equser 0.0.4

User toolkit for power quality data from EQ Wave sensors

equser

User toolkit for power quality data from EQ Wave sensors.

Overview

equser is a Python library for loading, analyzing, and visualizing continuous waveform (CPOW) and power monitoring (PMon) data from EQ Wave hardware. It provides:

• Data loading (data): Load CPOW and PMon Parquet files with automatic scaling
• Waveform analysis (analysis): Zero-crossing detection, cycle extraction
• Visualization (plotting): Static plots for power quality data (requires [analysis])
• API client (api): REST and WebSocket clients for EQ gateways (requires [analysis])
• Live acquisition (pmon): Real-time sensor data acquisition (requires [daq])
• CLI tools: Command-line interface for monitoring and conversion

Installation

Base installation (data loading + analysis)

pip install equser

With plotting and API support

pip install equser[analysis]

With JupyterLab notebook environment

pip install equser[jupyter]

With live sensor acquisition

pip install equser[daq]

Full installation (all features)

pip install equser[full]

Quick Start

Load and explore CPOW data

from equser.data import load_cpow_scaled

result = load_cpow_scaled('20250623_075056.parquet')
print(f"Voltage A peak: {result['VA'].max():.1f} V")
print(f"Start time: {result['start_time']}")
print(f"Sample rate: {result['sample_rate']} Hz")

Load PMon summary data

from equser.data import load_pmon

table = load_pmon('20250623_0750.parquet')
print(table.column_names)

Analyze waveform zero crossings

import numpy as np
from equser.data import load_cpow_scaled, SAMPLE_RATE_HZ
from equser.analysis import find_zero_crossings

result = load_cpow_scaled('cpow_data.parquet')
time = np.arange(len(result['VA'])) / SAMPLE_RATE_HZ
crossings, indices = find_zero_crossings(result['VA'], time)
print(f"Found {len(crossings)} zero crossings")

Plot data (requires [analysis])

from equser.plotting import PowerMonitorPlotter, WaveformPlotter

# Plot power monitor data
plotter = PowerMonitorPlotter()
plotter.plot_file('pmon_data.parquet')

# Plot waveform data
wf_plotter = WaveformPlotter()
wf_plotter.plot_file('cpow_data.parquet')

Query a gateway (requires [analysis])

from equser.api import GatewayClient

client = GatewayClient('http://gateway:8080')
devices = client.list_devices()
table = client.get_pmon_data(devices[0]['id'])

The class was previously named SynapseClient; that name is preserved as a deprecated module-level alias and still resolves to GatewayClient, so existing code using from equser.api import SynapseClient continues to work without modification. Importing the alias emits a DeprecationWarning; the alias will be removed in a future release. Migrate to from equser.api import GatewayClient. (A future DatalakeClient will provide cross-site queries against the server-side aggregated datalake; the gateway-vs-datalake split mirrors the addressing model.)

Command Line

# Start power monitoring (requires EQ Wave sensor + [daq])
equser pmon acquire -c config.yaml

# Convert Avro files to Parquet (requires [daq])
equser pmon convert data/*.avro --remove

# Plot data file (requires [analysis])
equser plot data.parquet

Configuration

equser looks for configuration in the following locations (in order):

1. EQUSER_CONFIG environment variable
2. ./equser.yaml (current directory)
3. ~/.config/equser/config.yaml (XDG config)
4. /etc/equser/config.yaml (system-wide)

Example configuration:

sensor:
  address: "192.168.10.10"
  port: 1535

pmon:
  connection:
    retry_delay: 3
  parquet:
    interval: 86400
    compression:
      method: ZSTD
      level: 4

Dependency Tiers

Extra	Description	Key Packages
(base)	Data loading, analysis, CLI	numpy, pyarrow, pyyaml, argcomplete, colorlog
[daq]	Live sensor acquisition	avro, fastavro
[analysis]	Plotting + API client	matplotlib, requests, websocket-client
[jupyter]	Full notebook environment	[analysis] + jupyterlab, duckdb, ipywidgets
[dev]	Development tools	pytest, ruff, mypy
[full]	All of the above (except dev)	-

Requirements

• Python 3.10 or later
• Linux (for hardware integration features)

Documentation

• API Documentation
• Changelog

License

MIT License — © 2026 EQ Systems Inc.

About

equser is developed by Energy Quotient for continuous waveform intelligence in power systems. It provides Python access to data from EQ gateways (which run EQ Coherence™ software; the underlying Debian package is currently named eq-synapse, pending rename to eq-coherence per syntropy-repo SEP-058).