Metadata-Version: 2.1
Name: cloudio-connector-python
Version: 1.1.0
Summary: Helper to create python cloudio applications
Author-email: Martin Meyer <meyer.mart@outlook.com>
License: MIT License        
        Copyright (c) 2022 Institute of Sustainable Energy, HES-SO Valais        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.        
Project-URL: Homepage, http://cloudio.hevs.ch/
Project-URL: Repository, https://github.com/cloudio-project/cloudio-connector-python
Keywords: cloudio,cloud.io,application,connector
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: requests
Requires-Dist: cbor
Requires-Dist: paho-mqtt

# cloudio-connector-python
This library is a helper to create python cloudio **applications**.

The cloudio project: http://cloudio.hevs.ch/

## The cloud.iO three layers
Cloud.iO is composed of 3 layers:

![alt text](https://github.com/cloudio-project/cloudio-connector-python/blob/develop/doc/images/three_layers.PNG?raw=true)

- The endpoints: distributed field devices that mainly measures and actuate things.
- Cloudio services: the cloud.iO server that communicate with the endpoints, stores the data and provide a http rest api to the applications.
- **The applications**: data analysis, controls the endpoint setpoints, ...

**This library is used to create applications.**

## The cloud.iO data model
Here is a quick reminder of the cloud.iO data model:
![alt text](https://github.com/cloudio-project/cloudio-connector-python/blob/develop/doc/images/data_model.PNG?raw=true)

**Note: You can have objects in objects, that's why an object list is needed to create an AttributeId.**

You can get the data model of an endpoint:
```
cc = CloudioConnector("https://example.com", "user", "password")

sp = cc.get_endpoint_structure('ba3d3ec2-23b6-45a8-827a-3b3133a69076')   
```

## Read/Write attributes
### Example
```
cc = CloudioConnector("https://example.com", "user", "password")

sp = AttributeId(uuid='ba3d3ec2-23b6-45a8-827a-3b3133a69076', node='myNode', 
                    objects=['myObject'], attribute='mySetPoint')
mea = AttributeId(uuid=cc.get_uuid('demo'), node='myNode', 
                    objects=['myObject'], attribute='myMeasure')

# get the last value of an attribute
last_val = cc.get_last_value(mea)
print(str(mea) + ' ' + str(last_val))

# get the mean value of the last 15 minutes
mean = cc.get_mean_value(mea, 15*60)

# write the value of an attribute
cc.write_value(sp, 1.0)      
```
## Get attributes time series
### Example
```
cc = CloudioConnector("https://example.com", "user", "password")

sp = AttributeId(uuid='ba3d3ec2-23b6-45a8-827a-3b3133a69076', node='myNode', 
                    objects=['myObject'], attribute='mySetPoint')
mea = AttributeId(uuid=cc.get_uuid('demo'), node='myNode', 
                    objects=['myObject'], attribute='myMeasure')

tm_mea = TimeSeries(mea, start=datetime.now() - datetime.timedelta(hours=24), 
                    stop=datetime.now(), resample='15m')
tm_sp = TimeSeries(sp, start=datetime.now() - datetime.timedelta(hours=24), 
                    stop=datetime.now(), resample='15m')

# get attribute time series
data = cc.get_time_series(tm_mea)
# data is the same as tm_mea.data

# convert cloudio time series to panda data frame
cc.data_frame(data, serie_name="My Measure")

# get multiple time series with multithreading
cc.get_multiple_time_series([tm_mea, tm_sp])
print(tm_mea.data)
print(tm_sp.data)
```
## Get notified for attribute new value
### Example
```
class Example(AttributeListener):
    def __init__(self):
        cc = CloudioConnector("https://example.com", "user", "password")
        cc.add_attribute_listener(self)

        attr = AttributeId(uuid=cc.get_uuid('demo'), node='myNode', 
                            objects=['myObject'], attribute='myMeasure'),
        
        # subscribe to attribute on change event
        cc.subscribe_to_attribute(attr)
        
    # this method is called when a subscribed attribute has changed
    def attribute_has_changed(self, attribute: AttributeId, value):
        print(str(attribute) + ' ' + str(value))
```
