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sq/README.md
Neil O'Toole 703f6d2427
Refactored verbose/header flags; inspect cmd now less verbose by default (#111) 
* Refactored verbose/header flags; inspect cmd now less verbose by default

* Updated changelog

* README update
2022-12-16 20:46:37 -07:00

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# sq: swiss-army knife for data
`sq` is a command line tool that provides `jq`-style access to
structured data sources such as SQL databases,
or document formats like CSV or Excel.
`sq` can perform cross-source joins,
execute database-native SQL, and output to a multitude of formats including JSON,
Excel, CSV, HTML, Markdown and XML, or insert directly to a SQL database.
`sq` can also inspect sources to view metadata about the source structure (tables,
columns, size) and has commands for common database operations such as copying
or dropping tables.
## Install
For other installation options, see [here](https://github.com/neilotoole/sq/wiki#install).
It is strongly advised to install [shell completion](#shell-completion).
### macOS
```shell
brew install neilotoole/sq/sq
```
### Windows
```
scoop bucket add sq https://github.com/neilotoole/sq
scoop install sq
```
### Linux
#### install.sh
The easiest method is to use [install.sh](./install.sh):
```shell
$ /bin/sh -c "$(curl -fsSL https://sq.io/install.sh)"
```
The script detects if any of `apt`, `yum`, or `brew` are installed, and
then installs via the usual procedure.
> Note that `https://sq.io/install.sh` is simply a redirect to [https://raw.githubusercontent.com/neilotoole/sq/master/install.sh](https://raw.githubusercontent.com/neilotoole/sq/master/install.sh).
You can of course directly use `apt`, `yum` etc. if desired. See the
wiki for [more installation options](https://github.com/neilotoole/sq/wiki#install).
## Shell completion
Shell completion is available for `bash`, `zsh`, `fish`, and `powershell`.
It is strongly recommended to install it.
Execute `sq completion --help` for the procedure.
## Quickstart
Use `sq help` to see command help. The [tutorial](https://github.com/neilotoole/sq/wiki/Tutorial) is the best place to start.
The [cookbook](https://github.com/neilotoole/sq/wiki/Cookbook) has recipes for common actions.
The major concept is: `sq` operates on data sources, which are treated as SQL databases (even if the source is really a CSV or XLSX file etc).
In a nutshell, you `sq add` a source (giving it a `handle`), and then execute commands against the source.
### Sources
Initially there are no sources.
```sh
$ sq ls
```
Let's add a source. First we'll add a SQLite database, but this could also be Postgres,
SQL Server, Excel, etc. Download the sample DB, and `sq add` the source. We
use `-h` to specify a _handle_ to use.
```sh
$ wget https://sq.io/testdata/sakila.db
$ sq add ./sakila.db -h @sakila_sl3
@sakila_sl3 sqlite3 sakila.db
$ sq ls -v
HANDLE DRIVER LOCATION OPTIONS
@sakila_sl3* sqlite3 sqlite3:/root/sakila.db
$ sq ping @sakila_sl3
@sakila_sl3 1ms pong
$ sq src
@sakila_sl3 sqlite3 sakila.db
```
The `sq ping` command simply pings the source to verify that it's available.
`sq src` lists the _active source_, which in our case is `@sakila_sl3`.
You can change the active source using `sq src @other_src`.
When there's an active source specified, you can usually omit the handle from `sq` commands.
Thus you could instead do:
```sh
$ sq ping
@sakila_sl3 1ms pong
```
### Query
Fundamentally, `sq` is for querying data. Using our jq-style syntax:
```sh
$ sq '.actor | .actor_id < 100 | .[0:3]'
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
```
The above query selected some rows from the `actor` table. You could also
use native SQL, e.g.:
```sh
$ sq sql 'SELECT * FROM actor WHERE actor_id < 100 LIMIT 3'
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
```
But we're flying a bit blind here: how did we know about the `actor` table?
