sql2json

Run SQL queries and get JSON (or CSV) on stdout — pipe it anywhere.

sql2json connects to any SQLAlchemy-supported database, executes a query, and writes the results as JSON to standard output. No server, no framework, no boilerplate.

sql2json --name mysql --query sales_monthly --date_from "START_CURRENT_MONTH-1"
# → [{"month": "January", "sales": 5000}, {"month": "February", "sales": 3000}]

The command commits by default, so writes persist:

sql2json --name mysql --query "UPDATE jobs SET done = 1 WHERE id = :id" --id 42
# → {"rowcount": 1}

Pass --read-only to run a statement without persisting anything (safe for exploration and agents).

Use cases

Scheduled reports: run a cron job that pulls yesterday's sales and posts the JSON to a dashboard (Geckoboard, Grafana, etc.)
Shell pipelines: pipe query results into jq, curl, or any CLI tool that speaks JSON
AI agent data retrieval: let an LLM agent query your database with a single subprocess call — see AGENTS.md
ETL glue: extract rows as JSON, transform with standard tools, load elsewhere
Monitoring & alerting: script threshold checks against live database metrics

Install

Published on PyPI: https://pypi.org/project/sql2json/

sql2json is a CLI tool, so the recommended way to install it is as an isolated tool that lives on your PATH without touching any project environment. The default command below also bundles the PostgreSQL and MySQL drivers so you can connect to those databases immediately:

uv tool install "sql2json[postgres,mysql]"
# or
pipx install "sql2json[postgres,mysql]"

Both methods work on modern, externally-managed systems (Manjaro/Arch, Debian 12+, Ubuntu 23.04+, Homebrew Python on macOS), where a plain system-wide pip install is refused with error: externally-managed-environment (PEP 668).

Quoting gotcha: in zsh and bash the square brackets are glob characters, so the package spec must be quoted — "sql2json[postgres,mysql]". Unquoted, the shell tries to expand [postgres,mysql] and errors before the installer ever runs. In PowerShell quoting is also safest: pipx install 'sql2json[postgres,mysql]'.

As a project dependency (library use)

If you import sql2json as a Python package, add it to your project or a virtualenv instead — keep the extras:

uv add "sql2json[postgres,mysql]"
# or, inside an activated venv:
pip install "sql2json[postgres,mysql]"

Database drivers (extras)

Extra	Installs	When you need it
(none)	—	SQLite only (built into Python)
`[postgres]`	`psycopg2-binary`	PostgreSQL
`[mysql]`	`PyMySQL`	MySQL / MariaDB
`[postgres,mysql]`	both	the recommended default

Minimal (SQLite only): a bare install ships no third-party DB drivers — fine if you only use SQLite, but connecting to Postgres/MySQL without the extras fails with ModuleNotFoundError: psycopg2 / pymysql. Install the extras you need:

uv tool install sql2json        # SQLite only — add [postgres]/[mysql] for those DBs
pipx install sql2json           # same, minimal

Adding drivers later — if you already installed sql2json and now need a driver, reinstall with the extras (or inject the driver into the isolated tool):

uv tool install "sql2json[postgres,mysql]" --force   # reinstall with drivers
pipx inject sql2json psycopg2-binary pymysql         # add to the pipx install

Other databases work too — install any SQLAlchemy-supported driver alongside sql2json. For example, MS SQL Server needs pyodbc:

uv tool install "sql2json" --with pyodbc
pipx inject sql2json pyodbc

Per-OS notes

Linux: system Python is externally-managed (PEP 668). uv tool and pipx install into ~/.local/bin — make sure it is on your PATH (pipx ensurepath sets this up).
macOS: Homebrew Python is externally-managed too, so prefer uv tool / pipx; they place scripts on your PATH the same way.
Windows: the sql2json.exe console script lands in the Python/uv/pipx Scripts directory — ensure it is on PATH, or use py -m sql2json .... In PowerShell and cmd, quote the extras: 'sql2json[postgres,mysql]'.

