PyDataColl can be roughly divided into three parts:
- An APIServer provides RESTful Services for client to pull/push data from/to devices and perform generic CRUD on devices, terms and items.
- A DeviceManager that manages all devices and terms connected to the system, listens messages send by APIServer that perform CRUD on devices and terms. It may be combined with some plugins to perform generic operation such as data checking, database saving and formula calculation.
- Many devices and terms under control of DeviceManager operate with coded data over communication channels(TCP/IP) so as to provide control of remote equipment(meter or sensor). Each type of Device can communicate with one type of meter with specify protocol, such as Modbus TCP, IEC 60870-5-104.
Prerequisites: PyDataColl runs on Python 3.5+. In addition to the requirements showed in requirements.txt, the following optional packages may be useful:
- Redis is heavily used by PyDataColl as NoSQL databases and IPC. If you deploy PyDataColl in local, make sure you have installed and started the Redis server.
- MySQL is used by DbSaver plugin to store device data in real-time. If you deploy PyDataColl in local, make sure you have installed and started the MySQL server.
- ujson is an ultra fast JSON encoder and decoder written in pure C with bindings for Python. This is an alternative json library and PyDataColl will use it automatically if possible.
- hiredis is a C library which can provide up to a 10x speed improvement in parsing responses from the Redis server. This is an alternative redis client and PyDataColl will use it automatically if possible.
Download the latest source code hosted on github, open a shell (CMD in Windows, Terminal in Linux and Mac OS X) and go to the source code directory, install required package using pip:
pip install -r requirements.txt
Then run the following to start PyDataColl server:
python -m pydatacoll.api_server
to stop server, press CTRL+C to exit
Visit http://localhost:8080 in browser to see the server information, if success, you will find something like this:
PyDataColl is running, available API: method: GET URL: http://localhost:8080/ method: GET URL: http://localhost:8080/api/v1/device_protocols method: GET URL: http://localhost:8080/api/v1/devices (...more omitted)
Congratulations! The server is running now. You can send request to server with your favorite http client! check RESTful API to see the API list.
Platforms: PyDataColl should run on any Unix-like platform, although for the best performance and scalability only
epoll) and BSD (with
kqueue) are recommended for production deployment (even though Mac OS X is
derived from BSD and supports kqueue, its networking performance is generally poor so it is recommended only for
development use). PyDataColl will also run on Windows, although this configuration is not officially supported and is
recommended only for development use.
This documentation is also available in PDF formats.
PyDataColl is offered under the Apache 2 license.