Metadata-Version: 2.5
Name: hsql
Version: 2.15.0
Summary: The headless SQL client for scripts and agents. Installs Harlequin.
Project-URL: Homepage, https://harlequin.sh
Project-URL: Documentation, https://harlequin.sh/docs/getting-started/index
Project-URL: Repository, https://github.com/tconbeer/harlequin
Project-URL: Bug Tracker, https://github.com/tconbeer/harlequin/issues
Project-URL: Changelog, https://github.com/tconbeer/harlequin/blob/main/CHANGELOG.md
Author-email: Ted Conbeer <tconbeer@users.noreply.github.com>
License-Expression: MIT
License-File: LICENSE
Keywords: agents,cli,harlequin,headless,sql
Classifier: Development Status :: 4 - Beta
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Requires-Python: >=3.10
Requires-Dist: harlequin==2.15.0
Description-Content-Type: text/markdown

# hsql

`hsql` is your agent's favorite SQL client. It's the headless CLI for
[Harlequin](https://harlequin.sh), and shares the same config and query engine,
with an interface optimized for agents, scripts, and automations.

> [!TIP]
> This README contains a small subset of the docs available at
> [harlequin.sh](https://harlequin.sh/docs/getting-started/hsql).

If you already use Harlequin and know about adapters and config files, jump ahead to [Running hsql](#running-hsql).

## Installing hsql

hsql is packaged with [Harlequin](https://pypi.org/project/harlequin/), so if you already use Harlequin,
hsql is already installed.

Otherwise, you can install hsql directly. hsql is a Python program, and there are many ways to install and run it. We strongly recommend using [uv](https://docs.astral.sh/uv):

1. [Install uv](https://docs.astral.sh/uv/getting-started/installation/#standalone-installer). From a POSIX shell, run:

   ```bash
   curl -LsSf https://astral.sh/uv/install.sh | sh
   ```

   Or using Windows Powershell:

   ```powershell
   powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
   ```

2. Install hsql as a tool using `uv`:

   ```bash
   uv tool install hsql
   ```

   This command will install hsql into an isolated environment and add it to your PATH so you can easily run the executable.

## Installing Database Adapters

hsql can connect to dozens of databases using adapter plug-ins. Adapters are distributed as their own Python packages that need to be installed into the same environment as hsql and harlequin.

For a list of known adapters provided either by the Harlequin maintainers or the broader community, see the [adapters](https://harlequin.sh/docs/adapters) page.

The adapter docs also include installation instructions (installing an adapter with Harlequin also installs it for hsql). Some adapters can be installed as Harlequin extras, like `postgres`. If you used `uv` to install hsql directly, you can add adapter packages using `--with`:

```bash
uv tool install hsql --with harlequin-postgres
```

You can install multiple extras:

```bash
uv tool install hsql --with harlequin-postgres --with harlequin-mysql
```

## Running hsql

Once hsql is installed, you run it from the command line. If you have used psql or the duckdb CLI, hsql will feel familiar, but hsql has the major advantage that is works with most databases and provides the same interface and produces the same output, regardless of the connected database. This means you (and your agent) can learn one tool, instead of several. In your shell, all hsql commands take the same form:

```bash
hsql [OPTIONS] [CONN_STR]
```

where `[OPTIONS]` is 0 or more pairs of the form `--[option-name] [option-value]`, and `[CONN_STR]` is 0 or more connection strings. `[OPTIONS]` are composed of both hsql options and adapter options. For a full list of options, run hsql with the `--help` option:

```bash
hsql --help
```

## Using hsql with DuckDB

hsql defaults to using its DuckDB database adapter, which ships with hsql and includes the full DuckDB in-process database.

Run a query against an in-memory DuckDB session, run hsql and pass in a query with the `-c` option:

```bash
$ hsql -c "select 1"
 1
---
 1
(1 row)
```

To query one or more DuckDB database files, pass in relative or absolute paths as connection strings (hsql will create DuckDB databases if they do not exist):

```bash
$ hsql "path/to/duck.db" -tAc "select count(*) from orders"
42
```

## Using hsql with SQLite and Other Adapters

hsql also ships with a SQLite3 adapter. To use that adapter, you specify the `--adapter sqlite` option. Like DuckDB, you can open an in-memory SQLite database by omitting the connection string:

```bash
$ hsql --adapter sqlite -c "select 'Ted' as author"
 author
--------
 Ted
(1 row)
```

You can query one or more SQLite database files by passing in their paths as connection strings; note that the `--adapter` option has a short alias, `-a`:

```bash
$ hsql -a sqlite "path/to/sqlite.db" -c "select * from users"
 id | name
----+---------
 1  | Ted
 2  | Patrick
(2 rows)
```

Other adapters work the same way; for example, Postgres:

```bash
$ hsql -a postgres "postgresql://example.com/postgres:5432" -c "select * from invoices"
```

> [!TIP]
> You should use Profiles to keep credentials out of your shell
> history. For more information, keep reading or see
> [the docs](https://harlequin.sh/docs/config-file/index) on
> config files.

