nidaqwrapper 0.1.0

Unified NI-DAQmx Python Wrapper

nidaqwrapper

Unified NI-DAQmx Python Wrapper.

A Python package that provides a clean, high-level interface to NI-DAQmx hardware. It consolidates analog input, analog output, and digital I/O into a single package with two layers: task classes for channel configuration and orchestrator classes for acquisition lifecycle management.

The architecture uses direct delegation -- nidaqmx.Task is the single source of truth. No intermediate state is maintained; every channel addition and timing configuration delegates immediately to the underlying driver.

Installation

pip install nidaqwrapper

Requires NI-DAQmx drivers installed on the system. The nidaqmx Python package communicates with the NI-DAQmx C driver, which must be installed separately from ni.com.

For development:

git clone https://github.com/tibor-barsi/nidaqwrapper.git
cd nidaqwrapper
pip install -e ".[dev]"

Quick Start

Accelerometer acquisition with software triggering:

from nidaqwrapper import AITask, DAQHandler

# Define an analog input task with two accelerometer channels
task = AITask('vibration_test', sample_rate=25600)
task.add_channel('accel_x', device_ind=0, channel_ind=0,
                 sensitivity=100, sensitivity_units='mV/g', units='g')
task.add_channel('accel_y', device_ind=0, channel_ind=1,
                 sensitivity=100, sensitivity_units='mV/g', units='g')

# Use DAQHandler for triggered acquisition
wrapper = DAQHandler()
wrapper.configure(task_in=task)
wrapper.connect()
wrapper.set_trigger(n_samples=25600, trigger_channel=0,
                    trigger_level=0.5, trigger_type='up', presamples=2560)
data = wrapper.acquire()  # shape: (25600, 2)
wrapper.disconnect()

Features

• Analog input (AITask) -- voltage, accelerometer (IEPE), force (IEPE), and custom linear scales
• Analog output (AOTask) -- voltage generation with continuous buffer regeneration
• Digital I/O (DITask / DOTask) -- on-demand single-sample and clocked continuous modes
• Single-task handler (DAQHandler) -- configure, connect, acquire/generate, disconnect lifecycle with software triggering via pyTrigger
• Multi-task synchronization (MultiHandler) -- hardware-triggered finite acquisition and validated multi-task pipelines
• TOML configuration -- save_config() / from_config() for portable, human-readable task definitions with device aliases
• Device discovery -- list_devices(), list_tasks(), get_connected_devices() for hardware enumeration
• Raw task injection -- from_task() on all task classes wraps pre-configured nidaqmx.Task objects
• Context manager support -- automatic resource cleanup with with statements
• Thread safety -- DAQHandler and MultiHandler use per-instance RLock for concurrent access

Usage Examples

Load an NI MAX task by name

from nidaqwrapper import DAQHandler

wrapper = DAQHandler()
wrapper.configure(task_in='MyInputTask', task_out='MyOutputTask')
wrapper.connect()
data = wrapper.acquire()
wrapper.disconnect()

Digital output

from nidaqwrapper import DOTask

with DOTask('relay_control') as do:
    do.add_channel('relays', lines='Dev1/port0/line0:3')
    do.start()
    do.write([True, False, True, False])

Digital input

from nidaqwrapper import DITask

with DITask('switches') as di:
    di.add_channel('sw', lines='Dev1/port0/line0:3')
    di.start()
    state = di.read()  # array of bool values, one per line

Analog output (continuous waveform)

import numpy as np
from nidaqwrapper import AOTask

task = AOTask('sig_gen', sample_rate=10000)
task.add_channel('ao_0', device_ind=0, channel_ind=0)
task.start()

t = np.linspace(0, 1, 10000)
signal = np.sin(2 * np.pi * 10 * t)  # 10 Hz sine
task.generate(signal)
# ...
task.clear_task()

TOML configuration (portable across machines)

from nidaqwrapper import AITask

# Save task configuration
task = AITask('vibration', sample_rate=25600)
task.add_channel('ch0', device_ind=0, channel_ind=0,
                 sensitivity=100, sensitivity_units='mV/g', units='g')
task.save_config('vibration.toml')
task.clear_task()