Escape hatch (avoid): on an externally-managed system you can force a system-wide install with pip install --break-system-packages "sql2json[postgres,mysql]", but this writes into the OS-managed Python and can break system tooling. Prefer uv tool / pipx (isolated) or a venv instead.

Running it

Once installed, invoke the tool directly:

sql2json --name default --query default

The sql2json command is available since v0.2.1. The original python -m sql2json ... form still works and is equivalent — use it on 0.2.0 and earlier, or whenever the package is installed but its scripts directory is not on your PATH (on Windows, py -m sql2json ...).

Upgrading

Carry the same extras through so the drivers stay installed:

uv tool upgrade sql2json                              # uv tool install
uv tool install "sql2json[postgres,mysql]" --force    # reinstall, refresh drivers
pipx upgrade sql2json                                 # pipx install
pip install --upgrade "sql2json[postgres,mysql]"      # inside a venv

Verify the installed version:

sql2json --version                       # or: sql2json -v
uv tool list                             # shows isolated tool versions
pipx list                                # shows pipx-managed versions

Docker

An official image is published to Docker Hub at docker.io/fsistemas/sql2json. It bundles drivers for PostgreSQL (psycopg2-binary) and MySQL / MariaDB (PyMySQL) in addition to SQLite, which is built into Python, and is built for both linux/amd64 and linux/arm64.

The examples below use Podman; every command works identically with docker — just swap the executable name. Docker Hub shows the current pull command, tags, and supported platforms: https://hub.docker.com/r/fsistemas/sql2json.

Quick test without a config file (pulls the image on first run):

podman run --rm docker.io/fsistemas/sql2json --query "SELECT 1 AS a, 2 AS b"
# → [{"a": 1, "b": 2}]

# Docker equivalent:
docker run --rm docker.io/fsistemas/sql2json --query "SELECT 1 AS a, 2 AS b"

Supported tags

Tag	Meaning
`latest`	Newest stable release. Moves on every release — convenient, but not pinned.
`X.Y.Z` (e.g. `0.3.0`)	A specific release. Immutable — recommended for production and CI.

podman pull docker.io/fsistemas/sql2json:0.3.0   # pin a release
podman pull docker.io/fsistemas/sql2json:latest  # newest stable

Usage

The image runs as an unprivileged user (app), whose home is /home/app, so config is read from /home/app/.sql2json.

Run with your own config by mounting ~/.sql2json:

podman run --rm \
  -v ~/.sql2json:/home/app/.sql2json \
  docker.io/fsistemas/sql2json --name default --query sales_monthly --date_from "START_CURRENT_MONTH-1"

For SQLite, mount both the config directory and the database file. Point the connection string in your config to the in-container path:

podman run --rm \
  -v ~/.sql2json:/home/app/.sql2json \
  -v /path/to/mydb.sqlite:/data/mydb.sqlite \
  docker.io/fsistemas/sql2json --name default --query default

{
    "connections": {
        "default": "sqlite:////data/mydb.sqlite"
    }
}

Write output files by mounting a host directory to /workspace, the container working directory. Because the container runs as a non-root user, map the container user to your host user so the written files are owned by you — --userns=keep-id for Podman, --user $(id -u):$(id -g) for Docker:

podman run --rm --userns=keep-id \
  -v ~/.sql2json:/home/app/.sql2json \
  -v $(pwd)/reports:/workspace \
  docker.io/fsistemas/sql2json --name default --query sales_monthly \
    --format csv --output "Sales_{CURRENT_DATE}"
# → ./reports/Sales_2026-05-17.csv on the host

# Docker equivalent:
docker run --rm --user $(id -u):$(id -g) \
  -v ~/.sql2json:/home/app/.sql2json \
  -v $(pwd)/reports:/workspace \
  docker.io/fsistemas/sql2json --name default --query sales_monthly \
    --format csv --output "Sales_{CURRENT_DATE}"

