laterite
A Rust-backed AGS4 toolchain for the AGS4 geotechnical data format — validate, read as typed data, query, build, fix, diff, certify, and convert ↔ Excel — with a modern, born-typed polars API.
Coming from python-ags4?
laterite.compat is a faithful, faster stand-in for its AGS4 and AGS4.utils
modules — swap from python_ags4 import AGS4 for
from laterite import compat as AGS4 and keep your code.
Install
pip install laterite # base AGS4 (polars + duckdb, pyarrow-free)
pip install "laterite[compat]" # + pandas (python-ags4 drop-in) — still pyarrow-free
pip install "laterite[compat,pyarrow]" # + the optional pyarrow accelerator (or [all])
Requires Python ≥ 3.12. The wheel is abi3, so one binary covers 3.12 / 3.13 /
3.14. Installing it also puts the lat CLI on your PATH.
The [compat] drop-in is pyarrow-free and fast on its own; adding pyarrow
swaps the pandas step for pyarrow's to_pandas and unlocks the Arrow-backed
string dtype — an accelerator, never a requirement.
Use
import laterite
# Validate — errors + warnings by default (FYI is opt-in)
report = laterite.validate("delivery.ags")
report.is_valid
for rule, findings in report.by_rule().items():
print(rule, len(findings))
# Read born-typed columns: a 2DP heading is a float, a DT a datetime
ags = laterite.read("delivery.ags")
ags.groups # ['PROJ', 'LOCA', 'SAMP', …]
ags["LOCA"]["LOCA_GL"][0] # → 12.3 (a polars DataFrame per group)
# SQL across groups, no conversion step
ags.sql("SELECT loca_id, count(*) FROM SAMP GROUP BY 1")
# Repair a dirty file into a fresh handle, then keep working with it
fixed = ags.fix(risky=True) # pads short rows, transliterates non-ASCII, …
# Typed graph: PROJ → LOCA → SAMP → …
from laterite.ags4 import read_typed
for loca in read_typed("delivery.ags").locas:
print(loca.loca_id, loca.loca_gl)
# python-ags4 drop-in — swap the import, keep your code
from laterite import compat as AGS4
tables, headings = AGS4.AGS4_to_dataframe("delivery.ags")
AGS4.dataframe_to_AGS4(tables, headings, "round-trip.ags")
read returns born-typed polars frames by default (or pandas with
read(..., backend="pandas")) — both pyarrow-free, read back from a
Python-owned in-memory DuckDB engine.
More than a faster python-ags4
python-ags4 is the
reference Python library for AGS4 — validation plus pandas read/write — and
it inspired this project. laterite matches that surface and adds a toolchain
on top:
laterite |
python-ags4 |
|
|---|---|---|
| Validate — numbered AGS4 rules | ✅ | ✅ |
| Read → data frames | ✅ born-typed polars or pandas | pandas, all strings |
| Build / write AGS4 · Excel ↔ AGS4 | ✅ | ✅ |
Repair engine (fix) |
✅ | — |
| SQL across groups · revision diff | ✅ | — |
Validity certificates (.ags.idx) |
✅ | — |
| Transport — zstd compress + age encrypt | ✅ | — |
| Typed PROJ → LOCA → SAMP graph | ✅ | — |
| pyarrow required | no (optional accelerator) | via pandas' own deps |
Performance
Synthetic, spec-valid AGS4 from ags4-forge — the wide scaffold: 123
groups, realistic type mix, zero findings. macOS arm64, hot files, mean of 5
warm runs, python-ags4 1.2.0 vs laterite 0.8.0. Both agree on the findings.
Validation
| File | python-ags4 check_file |
laterite.validate |
speedup |
|---|---|---|---|
| 4.9 MB · 459 BH | 1.5 s | 50 ms | 30.0× |
| 24.9 MB · 2,219 BH | 3.7 s | 266 ms | 13.9× |
| 102.7 MB · 8,872 BH | 12.3 s | 1.1 s | 11.7× |
| 275.5 MB · 22,813 BH | 34.1 s | 2.6 s | 13.0× |
| 549.7 MB · 45,107 BH | 70.0 s | 5.4 s | 12.9× |
Read → typed — the honest comparison for real work. python-ags4 needs
AGS4_to_dataframe + convert_to_numeric on every group to get numbers, and
still leaves dates as text; laterite.read is born-typed, dates included.
| File | python-ags4 + convert_to_numeric |
laterite.read |
speedup |
|---|---|---|---|
| 4.9 MB | 187 ms | 26 ms | 7.2× |
| 24.9 MB | 811 ms | 136 ms | 6.0× |
| 102.7 MB | 3.4 s | 541 ms | 6.3× |
| 275.5 MB | 8.9 s | 1.4 s | 6.4× |
| 549.7 MB | 17.5 s | 2.9 s | 6.0× |
Read → strings — like for like, both returning pandas frames of text.
| File | python-ags4 AGS4_to_dataframe |
laterite.compat |
speedup |
|---|---|---|---|
| 4.9 MB | 144 ms | 49 ms | 2.9× |
| 24.9 MB | 718 ms | 206 ms | 3.5× |
| 102.7 MB | 2.8 s | 870 ms | 3.2× |
| 275.5 MB | 7.3 s | 2.2 s | 3.3× |
| 549.7 MB | 15.2 s | 4.6 s | 3.3× |
The ratio holds as files grow — the gap is a constant factor, not a head start
that erodes. Reproduce any of this with
uv run python tools/bench-vs-python-ags4.py in the repo: it generates the
rungs, verifies each against a pinned SHA-256 so a change to the generator can't
move the numbers unnoticed, and prints these exact tables.
Parity + clean-room
121 / 131 of python-ags4 1.2.0's own test suite passes through
laterite.compat (92 %); the 10 remaining are deliberate non-closures,
documented rule by rule. A weekly job compares the two public surfaces, so a
function added upstream can't quietly go missing here.
Two caveats worth knowing before you swap the import. compat mirrors the
library API — python-ags4's ags4_cli command is not mirrored, because
laterite ships lat instead with its own JSON shapes; and compat is one flat
module rather than a package, so from laterite.compat import AGS4 (a submodule
import) is not the shape — use from laterite import compat as AGS4.
The validator is clean-room from the published AGS4 specification, not adapted from another library's source — python-ags4 is LGPL-3.0, and that separation is what lets laterite ship under MIT. Details: COMPAT.md · OBSERVATIONS.md.
One engine, every stack
laterite on PyPI is the Python surface of one Rust AGS4 engine, shared
across:
| Surface | Package | Get it |
|---|---|---|
| Python | laterite — PyPI |
pip install laterite |
| Node.js | laterite — npm |
npm install laterite |
| CLI | lat |
bundled with this wheel |
| DuckDB | laterite_ags4 — community extension |
INSTALL laterite_ags4 FROM community; |
| Browser | validator + data explorer — WASM | open in a browser |
Scriptable output is byte-identical across all of them, so a CI gate and a notebook can't disagree.
Docs
Full documentation — Learn, Cookbook, Concepts, and the Python API reference — at https://niko86.github.io/laterite/docs/.
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