### Inspect
`sq inspect` is your friend (output abbreviated):
```sh
HANDLE DRIVER NAME FQ NAME SIZE TABLES LOCATION
@sakila_sl3 sqlite3 sakila.db sakila.db/main 5.6MB 21 sqlite3:/Users/neilotoole/work/sq/sq/drivers/sqlite3/testdata/sakila.db
TABLE ROWS COL NAMES
actor 200 actor_id, first_name, last_name, last_update
address 603 address_id, address, address2, district, city_id, postal_code, phone, last_update
category 16 category_id, name, last_update
```
Use the `--verbose` (`-v`) flag to see more detail. And use `--json` (`-j`) to output in JSON (output abbreviated):
```shell
$ sq inspect -j
{
"handle": "@sakila_sl3",
"name": "sakila.db",
"driver": "sqlite3",
"db_version": "3.31.1",
"location": "sqlite3:///root/sakila.db",
"size": 5828608,
"tables": [
{
"name": "actor",
"table_type": "table",
"row_count": 200,
"columns": [
{
"name": "actor_id",
"position": 0,
"primary_key": true,
"base_type": "numeric",
"column_type": "numeric",
"kind": "decimal",
"nullable": false
}
```
Combine `sq inspect` with [jq](https://stedolan.github.io/jq/) for some useful capabilities. Here's how to [list](https://github.com/neilotoole/sq/wiki/Cookbook#list-name-of-each-table-in-a-source) all the table names in the active source:
```sh
$ sq inspect -j | jq -r '.tables[] | .name'
actor
address
category
city
country
customer
[...]
```
And here's how you could [export](https://github.com/neilotoole/sq/wiki/Cookbook#export-all-tables-to-csv) each table to a CSV file:
```sh
$ sq inspect -j | jq -r '.tables[] | .name' | xargs -I % sq .% --csv --output %.csv
$ ls
actor.csv city.csv customer_list.csv film_category.csv inventory.csv rental.csv staff.csv
address.csv country.csv film.csv film_list.csv language.csv sales_by_film_category.csv staff_list.csv
category.csv customer.csv film_actor.csv film_text.csv payment.csv sales_by_store.csv store.csv
```
Note that you can also inspect an individual table:
```sh
$ sq inspect -v @sakila_sl3.actor
TABLE ROWS TYPE SIZE NUM COLS COL NAMES COL TYPES
actor 200 table - 4 actor_id, first_name, last_name, last_update numeric, VARCHAR(45), VARCHAR(45), TIMESTAMP
```
### Insert Output Into Database Source
`sq` query results can be output in various formats (JSON, XML, CSV, etc), and can also be "outputted" as an *insert* into database sources.
That is, you can use `sq` to insert results from a Postgres query into a MySQL table, or copy an Excel worksheet into a SQLite table, or a push a CSV file into a SQL Server table etc.
> **Note:** If you want to copy a table inside the same (database) source, use `sq tbl copy` instead, which uses the database's native table copy functionality.
For this example, we'll insert an Excel worksheet into our `@sakila_sl3` SQLite database. First, we download the XLSX file, and `sq add` it as a source.
```sh
$ wget https://sq.io/testdata/xl_demo.xlsx
$ sq add ./xl_demo.xlsx --opts header=true
@xl_demo_xlsx xlsx xl_demo.xlsx
$ sq @xl_demo_xlsx.person
uid username email address_id
1 neilotoole neilotoole@apache.org 1
2 ksoze kaiser@soze.org 2
3 kubla kubla@khan.mn NULL
[...]
```
Now, execute the same query, but this time `sq` inserts the results into a new table (`person`) in `@sakila_sl3`:
```shell
$ sq @xl_demo_xlsx.person --insert @sakila_sl3.person
Inserted 7 rows into @sakila_sl3.person
$ sq inspect -v @sakila_sl3.person
TABLE ROWS TYPE SIZE NUM COLS COL NAMES COL TYPES
person 7 table - 4 uid, username, email, address_id INTEGER, TEXT, TEXT, INTEGER
$ sq @sakila_sl3.person
uid username email address_id
1 neilotoole neilotoole@apache.org 1
2 ksoze kaiser@soze.org 2
3 kubla kubla@khan.mn NULL
[...]
```
### Cross-Source Join
`sq` has rudimentary support for cross-source joins. That is, you can join an Excel worksheet with a CSV file, or Postgres table, etc.