MS SQL Server needs system-level ODBC libraries, so install the driver in a derived image:

FROM docker.io/fsistemas/sql2json
RUN pip install --no-cache-dir pyodbc

Build from source (development)

The published image installs sql2json from PyPI. To build an image from a local checkout instead — for example to try an unreleased change — pass the VERSION build arg (or omit it to install the latest PyPI release):

podman build -t sql2json .                       # latest PyPI release
podman build --build-arg VERSION=0.3.0 -t sql2json .   # pin a release
podman run --rm sql2json --query "SELECT 1 AS a, 2 AS b"

Try it with docker compose

The repo includes a docker-compose.yml that starts PostgreSQL and MySQL with demo-only credentials, a small sales table, and a pre-wired docker/config.json. The database ports bind to 127.0.0.1 for local testing.

Start the databases:

docker compose up -d postgres mysql

Run queries against PostgreSQL:

docker compose run --rm sql2json --name pg --query version
# → [{"version": "PostgreSQL 16.x ..."}]

docker compose run --rm sql2json --name pg --query sales
# → [{"id": 1, "month": "January", "amount": 5000.0}, ...]

docker compose run --rm sql2json --name pg --query sales_by_month --min_amount 4000
# → [{"month": "January", "amount": 5000.0}, {"month": "March", "amount": 7100.75}]

Run the same shared demo queries against MySQL by switching --name:

docker compose run --rm sql2json --name mysql --query sales

The demo config also uses connection_queries for dialect-specific named queries. For example, database_name is defined separately for PostgreSQL and MySQL, while version, sales, and sales_by_month remain shared/global queries:

docker compose run --rm sql2json --list-queries
# → {"global": ["version", "sales", "sales_by_month"], "connections": {"pg": ["database_name"], "mysql": ["database_name"]}}

# Same query name, scoped SQL for each connection:
docker compose run --rm sql2json --name pg --query database_name
docker compose run --rm sql2json --name mysql --query database_name

Tear down when done:

docker compose down

The demo config lives in docker/config.json and the seed table in docker/initdb.sql.

Real database verification

The fast unit suite runs against in-memory SQLite and needs no Docker:

uv run pytest

A separate, opt-in integration suite verifies the documented demo paths (named connection lookup, named query lookup, bind parameters, Decimal values, and JSON serialization) against real PostgreSQL and MySQL. By default it provisions ephemeral databases in code with testcontainers, so a bare run just works given a running Docker/Podman (no pre-provisioned stack):

uv run --extra integration pytest -m integration tests/integration

The integration tests are marked integration and deselected by default, so uv run pytest stays Docker-free. To run them against an already-running database instead of starting containers, point at it with SQL2JSON_TEST_PG_URL / SQL2JSON_TEST_MYSQL_URL. ./scripts/test-integration.sh uses exactly that to provision the docker-compose.yml services, run the suite, and tear them down:

./scripts/test-integration.sh

Each test skips cleanly when no container runtime is available or its database is unreachable, so a machine without Docker never sees failures. In CI, the integration job in .github/workflows/ci.yml provisions the services and runs the same suite.

Quality gates

The same checks that CI enforces can be run locally. See CONTRIBUTING.md for details.

uv run --extra dev black --check .   # formatting
uv run --extra dev flake8            # linting
uv run --extra dev mypy              # type checking
uv run --extra dev pytest --cov      # tests + coverage (gated at 90%)

uv run --extra dev black . reformats in place. CI (.github/workflows/ci.yml) runs these on every pull request and on pushes to master: a quality job for black/flake8/mypy, a unit job across Python 3.10–3.13 with the coverage gate, and the database integration job.

