish
* assertResponseConsistent - allows asserting function's response content consistency by accepting a callable object that must return a boolean value that states the consistency


In order to run tests, use the following command:
```bash
pytest -v -s --tb=long func.py
```

```bash
$ pytest -v -s --tb=long func.py
======================================================================================= func session starts ========================================================================================
platform darwin -- Python 3.6.2, pytest-3.7.1, py-1.5.4, pluggy-0.7.1 -- /usr/bin/python3.6
cachedir: .pytest_cache
rootdir: /func, inifile:
plugins: cov-2.4.0
collected 1 item

func.py::TestFuncWithData::test_in_time PASSED
func.py::TestFuncWithData::test_response_with_data PASSED
func.py::TestFuncWithoutData::test_in_time PASSED
func.py::TestFuncWithoutData::test_response_without_data PASSED


===================================================================================== 1 passed in 0.11 seconds =====================================================================================
```

To add coverage first install one more package:
```bash
pip install pytest-cov
```
then run tests with coverage flag:
```bash
pytest -v -s --tb=long --cov=func func.py
```

```bash
$ pytest -v -s --tb=long func.py
======================================================================================= func session starts ========================================================================================
platform darwin -- Python 3.6.2, pytest-3.7.1, py-1.5.4, pluggy-0.7.1 -- /usr/bin/python3.6
cachedir: .pytest_cache
rootdir: /func, inifile:
plugins: cov-2.4.0
collected 1 item

func.py::TestFuncWithData::test_in_time PASSED
func.py::TestFuncWithData::test_response_with_data PASSED
func.py::TestFuncWithoutData::test_in_time PASSED
func.py::TestFuncWithoutData::test_response_without_data PASSED


---------- coverage: platform darwin, python 3.6.2-final-0 -----------
Name Stmts Miss Cover
-----------------------------
func.py 31 1 97%


===================================================================================== 1 passed in 0.17 seconds =====================================================================================
```



If you'd like to add more assertions to an upstream - please open an issue.


Applications powered by Fn: Concept
-----------------------------------

FDK is not only about developing functions, but providing necessary API to build serverless applications
that look like nothing but classes with methods powered by Fn.

```python
import requests

from fdk.application import decorators


@decorators.fn_app
class Application(object):

def __init__(self, *args, **kwargs):
pass

@decorators.with_fn(fn_image="denismakogon/fdk-python-echo:0.0.1")
def env(self, fn_data=None, **kwargs):
return fn_data

@decorators.fn(fn_type="sync")
def square(self, x, y, *args, **kwargs):
return x * y

@decorators.fn(fn_type="sync", dependencies={
"requests_get": requests.get
})
def request(self, *args, **kwargs):
requests_get = kwargs["dependencies"].get("requests_get")
r = requests_get('https://api.github.com/events')
r.raise_for_status()
return r.text


if __name__ == "__main__":
app = Application(config={})

res, err = app.env()
if err:
raise err
print(res)

res, err = app.traceback()
if err:
raise err
print(res)

res, err = app.square(10, 20)
if err:
raise err
print(res)

res, err = app.request()
if err:
raise err
print(res)

```
In order to identify to which Fn instance code needs to talk set following env var:

```bash
export FN_API_URL = http://localhost:8080
```
with respect to IP address or domain name where Fn lives.


Applications powered by Fn: supply data to a function
-----------------------------------------------------

At this moment those helper - decorators let developers interact with Fn - powered functions as with regular class methods.
In order to pass necessary data into a function developer just needs to do following
```python

if __name__ == "__main__":
app = Application(config={})

app.env(keyone="blah", keytwo="blah", somethingelse=3)

```
Key - value args will be turned into JSON instance and will be sent to a function as payload body.


Applications powered by Fn: working with function's result
----------------------------------------------------------

In order to work with result from function you just need to read key - value argument `fn_data`:
```python
@decorators.with_fn(fn_image="denismakogon/py-traceback-test:0.0.1",
fn_format="http")
def traceback(self, fn_data=None):
return fn_data
```

Applications powered by Fn: advanced serverless functions
---------------------------------------------------------

Since release v0.0.3 developer can consume new API to build truly serverless functions
without taking care of Docker images, application, etc.

```python
@decorators.fn(fn_type="sync")
def square(self, x, y, *args, **kwargs):
return x * y

@decorators.fn(fn_type="sync", dependencies={
"requests_get": requests.get
})
def request(self, *args, **kwargs):
requests_get = kwargs["dependencies"].get("requests_get")
r = requests_get('https://api.github.com/events')
r.raise_for_status()
return r.text
```

Each function decorated with `@decorator.fn` will become truly serverless and distributed.
So, how it works?

* A developer writes function
* FDK(Fn - powered app) creates a recursive Pickle v4.0 with 3rd - party dependencies
* FDK(Fn - powered app) transfers pickled object to a function based on Python3 GPI(general purpose image)
* FDK unpickles function and its 3rd - party dependencies and runs it
* Function sends response back to Fn - powered application function caller

So, each CPU - intensive functions can be sent to Fn with the only load on networking(given example creates 7kB of traffic between app's host and Fn).


Applications powered by Fn: exceptions
--------------------------------------

Applications powered by Fn are following Go - like errors concept. It gives you full control on errors whether raise them or not.
```python
res, err = app.env()
if err:
raise err
print(res)

```
Each error is an instance fn `FnError` that encapsulates certain logic that makes hides HTTP errors and turns them into regular Python - like exceptions.