## Configuring hsql and Using Profiles

hsql supports a number of options for setting the query limit, configuring output formats, and defining connection parameters. Options can be passed as command-line flags, or read from [config files](https://harlequin.sh/docs/config-file/index). Config files store configurations under separate profiles, so you can easily switch between databases by reading from different profiles with the `-P` option:

```bash
$ hsql -P prod -c "select count(*) from orders" --csv
$ hsql -P dev -c "select * from users" --vertical --limit 5
$ hsql -P warehouse -c "..." --format parquet -o invoices.pq
```

hsql reads the same config files as Harlequin, and merges them one profile at a time, nearest file first; pass `--config-path PATH` to read a single file instead, or `-P None` to skip them entirely.

### Keeping Credentials Out of Config Files

A profile's string values can name environment variables, so a config file your team shares — and commits — holds no credentials:

```toml
[profiles.prod]
adapter = "postgres"
host = "${MYHOST:-localhost}"  # ${VAR:-default} supplies a default
password = "${MYPASSWORD}"     # ${VAR} is required; hsql exits 2 if it is unset
```

Write `$${` for a literal `${`, if a value really does start with one.

Values an adapter declares as secrets are masked wherever hsql prints them — `--config show`, `--info`, and error messages — as is the password inside a connection string.

### Inspecting and Writing Config Files

Five `--config` modes work on your config files instead of running SQL, and none of them connects to a database:

- `list-profiles` — the names you can pass to `-P`, with each one's adapter, and which is the default.
- `show` — the merged config as TOML, with the file each value came from beside it; `--json` for JSON.
- `validate` — every problem in every discovered file, exiting `2` if it finds any.
- `schema` — a JSON Schema for a config file, covering every adapter you have installed; point your editor at it for completion and validation as you type.
- `init` — a profile written from the options you pass, prompting for nothing: `hsql --config init -P prod -a sqlite ./my.db --limit -1` writes `[profiles.prod]` into the nearest config file.

```bash
$ hsql --config show
default_profile = "dev" # from /home/user/.config/harlequin/harlequin.toml

[profiles.dev] # from /home/user/proj/harlequin.toml, overriding /home/user/.config/harlequin/harlequin.toml
adapter = "postgres"
host = "${MYHOST:-localhost}"
password = "********"
limit = 100
```

`list-profiles` and `validate` are result sets, so `--csv`, `-t`, `-A` and `-o` work on them as they do on a query.

## Data Layouts and File Formats

hsql supports all of the following formats for displaying and writing data:
- table
- markdown (alias: md)
- vertical
- csv
- tsv
- json
- jsonl (alias: ndjson)
- parquet
- orc
- feather (alias: arrow)
- none (suppresses output)

You can select a format with the `--format <name>` or using the shorthand `--<name>`, so these are equivalent: `--format csv`, `--csv`.

Some layouts can present the results from multiple queries. Others will raise an error and exit with code 2 if multiple queries are executed.

Additionally, for any layout, pass `--stats` to print summary info as JSON to stderr:

```bash
$ hsql -c "select 1" --format none  --stats
{"status":"ok","statements":1,"rows":1,"truncated":false,"limit":500,"elapsed_ms":1,"columns":[{"name":"1","type":"#"}]}
```

## Exploring the Catalog

Before you can write a query, you have to know what is in the database. `--catalog` lists the objects one level below `--path`, and exits without running SQL:

```bash
$ hsql "path/to/duck.db" --catalog
 path | name | query_name | type     | type_label
------+------+------------+----------+------------
 duck | duck | "duck"     | database | db
(1 row)
```

Every row's `path` is what lists that object's own children, so you walk down one level at a time:

```bash
$ hsql "path/to/duck.db" --catalog --path duck
 path           | name      | query_name         | type   | type_label
----------------+-----------+--------------------+--------+------------
 duck.analytics | analytics | "duck"."analytics" | schema | sch
 duck.main      | main      | "duck"."main"      | schema | sch
(2 rows)

$ hsql "path/to/duck.db" --catalog --path duck.analytics
 path                        | name         | query_name                 | type       | type_label
-----------------------------+--------------+----------------------------+------------+------------
 duck.analytics.customers    | customers    | "analytics"."customers"    | BASE TABLE | t
 duck.analytics.order_totals | order_totals | "analytics"."order_totals" | VIEW       | v
 duck.analytics.orders       | orders       | "analytics"."orders"       | BASE TABLE | t
(3 rows)

$ hsql "path/to/duck.db" --catalog --path duck.analytics.orders
 path                              | name        | query_name    | type          | type_label
-----------------------------------+-------------+---------------+---------------+------------
 duck.analytics.orders.customer_id | customer_id | "customer_id" | BIGINT        | ##
 duck.analytics.orders.id          | id          | "id"          | BIGINT        | ##
 duck.analytics.orders.placed_at   | placed_at   | "placed_at"   | TIMESTAMP     | ts
 duck.analytics.orders.total       | total       | "total"       | DECIMAL(18,2) | #.#
(4 rows)
```