Quick start

1. Create the config file:

mkdir -p ~/.sql2json
cat > ~/.sql2json/config.json << 'EOF'
{
    "connections": {
        "default": "sqlite:///mydb.sqlite"
    },
    "queries": {
        "default": "SELECT 1 AS a, 2 AS b"
    },
    "connection_queries": {
        "default": {
            "healthcheck": "SELECT 'ok' AS status"
        }
    }
}
EOF

2. Run a query:

sql2json
# → [{"a": 1, "b": 2}]

3. Try inline SQL:

sql2json --name default --query "SELECT date('now') AS today"
# → [{"today": "2026-05-16"}]

Configuration

By default sql2json looks for a config file in this order:

./sql2json.json (current directory)
./.sql2json/config.json (current directory)
~/.sql2json/config.json (home directory)

Use --config /path/to/config.json to override.

Config file format

{
    "connections": {
        "default": "sqlite:///test.db",
        "postgres": "postgresql://scott:tiger@localhost:5432/mydb",
        "mysql": "mysql://scott:tiger@localhost/foo"
    },
    "queries": {
        "default": "SELECT 1 AS a, 2 AS b",
        "sales_monthly": "SELECT inv.month, SUM(inv.amount) AS sales FROM invoices inv WHERE inv.date >= :date_from",
        "total_sales": "SELECT SUM(inv.amount) AS sales FROM invoices inv WHERE inv.date >= :date_from",
        "long_query": "@/path/to/my_query.sql"
    },
    "connection_queries": {
        "postgres": {
            "now": "SELECT CURRENT_TIMESTAMP AS ts",
            "table_sizes": "SELECT schemaname, relname, pg_total_relation_size(relid) AS bytes FROM pg_catalog.pg_statio_user_tables"
        },
        "mysql": {
            "now": "SELECT NOW() AS ts",
            "table_sizes": "SELECT table_schema, table_name, data_length + index_length AS bytes FROM information_schema.tables WHERE table_schema = DATABASE()"
        }
    }
}

Note: Both "connections" and "conections" (legacy typo) are accepted. Existing config files do not need to be updated.

Connection strings follow SQLAlchemy URL format. Query values starting with @ are treated as paths to .sql files.

connection_queries is optional and only needed for queries that are valid for a specific connection or SQL dialect. Its shape is a top-level map of connection name to query-name to SQL. Existing configs that omit this key continue to work unchanged; queries remains valid for shared/global named queries that can run unchanged across connections.

Named query lookup is connection-aware: sql2json --name postgres --query now first checks connection_queries.postgres.now; if it is not present, it falls back to queries.now; if neither exists, --query is treated as raw SQL or an @/path.sql file reference.

CLI reference

sql2json [options] [--param value ...]

Flag	Default	Description
`--name`	`default`	Connection name from config, or a raw SQLAlchemy URL
`--query`	`default`	Named query, raw SQL string, or `@/path/file.sql`
`--config`	(lookup order above)	Path to a specific config file
`--first`	`False`	Return only the first row (object, not array)
`--key`	`""`	Extract one column as value (scalar with `--first`), or dict key (with `--value`)
`--value`	`""`	Used with `--key` to produce `{key_col: value_col}` dicts
`--wrapper`	`False`	Wrap result in `{"data": [...]}` (bare `--wrapper`/`True`); pass a string (e.g. `--wrapper=items`) to wrap under a custom key: `{"items": [...]}`
`--jsonkeys`	`""`	Comma-separated columns whose string values should be parsed as JSON
`--format`	`json`	Output format: `json`, `csv`, `excel`
`--output`	(stdout)	Save to file; filename supports `{CURRENT_DATE}` etc.
`--list-connections`	—	Print JSON array of configured connection names and exit
`--list-queries`	—	Print configured query names and exit. Default shape is `{"global": [...], "connections": {...}}`; pass `--list-queries legacy` for the old flat global query list
`--version` / `-v`	—	Print the installed version (`sql2json <version>`) and exit

Extra --key value flags become SQL bind parameters (:key in your query).

