libscanio
Stream CSV, NDJSON, and flat JSON files, filter rows, and validate data with a Zig engine exposed through a CPython extension.
Install
pip install libscanio==0.1.2
Prebuilt wheels support CPython 3.10–3.14 on Linux x64/ARM64 (glibc 2.28+), Windows x64, and macOS 14+ on Intel and Apple Silicon. A matching wheel needs no Zig installation or C compiler. Alpine/musl, Windows ARM64, and PyPy are not included in this release.
The core APIs have no third-party Python runtime dependencies. Only
scan_table() requires an optional installation of PyArrow and currently
returns a pyarrow.Table.
Supported file formats
These three files represent the same rows:
orders.csv
id,amount
1,50
2,150
orders.ndjson — one flat JSON object per line:
{"id": 1, "amount": 50}
{"id": 2, "amount": 150}
orders.json — an array of flat JSON objects:
[
{"id": 1, "amount": 50},
{"id": 2, "amount": 150}
]
File-based APIs select the format from the file extension. The same filters, scans, batches, and validation rules work across all three formats. Scanned values are strings, including numbers from JSON.
Scan and filter
import libscanio
for path in ("orders.csv", "orders.ndjson", "orders.json"):
for row in libscanio.scan(path, where="amount > 100"):
print(row) # {"id": "2", "amount": "150"}
count = libscanio.count(path, where="amount > 100") # 1
for batch in libscanio.scan_batches(path, batch_size=1024, as_dict=False):
for values in batch:
print(values) # tuple of strings
Streaming keeps memory bounded by parser buffers and the current batch.
scan_array(), sorting, and table collection retain results and use memory
proportional to the data they collect. Close streaming generators if you stop early.
Validate uploads
import libscanio
schema = {"amount": {"min": 0}}
# Default: stop at the first failure and return a boolean.
ok = libscanio.validate(b"amount\n10\n", schema)
# Uploaded JSON and NDJSON bytes require an explicit format.
ok_json = libscanio.validate(b'[{"amount": 10}]', schema, format="json")
ok_ndjson = libscanio.validate(b'{"amount": 10}\n', schema, format="ndjson")
# Paths infer the format from their extension.
for path in ("orders.csv", "orders.ndjson", "orders.json"):
assert libscanio.validate(path, schema)
# Full: return only failed rows and their errors.
failures = libscanio.validate(b"amount\n-1\n", schema, mode="full")
# [{'values': ['-1'], 'errors': [{'column': 0, 'column_name': 'amount',
# 'rule': 'below_min', 'value': '-1'}]}]
Validation accepts bytes or a file path. Bytes default to CSV; pass
format="ndjson" or format="json" when appropriate. Full validation retains
all failures, so its memory use grows with the number of rejected rows.
validate_report() returns summary counters and a bounded error list.
validate_iter() and validate_batches() expose rows and validation errors.
Limits and documentation
Fields are strings unless explicitly converted. CSV multiline quoted records and nested JSON are not supported. Native calls currently hold the Python GIL.
Source builds require the full repository checkout, Zig 0.15.2, CPython
headers, setuptools, and a C compiler. From the repository root, run
python -m pip install ./python.
Licensed under Apache-2.0.
1 maintainer
Metadata
1 maintainer
Release files for libscanio 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 20.9 MB
Release files / libscanio-0.1.2-cp314-cp314-win_amd64.whl
| Download URL | libscanio-0.1.2-cp314-cp314-win_amd64.whl |
|---|---|
| Size | 474.1 kB |
| Tags | CPython 3.14 Windows x86-64 |
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| Size | 450.7 kB |
| Tags | CPython 3.10 macOS 14.0+ x86-64 |
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| Size | 422.0 kB |
| Tags | CPython 3.10 macOS 14.0+ ARM64 |
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