csvql-query
Query CSV files with SQL from Python — powered by a Zig/SIMD engine.
Zero-copy mmap reads + SIMD parsing happen before Python ever sees the data. Faster than DuckDB on typical workloads, no dependencies required.
Installation
pip install csvql-query
Quick Start
import csvql
# Returns a list of dicts (like csv.DictReader, but with SQL)
rows = csvql.query("SELECT name, salary FROM 'employees.csv' WHERE salary > 100000 ORDER BY salary DESC")
# [{'name': 'Alice', 'salary': '185000'}, ...]
# Raw CSV string
csv_str = csvql.query_csv("SELECT * FROM 'data.csv' LIMIT 10")
# pandas DataFrame (pandas must be installed)
df = csvql.query_df("SELECT category, COUNT(*) as n FROM 'sales.csv' GROUP BY category")
# (headers, rows) tuples — no dependencies
headers, rows = csvql.query_tuples("SELECT name, age FROM 'users.csv' WHERE age > 25")
API
| Function | Returns | Description |
|---|---|---|
query(sql) |
list[dict] |
Execute SQL, get list of dicts |
query_csv(sql) |
str |
Execute SQL, get raw CSV string |
query_df(sql) |
DataFrame |
Execute SQL, get pandas DataFrame |
query_tuples(sql) |
(list[str], list[tuple]) |
Execute SQL, get (headers, rows) |
SQL Support
The SQL path is embedded in the query string (same as the CLI):
# Filtering, ordering, limiting
csvql.query("SELECT name, city FROM 'data.csv' WHERE age > 30 ORDER BY name LIMIT 5")
# Aggregation
csvql.query("SELECT department, AVG(salary) FROM 'emp.csv' GROUP BY department")
# Unix pipes — use '-' as the filename
import subprocess, sys
# or just pass stdin data via the engine directly
Full SQL reference: SIMPLE_QUERY_LANGUAGE.md
Performance
- mmap + SIMD parsing — data is never copied into Python memory
- Parallel chunk processing on multi-core machines
- Typically 5–9x faster than DuckDB on 1M-row CSVs
Requirements
- Python ≥ 3.10
- macOS (x86_64 / arm64) or Linux (x86_64)
pandasoptional — only needed forquery_df()
Links
1 maintainer
Metadata
1 maintainer
Release files for csvql-query 2.4.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| csvql_query-2.4.3-py3-none-manylinux_2_17_x86_64.whl | Python 3 | none | Linux glibc 2.17+ x86-64 | Details |
| csvql_query-2.4.3-py3-none-macosx_12_0_x86_64.whl | Python 3 | none | macOS 12.0+ x86-64 | Details |
| csvql_query-2.4.3-py3-none-macosx_12_0_arm64.whl | Python 3 | none | macOS 12.0+ ARM64 | Details |
Total release size: 3.0 MB
Release files / csvql_query-2.4.3-py3-none-manylinux_2_17_x86_64.whl
| Download URL | csvql_query-2.4.3-py3-none-manylinux_2_17_x86_64.whl |
|---|---|
| Size | 2.2 MB |
| Tags | Linux glibc 2.17+ x86-64 Python 3 |
|
SHA-256 checksum How to use checksums |
d6ed38cec7d179cc446efcb1037cad3d7e01e146ac65fc952a4c86f5add959ce
|
|
BLAKE2b-256 checksum How to use checksums |
66233012ba02e9821095386931e7db128e6451d8527c4532147a32d1986fe149
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Release files / csvql_query-2.4.3-py3-none-macosx_12_0_x86_64.whl
| Download URL | csvql_query-2.4.3-py3-none-macosx_12_0_x86_64.whl |
|---|---|
| Size | 421.5 kB |
| Tags | Python 3 macOS 12.0+ x86-64 |
|
SHA-256 checksum How to use checksums |
9b1a84b8a60bbac4c9c2c6a884840347f113509d4efc2a4e5b3164db654a7bc3
|
|
BLAKE2b-256 checksum How to use checksums |
d4e7c94e2e940de681ea6ae7b57c83e48f9231bd8459bd55bb989f0f6ed8dacc
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Release files / csvql_query-2.4.3-py3-none-macosx_12_0_arm64.whl
| Download URL | csvql_query-2.4.3-py3-none-macosx_12_0_arm64.whl |
|---|---|
| Size | 421.5 kB |
| Tags | Python 3 macOS 12.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
074e0aa06999f95f6217a2ba2a015cc87cae7da7d8803cd0ba937fd7879b36d5
|
|
BLAKE2b-256 checksum How to use checksums |
64a8c5ad8fa51d526e16f181347e2aa837df69d385ab03e89a023d030dffa792
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