Discovery

Before writing a query, inspect what is configured:

sql2json --list-connections
# → ["default", "mysql", "reporting"]

sql2json --list-queries
# → {"global": ["default", "sales_monthly"], "connections": {"mysql": ["table_sizes"]}}

sql2json --list-queries legacy
# → ["default", "sales_monthly"]

Use the scoped discovery output to choose an appropriate --name/--query pair. For a given connection, an entry under connections.<name> overrides a same-named global query; otherwise the global query is used as a fallback.

Writing data & read-only mode

There is one command and it commits by default (autocommit). It runs any kind of SQL — SELECT, DML (INSERT / UPDATE / DELETE), and DDL (CREATE / ALTER / DROP):

Statement	Result
`SELECT` / `... RETURNING`	returns rows, shaped by the usual transform flags
INSERT / UPDATE / DELETE / DDL (returns no rows)	persists and prints `{"rowcount": N}` (DDL / count-unknown statements report `{"rowcount": 0}` consistently across databases)

# DDL — create a table (persists)
sql2json --name mydb --query "CREATE TABLE sessions (id INTEGER, expires_at TEXT)"
# → {"rowcount": 0}

# DML — delete rows (persists, prints the affected-row count)
sql2json --name mydb --query "DELETE FROM sessions WHERE expires_at < :cutoff" \
  --cutoff "CURRENT_DATE-30"
# → {"rowcount": 12}

# RETURNING streams the new rows back, shaped by the usual flags
sql2json --name mydb \
  --query "INSERT INTO users (email) VALUES (:e) RETURNING id, email" --e a@b.com
# → [{"id": 7, "email": "a@b.com"}]

`--read-only` (safe mode)

Pass --read-only to run a statement without persisting anything. The statement still executes, but a real database read-only transaction is requested where supported — SQLite, PostgreSQL, and MySQL — so a write is rejected by the database up front, with an unconditional rollback as a portable backstop for any other backend. A write under --read-only reports {"rowcount": ...} and prints a notice to stderr, leaving stdout as clean JSON; SELECT returns rows as usual with no notice.

# SELECT under --read-only behaves exactly like a normal read
sql2json --read-only --name mydb --query "SELECT count(*) AS n FROM users"
# → [{"n": 1234}]

# A write under --read-only does not persist
sql2json --read-only --name mydb --query "DELETE FROM users WHERE id = :id" --id 42
# stdout → {"rowcount": 0}
# stderr → read-only mode: write not persisted (re-run without --read-only to commit the change).

Safety: because the command commits by default, gate it in locked-down deployments and prefer --read-only for agents, automation, and exploration — anywhere that must not mutate data. Note --read-only still runs the statement (then rolls it back / has it rejected), so it is not a syntactic guard against destructive SQL.

Date variables

Extra parameters whose values match a built-in variable are resolved to real dates before the query runs:

Variable	Resolves to
`CURRENT_DATE`	Today's date
`START_CURRENT_MONTH`	First day of the current month
`END_CURRENT_MONTH`	Last day of the current month
`START_CURRENT_YEAR`	First day of the current year
`END_CURRENT_YEAR`	Last day of the current year

Arithmetic — the unit depends on the variable:

CURRENT_DATE-7          → 7 days ago
START_CURRENT_MONTH+1   → first day of next month
START_CURRENT_YEAR-1    → first day of last year

Custom format — append |strftime_format:

--min_date "CURRENT_DATE|%Y-%m-%d 00:00:00"
# → "2026-05-16 00:00:00"

--min_date "START_CURRENT_YEAR|%Y-%m-%d 00:00:00"
# → "2026-01-01 00:00:00"

Output transformations

Array of objects (default)

sql2json --name mysql --query sales_monthly --date_from "START_CURRENT_MONTH-1"

[
    {"month": "January", "sales": 5000},
    {"month": "February", "sales": 3000}
]

