A fast and performant SQLite extension for CSV files, written in Rust! Based on sqlite-loadable-rs
and the wonderful csv crate.
- Query CSVs, TSVs, and other-SVs as SQLite virtual tables
- The "reader" interface lets you query CSVs from other data sources, such as
sqlite-http
- Builtin support for querying CSVs with gzip or zstd compression
See Introducing sqlite-xsv: The Fastest CSV Parser for SQLite (Jan 2023) for more details!
Note Nothing to do with xsv, but is based on the same csv crate. This is named
sqlite-xsv
to distinguish between the official SQLite CSV Virtual table and thesqlean
vsv extension.
.load ./xsv0
create virtual table temp.students using csv(
filename="students.csv"
);
select * from temp.students;
/*
┌────┬───────┬─────┬─────────┐
│ id │ name │ age │ process │
├────┼───────┼─────┼─────────┤
│ 1 │ alex │ 10 │ .9 │
│ 2 │ brian │ 20 │ .7 │
│ 3 │ craig │ 30 │ .3 │
└────┴───────┴─────┴─────────┘
*/
Provide a schema for CSVs that lack headers, or to provide types on columns.
create virtual table temp.students_no_header using csv(
filename="students_no_header.csv",
header=false,
id text,
name text,
age int,
);
select * from temp.students_no_header;
Query files that are gzip'ed or compressed with zstd
directly.
create virtual table temp.students_gz using csv(
filename="students.csv.gz"
);
select * from temp.students_gz;
create virtual table temp.students_zst using csv(
filename="students.csv.zst"
);
select * from temp.students_zst;
Use the csv_reader
API and the fsdir()
function in the SQLite CLI to read from several CSV files in one query.
create virtual table temp.students_reader using csv_reader(
id integer,
name text,
age integer,
progess real
);
with files as (
select name as path
from fsdir('tests/data/student_files')
)
select
files.path,
students.*
from files
join students_reader(files.path) as students
where files.path like '%.csv';
/*
┌────────────────────────────────┬────┬───────────┬─────┬─────────┐
│ path │ id │ name │ age │ progess │
├────────────────────────────────┼────┼───────────┼─────┼─────────┤
│ tests/data/student_files/a.csv │ 1 │ alex │ 10 │ 0.9 │
│ tests/data/student_files/a.csv │ 2 │ adrian │ 20 │ 0.8 │
│ tests/data/student_files/a.csv │ 3 │ andres │ 30 │ 0.7 │
│ tests/data/student_files/c.csv │ 1 │ craig │ 70 │ 0.4 │
│ tests/data/student_files/c.csv │ 2 │ catherine │ 90 │ 0.5 │
│ tests/data/student_files/c.csv │ 3 │ coin │ 80 │ 0.6 │
│ tests/data/student_files/b.csv │ 1 │ brian │ 60 │ 0.1 │
│ tests/data/student_files/b.csv │ 2 │ beto │ 50 │ 0.2 │
│ tests/data/student_files/b.csv │ 3 │ brandy │ 40 │ 0.3 │
└────────────────────────────────┴────┴───────────┴─────┴─────────┘
*/
Query CSVs from HTTP endpoints, with the reader API and sqlite-http
. Note: Only works for CSVs that work in memory, for now.
.load ./http0
-- Reading a CSV from the wonderful LA Times COVID project
-- https://github.com/datadesk/california-coronavirus-data
create virtual table temp.cdph_age_reader using csv_reader(
date,
age text,
confirmed_cases_total int,
confirmed_cases_percent float,
deaths_total int,
deaths_percent float
);
create table cdph_age as
select *
from temp.cdph_age_reader(
http_get_body(
'https://raw.githubusercontent.com/datadesk/california-coronavirus-data/master/cdph-age.csv'
)
);
select *
from cdph_age
limit 5;
/*
┌────────────┬───────┬───────────────────────┬─────────────────────────┬──────────────┬────────────────┐
│ date │ age │ confirmed_cases_total │ confirmed_cases_percent │ deaths_total │ deaths_percent │
├────────────┼───────┼───────────────────────┼─────────────────────────┼──────────────┼────────────────┤
│ 2023-01-03 │ 0-4 │ 371691 │ 0.034 │ 32 │ 0.0 │
│ 2023-01-03 │ 80+ │ 292252 │ 0.027 │ 37038 │ 0.378 │
│ 2023-01-03 │ 18–34 │ 3416056 │ 0.312 │ 1655 │ 0.017 │
│ 2023-01-03 │ 35–49 │ 2530259 │ 0.231 │ 6135 │ 0.063 │
│ 2023-01-03 │ 50–59 │ 1379087 │ 0.126 │ 10892 │ 0.111 │
└────────────┴───────┴───────────────────────┴─────────────────────────┴──────────────┴────────────────┘
*/
See docs.md
for a full API reference.
Language | Install | |
---|---|---|
Python | pip install sqlite-xsv |
|
Node.js | npm install sqlite-xsv |
|
Deno | deno.land/x/sqlite_xsv |
|
Ruby | gem install sqlite-xsv |
|
Rust | cargo add sqlite-xsv |
|
Github Release |
The Releases page contains pre-built binaries for Linux amd64, MacOS amd64 (no arm yet), and Windows.
If you want to use sqlite-xsv
as a Runtime-loadable extension, Download the xsv0.dylib
(for MacOS), xsv0.so
(Linux), or xsv0.dll
(Windows) file from a release and load it into your SQLite environment.
Note: The
0
in the filename (xsv0.dylib
/xsv0.so
/xsv0.dll
) denotes the major version ofsqlite-xsv
. Currentlysqlite-xsv
is pre v1, so expect breaking changes in future versions.
For example, if you are using the SQLite CLI, you can load the library like so:
.load ./xsv0
select xsv_version();
-- v0.0.1
Or in Python, using the builtin sqlite3 module:
import sqlite3
con = sqlite3.connect(":memory:")
con.enable_load_extension(True)
con.load_extension("./xsv0")
print(con.execute("select xsv_version()").fetchone())
# ('v0.0.1',)
Or in Node.js using better-sqlite3:
const Database = require("better-sqlite3");
const db = new Database(":memory:");
db.loadExtension("./xsv0");
console.log(db.prepare("select xsv_version()").get());
// { 'xsv_version()': 'v0.0.1' }
For Datasette, it is currently NOT recommended to load sqlite-xsv
in public Datasette instances. This is because the SQL API reads files from the filesystem, which is dangerous on Datasette instances. This may be changed in future version of `sqlite-xsv.