A listing is rows, so every format and output option applies to it, exactly as they do to a query:

```bash
$ hsql "path/to/duck.db" --catalog --path duck.analytics -tA --csv
duck.analytics.customers,customers,"""analytics"".""customers""",BASE TABLE,t
duck.analytics.order_totals,order_totals,"""analytics"".""order_totals""",VIEW,v
duck.analytics.orders,orders,"""analytics"".""orders""",BASE TABLE,t
```

### Searching the Catalog

Walking is the wrong tool for *where does `orders` live* and *which tables have a `customer_id`*. `--catalog-search TERM` searches every level of the catalog at once, for objects whose name contains TERM:

```bash
$ hsql "path/to/duck.db" --catalog-search customer_id
 path                                    | name        | query_name    | type   | type_label
-----------------------------------------+-------------+---------------+--------+------------
 duck.analytics.order_totals.customer_id | customer_id | "customer_id" | BIGINT | ##
 duck.analytics.orders.customer_id       | customer_id | "customer_id" | BIGINT | ##
 duck.main.staging_events.customer_id    | customer_id | "customer_id" | BIGINT | ##
(3 rows)
```

`--path` narrows the search to one subtree, and the output can be laid out like any query:

```bash
$ hsql "path/to/duck.db" --catalog-search order --path duck.analytics -tA
duck.analytics.order_totals|order_totals|"analytics"."order_totals"|VIEW|v
duck.analytics.orders|orders|"analytics"."orders"|BASE TABLE|t
```

Note: not all adapters support catalog search at this time.

## Scripting with hsql

> [!WARNING]
> To make hsql safe and efficient for agents, by default hsql applies a 500-row
> limit to all queries. To remove this limit, use `--limit -1` or set
> `limit = -1` in your profile. If limits truncate data, hsql will print
> a warning on stderr; we recommend that you do NOT suppress or redirect 
> that message so do NOT use hsql with `2>/dev/null`.

hsql can write data to files, either with the `-o` option or by piping output (hsql only writes data to stdout; other messages go to stderr):

```bash
$ hsql -P prod --limit -1 -c "select * from users" --format parquet -o "users.pq"
$ hsql -P prod --limit -1 -c "select * from users" --csv > users.csv
```

hsql can execute multiple statements in one invocation, and supports several methods for doing so:
- Pass `-c` multiple times
- Include multiple queries, separated by `;`, in one `-c` option
- Pass one or more .sql files with `-f`, with multiple statements in each
- Use `--result` to define which queries output data to stdout
- Use `--on-error` to either `stop` or `continue` if one or more queries produces an error.

In other words, this works:
```bash
$ hsql -P prod --limit -1 --format md --result all --on-error stop \
    -f ./setup.sql \
    -c "select count(*) from raw_table" \
    -f ./build-models.sql \
    -c "select count(*) from modeled_table" 
```

hsql's exit codes are meaningful and stable:

- 0: Success
- 1: Query error
- 2: Usage/config error
- 3: Connection error
- 4: Timeout
- 130: Interrupted

You can also use `--stats` and `jq` together to error on a truncated query:
```bash
hsql --limit -1 -c "select 1" --csv -o data.csv --stats 2>&1 | jq -e '.truncated | not' > /dev/null
```

> [!TIP]
> A script or agent that runs many invocations against the same database can
> hold one connection open instead of reconnecting for each one.
> `hsql --serve dev -P dev` runs a session named `dev`, and
> `hsql --session dev -c "..."` (or `HSQL_SESSION=dev`) sends invocations to
> it, which answer in milliseconds. A session is state rather than a cache:
> temp tables, settings and open transactions survive from one invocation to
> the next. POSIX only; see
> [warm sessions](https://harlequin.sh/docs/hsql/sessions).

## Running Safely

Two options bound what an invocation can do, and hsql refuses to run at all if the adapter cannot enforce them.

