Metadata-Version: 2.1
Name: volttron-threshold-detection
Version: 2.0.0rc0
Summary: The `volttron-threshold-detection` agent will publish an alert when a value published to a topic exceeds or falls below a configured value.
Home-page: https://github.com/eclipse-volttron/volttron-threshold-detection
License: Apache-2.0
Author: VOLTTRON Team
Author-email: volttron@pnnl.gov
Requires-Python: >=3.10,<4.0
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Other Audience
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Dist: volttron-core (>=2.0.0rc0)
Project-URL: Repository, https://github.com/eclipse-volttron/volttron-threshold-detection
Description-Content-Type: text/markdown

# volttron-threshold-detection

The ThresholdDetectionAgent will publish an alert when a value published to a topic exceeds or falls below a configured
value.

The agent subscribes to the topics listed in the configuration file and publishes alerts when the callback receives a
value for the point above the max (if configured) or below the min (if configured) corresponding to the point in the
configuration file.

## Requires

* python >= 3.10
* volttron >= 10.0

## Installation

Before installing, VOLTTRON should be installed and running.  Its virtual environment should be active.
Information on how to install of the VOLTTRON platform can be found
[here](https://github.com/eclipse-volttron/volttron-core).

Create a directory called `config` and use the change directory command to enter it.

```shell
mkdir config
cd config
```

After entering the config directory, create a file called `threshold_detection_config.json`, use the below JSON to populate your new file. Refer to the configuration overview if needed.

The Threshold Detection agent supports observing individual point values from their respective topics or from a device's
    all publish.  Points to watch are configured as JSON key-value pairs as follows:

* Key:  The key is the point topic for the point to watch, or the device's "all" topic if watching points from the all
publish (i.e. "devices/campus/building/device/point" or "devices/campus/building/device/all" if using the all topic)

* Value:  Using point topic: JSON object specifying the min ('threshold_min') and max ('threshold_max) threshold values
for the point.  Only one of the thresholds are required, but both may be used.

    Example:

    ```json
    {
        "point0": {
            "threshold_max": 10,
            "threshold_min": 0
        },
        "point1": {
            "threshold_max": 42
        }
    }
    ```

    Using device "all" topic:  JSON object with the key as the point name and value being the threshold object described
    above.

    Example 2:

    ```json
    {
        "devices/fake/fakedevice/all": {
            "OutsideAirTemperature1": {
                "threshold_max": 60,
                "threshold_min": 0
            },
            "OutsideAirTemperature2": {
                "threshold_max": 42
            }
        }
    }
    ```

After creating your configuration file. install and start the threshold detection agent in VOLTTRON.

```shell
vctl install volttron-threshold-detection --agent-config threshold_detection_config.json --vip-identity platform.threshold_detection --start
```

View the status of the installed agent.

```shell
vctl status
```

## Development

Please see the following for contributing guidelines [contributing](https://github.com/eclipse-volttron/volttron-core/blob/develop/CONTRIBUTING.md).

Please see the following helpful guide about [developing modular VOLTTRON agents](https://github.com/eclipse-volttron/volttron-core/blob/develop/DEVELOPING_ON_MODULAR.md)

## Disclaimer Notice

This material was prepared as an account of work sponsored by an agency of the
United States Government.  Neither the United States Government nor the United
States Department of Energy, nor Battelle, nor any of their employees, nor any
jurisdiction or organization that has cooperated in the development of these
materials, makes any warranty, express or implied, or assumes any legal
liability or responsibility for the accuracy, completeness, or usefulness or any
information, apparatus, product, software, or process disclosed, or represents
that its use would not infringe privately owned rights.

Reference herein to any specific commercial product, process, or service by
trade name, trademark, manufacturer, or otherwise does not necessarily
constitute or imply its endorsement, recommendation, or favoring by the United
States Government or any agency thereof, or Battelle Memorial Institute. The
views and opinions of authors expressed herein do not necessarily state or
reflect those of the United States Government or any agency thereof.

