---
id: pyjls
version: "0.18.0"
license: Apache 2.0
license_treatment: permissive
maintenance: active
---

# pyjls — Joulescope™ file format

License: permissive · Maintenance: active · Downloads: 133.6K/mo

## What it is and what it does

pyjls is a Python binding to the C implementation of the JLS (Joulescope file format) specification, designed for efficient storage and retrieval of high-frequency, multi-source time-series signal data. It addresses limitations of earlier formats by supporting flexible signal types (fixed and variable sample rate), multiple simultaneous data sources, annotations, and fast random access via pre-computed signal summaries. The format uses a tag-length-value structure similar to MPEG4 and PNG, with integrated CRC32C integrity checks.

The package is built on numpy and platform-specific dependencies, with pre-compiled wheels for Windows, macOS (Intel and ARM), and Linux (x86_64 and aarch64). It targets developers and researchers working with instrumentation data (power measurement, oscilloscope captures, embedded system logging) where both storage efficiency and rapid waveform visualization matter. Active development indicates ongoing refinement, though some features (compression, corrupted-file recovery) remain in progress.

Use it for:

- Store and retrieve power-measurement data from Joulescope instruments with fast zoomed-out summaries for UI rendering.
- Log multi-channel sensor or oscilloscope data with UTC timestamps and sample-rate correlation for post-analysis.
- Annotate captured signals with timestamped markers or text notes without rewriting the entire data file.
- Archive high-frequency embedded-system traces (UART, GPIO, current) with flexible data types and multiple simultaneous sources.
- Perform fast seek and navigation on large multi-day signal captures without loading entire files into memory.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Reads and writes JLS (Joulescope) files, a specialized format for storing high-frequency time-series signal data with built-in summaries, annotations, and multi-source support.

Yes, if you are working with Joulescope instruments or need a specialized format for high-frequency multi-source signal storage with fast random access and summaries. The active maintenance, permissive license, and lack of known vulnerabilities support adoption. Medium install friction (compiled wheels, Python 3.12+ requirement) is acceptable for the target use case. Not suitable if you need a general-purpose time-series database or format—this is purpose-built for instrumentation.

## Install

pip install pyjls
uv add pyjls
poetry add pyjls

## Installing pyjls

Before you install: Medium install friction due to compiled wheels for multiple platforms and Python versions (3.12–3.14). Dependency on numpy and pywin32 adds setup complexity on Windows. Active maintenance with recent release (5 days old) and stable repository status.

License in practice: Apache 2.0 permissive license allows commercial and private use with minimal restrictions; attribution required but no copyleft obligations.

Quickstart:

pip install pyjls
import pyjls
# Open and read a JLS file
with pyjls.Reader('data.jls') as reader:
    signal_data = reader.read_signal(source_id=0, signal_id=0)

Requires Python 3.12 or later; Windows users need pywin32 installed and configured.

Verify before relying:

- Whether the package provides high-level APIs for writing JLS files or only reading.
- Performance characteristics (read/write speed, memory usage) for typical file sizes.
- Availability of comprehensive documentation beyond the README.
- Support for VSR (variable sample rate) signals, marked as 'under development' in the description.

## Package facts

- License: Apache 2.0 (permissive)
- Python support: supports_current
- Install friction: medium
- Maintenance: active
- Downloads: 133.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

joulescope file format, time series data storage, signal waveform file format, high-frequency data capture, jls file reader writer, multi-source signal logging, fast waveform summaries, signal-processing, instrumentation, file-format

[View on SkillFed](https://skillfed.io/packages/pyjls) · [View on PyPI](https://pypi.org/project/pyjls/)