Tutorial

This tutorial walks through sq’s features.

If you haven’t installed sq, see here. If you’ve already installed sq, check that you’re on a recent version like so:

$ sq version
sq v0.40.0

If your version is older than that, please upgrade. Then start with sq help.

Basics

Let’s set out with an example. We’ll use a SQLite database, prepopulated with the Sakila dataset. Note that for many of these examples, the output will be abbreviated for brevity.

# No data source added to sq yet, so "sq ls" is empty.
$ sq ls

# Download the sample db.
$ wget https://sq.io/testdata/sakila.db

# Add a new source
$ sq add ./sakila.db --handle @tutorial_db
@tutorial_db  sqlite3  sakila.db

# The new source should show up in "sq ls".
$ sq ls
@tutorial_db  sqlite3  sakila.db

# For many commands, add -v (--verbose) to see more detail.
$ sq ls -v
HANDLE        ACTIVE  DRIVER   LOCATION                                                           OPTIONS
@tutorial_db  active  sqlite3  sqlite3:///Users/neilotoole/work/sq/sq/scratch/tutorial/sakila.db

# Now, let's have a look at our new source. Output abbreviated for brevity.
$ sq inspect @tutorial_db
SOURCE        DRIVER   NAME       FQ NAME         SIZE   TABLES  VIEWS  LOCATION
@tutorial_db  sqlite3  sakila.db  sakila.db/main  5.6MB  16      5      sqlite3:///Users/neilotoole/work/sq/sq/scratch/tutorial/sakila.db

NAME                    TYPE   ROWS   COLS
actor                   table  200    actor_id, first_name, last_name, last_update
address                 table  603    address_id, address, address2, district, city_id, postal_code, phone, last_update
category                table  16     category_id, name, last_update
city                    table  600    city_id, city, country_id, last_update
country                 table  109    country_id, country, last_update
customer                table  599    customer_id, store_id, first_name, last_name, email, address_id, active, create_date, last_update
film                    table  1000   film_id, title, description, release_year, language_id, original_language_id, rental_duration, rental_rate, length, replacement_cost, rating, special_features, last_update
film_actor              table  5462   actor_id, film_id, last_update

Let’s step through the above:

  • sq ls: list the current sources. There are none.
  • wget: download a SQLite datafile to use for this demo.
  • sq add: add a source. The driver type is detected to be sqlite3, and we give this source the handle @tutorial_db.
  • sq ls: lists the sources again; this time we see our new @tutorial_db source.
  • sq ls -v: lists the sources yet again, this time verbosely (-v).
  • sq inspect: inspects @tutorial_db, showing the structure of the source.

👉 Most sq commands feature sophisticated shell completion. Try it out by hitting TAB when typing a command.

Query

Now that we have added a source to sq, we can query it. Let’s select everything from the actor table.

$ sq @tutorial_db.actor
actor_id  first_name   last_name     last_update
1         PENELOPE     GUINESS       2020-02-15T06:59:28Z
2         NICK         WAHLBERG      2020-02-15T06:59:28Z
3         ED           CHASE         2020-02-15T06:59:28Z

# Being that "@tutorial_db" is the active source, you can omit the handle:
$ sq .actor
actor_id  first_name   last_name     last_update
1         PENELOPE     GUINESS       2020-02-15T06:59:28Z
2         NICK         WAHLBERG      2020-02-15T06:59:28Z
3         ED           CHASE         2020-02-15T06:59:28Z

That listed the contents of the actor table.

The same query can be executed in native SQL:

$ sq sql "SELECT * FROM actor"
actor_id  first_name   last_name     last_update
1         PENELOPE     GUINESS       2020-02-15T06:59:28Z
2         NICK         WAHLBERG      2020-02-15T06:59:28Z
3         ED           CHASE         2020-02-15T06:59:28Z

Let’s look at some examples of using the SLQ query language. See the query guide for in-depth documentation.

$ sq '.actor | where(.first_name == "MARY")'
actor_id  first_name  last_name  last_update
66        MARY        TANDY      2020-02-15T06:59:28Z
198       MARY        KEITEL     2020-02-15T06:59:28Z

It should be obvious that the above query effectively performs a WHERE first_name = 'MARY'.

