git clone https://github.com/apache/openwhisk-runtime-python cd openwhisk-runtime-python
Build docker image using Python 3.7 (recommended). This tutorial assumes you're building with python 3.7. Run local_build.sh to build docker. This script takes two parameters as input
-r Specific runtime image folder name to be built, it can be one of python3Action, python39Action, python310Action, or python311Action-t The name for docker image and tag used for building the docker image. Example: action-python-v3.7:1.0-SNAPSHOTcd tutorials chmod 755 local_build.sh cd .. ./tutorials/local_build.sh -r python3Action -t action-python-v3.7:1.0-SNAPSHOT
Check docker IMAGE ID (3rd column) for repository action-python-v3.7
docker images
If the local_build.sh script is sucessful, you should see an image that looks something like:
action-python-v3.7 1.0-SNAPSHOT ...
This is required if you’re pushing your docker image to a registry e.g. dockerHub
docker tag <docker_image_ID> <dockerHub_username>/action-python-v3.7:1.0-SNAPSHOT
Run docker on localhost with either the following commands:
docker run -p 127.0.0.1:80:8080/tcp --name=bloom_whisker --rm -it action-python-v3.7:1.0-SNAPSHOT
Or run the container in the background (Add -d (detached) to the command above)
docker run -d -p 127.0.0.1:80:8080/tcp --name=bloom_whisker --rm -it action-python-v3.7:1.0-SNAPSHOT
Note: If you run your docker container in the background you'll want to stop it with:
docker stop <container_id>
Where <container_id> is obtained from docker ps command bellow
List all running containers
docker ps
or
docker ps -a
You should see a container named bloom_whisker being run and a <container_id> associated with it in the first column.
Docker image can be tested by creating functions. This documents lists creating three types of functions
Create a function (Each container can only hold one function). In this first example we'll be creating a very simple Helloworld function. Create a json file called python-data-init-run.json which will contain the function that looks something like the following:
NOTE: value of code is the actual payload and must match the syntax of the target runtime language, in this case python
{ "value": { "name" : "python-helloworld", "main" : "main", "binary" : false, "code" : "def main(args): return {'payload': 'Hello World!'}" } }
To issue the action against the running runtime, we must first make a request against the init API We need to issue POST requests to init our function This step can be run using either curl, wget, or Postman
Using curl
The option -d signifies we're issuing a POST request in curl
curl -d "@python-data-init-run.json" -H "Content-Type: application/json" http://localhost/init
Using wget
The option --post-file signifies we're issuing a POST request in wget
wget --post-file=python-data-init-run.json --header="Content-Type: application/json" http://localhost/init
Using postman
The above can also be achieved with Postman by setting the headers and body accordingly
Clientresponse should be as below
{"ok":true}
Server will remain silent in this case
Now we can invoke/run our function agains the run API with:
Using curl
POST request
curl -d "@python-data-init-run.json" -H "Content-Type: application/json" http://localhost/run
GET request
curl --data-binary "@python-data-init-run.json" -H "Content-Type: application/json" http://localhost/run
Using wget
POST request
The -O- is to redirect wget response to stdout.
wget -O- --post-file=python-data-init-run.json --header="Content-Type: application/json" http://localhost/run
GET request
wget -O- --body-file=python-data-init-run.json --method=GET --header="Content-Type: application/json" http://localhost/run
Using postman
The above can also be achieved with Postman by setting the headers and body accordingly.
The same file python-data-init-run.json from function initialization request is used to trigger(run) the function. It is not necessary nor recommended. To trigger a function we only need to pass the parameters of the function. Hence, instead in the above example, it is prefered to create a file called python-data-params.json that looks like the following:
{ "value": {} }
And trigger/run the function with the following:
curl --data-binary "@python-data-params.json" -H "Content-Type: application/json" http://localhost/run
This also works with wget and postman equivalents. Make sure you have the correct request type set and the respective body. Also set the correct headers key value pairs, which for us is “Content-Type: application/json”
After you trigger the function with one of the above commands you should expect the following client response:
{"payload": "Hello World!"}
And Server expected response:
XXX_THE_END_OF_A_WHISK_ACTIVATION_XXX XXX_THE_END_OF_A_WHISK_ACTIVATION_XXX
Note: If your container still running from the previuous example you must stop it and re-run it before proceding. Remember that each python runtime can only hold one function (which cannot be overrided due to security reasons).
