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This guide is meant to shed more clarity on how python methods are defined and used on the C3 AI Suite. For now, this is primarily a discussion about ActionRuntimes and how they can affect the execution of your Python methods, as well as how to define them.

Python Action Runtimes

Whenever the C3 AI Suite runs a python method, it first loads an associated 'ActionRuntime' and runs python within that. Essentially, an ActionRuntime is a conda virtual environment. To define a new ActionRuntime, you must provide an action runtime definition in the seed data of your C3 package. An ActionRuntime definition is a .json file with the following format displayed with the following example:

Code Block
{
  "id": "py-deepLearning" ,
  "name": "py-deepLearning",
  "connector": "remote",
  "language": "Python",
  "runtime": "CPython",
  "runtimeVersion": "3.6",
  "modules": {
    "conda.numpy": "=1.15.2",
    "conda.cython": "=0.29.12",
    "conda.scikit-learn": "=0.21.2",
    "conda.scipy": "=1.2.1",
    "conda.pip": "=10.0.1",
    "conda.ply": "=3.11",
    "conda.pandas": "=0.22.0",
    "conda.openblas": "=0.3.6",
    "conda.matplotlib": "=3.1.0",
    "conda.dill": "=0.2.8.2",
    "pip.tensorflow": "==1.9.0",
    "pip.slimit": "==0.8.1",
    "pip.jsonpickle": "==1.2",
    "pip.js2py": "==0.66",
    "pip.treeinterpreter": "==0.2.2",
    "pip.eli5": "==0.9.0",
    "pip.nltk": "==3.2.4",
    "conda.libgfortran": "=3.0",
    "pip.textblob": "==0.12.0"        
  },
  "repositories": [
    "https://repo.continuum.io/pkgs/main",
    "https://artifacts.c3-e.com/v1/anaconda",
    "conda-forge"
  ]
}

Here, we are using the .json format to define a new instance of the ActionRuntime type Type which will be created when you provision your package. ( See the DTI Guide to C3 : Data Integration on C3 AI Suite for more about the .json seed data format).

We'll dwell on some Some important fields .are:

  • runtimeVersion: This field specifies the version of python to use. Currently, the latest supported python is 3.6.
  • modules: This is a dictionary defining packages and their requested versions. Any conda package should be specified like 'conda.<package_name>'. Then the version is specified with "=<version>". Any pip package should be specified like 'pip.<package_name>', then the version is specified with "==<version>". The difference in the version specification is down to the difference between how conda and pip expect version specifications on the command line. For conda, this is '<package>=<version>'. For pip, this is '<package>==<version>'.
  • repositories: This field contains a list of conda repository names or urlsURLs.

...

Checking Your Defined ActionRuntimes

You can check what ActionRuntimes are already defined on your C3 clusterCluster. The type Type CondaActionRuntime defines the method 'requirementsFileForLanguage' which allows you to get a dictionary linking ActionRuntime names with their requirements files.

In the Static Console, you can do the followingrun:

Code Block
languagejs
var res = CondaActionRuntime.requirementsFilesForLanguage('Python');
for (k in res) {
  console.log(k);
}

And Or via a python connection:

Code Block
res = c3.CondaActionRuntime.requirementsFilesForLanguage('Python')
for k in res:
  print(k)

Additionally, the DTI C3DTI provide the 'provision-action-runtime.py' helper script. This is available in the c3-helper-scripts github repository here: https://github. com/c3aidti/c3-helper-scripts Once you download this repository, the `provision`provision-action-runtime.py` py` script can used to list action runtimes as follows:

Code Block
python provision-action-runtime.py --server <vanity_url> --tenant <tenant> --tag <tag> --list

...

Inspect Installed Packages for an ActionRuntime

We can also inspect the installed packages for a given action runtime by looking at the 'value' of the appropriate key. For example, in JavaScript, we have:

Code Block
var res = CondaActionRuntime.requirementsFilesForLanguage('Python')
console.log(res['py-mlutils_1_0_0'])

...

Code Block
#conda env create --file requirements.yaml
name: py-mlutils_1_0_0
channels:
- https://repo.continuum.io/pkgs/main
dependencies:
- dill=0.2.8.2
- numpy=1.15.2
- pandas=0.23.4
- python-dateutil
- python=3.6

We get the same thing by running the following in Python.Or in python:

Code Block
res = c3.CondaActionRuntime.requirementsFilesForLanguage('Python')
print(res['py-mlutils_1_0_0'])

Specifying

...

ActionRuntime

...

Method

When defining a new python method on a Type, we specify the ActionRuntime environment with the `py` annotation. For example, consider the method 'getFileSourceSpec' in the IDXFile type Type in the mnistExample: https://github.com/c3aidti/mnistExample

Code Block
@py(env='idxfile')
getFileSourceSpecPreprocess: member function(serializedPreprocessor: string, preprocessFuncName: string, enableLocalClientStorage: boolean = true): !FileSourceSpec py server

Here, we see the 'py' annotation being used with the parameter 'env'. This paramter parameter contains the string 'idxfile'. This means the 'getFileSourceSpecPreprocess' function will be run with the 'py-idxfile' ActionRuntime Environmentenvironment.

Inline Python Methods

Methods can be implemented as 'inline' (see 'Inline Methods' here: https://developer.c3.ai/docs/7.12.17/topic/methods ). In the context of Python methods, this means if you're currently executing the function from a Python context, the method will be executed in your current python context.

This means if you define an inline python method which requires specific packages not normally available, the method will fail if your context doesn't have the necessary packages.

...

Additional Resources