`--read-only` (or `-r`) connects in a mode the database itself refuses writes in:

```bash
$ hsql -r "path/to/duck.db" -c "insert into orders values (1)"
hsql: error: Invalid Input Error: Cannot execute statement of type "INSERT" on database "duck" which is attached in read-only mode!
```

`--timeout SECONDS` limits the duration of executing and fetching a query, and exits `4` when it runs out:

```bash
$ hsql --timeout 0.5 -c "select count(*) from range(100000000000) t(i)"
hsql: error: timed out after 0.5s
```

Both are also profile keys:

```toml
[profiles.agent]
adapter = "postgres"
read_only = true
timeout = 30
```

hsql refuses to open a connection with an adapter that cannot enforce `--read-only` or `--timeout`.

`hsql --info` reports `implements_read_only` and `implements_cancel` for every installed adapter.

## Describing hsql to an Agent

`hsql --help` is written for a person; two flags answer the same questions as JSON, so an agent can find its way around an installation it has never seen. `--spec` is a machine-readable `--help`: every option on the command, plus the connection options every installed adapter declares, each with its type, choices, default and help text. `--info` describes the installation instead — versions, platform, the config files hsql found, the profile that would be active, and what each installed adapter declares it supports — so a script can check that an adapter is there, and what it can do, before depending on it.

```bash
$ hsql --info -a sqlite | jq '.adapters.sqlite'
{
  "distribution": "harlequin",
  "version": "2.10.0",
  "capabilities": {
    "implements_cancel": true,
    "implements_catalog_search": true,
    "implements_read_only": true,
    "implements_validate_sql": false
  },
  "error": null
}
```

Neither connects to a database, both write JSON to stdout, and `-a NAME` narrows either one to a single adapter, which is much faster than importing them all.

## Installing the Agent Skill

hsql ships an [Agent Skill](https://agentskills.io) that teaches an agent how to drive it: ask before you assume, keep credentials off the command line, read the catalog before writing SQL, consider a warm session, watch the 500-row limit, branch on the exit code, and hand off to `harlequin` when a human should drive. `hsql --skill` installs it, with no network and matched to the version you have:

```bash
$ hsql --skill -o ~/.claude/skills/hsql/          # for you, in every project
$ hsql --skill -o .claude/skills/hsql/            # for this repo, committed with it
note: wrote 6 files to .claude/skills/hsql: SKILL.md, references/config.md, references/queries.md, references/scripting.md, references/sessions.md, references/troubleshooting.md
```

With no `-o`, `hsql --skill` writes `SKILL.md` to stdout, so you can read it before you install it.

In Claude Code, the same skill is a plugin in Harlequin's repository:

```
/plugin marketplace add tconbeer/harlequin
/plugin install hsql@harlequin
```

## Keep Reading at [harlequin.sh](https://harlequin.sh/docs/getting-started/hsql)

Visit [harlequin.sh](https://harlequin.sh/docs/getting-started/hsql) for an overview of features and full documentation.

## Getting Help

To view all command-line options for Harlequin and all installed adapters, after installation, simply type:

```bash
hsql --help
```

[GitHub Discussions](https://github.com/tconbeer/harlequin/discussions) are a good place to ask questions, request features, and say hello.

[GitHub Issues](https://github.com/tconbeer/harlequin/issues) are the best place to report bugs.

## Sponsoring Harlequin and hsql

Please consider [sponsoring Harlequin's author](https://github.com/sponsors/tconbeer), so he can continue to dedicate time to hsql.

## Contributing

Thanks for your interest in Harlequin! Harlequin and hsql are primarily maintained by [Ted Conbeer](https://github.com/tconbeer), but he welcomes all contributions!

Please see [`CONTRIBUTING.md`](./CONTRIBUTING.md) for more information.

## Differences from psql

`-c`, `-f`, `-t`, `-A` and `-x` mean what they mean in psql, so `hsql -tAc "select count(*) from orders"` prints a bare number, exactly as it would there. These do not:

| | psql | hsql |
|---|---|---|
| `-P` | `--pset`, an output setting | `--profile`, a config-file profile |
| Field separator | `-F` | `--csv`, `--format tsv`, or any other `--format` |
| Listing databases | `-l` | `--catalog` |
| Describing an object | `\d`, `\dt` | `--catalog --path`, `--catalog-search` |
| Stopping on the first error | `-v ON_ERROR_STOP=1` | `--on-error stop`, which is the default |
| One transaction | `-1` | write `begin` and `commit` in your script |
| `-o` | a file for query output | a file, or a directory that gets one file per result set |
| Connection flags | `-h`, `-p`, `-U`, built in | the adapter's, so `hsql --help -a postgres` lists them |
| Row limits | none | 500 rows by default; `--limit -1` removes it |
| Suppressing chatter | `-q` | nothing to suppress: stdout is only ever results |
| Exit codes | `1` its own error, `2` connection, `3` script error | `1` query error, `2` usage/config, `3` connection, `4` timeout |
