Skip to main content

sigilyx

YXDB reader and writer for Python.

PyPI Python License: Apache-2.0

YXDB is the native binary format used by Alteryx Designer. sigilyx reads and writes .yxdb files using Polars DataFrames, PyArrow Tables, or Pandas DataFrames.

The core is written in Rust. No native Alteryx Designer installation is required.

Format scope: sigilyx has full read/write support for the E1 (original engine) YXDB layout. Experimental read support for E2 (AMP engine) is included - 13 field types have been verified against real E2 files; 4 rare types (Blob, SpatialObj, Time, WString) have speculative decoders behind an opt-in flag. E2 writing is not yet supported. See SPECIFICATION-E2.md for details.

Installation

pip install sigilyx                     # Polars only (default)
pip install "sigilyx[arrow]"            # + PyArrow
pip install "sigilyx[pandas]"           # + Pandas + PyArrow
pip install "sigilyx[all]"              # all extras

Requires Python 3.9+. Pre-built wheels for Windows, macOS, and Linux (x64 and ARM).

Quick Start

import polars as pl
import sigilyx  # importing registers pl.read_yxdb(), df.yxdb, etc.

# Read
df = pl.read_yxdb("data.yxdb")

# Write
df.yxdb.write("output.yxdb")

API

Polars Integration

Importing sigilyx registers official Polars namespace plugins and top-level IO aliases. No extra calls needed - just import sigilyx.

import polars as pl
import sigilyx

# Top-level IO (mirrors pl.read_parquet / pl.scan_parquet style)
df = pl.read_yxdb("data.yxdb")           # returns pl.DataFrame
lf = pl.scan_yxdb("data.yxdb")           # returns pl.LazyFrame (IO plugin)

# Namespace API on DataFrame / LazyFrame
df.yxdb.write("output.yxdb")             # pl.DataFrame → .yxdb file
lf.yxdb.sink("output.yxdb")              # pl.LazyFrame → .yxdb file (streaming)

Reading

import sigilyx as yx

# Polars DataFrame - fastest, zero-copy via Arrow C Data Interface
df = yx.read_yxdb("data.yxdb")

# PyArrow Table
table = yx.read_yxdb_arrow("data.yxdb")

# Pandas DataFrame (via PyArrow)
pdf = yx.read_yxdb_pandas("data.yxdb")

Writing

import sigilyx as yx

# Polars DataFrame
yx.write_yxdb("output.yxdb", df)

# PyArrow Table
yx.write_yxdb_arrow("output.yxdb", table)

# Pandas DataFrame
yx.write_yxdb_pandas("output.yxdb", pdf)

Streaming / Batched Read

Iterate over large files with constant memory usage:

import sigilyx as yx

# Basic iteration - each batch is a Polars DataFrame
for batch in yx.read_yxdb_batches("data.yxdb", batch_size=100_000):
    process(batch)

# Column projection - only materialise the columns you need
for batch in yx.read_yxdb_batches("data.yxdb", columns=["Id", "Name", "Amount"]):
    process(batch)

# Row limit - stop after N total rows
for batch in yx.read_yxdb_batches("data.yxdb", n_rows=5_000):
    process(batch)

Lazy Scan

import polars as pl
import sigilyx as yx

# Returns a Polars LazyFrame backed by a native Rust streaming reader.
# Only the YXDB header is read on construction; data streams on .collect().
lf = yx.scan("data.yxdb")

result = lf.filter(pl.col("amount") > 100).collect()

# Projection pushdown - only selected columns are materialised in Rust
top10 = lf.select("id", "name").head(10).collect()

Pushdown support: projection (select / with_columns) and row-limit (n_rows / .head()) are pushed down to the Rust reader. Predicate pushdown is not possible - YXDB rows are LZF-compressed with no block-level statistics, so .filter() is applied after the scan.

Metadata

import sigilyx as yx

# Inspect schema without reading any row data
fields = yx.read_yxdb_fields("data.yxdb")
for f in fields:
    print(f.name, f.field_type, f.size)

# Record count from the file header - no data read
n = yx.record_count("data.yxdb")

Field Types

YXDB Type Polars / Arrow Type Notes
Bool Boolean
Byte Int16 Unsigned byte stored as Int16
Int16 Int16
Int32 Int32
Int64 Int64
Float Float32
Double Float64
FixedDecimal Decimal Precision and scale preserved
String String / Utf8 Fixed-width, ASCII/Latin-1
WString String / Utf8 Fixed-width, UTF-16 decoded
V_String String / LargeUtf8 Variable-length, ASCII/Latin-1
V_WString String / LargeUtf8 Variable-length, UTF-16 decoded
Date Date Days since Unix epoch
DateTime Datetime(us) Microsecond precision
Time Time Nanosecond precision
Blob Binary / LargeBinary Variable-length binary
SpatialObj Binary / LargeBinary Geometry as ISO WKB or raw SHP bytes

