databear 1.2.0

A Python based data logger

DataBear

General purpose data aquistion, processing, and logging platform written in Python. DataBear is hardware independent, but is meant to be easily integrated via a custom hardware interface provided by the user.

Goals:

• Easy to use - intuitive setup and configuration.
• Versatile
  • Use on any hardware device that runs Python.
  • Compatible with most sensor output.
• Extendible
  • User can integrate platform with new sensor and methods.

Some potential usage scenarios:

Here are some random ideas to give a sense for DataBear capabilities (some capabilities under development).

• Run DataBear on a Raspberry Pi (https://www.raspberrypi.org/) to read a Modbus temperature sensor. The sensor could be connected to a USB port on the Pi via an RS485 to USB converter and data could be read every second, averaged, and stored to CSV.
• Integrate DataBear into an existing Linux based measurement platform, such as the Dyacon MDL-700 (https://dyacon.com). In this case, DataBear is utilized by pyMDL (https://github.com/dyacon/pyMDL) to schedule measurement and storage, while pyMDL specifies hardware configuration.

Ideal Datalogger Features vs Data Bear 1.2

Ideal Feature	Data Bear
Adjustable sampling rates for all measurements	☑
Concurrent measurement of all sensors
Adjustable rates of data storage	☑
Store metadata associated with data values	☑
Supports polled or continuously streaming sensors	☑

Installation

• pip install databear

Usage

1. Check to see if a class has been created for your sensor(s) in DataBear/sensors. Since this project is new, it is likely you will need to create a sensor class or modify an existing one (See "Sensor Class Interface").
2. Create a class for your sensor(s) following the interface defined below. Use existing classes as examples or templates. Share your sensor class with the DataBear project so others can use it.
3. Create a new configuration file following the example shown in config.yaml.
4. Create a short script to initialize and run DataBear. This script will register your sensor(s) class with DataBear and load the configuration file. See example.py for details.

Sensor Class Interface (V0.1)

Class Name: (Format optional but recommended)

• <manufacturer><Model> Example - class dyaconWSD2:

Instantiation (Mandatory)

• Inputs:
  • ‘name’ - [string] User configurable sensor name
  • ‘settings’ - [dictionary] A dictionary of settings that are necessary for mandatory methods and attributes.
• Attributes:
  • sn - [string] Sensor serial number specified in ‘settings’.
  • frequency - [float] Sensor measurement frequency in seconds specified in ‘settings’ dictionary.
  • maxfrequency - [float] Maximum frequency in seconds that the sensor can measure.
  • data - [dictionary] Stores data for each measurement.
    • Initialize to {<key>: [ ] , ...} where <key> is the name of each measurement.
  • Any other sensor specific setting.
    • For example, some sensors/hardware may require certain settings like 'serial protocol' and 'duplex'.
• Errors
  • A sensorConfigError should be raised if there is a missed setting.

Methods (Mandatory)

• ‘measure( )’ - Implements coding required to obtain data for each measurement.

  • No inputs
  • Data for each measurement is added to the ‘data’ attribute.
  • Data should consist of a tuple of the form (<timestamp>,<datavalue>)
    • data[<measurement name>] = (<timestamp>,<datavalue>)

• 'getdata(name, startdate, enddate)' - Retrieves data from the 'data' dictionary for a measurement

  • Return - [(timestamp,value),(timestamp,value),...]

• ‘cleardata(name, startdate, enddate)’ - Clears data associated with a given measurement.