Skip to main content

CLI tool and Python utility functions for manipulating SQLite databases

Project description

sqlite-utils

PyPI Changelog Python 3.x Tests Documentation Status codecov License

Python CLI utility and library for manipulating SQLite databases.

Some feature highlights

Read more on my blog: sqlite-utils: a Python library and CLI tool for building SQLite databases and other entries tagged sqliteutils.

Installation

pip install sqlite-utils

Or if you use Homebrew for macOS:

brew install sqlite-utils

Using as a CLI tool

Now you can do things with the CLI utility like this:

$ sqlite-utils memory dogs.csv "select * from t"
[{"id": 1, "age": 4, "name": "Cleo"},
 {"id": 2, "age": 2, "name": "Pancakes"}]

$ sqlite-utils insert dogs.db dogs dogs.csv --csv
[####################################]  100%

$ sqlite-utils tables dogs.db --counts
[{"table": "dogs", "count": 2}]

$ sqlite-utils dogs.db "select id, name from dogs"
[{"id": 1, "name": "Cleo"},
 {"id": 2, "name": "Pancakes"}]

$ sqlite-utils dogs.db "select * from dogs" --csv
id,age,name
1,4,Cleo
2,2,Pancakes

$ sqlite-utils dogs.db "select * from dogs" --table
  id    age  name
----  -----  --------
   1      4  Cleo
   2      2  Pancakes

You can import JSON data into a new database table like this:

$ curl https://api.github.com/repos/simonw/sqlite-utils/releases \
    | sqlite-utils insert releases.db releases - --pk id

Or for data in a CSV file:

$ sqlite-utils insert dogs.db dogs dogs.csv --csv

sqlite-utils memory lets you import CSV or JSON data into an in-memory database and run SQL queries against it in a single command:

$ cat dogs.csv | sqlite-utils memory - "select name, age from stdin"

See the full CLI documentation for comprehensive coverage of many more commands.

Using as a library

You can also import sqlite_utils and use it as a Python library like this:

import sqlite_utils
db = sqlite_utils.Database("demo_database.db")
# This line creates a "dogs" table if one does not already exist:
db["dogs"].insert_all([
    {"id": 1, "age": 4, "name": "Cleo"},
    {"id": 2, "age": 2, "name": "Pancakes"}
], pk="id")

Check out the full library documentation for everything else you can do with the Python library.

Related projects

  • Datasette: A tool for exploring and publishing data
  • csvs-to-sqlite: Convert CSV files into a SQLite database
  • db-to-sqlite: CLI tool for exporting a MySQL or PostgreSQL database as a SQLite file
  • dogsheep: A family of tools for personal analytics, built on top of sqlite-utils

Project details


Release history Release notifications | RSS feed

This version

3.17

Download files

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

Source Distribution

sqlite-utils-3.17.tar.gz (150.5 kB view details)

Uploaded Source

Built Distribution

sqlite_utils-3.17-py3-none-any.whl (50.6 kB view details)

Uploaded Python 3

File details

Details for the file sqlite-utils-3.17.tar.gz.

File metadata

  • Download URL: sqlite-utils-3.17.tar.gz
  • Upload date:
  • Size: 150.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.9.6

File hashes

Hashes for sqlite-utils-3.17.tar.gz
Algorithm Hash digest
SHA256 77acd202aa568a1f6888c5d8879f306bb3f8acedc82df0df98eb615caa491abb
MD5 9ffe93144f57f50d37b13c4e064e9c9b
BLAKE2b-256 25748b01977bdb32a8296584943ee23495b1f0154257b50c3b094f76be17ed41

See more details on using hashes here.

File details

Details for the file sqlite_utils-3.17-py3-none-any.whl.

File metadata

  • Download URL: sqlite_utils-3.17-py3-none-any.whl
  • Upload date:
  • Size: 50.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.9.6

File hashes

Hashes for sqlite_utils-3.17-py3-none-any.whl
Algorithm Hash digest
SHA256 d2fb49fd0180e0dd5ef0b3a6e76c1aa0a5dbe0498704f2fafc7076aeb6d14958
MD5 a92885237eb3dbb293e9126a75a78f1d
BLAKE2b-256 495ba013a5fc09fa3ad0c409bb4822582972834ca2656949b6a63a73d2fbe284

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page