$ sq '.actor | .first_name, .last_name | .[2:5]'
first_name  last_name
ED          CHASE
JENNIFER    DAVIS
JOHNNY      LOLLOBRIGIDA

Above we select (zero-indexed) rows 2-5, and output columns first_name and last_name. The same could be accomplished by:

$ sq sql 'SELECT first_name, last_name FROM actor LIMIT 3 OFFSET 2'
first_name  last_name
ED          CHASE
JENNIFER    DAVIS
JOHNNY      LOLLOBRIGIDA

We could also output in JSON using the -j (--json) flag:

[
  {
    "first_name": "ED",
    "last_name": "CHASE"
  },
  {
    "first_name": "JENNIFER",
    "last_name": "DAVIS"
  },
  {
    "first_name": "JOHNNY",
    "last_name": "LOLLOBRIGIDA"
  }
]

The --jsonl (JSON lines) format is sometimes more convenient:

{"first_name": "ED", "last_name": "CHASE"}
{"first_name": "JENNIFER", "last_name": "DAVIS"}
{"first_name": "JOHNNY", "last_name": "LOLLOBRIGIDA"}

There are several other output formats available.

Join

We can join across the tables of the database.:

$ sq '.actor | join(.film_actor, .actor_id) | join(.film, .film_id) | .first_name, .last_name, .title:film_title'
first_name   last_name     film_title
PENELOPE     GUINESS       ACADEMY DINOSAUR
PENELOPE     GUINESS       ANACONDA CONFESSIONS
PENELOPE     GUINESS       ANGELS LIFE
PENELOPE     GUINESS       BULWORTH COMMANDMENTS

Stdin

Let’s grab another data source, this time in CSV. We’ll download the file.

$ wget https://sq.io/testdata/film.csv

Now let’s take a look at it:

$ cat film.csv | sq inspect -v
SOURCE  DRIVER  NAME    FQ NAME  SIZE     TABLES  VIEWS  LOCATION
@stdin  csv     @stdin  @stdin   189.6KB  1       0      @stdin

NAME  TYPE   ROWS  COLS  NAME                  TYPE      PK
data  table  1000  13    film_id               INTEGER
                         title                 TEXT
                         description           TEXT
                         release_year          INTEGER
                         language_id           INTEGER
                         original_language_id  TEXT
                         rental_duration       INTEGER
                         rental_rate           NUMERIC
                         length                INTEGER
                         replacement_cost      NUMERIC
                         rating                TEXT
                         special_features      TEXT
                         last_update           DATETIME

Note that because CSV is monotable (only has one table of data), its data is represented as a single table named data.

We can pipe that CSV file to sq and performs the usual actions on it:

$ cat film.csv | sq '.data | .title, .release_year | .[2:5]'
title             release_year
ADAPTATION HOLES  2006
AFFAIR PREJUDICE  2006
AFRICAN EGG       2006

We could continue to cat the CSV file to sq, but being that we’ll use it later in this tutorial, we’ll add it as a source:

$ sq add film.csv --handle @film_csv
@film_csv  csv  film.csv

We’ve now got two sources: a SQLite database (@tutorial_db), and a CSV file (@film_csv). We can join across those sources:

$ sq '.actor | join(.film_actor, .actor_id) | join(@film_csv.data, .film_id) | .first_name, .last_name, .title | .[0:5]'
first_name  last_name  title
PENELOPE    GUINESS    ACADEMY DINOSAUR
PENELOPE    GUINESS    ANACONDA CONFESSIONS
PENELOPE    GUINESS    ANGELS LIFE
PENELOPE    GUINESS    BULWORTH COMMANDMENTS
PENELOPE    GUINESS    CHEAPER CLYDE

Active Source

Now that we’ve added multiple sources, let’s see what sq ls has to say:

$ sq ls
@film_csv      csv      film.csv
@tutorial_db*  sqlite3  sakila.db

Note that @tutorial_db is the active source (it has an asterisk beside it, and renders in a different color on a color terminal).

