Type Inference

Scythe infers types from your SQL schema and query structure. The key insight: not all columns are nullable, and not all nullable columns stay nullable after transformation.

Neutral Type System

Scythe uses a language-neutral type vocabulary internally. Each backend maps these to concrete types.

Neutral Type	PostgreSQL Source
bool	BOOLEAN
int16	SMALLINT
int32	INTEGER, SERIAL
int64	BIGINT, BIGSERIAL
float32	REAL
float64	DOUBLE PRECISION
string	TEXT, VARCHAR, CHAR
bytes	BYTEA
decimal	NUMERIC, DECIMAL
uuid	UUID
date	DATE
time	TIME
time_tz	TIME WITH TIME ZONE
datetime	TIMESTAMP
datetime_tz	TIMESTAMPTZ
interval	INTERVAL
json	JSON, JSONB
inet	INET, CIDR

Nullability from JOINs

Columns from the right side of a LEFT JOIN are always nullable, even if the column is defined as NOT NULL:

-- @name GetUserOrders
-- @returns :many
SELECT u.id, u.name, o.total
FROM users u
LEFT JOIN orders o ON u.id = o.user_id;

Column	Type	Nullable	Reason
u.id	int32	no	Left side of LEFT JOIN
u.name	string	no	Left side of LEFT JOIN
o.total	decimal	yes	Right side of LEFT JOIN

Similarly, columns from the left side of a RIGHT JOIN become nullable.

The same widening applies to LEFT SEMI JOIN and LEFT ANTI JOIN (the non-preserved side’s columns are not projected, but the widening rule is the same as LEFT JOIN). FULL OUTER JOIN widens both sides – every column from either table can be NULL, since a row might exist on only one side. This also applies inside nested joins (parenthesized FROM clauses).

Nullability from COALESCE

COALESCE strips nullability when any argument – not just the last one – is non-nullable:

-- @name GetUserDisplayName
-- @returns :one
SELECT COALESCE(nickname, name, 'Anonymous') AS display_name
FROM users WHERE id = $1;

display_name is non-nullable because the final fallback 'Anonymous' is a non-null literal. The same result holds if any earlier argument – not only the last – is itself non-nullable (for example a NOT NULL column), even if later arguments are nullable.

-- @name GetUserNickname
-- @returns :one
SELECT COALESCE(nickname, name) AS display_name
FROM users WHERE id = $1;

If both nickname and name are nullable columns, display_name remains nullable.

Oracle exception

On Oracle, empty string literals ('', N'') evaluate to NULL rather than an empty value. A literal fallback like COALESCE(email, '') is treated as a non-null literal on every other dialect, but on Oracle the fallback itself is NULL, so display_name stays nullable there. See Oracle: Empty string is NULL and the live conformance fixture testing_data/nullability_live/coalesce_non_null/live_coalesce_with_empty_string_default_is_null_on_oracle.json.

Nullability from Aggregates

Aggregate functions have specific nullability rules for ordinary (non-windowed) aggregation:

Function	Nullable?	Reason
COUNT(*)	no	Always returns a number
COUNT(col)	no	Always returns a number
SUM(col)	yes	Returns NULL for empty sets
AVG(col)	yes	Returns NULL for empty sets
MIN(col)	yes	Returns NULL for empty sets
MAX(col)	yes	Returns NULL for empty sets

-- @name GetUserStats
-- @returns :one
SELECT
    COUNT(*) AS total_orders,
    SUM(total) AS revenue,
    MAX(created_at) AS last_order
FROM orders WHERE user_id = $1;

Column	Nullable	Reason
total_orders	no	COUNT is never null
revenue	yes	SUM returns NULL for empty result
last_order	yes	MAX returns NULL for empty result

Windowed aggregates

A windowed aggregate (OVER (...)) produces one output row per input row, so an empty result set means zero output rows rather than a NULL aggregate value. Nullability differs from the non-windowed case above:

Function	Windowed nullability	Reason
SUM(col) OVER (...)	no	Cannot be evaluated over zero rows within the window
AVG(col) OVER (...)	no	Same as SUM
MIN(col) OVER (...) / MAX(col) OVER (...)	same as col	Takes the nullability of the argument column, not true

Aggregate result types

Aggregates can widen the argument’s neutral type, not just its nullability:

Function	Argument type	Result type
SUM	int32 (or narrower)	int64
SUM	int64	decimal (arbitrary precision, since int64 has no wider integer type)
SUM	float type	Same float type, unwidened
AVG	non-float	decimal
AVG	float type	float64

Nested aggregates

On PostgreSQL, json_agg(alias.*), jsonb_agg(alias.*), row_to_json(alias.*), to_json(alias.*) and to_jsonb(alias.*) resolve to a struct scythe synthesizes from the aggregated relation, not to an opaque json scalar. The neutral type is json_nested<T>:

Expression	Join	Neutral type
json_agg(o.*), jsonb_agg(o.*)	inner	json_nested<array<GetUserOrdersRowOrders>>
json_agg(o.*), jsonb_agg(o.*)	outer	json_nested<array<nullable<GetUserOrdersOuterRowOrders>>>
row_to_json(o.*), to_json(o.*), to_jsonb(o.*)	–	json_nested<GetOrderPayloadRowPayload>

jsonb_agg differs from json_agg only in storage type, and to_json/to_jsonb over a whole-row reference return the same document row_to_json does, so each pair infers the same shape.

The struct name is the query name, then Row, then the output column name: query GetUserOrders with an AS orders column produces GetUserOrdersRowOrders. A name that collides with a composite or enum in the catalog gains a numeric suffix. Fields are the aggregated relation’s columns in schema order, each keeping its own schema nullability.

