sqlite-utils command-line tool

The sqlite-utils command-line tool can be used to manipulate SQLite databases in a number of different ways.

Running queries and returning JSON

You can execute a SQL query against a database and get the results back as JSON like this:

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

This is the default subcommand for sqlite-utils, so you can instead use this:

$ sqlite-utils dogs.db "select * from dogs"

Use --nl to get back newline-delimited JSON objects:

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

You can use --arrays to request ararys instead of objects:

$ sqlite-utils dogs.db "select * from dogs" --arrays
[[1, 4, "Cleo"],
 [2, 2, "Pancakes"]]

You can also combine --arrays and --nl:

$ sqlite-utils dogs.db "select * from dogs" --arrays --nl
[1, 4, "Cleo"]
[2, 2, "Pancakes"]

If you want to pretty-print the output further, you can pipe it through python -mjson.tool:

$ sqlite-utils dogs.db "select * from dogs" | python -mjson.tool
[
    {
        "id": 1,
        "age": 4,
        "name": "Cleo"
    },
    {
        "id": 2,
        "age": 2,
        "name": "Pancakes"
    }
]

Nested JSON values

If one of your columns contains JSON, by default it will be returned as an escaped string:

$ sqlite-utils dogs.db "select * from dogs" | python -mjson.tool
[
    {
        "id": 1,
        "name": "Cleo",
        "friends": "[{\"name\": \"Pancakes\"}, {\"name\": \"Bailey\"}]"
    }
]

You can use the --json-cols option to automatically detect these JSON columns and output them as nested JSON data:

$ sqlite-utils dogs.db "select * from dogs" --json-cols | python -mjson.tool
[
    {
        "id": 1,
        "name": "Cleo",
        "friends": [
            {
                "name": "Pancakes"
            },
            {
                "name": "Bailey"
            }
        ]
    }
]

Running queries and returning CSV

You can use the --csv option (or -c shortcut) to return results as CSV:

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

This will default to including the column names as a header row. To exclude the headers, use --no-headers:

$ sqlite-utils dogs.db "select * from dogs" --csv --no-headers
1,4,Cleo
2,2,Pancakes

Running queries and outputting a table

You can use the --table option (or -t shortcut) to output query results as a table:

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

You can use the --fmt (or -f) option to specify different table formats, for example rst for reStructuredText:

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

For a full list of table format options, run sqlite-utils query --help.

Returning all rows in a table

You can return every row in a specified table using the rows subcommand:

$ sqlite-utils rows dogs.db dogs
[{"id": 1, "age": 4, "name": "Cleo"},
 {"id": 2, "age": 2, "name": "Pancakes"}]

This command accepts the same output options as query - so you can pass --nl, --csv, --no-headers, --table and --fmt.

Listing tables

You can list the names of tables in a database using the tables subcommand:

$ sqlite-utils tables mydb.db
[{"table": "dogs"},
 {"table": "cats"},
 {"table": "chickens"}]

You can output this list in CSV using the -csv option:

$ sqlite-utils tables mydb.db --csv --no-headers
dogs
cats
chickens

If you just want to see the FTS4 tables, you can use --fts4 (or --fts5 for FTS5 tables):

$ sqlite-utils tables docs.db --fts4
[{"table": "docs_fts"}]

Use --counts to include a count of the number of rows in each table:

$ sqlite-utils tables mydb.db --counts
[{"table": "dogs", "count": 12},
 {"table": "cats", "count": 332},
 {"table": "chickens", "count": 9}]

Use --columns to include a list of columns in each table:

$ sqlite-utils tables dogs.db --counts --columns
[{"table": "Gosh", "count": 0, "columns": ["c1", "c2", "c3"]},
 {"table": "Gosh2", "count": 0, "columns": ["c1", "c2", "c3"]},
 {"table": "dogs", "count": 2, "columns": ["id", "age", "name"]}]

The --nl, --csv and --table options are all available.

Inserting JSON data

If you have data as JSON, you can use sqlite-utils insert tablename to insert it into a database. The table will be created with the correct (automatically detected) columns if it does not already exist.

You can pass in a single JSON object or a list of JSON objects, either as a filename or piped directly to standard-in (by using - as the filename).

Here’s the simplest possible example:

$ echo '{"name": "Cleo", "age": 4}' | sqlite-utils insert dogs.db dogs -

To specify a column as the primary key, use --pk=column_name.

To create a compound primary key across more than one column, use --pk multiple times.

