Volkov Data Ecosystem

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A cross-platform, two-pane file manager in the style of Volkov Commander, written in Python on prompt_toolkit. It browses the local filesystem and steps inside NIC-MLA containers, showing each logged record as a file.

Status: 1.2 — built against NIC-MLA v1.2. Two-pane browsing, file operations, file/record viewer, and an MLA backend that browses and views records — with limited editing of the self-describing tables (not a general record editor, and not strictly read-only). MLA is a deliberately dumb container, so the backend leans on those tables: the schema table decodes each packed payload into real values + units, and the station table turns the log's 1-byte station index into real region/number — both flow straight into CSV/SQL export, and both are editable in place via the F4 table editor.

The design mirrors MLA's own philosophy — dumb libraries + thin glue: reusable, format-aware libraries underneath (export, plus the vendored MLA + its schema reader), with the backends as thin adapters on top. All of volkov_core/ is GUI-free, so it can be reused headless.

Run

pip install -r requirements.txt
python3 volkov_data.py [left_dir] [right_dir]

Keys

Key	Action
Tab	switch panel
↑/↓ PgUp/PgDn Home/End	move cursor
Enter	open dir / step into .mla / go up (..)
F1	info about the selected item / record
F2	check an .mla container — report valid / dead / damaged slots
F3	view file or record payload (text/hex)
F4	on a record: decoded value(s) + units · on .. inside an editable .mla: schema/station table editor
F5	copy selected file to the other panel
F6	rename or move — inside an .mla, export all records to CSV
F7	make directory
F8	delete (with confirmation)
F9	pull-down menu (sorting, language, export to SQL, …)
F10 / q / Ctrl-Q	quit · Esc closes any overlay

Press Enter on samples/weather.mla to step inside and browse its records.

Tests

The volkov_core/ logic is GUI-free, so it is covered by a stdlib unittest suite (no extra dependencies):

python3 -m unittest discover -s tests

The tests build throwaway MLA containers on the fly and also smoke-test the committed samples/weather.mla.

Layout

volkov_data.py           prompt_toolkit GUI (thin shell over volkov_core)
volkov_core/             GUI-free logic — reusable headless
  backend.py               storage-backend abstraction (VdeEntry / VdeBackend)
  local.py                 VdeLocalBackend — host filesystem
  mla.py                   VdeMlaBackend — thin adapter: records as "files",
                           schema decode + station resolve + export
  export.py                dumb library — generic rows → CSV / SQLite bytes
  stations.py              glue — station index → real region/number
samples/make_sample.py   generator for a self-describing sample datalogger file
samples/weather.mla      committed sample (packed rows + schema + stations)
tests/                   stdlib unittest suite for volkov_core (GUI-free)
third_party/nic_mla/     vendored NIC-MLA (Python reference) — canonical data format
third_party/nic_dmd/     vendored NIC-DMD — decodes compressed (keyframe/delta) records
  tools/mla_schema.py      host-only schema/station builders + readers (VDE links)

The desktop reads the logger format through MLA's Python reference
(`third_party/nic_mla/nic_mla.py`) and decodes payloads + stations via the
host-only reader (`tools/mla_schema.py`), both kept byte-identical to the C core.
The Volkov Commander sources are a **behavior reference only** — not ported code.

Datalogger (multi-profile)

Detect and export a datalogger .mla (several station profiles in one file): volkov_core.datalogger — is_datalogger() + export_csv() / export_sqlite(). Full spec in NIC-MLA DESIGN-MLA-datalogger.md.

License

MIT License — Copyright (c) 2026 NIC — Native Intellect Community

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Acknowledgements

To my brother for advice during the development of this project. For technical assistance with code optimisation, to AI assistants Claude (Anthropic) and Gemini (Google).

★ Viva La Resistánce ★