PyeDNA

PyeDNA ("pie-dee-en-ay") is a Python wrapper library for the C++ EzDnaApi, written for data analysts who wish to work with eDNA data in the context of a pandas DataFrame. By converting eDNA data into a DataFrame, data analysis can be accomplished using familiar tools like scikit-learn, statsmodels, etc. New functions will be added upon request.

Disclaimer

PyeDNA is a wrapper library for the API of a data historian called eDNA. eDNA is developed by InStepSoftware, LLC (http://www.instepsoftware.com/), who holds all rights to the eDNA software. PyeDNA does not contain any proprietary code, and is merely a wrapper for functions that must be obtained from a legal, licensed version of EzDnaApi.dll.

This is fan-supported project and is not affiliated in any way with InStepSoftware, LLC. The maintainer enjoys working with eDNA and wishes them the best. :)

Getting Started

PyeDNA currently requires that a legal, licensed version of the EzDnaApi be located in the following directory:

C:\Program Files (x86)\eDNA\EzDnaApi64.dll

Currently, only the 64-bit version of eDNA is supported. Python 2 is not supported.

Required libraries: numba, numpy, pandas

PyeDNA can be installed using pip:

pip install pyedna

Documentation

Current documentation can be found here.

Basic Examples

All of the core data pulling functions are located in the GetHist function, which will return a pandas DataFrame with the timestamp, value, and status columns. For example, the following code will pull snap data from TESTPNT1 over a 30-second interval:

import pyedna.ezdna as dna

tag = "TESTSITE.TESTSERVICE.TESTPNT1" # format site.service.tag

start = "12/01/16 01:01:01" # format mm/dd/yy hh:mm:ss

end = "01/03/17 01:01:01" # format mm/dd/yy hh:mm:ss

period = "00:00:30" # format hh:mm:ss

df = dna.GetHist(tag, start, end, period=period, mode="snap")

Raw data may be obtained from TESTPNT1 using:

df = dna.GetHist(tag, start, end, mode="raw")

Other supported pull types include Average, Interpolated, Max, and Min. Please refer to eDNA documentation for more description about these pull types.

Multiple tags can be pulled (in Raw mode) at the same time using:

tags = ["TESTSITE.TESTSERVICE.TESTPNT1", "TESTSITE.TESTSERVICE.TESTPNT2", "TESTSITE.TESTSERVICE.TESTPNT3", "TESTSITE.TESTSERVICE.TESTPNT4"]

df = dna.GetMultipleTags(tags, start, end)

A list of connected services may be obtained using GetServices:

services = dna.GetServices()

A list of point information for a given service can be found using GetPoints:

points = dna.GetPoints("TESTSITE.TESTSERVICE")