First row only (`--first`)

sql2json --name mysql --query total_sales --date_from "CURRENT_DATE-10" --first

{"sales": 500}

Single value (`--first --key`)

sql2json --name mysql --query total_sales --date_from "CURRENT_DATE-10" --first --key sales

Key-value pairs (`--key --value`)

sql2json --name mysql --query sales_monthly --date_from "START_CURRENT_MONTH-1" --key month --value sales

[
    {"January": 5000},
    {"February": 3000}
]

Wrapped for dashboards (`--wrapper`)

sql2json --name mysql --query sales_monthly --date_from "START_CURRENT_MONTH-1" --wrapper

{
    "data": [
        {"month": "January", "sales": 5000},
        {"month": "February", "sales": 3000}
    ]
}

Pass a string to wrap under a custom key instead of data:

sql2json --name mysql --query sales_monthly --date_from "START_CURRENT_MONTH-1" --wrapper=items

{
    "items": [
        {"month": "January", "sales": 5000},
        {"month": "February", "sales": 3000}
    ]
}

Parse JSON columns (`--jsonkeys`)

When a column contains a JSON string from a database JSON function, use --jsonkeys to parse it:

sql2json --name mysql --query json_report --jsonkeys "payload,metadata"

Without --jsonkeys those columns would be escaped strings; with it they are inlined as JSON.

Inline SQL

No need to define every query in the config file:

sql2json --name mysql --query "SELECT NOW() AS ts" --first --key ts

External `.sql` file

# Defined in config.json as "@/path/to/file.sql"
sql2json --name mysql --query long_query --min_age 18

# Or pass the path directly
sql2json --name mysql --query "@/path/to/my_query.sql" --min_age 18

File output

Use --output to write to a file instead of stdout. The --format flag controls the extension (default json):

# CSV file
sql2json --name mysql --query sales_monthly --date_from "START_CURRENT_MONTH-1" --format csv --output Sales
# → Sales.csv

# Excel file
sql2json --name mysql --query sales_monthly --date_from "START_CURRENT_MONTH-1" --format excel --output Sales
# → Sales.xls

# JSON file
sql2json --name mysql --query sales_monthly --date_from "START_CURRENT_MONTH-1" --format json --output Sales
# → Sales.json

Dated filenames — use date variables in --output:

sql2json --name mysql --query sales_monthly --date_from "START_CURRENT_MONTH" \
    --format csv --output "Sales_{START_CURRENT_MONTH}_{CURRENT_DATE}"
# → Sales_2026-05-01_2026-05-16.csv

sql2json --name mysql --query sales_monthly --date_from "CURRENT_DATE" \
    --format csv --output "reports/Sales_{CURRENT_DATE}"
# → reports/Sales_2026-05-16.csv

Note: --output does not create directories. Create the target folder first.

Note: CSV requires --output (it cannot be written to stdout).

Python API

The supported Python API mirrors the user-facing CLI capabilities while keeping implementation details private:

from sql2json import list_connections, list_queries, run_query2json, run_query_by_name

rows = run_query2json(
    name="sqlite:///:memory:",
    query="SELECT :person_name AS name, :score AS score",
    person_name="Ada",
    score=42,
)

connections = list_connections("/path/to/config.json")
queries = list_queries("/path/to/config.json")                      # global legacy names
scoped_queries = list_queries("/path/to/config.json", scoped=True)   # {"global": [...], "connections": {...}}
mysql_queries = list_queries("/path/to/config.json", connection="mysql")

Use run_query2json() for inline SQL, named queries, SQL files with @/path.sql, bind/date parameters, first, key, value, wrapper, jsonkeys, and timezone. Use run_query_by_name() when you specifically want the lower-level named connection/query call.

Named query resolution in the Python API matches the CLI: connection-scoped query first, global query fallback, then raw SQL or @file handling for run_query2json().

