pyseapc 0.0.4
SE APC external Python interface
Requires Python: >=3.9

# Python SDK for Schneider Electric EcoStruxure Automation Expert Advanced Process Control

This package allows user Python installations to interact with Schneider Electric EcoStruxure Automation Expert Advanced Process Control (APC) as an external Python environment. This extends the functionality of the APC director environment native Python environments including the ability to import popular AI, optimization and analysis packages. 

## Installation with an internet connection
For machines with an internet connection simply run the following command from the machine hosting the Python environment to install this package and all dependencies.

`pip install pyseapc`

## Installing without and internet connection
The process of installing `pyseapc` on machines without a direct internet connection requires three steps: Downloading the package and dependencies on a machine with internet, transfering the files to the target machine, and installing the package and dependencies on the target machine.

1. Downloading the packages on an internet-connected machine
    This process must be done from a machine with the same operating system, Python version and CPU architecture as the target machine that will be running the external Python environment. This is because some of the dependencies have different installationg files depending the the target machine configuration. Docker containers or virtual machines can be quite useful for this if finding an internet-connected machine with the specifications is difficult.
On the internet-connected machine create a raw text file (.txt) name “requirements.txt” and paste the following contents into that file. Notepad or similar is useful for this. Do not use MS Word.

```
cffi==1.17.1
cryptography==45.0.5
grpcio==1.73.1
grpcio-tools==1.73.1
protobuf==6.31.1
pycparser==2.22
pyseapc==0.0.1
pyOpenSSL==25.1.0
setuptools==80.9.0
typing_extensions==4.14.1
```

Run the following command from the directory containing “requirements.txt”: 

`pip wheel -r requirements.txt --wheel-dir wheelhouse`

This will create a directory named “wheelhouse” that contains the proper versions and architectures for all the necessary dependencies.

2.  Transferring the packages to the target machine

Copy  requirements.txt and wheelhouse to the target machine using whatever secure method required.

3.  Installing the packages on the target machine

Run the following command on the target machine from the directory containing wheelhouse and requirements.txt. 

`pip install --no-index --find-links=./wheelhouse -r requirements.txt`

Test running a Python script with `import pyseapc`. If this import succeeds, the offline installation was successful.

## Examples
A sample Python script is given below:

```python
import pyseapc
import numpy

def user_method(inputs: dict):
    result = {
        'average': np.mean(data['cv1']),
        'stddev': np.std(data['cv1']),
        'min': np.min(data['cv1']),
        'max': np.max(data['cv1']),
    }
    return result

app = pyseapc.ExternalPythonEnvironment(user_method, generate_ssl_keys=True)
app.start(5001)
```

The corresponding Director code:
```python
apcglobal(cvValues = [])
controllerName = "DRYER"
cvTags = GetTagList(controllerName, "ControlledVariable")
serverAddress = "https://localhost:5001"

cvValues.append(GetControllerAttributes(controllerName, "OutletAirTemp", "ControlledVariable", "ProcessValue"))

cert = '''-----BEGIN CERTIFICATE-----
Copy of the public certificate here as printed by the Python process
-----END CERTIFICATE-----'''

results = CallRemotePython({'values': cvValues}, serverAddress, cert)

# A specific time can also be set
# results = CallRemotePythonWithTimeout({'values': cvValues}, serverAddress, cert, 5)
print "Rolling Statistical Values:", results

```

Additional examples and documentation are available with the documentation distributed with APC.