Skip to main content

csvql-query

CI License: MIT PyPI

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)
  • pandas optional — only needed for query_df()

Links

Metadata

Release files for csvql-query 2.4.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for csvql-query 2.4.0
File Interpreter ABI Platform
csvql_query-2.4.0-py3-none-manylinux_2_17_x86_64.whl Python 3 none Linux glibc 2.17+ x86-64 Details
csvql_query-2.4.0-py3-none-macosx_12_0_x86_64.whl Python 3 none macOS 12.0+ x86-64 Details
csvql_query-2.4.0-py3-none-macosx_12_0_arm64.whl Python 3 none macOS 12.0+ ARM64 Details

Total release size: 2.9 MB

Release files / csvql_query-2.4.0-py3-none-manylinux_2_17_x86_64.whl

Download URL csvql_query-2.4.0-py3-none-manylinux_2_17_x86_64.whl
Size 2.1 MB
Tags Linux glibc 2.17+ x86-64 Python 3
SHA-256 checksum
How to use checksums
3e4f041ffc53962278029eb53dbd4e876819db276eb75db557a353dbcdde718f
BLAKE2b-256 checksum
How to use checksums
7d1576025ff9a4fa5baecaea8c751c0ff98bbc937b36d12a1df4d94eaef9a7af
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-2.4.0-py3-none-macosx_12_0_x86_64.whl

Download URL csvql_query-2.4.0-py3-none-macosx_12_0_x86_64.whl
Size 416.9 kB
Tags Python 3 macOS 12.0+ x86-64
SHA-256 checksum
How to use checksums
4bffb4e01d0ea2d473baee8f9765edafa3b36bb60bec0dae4d90b772358f8384
BLAKE2b-256 checksum
How to use checksums
2fa7524b6d07fe930fa737eee431959440fb2a12902043877f6d49e838b48da5
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-2.4.0-py3-none-macosx_12_0_arm64.whl

Download URL csvql_query-2.4.0-py3-none-macosx_12_0_arm64.whl
Size 416.9 kB
Tags Python 3 macOS 12.0+ ARM64
SHA-256 checksum
How to use checksums
858a11bbc1f9a9b480acfe7ba16342b633ac63cd9bb6ace1ec8d04dff94926c3
BLAKE2b-256 checksum
How to use checksums
7ee68db873b89d11edd35646185a5cb8a07001ceb4f05b76f696e4f1241d3b94
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.14

Release history Release notifications | RSS feed

2.9.0

5 release files

2.8.1

5 release files

2.8.0

5 release files

2.7.0

5 release files

2.6.3

5 release files

2.6.2

5 release files

2.6.0

3 release files

2.5.0

3 release files

2.4.3

3 release files

2.4.1

3 release files

This release

2.4.0 This release

3 release files

2.3.0

3 release files

2.2.0

3 release files

2.1.1

3 release files

2.1.0

3 release files

2.0.4

3 release files

2.0.3

3 release files

2.0.2

3 release files

2.0.1

3 release files

2.0.0

3 release files

1.9.0

3 release files

1.8.0

3 release files

1.7.2

3 release files

1.7.1

3 release files

1.7.0

3 release files

1.6.1

3 release files

1.6.0

3 release files

1.5.13

3 release files

1.5.12

3 release files

1.5.11

3 release files

1.5.10

3 release files

1.5.9

3 release files

1.5.8

3 release files

1.5.7

3 release files

1.5.6

3 release files

1.5.5

3 release files

1.5.1

3 release files

1.5.0

3 release files

1.4.0

3 release files

1.3.0

3 release files

1.1.1

3 release 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