# Recreate the same task on another machine
task = AITask.from_config('vibration.toml')
task.start()

The generated TOML file uses device aliases, so only the [devices] section needs editing when moving between machines:

[task]
name = "vibration"
sample_rate = 25600
type = "input"

[devices]
dev0 = "cDAQ1Mod1"  # NI 9234

[[channels]]
name = "ch0"
device = "dev0"
channel = 0
sensitivity = 100
sensitivity_units = "mV/g"
units = "g"

Multi-task synchronized acquisition

from nidaqwrapper import MultiHandler

adv = MultiHandler()
adv.configure(input_tasks=[task1, task2])
adv.connect()
adv.set_trigger(n_samples=25600, trigger_channel=0, trigger_level=0.5)
data = adv.acquire()
adv.disconnect()

Context manager (automatic cleanup)

from nidaqwrapper import DAQHandler

with DAQHandler(task_in='MyTask') as wrapper:
    wrapper.connect()
    wrapper.set_trigger(n_samples=1000, trigger_channel=0, trigger_level=0.1)
    data = wrapper.acquire()
# Resources automatically cleaned up

Wrap a raw nidaqmx.Task

import nidaqmx
from nidaqwrapper import AITask

raw_task = nidaqmx.Task('external')
raw_task.ai_channels.add_ai_voltage_chan('Dev1/ai0')
raw_task.timing.cfg_samp_clk_timing(rate=25600)

wrapped = AITask.from_task(raw_task)
# Use wrapped task with DAQHandler or read directly
data = wrapped.acquire()  # shape: (n_channels, n_samples)
raw_task.close()  # Caller retains ownership

API Reference

Task Classes

Class	Module	Purpose
AITask	ai_task	Analog input -- channels, timing, acquisition
AOTask	ao_task	Analog output -- channels, timing, generation
DITask	digital	Digital input -- on-demand and clocked reads
DOTask	digital	Digital output -- on-demand and clocked writes

Orchestrators

Class	Module	Purpose
DAQHandler	handler	Single-task handler with software triggering, auto-reconnection
MultiHandler	multi_handler	Multi-task orchestrator with hardware trigger validation

Utility Functions

Function	Purpose
list_devices()	List connected NI-DAQmx devices with product types
list_tasks()	List tasks saved in NI MAX
get_connected_devices()	Get set of connected device name strings
get_task_by_name(name)	Load a pre-configured task from NI MAX
UNITS	Dict mapping unit strings ('g', 'mV/g', 'V', etc.) to nidaqmx constants

Data Format

The public API uses (n_samples, n_channels) for all multi-channel data. Internal transposition to nidaqmx's (n_channels, n_samples) layout is handled automatically.

• DAQHandler.acquire() returns (n_samples, n_channels) or a dict
• DAQHandler.read_all_available() returns (n_samples, n_channels)
• DAQHandler.read() returns (n_channels,) -- single sample
• AITask.acquire() returns (n_channels, n_samples) -- internal format
• AOTask.generate(signal) accepts (n_samples, n_channels) or (n_samples,)

Requirements

• Python >= 3.9
• NI-DAQmx drivers (system-level installation)
• numpy >= 1.20
• nidaqmx >= 0.8.0
• pyTrigger >= 0.3.0
• tomli >= 1.0 (Python < 3.11 only; Python 3.11+ uses built-in tomllib)

Testing

nidaqwrapper uses a three-tier test strategy:

Tier	Command	Requirements
Mocked	uv run pytest	None (default)
Simulated	uv run pytest -m simulated -v	NI-DAQmx driver + simulated device
Hardware	uv run pytest -m hardware -v	Physical NI hardware

The mocked tier (630 tests) runs by default and requires no NI-DAQmx driver. The simulated tier uses the real driver with simulated devices to catch API contract violations. The hardware tier validates real-world timing and physical signals.

See TESTING.md for detailed setup instructions, troubleshooting, and how to configure simulated devices.

License

MIT License -- Copyright (c) 2026 Tibor Barsi and contributors