rypipe documentation¶
rypipe is a format-agnostic columnar engine that turns byte streams into
Apache Arrow record batches. It separates format-specific parsing from
format-agnostic execution, so the same engine can parse XML, JSON, CSV,
HTML, or any other row-oriented format once you provide a small adapter.
rypipe itself does not ship parsers for any format. Adapters live in
separate packages. Install the engine plus the adapters you need.
What rypipe is¶
- A Rust workspace with two crates:
rypipe-core: the generic engine.rypipe-python: PyO3 bindings and helper functions for adapter packages.- Zero-copy friendly: decoders emit borrowed strings; the engine copies only when necessary.
- GIL-free parsing: all heavy work runs outside Python's GIL.
- Memory-bounded and parallel by design.
What rypipe is not¶
- Not a full query engine. It handles projection, renaming, dropping, casting, filtering, and dictionary encoding, not joins, aggregations, or SQL.
- Not a one-size-fits-all parser. Each format needs a
RecordParser+Splitteradapter from a separate package.
Quick start¶
From Python¶
import rypipe
import my_adapter
# Format is inferred from the extension; mode defaults to parallel.
table = rypipe.read(
"data.myfmt",
fields={"amount": "float64"},
filter={"field": "status", "op": "==", "value": "active"},
)
print(table.num_rows, table.num_columns)
From Rust¶
use rypipe_core::{ExecutionPlan, FieldType, Pipeline};
use my_adapter::{MySplitter, MyDecoder}; // separate adapter crate
let batch = Pipeline::new(MySplitter::new(), MyDecoder::new())
.with_plan(
ExecutionPlan::new()
.type_as("amount", FieldType::Float64)
.filter_eq("status", "active"),
)
.read_path("data.myfmt", false, false)?;
Guides¶
- Architecture: how the pieces fit together.
- Python API: the
rypipepackage and_rypipehelpers. - Rust API: using
rypipe-coreand writing custom adapters. - Writing a format adapter: adding CSV, JSON, etc.
- Performance: benchmarks and tuning knobs.