Create a json file called python-data-init-params.json which will contain the function to be initialized that looks like the following:
{ "value": { "name": "python-helloworld-with-params", "main" : "main", "binary" : false, "code" : "def main(args): return {'payload': 'Hello ' + args.get('name') + ' from ' + args.get('place') + '!!!'}" } }
Also create a json file python-data-run-params.json which will contain the parameters to the function used to trigger it. Notice here we're creating 2 separate file from the beginning since this is good practice to make the disticntion between what needs to be send via the init API and what needs to be sent via the run API:
{ "value": { "name": "UFO", "place": "Mars" } }
To initialize the function make sure the python runtime container is running. If not, spin the container by following Run docker image step. Issue a POST request against the init API with the following command:
Using curl
curl -d “@python-data-init-params.json” -H “Content-Type: application/json” http://localhost/init
Using wget
wget --post-file=python-data-init-params.json --header=“Content-Type: application/json” http://localhost/init
Using postman
The above can also be achieved with Postman by setting the headers and body accordingly
Client response should be as below
{"ok":true}
Server will remain silent in this case
To run/trigger the function issue requests against the run API with the following command:
Using curl
POST request
curl -d "@python-data-run-params.json" -H "Content-Type: application/json" http://localhost/run
GET request
curl --data-binary "@python-data-run-params.json" -H "Content-Type: application/json" http://localhost/run
Using wget
POST request
The -O- is to redirect wget response to stdout.
wget -O- --post-file=python-data-run-params.json --header="Content-Type: application/json" http://localhost/run
GET request
wget -O- --body-file=python-data-run-params.json --method=GET --header="Content-Type: application/json" http://localhost/run
Using postman
The above can also be achieved with Postman by setting the headers and body accordingly.
After you trigger the function with one of the above commands you should expect the following client response:
{"payload": "Hello UFO from Mars!!!"}
And Server expected response:
XXX_THE_END_OF_A_WHISK_ACTIVATION_XXX XXX_THE_END_OF_A_WHISK_ACTIVATION_XXX
This function will calculate the nth Fibonacci number. It calculates the nth number of the Fibonacci sequence recursively in O(n) time.
def fibonacci(n, mem): if (n == 0 or n == 1): return 1 if (mem[n] == -1): mem[n] = fibonacci(n-1, mem) + fibonacci(n-2, mem) return mem[n] def main(args): n = int(args.get('fib_n')) mem = [-1 for i in range(n+1)] result = fibonacci(n, mem) key = 'Fibonacci of n == ' + str(n) return {key: result}
Create a json file called python-fib-init.json to initialize our fibonacci function and insert the following. (It’s the same code as above but since we can’t have a string span multiple lines in JSON we need to put all this code in one line and this is how we do it. It’s ugly but not much we can do here)
{ "value": { "name": "python-recursive-fibonacci", "main" : "main", "binary" : false, "code" : "def fibonacci(n, mem):\n\tif (n == 0 or n == 1):\n\t\treturn 1\n\tif (mem[n] == -1):\n\t\tmem[n] = fibonacci(n-1, mem) + fibonacci(n-2, mem)\n\treturn mem[n]\n\ndef main(args):\n\tn = int(args.get('fib_n'))\n\tmem = [-1 for i in range(n+1)]\n\tresult = fibonacci(n, mem)\n\tkey = 'Fibonacci of n == ' + str(n)\n\treturn {key: result}" } }
Create a json file called python-fib-run.json which will be used to run/trigger our function with the appropriate argument:
{ "value": { "fib_n": "40" } }
To initialize the function make sure the python runtime container is running. If not, spin the container by following Run docker image step. Initialize our fibonacci function by issuing a POST request against the init API with the following command:
Using curl
curl -d “@python-fib-init.json” -H “Content-Type: application/json” http://localhost/init
Using wget
wget --post-file=python-fib-init.json --header=“Content-Type: application/json” http://localhost/init
Using postman
The above can also be achieved with Postman by setting the headers and body accordingly
Client response should be as below
{"ok":true}
You've noticed by now that init API always returns {"ok":true} for a successful initialized function. And the server, again, will remain silent
Trigger/run the function with a request against the run API with the following command:
Using curl
POST request
curl -d "@python-fib-run.json" -H "Content-Type: application/json" http://localhost/run
GET request
curl --data-binary "@python-fib-run.json" -H "Content-Type: application/json" http://localhost/run
Using wget
POST request
The -O- is to redirect wget response to stdout.
wget -O- --post-file=python-fib-run.json --header="Content-Type: application/json" http://localhost/run
GET request
wget -O- --body-file=python-fib-run.json --method=GET --header="Content-Type: application/json" http://localhost/run
Using postman
The above can also be achieved with Postman by setting the headers and body accordingly.
After you trigger the function with one of the above commands you should expect the following client response:
{"Fibonacci of n == 40": 165580141}
And Server expected response:
XXX_THE_END_OF_A_WHISK_ACTIVATION_XXX XXX_THE_END_OF_A_WHISK_ACTIVATION_XXX
Yyou can edit python-fib-run.json and try other fib_n values. Save python-fib-run.json and trigger the function again. Notice that here we‘re just modifying the parameters of our function; therefore, there’s no need to re-run/re-initialize our container that contains our Python runtime.
You can also automate most of this process through docker actions by using invoke.py