Python API errors are normal Python exceptions. The CLI-only JSON stderr envelope is not used by the Python API.

Supported public imports are exported from sql2json.__all__. Internal helpers in sql2json.sql2json, sql2json.__main__, or sql2json.parameter.parameter_parser are implementation details and should not be imported by users. sql2json.parameter.parse_parameter remains public for date-variable resolution; lower-level date helper functions are private.

See examples/python_api for runnable examples covering named queries, inline SQL, discovery, output shapes, JSON columns, date parameters, SQL files, and exception handling.

Public API surface

sql2json treats the following as its supported, public surface. Everything else is an implementation detail that may change without notice.

Python API — the names exported from sql2json.__all__:

run_query2json, run_query_by_name
list_connections, list_queries
parse_parameter (from sql2json.parameter)
__version__

CLI compatibility contract — the supported, stable CLI behavior:

Documented flags: --name, --query, plus --first, --key, --value, --wrapper, --jsonkeys, --format, --output, --timezone, and arbitrary --<bind_param> values.
Output shapes: JSON to stdout (default), CSV and Excel via --format/--output.
Error contract: a structured JSON error envelope on stderr with a non-zero exit code.

Versioning: sql2json is pre-1.0 (0.x) and carries no API stability guarantee under SemVer — breaking changes ship in a minor bump (e.g. 0.1.x → 0.2.0), not a major. A real stability contract would be an explicit 1.0.0 decision.

For AI agents

sql2json is designed to be called as a subprocess by AI agents and LLMs. It outputs clean JSON to stdout, structured errors to stderr, and supports discovery commands so an agent can orient itself before querying.

See AGENTS.md for the full agent integration guide, including discovery flags, error handling, the Python API, and security notes.

Contributing

Issues and pull requests are welcome — see CONTRIBUTING.md for local setup and the quality gates. Releases are maintainer-only (RELEASING.md).

Security

sql2json executes the SQL it is given and config files may contain database credentials. See SECURITY.md for the security model and how to report a vulnerability privately.

Name		Name	Last commit message	Last commit date
.github/workflows		.github/workflows
docker		docker
docs		docs
examples/python_api		examples/python_api
scripts		scripts
skills/sql2json		skills/sql2json
sql2json		sql2json
tests		tests
.dockerignore		.dockerignore
.flake8		.flake8
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
.python-version		.python-version
AGENTS.md		AGENTS.md
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
CONTRIBUTING.md		CONTRIBUTING.md
Dockerfile		Dockerfile
LICENSE		LICENSE
README.md		README.md
RELEASING.md		RELEASING.md
SECURITY.md		SECURITY.md
WORKFLOW.local.md		WORKFLOW.local.md
WORKFLOW.md		WORKFLOW.md
docker-compose.yml		docker-compose.yml
pyproject.toml		pyproject.toml
uv.lock		uv.lock

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sql2json

Use cases

Install

As a project dependency (library use)

Database drivers (extras)

Per-OS notes

Running it

Upgrading

Docker

Supported tags

Usage

Build from source (development)

Try it with docker compose

Real database verification

Quality gates

Quick start

Configuration

Config file format

CLI reference

Discovery

Writing data & read-only mode

--read-only (safe mode)

Date variables

Output transformations

Array of objects (default)

First row only (--first)

Single value (--first --key)

Key-value pairs (--key --value)

Wrapped for dashboards (--wrapper)

Parse JSON columns (--jsonkeys)

Inline SQL

External .sql file

File output

Python API

Public API surface

For AI agents

Contributing

Security

License

About

Topics

Resources

Contributing

Security policy

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Used by

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Languages

`--read-only` (safe mode)

First row only (`--first`)

Single value (`--first --key`)

Key-value pairs (`--key --value`)

Wrapped for dashboards (`--wrapper`)

Parse JSON columns (`--jsonkeys`)

External `.sql` file