Links

License

Apache License 2.0.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sigilyx-0.3.2.tar.gz (147.7 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

sigilyx-0.3.2-cp39-abi3-win_amd64.whl (7.1 MB view details)

Uploaded CPython 3.9+Windows x86-64

sigilyx-0.3.2-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (6.7 MB view details)

Uploaded CPython 3.9+manylinux: glibc 2.17+ x86-64

sigilyx-0.3.2-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (6.0 MB view details)

Uploaded CPython 3.9+manylinux: glibc 2.17+ ARM64

sigilyx-0.3.2-cp39-abi3-macosx_11_0_arm64.whl (5.8 MB view details)

Uploaded CPython 3.9+macOS 11.0+ ARM64

File details

Details for the file sigilyx-0.3.2.tar.gz.

File metadata

  • Download URL: sigilyx-0.3.2.tar.gz
  • Upload date:
  • Size: 147.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for sigilyx-0.3.2.tar.gz
Algorithm Hash digest
SHA256 4d468895f54428ee75481ff7a2845db5be78fdd8abbf8beb089b75b35d94c1fd
MD5 6a0259541d2488ac559bd686964cdb0d
BLAKE2b-256 d35a2093f331e21d59b4bb30d3ab52a1bec2a042bbe4f53dc9d928a43fb6e609

See more details on using hashes here.

Provenance

The following attestation bundles were made for sigilyx-0.3.2.tar.gz:

Publisher: publish-pypi.yml on Sigilweaver/SigilYX

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sigilyx-0.3.2-cp39-abi3-win_amd64.whl.

File metadata

  • Download URL: sigilyx-0.3.2-cp39-abi3-win_amd64.whl
  • Upload date:
  • Size: 7.1 MB
  • Tags: CPython 3.9+, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for sigilyx-0.3.2-cp39-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 943cbfc831c20ab9d36314f7aa7d593b47dc98c5a7ae7363890b8250079267eb
MD5 66c2a7beb10c7f5f69ca5c92dfb23b35
BLAKE2b-256 c549e0633ecbcd1583f3d00eca148c60928b83189775cbecc123d556d311d3df

See more details on using hashes here.

Provenance

The following attestation bundles were made for sigilyx-0.3.2-cp39-abi3-win_amd64.whl:

Publisher: publish-pypi.yml on Sigilweaver/SigilYX

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sigilyx-0.3.2-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for sigilyx-0.3.2-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 26573cbc80720900b3b7de09ccf88f67270b1883b378828aed12dd2e271e58a1
MD5 e521001cb35b1b7b683870fdb2d3114b
BLAKE2b-256 660a0fbb8cd570851f3664c65f7ef39477c3892ebe958c7deeb9077f5beac27e

See more details on using hashes here.

Provenance

The following attestation bundles were made for sigilyx-0.3.2-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl:

Publisher: publish-pypi.yml on Sigilweaver/SigilYX

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sigilyx-0.3.2-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for sigilyx-0.3.2-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 13b356ed3faff37eb71022564aa6b3b8ac55c7cec75017cbc95289ff5afd84f2
MD5 3d3576e041122b6e1c4c173649c21c2a
BLAKE2b-256 2e7e4ab705b295b9643bca3f8daf38672fdf468909e87c88c6a59da2d60f15c1

See more details on using hashes here.

Provenance

The following attestation bundles were made for sigilyx-0.3.2-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl:

Publisher: publish-pypi.yml on Sigilweaver/SigilYX

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sigilyx-0.3.2-cp39-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for sigilyx-0.3.2-cp39-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 274ba1ca206d16362d3980e1473d7b3ddfac73300ef47d2b1d71e20cddc91bb7
MD5 6966a17368ce9e93ab57425eb446693d
BLAKE2b-256 0e2c708eecb769543fd5a54d7eae985f806a72058d6824428f811a352a12cfc1

See more details on using hashes here.

Provenance

The following attestation bundles were made for sigilyx-0.3.2-cp39-abi3-macosx_11_0_arm64.whl:

Publisher: publish-pypi.yml on Sigilweaver/SigilYX

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

0.4.0

5 files

0.3.3

5 files

This release

0.3.2 This release

5 files

0.3.1

5 files

0.3.0

4 files

0.2.1

4 files

0.0.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page