{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/7"},{"label":"Utilities","url":"https://skillfed.io/packages/category/utilities/9"},{"label":"Testing","url":"https://skillfed.io/packages/category/software-development-testing/5"},{"label":"Embedded Systems","url":"https://skillfed.io/packages/category/software-development-embedded-systems"},{"label":"Hardware Drivers","url":"https://skillfed.io/packages/category/system-hardware-hardware-drivers"}],"enrichment":{"capability":"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.","skillfed_tags":["signal-processing","instrumentation","file-format"],"use_cases":["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."],"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.\n\nThe 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.","worth_installing":"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\u2014this is purpose-built for instrumentation."},"id":"pyjls","links":{"html":"https://skillfed.io/packages/pyjls","md":"https://skillfed.io/packages/pyjls.md","pypi":"https://pypi.org/project/pyjls/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-09","license_spdx":null,"license_treatment":"permissive","name":"pyjls","python_support":"supports_current","summary":"Joulescope\u2122 file format"},"popularity":{"monthly_downloads":133559,"position":11505,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.18.0"}