We can do this with @film_csv:

$ sq '@film_csv.data | .title | .[0:2]'
title
ACADEMY DINOSAUR
ACE GOLDFINGER

But not this:

$ sq '.data | .title | .[0:2]'
sq: SQL query against @tutorial_db failed: SELECT "title" FROM "data" LIMIT 2 OFFSET 0: no such table: data

Because the active source is still @tutorial_db. To see the active source:

$ sq src
@tutorial_db  sqlite3  sakila.db

Let’s switch the active source to the CSV file:

$ sq src @film_csv
@film_csv  csv  film.csv

Now we can use the shorthand form (omit the @film_csv handle) and sq will look for table .data in the active source (which is now @film_csv):

$ sq '.data | .title | .[0:2]'
title
ACADEMY DINOSAUR
ACE GOLDFINGER

Ping

A useful feature is to ping the sources to verify that they’re accessible:

# Ping sources in the root group, i.e. all sources.
$ sq ping /
@film_csv           0s  pong
@tutorial_db       1ms  pong

Instead of pinging all the sources in the group, we can specify the sources explicitly:

$ sq ping @film_csv @tutorial_db
@film_csv           0s  pong
@tutorial_db       1ms  pong

SQL Sources

Having read this far, you can be forgiven for thinking that sq only deals with file formats such as CSV or even SQLite, but that is not the case. Let’s add some SQL databases.

First we’ll do Postgres; we’ll start a pre-built Sakila database via docker on port (note that it will take a moment for the Postgres container to start up):

$ docker run -d -p 5432:5432 sakiladb/postgres:latest

Let’s add that Postgres database as a source:

$ sq add 'postgres://sakila:p_ssW0rd@localhost/sakila' --handle @sakila_pg
@sakila_pg  postgres  sakila@localhost/sakila

If you don’t want to type the password on the command line, use -p to be prompted:

$ sq add 'postgres://sakila@localhost/sakila' -p
Password: [ENTER]

The new source should show up in sq ls:

@film_csv*    csv       film.csv
@sakila_pg    postgres  sakila@localhost/sakila
@tutorial_db  sqlite3   sakila.db

Ping the new source just for fun:

$ sq ping @sakila_pg
@sakila_pg      29ms  pong

Now we’ll add and start a MySQL instance of Sakila:

$ docker run -d -p 3306:3306 sakiladb/mysql:latest
$ sq add "mysql://sakila:p_ssW0rd@localhost/sakila" --handle @sakila_my
@sakila_my  mysql  sakila@localhost/sakila

And get some data from @sakila_my:

$ sq '@sakila_my.actor | .[0:2]'
actor_id  first_name  last_name  last_update
1         PENELOPE    GUINESS    2006-02-15 04:34:33 +0000 UTC
2         NICK        WAHLBERG   2006-02-15 04:34:33 +0000 UTC

Insert & Modify

In addition to JSON, CSV, etc., sq can write query results to database tables.

We’ll use the film_category table as an example: the table is in both @sakila_pg and @sakila_my. We’re going to truncate the table in @sakila_my and then repopulate via a query against @sakila_pg.

# First, set the active source to @sakila_my for convenience.
$ sq src @sakila_my
@sakila_my  mysql  sakila@localhost/sakila

# Now, let's confirm the counts
$ sq '@sakila_pg.film_category | count'
count
1000

$ sq '@sakila_my.film_category | count'
count
1000

Make a copy of the table as a backup.

$ sq tbl copy .film_category .film_category_bak
Copied table: @sakila_my.film_category --> @sakila_my.film_category_bak (1000 rows copied)

Note that the sq tbl copy makes use each database’s own table copy functionality. Thus sq tbl copy can’t be used to directly copy a table from one database to another. But sq provides a means of doing this, keep reading.

Truncate the @sakila_my.film_category table:

$ sq tbl truncate @sakila_my.film_category
Truncated 1000 rows from @sakila_my.film_category

$ sq '@sakila_my.film_category | count'
count
0

The @sakila_my.film_category table is now empty. But we can repopulate it via a query against @sakila_pg. For this example, we’ll just do 500 rows.

$ sq '@sakila_pg.film_category | .[0:500]' --insert @sakila_my.film_category
Inserted 500 rows into @sakila_my.film_category

$ sq '@sakila_my.film_category | count'
count
500

We can now use the sq tbl commands to restore the previous state.

$ sq tbl drop .film_category
Dropped table @sakila_my.film_category

# Restore the film_category table from the backup table we made earlier
$ sq tbl copy .film_category_bak .film_category
Copied table: @sakila_my.film_category_bak --> @sakila_my.film_category (1000 rows copied)

# Verify that the table is restored
$ sq '.film_category | count'
count
1000

# Get rid of the backup table
$ sq tbl drop .film_category_bak
Dropped table @sakila_my.film_category_bak

jq

Note that sq plays nicely with jq. For example, list the names of the columns in table @sakila_pg.actor:

$ sq inspect --json @sakila_pg.actor | jq -r '.columns[] | .name'
actor_id
first_name
last_name
last_update
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