If you feed it a JSON list it will insert multiple records. For example, if dogs.json looks like this:

[
    {
        "id": 1,
        "name": "Cleo",
        "age": 4
    },
    {
        "id": 2,
        "name": "Pancakes",
        "age": 2
    },
    {
        "id": 3,
        "name": "Toby",
        "age": 6
    }
]

You can import all three records into an automatically created dogs table and set the id column as the primary key like so:

$ sqlite-utils insert dogs.db dogs dogs.json --pk=id

You can skip inserting any records that have a primary key that already exists using --ignore:

$ sqlite-utils insert dogs.db dogs dogs.json --ignore

You can also import newline-delimited JSON using the --nl option. Since Datasette can export newline-delimited JSON, you can combine the two tools like so:

$ curl -L "https://latest.datasette.io/fixtures/facetable.json?_shape=array&_nl=on" \
    | sqlite-utils insert nl-demo.db facetable - --pk=id --nl

This also means you pipe sqlite-utils together to easily create a new SQLite database file containing the results of a SQL query against another database:

$ sqlite-utils json sf-trees.db \
    "select TreeID, qAddress, Latitude, Longitude from Street_Tree_List" --nl \
  | sqlite-utils insert saved.db trees - --nl
# This creates saved.db with a single table called trees:
$ sqlite-utils csv saved.db "select * from trees limit 5"
TreeID,qAddress,Latitude,Longitude
141565,501X Baker St,37.7759676911831,-122.441396661871
232565,940 Elizabeth St,37.7517102172731,-122.441498017841
119263,495X Lakeshore Dr,,
207368,920 Kirkham St,37.760210314285,-122.47073935813
188702,1501 Evans Ave,37.7422086702947,-122.387293152263

Inserting CSV or TSV data

If your data is in CSV format, you can insert it using the --csv option:

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

For tab-delimited data, use --tsv:

$ sqlite-utils insert dogs.db dogs docs.tsv --tsv

Upserting data

Upserting works exactly like inserting, with the exception that if your data has a primary key that matches an already exsting record that record will be replaced with the new data.

After running the above dogs.json example, try running this:

$ echo '{"id": 2, "name": "Pancakes", "age": 3}' | \
    sqlite-utils upsert dogs.db dogs - --pk=id

This will replace the record for id=2 (Pancakes) with a new record with an updated age.

Adding columns

You can add a column using the add-column command:

$ sqlite-utils add-column mydb.db mytable nameofcolumn text

The last argument here is the type of the column to be created. You can use one of text, integer, float or blob. If you leave it off, text will be used.

You can add a column that is a foreign key reference to another table using the --fk option:

$ sqlite-utils add-column mydb.db dogs species_id --fk species

This will automatically detect the name of the primary key on the species table and use that (and its type) for the new column.

You can explicitly specify the column you wish to reference using --fk-col:

$ sqlite-utils add-column mydb.db dogs species_id --fk species --fk-col ref

You can set a NOT NULL DEFAULT 'x' constraint on the new column using --not-null-default:

$ sqlite-utils add-column mydb.db dogs friends_count integer --not-null-default 0

Adding columns automatically on insert/update

You can use the --alter option to automatically add new columns if the data you are inserting or upserting is of a different shape:

$ sqlite-utils insert dogs.db dogs new-dogs.json --pk=id --alter

Adding foreign key constraints

The add-foreign-key command can be used to add new foreign key references to an existing table - something which SQLite’s ALTER TABLE command does not support.

To add a foreign key constraint pointing the books.author_id column to authors.id in another table, do this:

$ sqlite-utils add-foreign-key books.db books author_id authors id

If you omit the other table and other column references sqlite-utils will attempt to guess them - so the above example could instead look like this:

$ sqlite-utils add-foreign-key books.db books author_id

See Adding foreign key constraints in the Python API documentation for further details, including how the automatic table guessing mechanism works.

Adding indexes for all foreign keys

If you want to ensure that every foreign key column in your database has a corresponding index, you can do so like this:

$ sqlite-utils index-foreign-keys books.db

Setting defaults and not null constraints

You can use the --not-null and --default options (to both insert and upsert) to specify columns that should be NOT NULL or to set database defaults for one or more specific columns:

$ sqlite-utils insert dogs.db dogs_with_scores dogs-with-scores.json \
    --not-null=age \
    --not-null=name \
    --default age 2 \
    --default score 5

Creating indexes

You can add an index to an existing table using the create-index subcommand:

$ sqlite-utils create-index mydb.db mytable col1 [col2...]

This can be used to create indexes against a single column or multiple columns.

The name of the index will be automatically derived from the table and columns. To specify a different name, use --name=name_of_index.

Use the --unique option to create a unique index.

Use --if-not-exists to avoid attempting to create the index if one with that name already exists.

Vacuum

You can run VACUUM to optimize your database like so:

$ sqlite-utils vacuum mydb.db

Optimize

The optimize command can dramatically reduce the size of your database if you are using SQLite full-text search. It runs OPTIMIZE against all of our FTS4 and FTS5 tables, then runs VACUUM.

If you just want to run OPTIMIZE without the VACUUM, use the --no-vacuum flag.

# Optimize all FTS tables and then VACUUM
$ sqlite-utils optimize mydb.db

# Optimize but skip the VACUUM
$ sqlite-utils optimize --no-vacuum mydb.db