piec 0.1.11

A collection of control and analysis code for experiments

PIEC — Python Integrated Experimental Control

PIEC is an open-source Python library that provides infrastructure for laboratory experiment design and operation through a standardized, hierarchical, object-oriented framework. Originally developed at Brown University as a fork of the ferroelectric testing-focused EKPY Python suite, PIEC is designed to be extended to any experimental domain that requires programmable instrument control.

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Installation

PIEC requires python 3.9 or higher. To install PIEC, run the following command in the terminal:

pip install piec

After this, decide whether you would like to run a specific measurment with a GUI or notebook (in which case you'll need to download the appropriate files from the Measurements folder). Otherwise, see below for information on how to start scripting. Depending on your instruments, you may also need:

Requirement	When needed	Download
NI-488.2	GPIB instruments	ni.com
NI-VISA	USB-TMC / Ethernet / GPIB via NI-VISA	ni.com
MCC Universal Library + mcculw	Digilent/MCC DAQ boards	mccdaq.com

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Overview

Instrument drivers in PIEC follow a type-first architecture with three layers of abstraction:

Layer	Role	Examples
Level 1 — Instrument	Base connection management and parameter validation (wraps PyVISA)	Instrument, Scpi
Level 2 — Category	Defines required methods and parameter standards for each instrument type	Awg, Oscilloscope, Lockin, Sourcemeter
Level 3 — Model	Implements hardware-specific logic for a particular instrument	Keysight81150a, RigolDS1000Z, Keithley2400

Measurement code targets the Level 2 interface, so instruments are interchangeable without code changes. Each category also provides a Virtual Instrument that returns simulated responses, enabling development and testing without physical hardware.

On top of this driver layer, Measurement classes coordinate multiple instruments to execute complete experiment protocols — configuring waveforms, triggering acquisition, processing data, and saving results — in a single method call. Pre-built GUIs and Jupyter notebooks are also provided for routine tasks.

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Quick Start

Virtual mode — no hardware required:

from piec.drivers.awg.virtual_awg import VirtualAwg

awg = VirtualAwg()
awg.set_waveform(1, 'sin')
awg.set_frequency(1, 1000)
awg.set_amplitude(1, 1.0)
awg.output(1, on=True)

Autodetection — connect and go:

from piec.drivers.autodetect import autodetect

awg   = autodetect('awg')
scope = autodetect('scope')

For a complete walkthrough, see the User Guide.

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Supported Instruments

Category	Models
Arbitrary Waveform Generator	Keysight 81150A, Agilent 33220A, Agilent 33500, Rigol DG1000, Rigol DG4000, Siglent SDG2000X
Oscilloscope	Keysight DSOX3024A, Agilent DSOX5000, Rigol DS1000Z, Tektronix TDS2000, Tektronix TDS6604, LeCroy SDA6020
Source Meter	Keithley 2400
Lock-in Amplifier	Stanford Research SR830
Digital Multimeter	Agilent 34410A, Keithley 2000, Keithley 193A
Pulser	Berkeley Nucleonics BNC 765
DAQ	MCC USB-231
DC Calibrator	EDC 522
Stepper Motor	Arduino Stepper (custom serial)

Full instrument list →

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Contributing

New drivers can be added by implementing a driver subclass alongside its Virtual Instrument, following the Driver Development Guide. New experiment types require implementing a Measurement subclass without modifying existing code.

For general guidelines, see the Contributing Guide.

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Support

Issues, bug reports, and feature requests: Issue Tracker

Maintainer: Geo Fratian — [e-mail]

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Citation

Please cite this software following the CITATION.cff.

Fratian, G., Qualls, A., Phan, J., Pankaj, R., & Caretta, L. (2026).
PIEC: A Python Library for Integrated Experimental Control [Software].
https://github.com/TransluSci/piec