> **Note:** The current mechanism for these joins is highly naive: `sq` copies the joined table from each source to a "scratch database" (SQLite by default), and then performs the JOIN using the scratch database's SQL interface. Thus, performance is abysmal for larger tables. There are massive optimizations to be made, but none have been implemented yet.
See the [tutorial](https://github.com/neilotoole/sq/wiki/Tutorial#join) for further details, but given an Excel source `@xl_demo` and a CSV source `@csv_demo`, you can do:
```sh
$ sq '@csv_demo.data, @xl_demo.address | join(.D == .address_id) | .C, .city'
C city
neilotoole@apache.org Washington
kaiser@soze.org Ulan Bator
nikola@tesla.rs Washington
augustus@caesar.org Ulan Bator
plato@athens.gr Washington
```
### Table Commands
`sq` provides several handy commands for working with tables. Note that these commands work directly against SQL database sources, using their native SQL commands.
```sh
$ sq tbl copy .actor .actor_copy
Copied table: @sakila_sl3.actor --> @sakila_sl3.actor_copy (200 rows copied)
$ sq tbl truncate .actor_copy
Truncated 200 rows from @sakila_sl3.actor_copy
$ sq tbl drop .actor_copy
Dropped table @sakila_sl3.actor_copy
```
### UNIX Pipes
For file-based sources (such as CSV or XLSX), you can `sq add` the source file, but you can also pipe it:
```shell
$ cat ./example.xlsx | sq .Sheet1
```
Similarly, you can inspect:
```shell
$ cat ./example.xlsx | sq inspect
```
## Data Source Drivers
`sq` knows how to deal with a data source type via a _driver_ implementation. To view the installed/supported drivers:
```sh
$ sq drivers
DRIVER DESCRIPTION USER-DEFINED DOC
sqlite3 SQLite false https://github.com/mattn/go-sqlite3
postgres PostgreSQL false https://github.com/jackc/pgx
sqlserver Microsoft SQL Server false https://github.com/denisenkom/go-mssqldb
mysql MySQL false https://github.com/go-sql-driver/mysql
csv Comma-Separated Values false https://en.wikipedia.org/wiki/Comma-separated_values
tsv Tab-Separated Values false https://en.wikipedia.org/wiki/Tab-separated_values
json JSON false https://en.wikipedia.org/wiki/JSON
jsona JSON Array: LF-delimited JSON arrays false https://en.wikipedia.org/wiki/JSON
jsonl JSON Lines: LF-delimited JSON objects false https://en.wikipedia.org/wiki/JSON_streaming#Line-delimited_JSON
xlsx Microsoft Excel XLSX false https://en.wikipedia.org/wiki/Microsoft_Excel
```
## Output Formats
`sq` has many output formats:
- `--table`: Text/Table
- `--json`: JSON
- `--jsona`: JSON Array
- `--jsonl`: JSON Lines
- `--csv` / `--tsv` : CSV / TSV
- `--xlsx`: XLSX (Microsoft Excel)
- `--html`: HTML
- `--xml`: XML
- `--markdown`: Markdown
- `--raw`: Raw (bytes)
## Acknowledgements
- Much inspiration is owed to [jq](https://stedolan.github.io/jq/).
- See [`go.mod`](https://github.com/neilotoole/sq/blob/master/go.mod) for a list of third-party packages.
- Additionally, `sq` incorporates modified versions of:
- [`olekukonko/tablewriter`](https://github.com/olekukonko/tablewriter)
- [`segmentio/encoding`](https://github.com/segmentio/encoding) for JSON encoding.
- The [_Sakila_](https://dev.mysql.com/doc/sakila/en/) example databases were lifted from [jOOQ](https://github.com/jooq/jooq), which in turn owe their heritage to earlier work on Sakila.
## Similar / Related / Noteworthy Projects
- [usql](https://github.com/xo/usql)
- [textql](https://github.com/dinedal/textql)
- [golang-migrate](https://github.com/golang-migrate/migrate)
- [octosql](https://github.com/cube2222/octosql)
- [rq](https://github.com/dflemstr/rq)
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