las-rs
A high-performance LAS file parser and writer, written in Rust with first-class Python bindings.
Reads and writes LAS 1.2, 2.0, and 3.0 well log files. Designed as a fast, drop-in alternative to lasio.
Available both as a Rust crate (las_rs on crates.io — pure Rust, no Python dependency) and as a Python package (las-rs on PyPI).
Installation
Python:
pip install las-rs
Prebuilt wheels are available for Python 3.10 -- 3.13 on Linux (x86_64), macOS (ARM), and Windows (x64).
Rust:
cargo add las_rs
The crate is pure Rust by default — no PyO3 or numpy in your dependency tree.
Quick start
import las_rs
# Read a LAS file
las = las_rs.read("welllog.las")
# Access header metadata
print(las.well["WELL"].value) # Well name
print(las.well["STRT"].value) # Start depth
print(las.index_unit) # "M", "FT", etc.
# Access curve data (numpy arrays)
gr = las["GR"]
depth = las.index
# Iterate curves
for name, data in las.items():
print(name, data.shape)
# Convert to pandas DataFrame
df = las.df()
Reading options
las = las_rs.read(
"welllog.las",
encoding="latin-1", # Auto-detected if omitted
ignore_header_errors=True, # Continue past malformed headers
ignore_data=True, # Parse headers only (fast)
null_policy=["-999", "-999.25"], # Custom null markers
dtypes={"STATUS": str}, # Keep specific curves as strings
)
read() accepts a file path, a pathlib.Path, a string containing LAS content, or any file-like object with a .read() method.
Working with curves
import numpy as np
# Add a curve
las.append_curve("CALC", data=np.zeros(len(las.index)), unit="GAPI", descr="Computed")
# Update a curve
las.update_curve(mnemonic="GR", data=new_data)
# Delete a curve
las.delete_curve(mnemonic="CALC")
# Stack selected curves into a 2D array
matrix = las.stack_curves(["GR", "NPHI", "RHOB"])
# Get full curve metadata
curve = las.get_curve("GR")
print(curve.mnemonic, curve.unit, curve.descr)
Writing and export
# Write LAS file
las.write("output.las", version=2.0)
# Export to CSV
las.to_csv("output.csv", units=True)
# JSON
json_str = las.json
Depth conversion
depth_m = las.depth_m # Index converted to meters
depth_ft = las.depth_ft # Index converted to feet
Rust
The same engine is usable directly from Rust, without the Python layer:
use las_rs::{read_file, parse, ReadOptions, NullPolicy};
// Read a file from disk (encoding auto-detected).
let las = read_file("welllog.las")?;
// Header metadata.
println!("well: {:?}", las.well_value("WELL"));
println!("index unit: {:?}", las.index_unit);
// Curve data — NULLs are represented as f64::NAN.
for name in las.curve_mnemonics() {
let n = las.curve_data(name).map_or(0, |d| d.len());
println!("{name}: {n} samples");
}
// Access the index (first) curve and a named curve.
let depth = las.index().unwrap_or(&[]);
if let Some(gr) = las.curve_data("GR") {
println!("first GR sample at depth {}: {}", depth[0], gr[0]);
}
// Parse from an in-memory string, with custom options.
let opts = ReadOptions { null_policy: Some(NullPolicy::Common), ..Default::default() };
let las2 = las_rs::parse_with("~VERSION\nVERS. 2.0:\n~ASCII\n", &opts)?;
// Write back out.
las.write_file("out.las")?;
let text: String = las.to_las_string()?;
# let _ = (parse, las2, text);
Ok::<(), las_rs::LasError>(())
Full API docs: docs.rs/las_rs.
License
1 maintainer
Metadata
1 maintainer
Release files for las-rs 0.2.1
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