The bare-identifier form (json_agg(o), where o is a table alias rather than a column) is recognized the same way.

Generated code

-- @name GetUsersWithOrders
-- @returns :many
SELECT u.id, u.name, json_agg(o.*) AS orders
FROM users u
JOIN orders o ON o.user_id = u.id
GROUP BY u.id, u.name;

Against an orders table of id, user_id, total, weight_kg, notes, created_at, the rust-sqlx backend emits:

#[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
pub struct GetUsersWithOrdersRowOrders {
    pub id: i32,
    pub user_id: i32,
    pub total: rust_decimal::Decimal,
    pub weight_kg: Option<f64>,
    pub notes: Option<String>,
    pub created_at: chrono::DateTime<chrono::Utc>,
}

#[derive(Debug, Clone, sqlx::FromRow)]
pub struct GetUsersWithOrdersRow {
    pub id: i32,
    pub name: String,
    pub orders: Option<sqlx::types::Json<Vec<GetUsersWithOrdersRowOrders>>>,
}

row_to_json has no array wrapper – one JSON object per output row rather than one element per aggregated row:

#[derive(Debug, Clone, sqlx::FromRow)]
pub struct GetUserAsJsonRow {
    pub payload: Option<sqlx::types::Json<GetUserAsJsonRowPayload>>,
}

Nullability of the aggregate

The column is always nullable: json_agg/jsonb_agg return NULL for an empty group, and row_to_json/to_json/to_jsonb over a null-extended row return SQL NULL.

An outer join widens the array element, not the fields. For a non-matching row PostgreSQL makes the whole-row variable itself NULL, so json_agg(o.*) aggregates one JSON null and the column’s value is [null] – never [{"id": null, ...}]. The same query over a LEFT JOIN therefore emits:

#[derive(Debug, Clone, sqlx::FromRow)]
pub struct GetUsersWithOrdersOuterRow {
    pub id: i32,
    pub orders: Option<sqlx::types::Json<Vec<Option<GetUsersWithOrdersOuterRowOrders>>>>,
}

json_agg(o.*) FILTER (WHERE o.id IS NOT NULL) – the idiom for suppressing that [null] – cannot produce a null element, but scythe does not prove that. The element stays optional.

JSON keys

The keys json_agg and row_to_json emit are the raw SQL column names, which need not match the generated field names. Each backend spells the mapping out:

Backend	Row field type for json_nested<T>	Key mapping
rust-sqlx	sqlx::types::Json<T>	#[serde(rename = "...")] where the field name differs
rust-tokio-postgres	postgres_types::Json<T>	same
go-pgx	T	json:"..." struct tag
python-psycopg3	T	a _from_json classmethod

A quoted mixed-case column keeps its key and renames the field:

    #[serde(rename = "createdAt")]
    pub created_at: chrono::DateTime<chrono::Utc>,

An enum reachable only through a nested struct is emitted with serde derives and per-variant renames, because inside a JSON result the value is decoded by serde rather than off the wire by the driver:

#[derive(Debug, Clone, PartialEq, Eq, sqlx::Type, serde::Serialize, serde::Deserialize)]
#[sqlx(type_name = "user_status", rename_all = "snake_case")]
pub enum UserStatus {
    #[serde(rename = "active")]
    Active,
    #[serde(rename = "inactive")]
    Inactive,
    #[serde(rename = "banned")]
    Banned,
}

Where it does not apply

Only the four backends in the table above emit nested structs. Every other backend rewrites the column to plain json, byte-identical to what it produced before nested inference existed – including the enums and composites reachable only through the discarded struct, which are not emitted.

Inference is also gated on the engine. PostgreSQL and CockroachDB infer nested structs; on every other engine json_agg keeps its plain json mapping. That includes Redshift and DuckDB, which map onto the PostgreSQL dialect but have no json_agg.

These are not covered:

• json_object_agg and jsonb_object_agg – plain json. They build an object keyed by the runtime values of their first argument (json_object_agg(o.id, o.status) yields {"1": "shipped"}), so there is no fixed field set to synthesize a struct from.
• json_agg/jsonb_agg over a scalar expression, or over a bare * – plain json.
• to_json/to_jsonb over a scalar expression – plain json, nullable exactly when the argument is (both are strict: to_json(NULL) is SQL NULL, not the JSON document null).
• json_build_object, json_build_array and their jsonb spellings – plain, non-nullable json. They are not strict, so a NULL argument becomes a JSON null inside a non-NULL document.
• json_strip_nulls/jsonb_strip_nulls – plain json, nullable exactly when the argument is. They are strict, unlike the json_build_* family they sit next to.
• array_agg and string_agg – unaffected, still array<T> and string.
• A nested aggregate over a nested aggregate – rejected with an error. Wrap one level per query.
• @json annotations, which produce json_typed<T> – untouched.

Two queries in one output file that derive the same struct name emit one definition when their field shapes match, and fail with an error naming both when they do not.

See Neutral Types for the full container table.

Nullability from CASE

CASE expressions are nullable if any branch can produce NULL:

-- @name GetUserTier
-- @returns :one
SELECT
    CASE
        WHEN total_spent > 1000 THEN 'gold'
        WHEN total_spent > 100 THEN 'silver'
        ELSE 'bronze'
    END AS tier
FROM users WHERE id = $1;

tier is non-nullable because all branches (including ELSE) produce non-null values.

SELECT
    CASE
        WHEN total_spent > 1000 THEN 'gold'
    END AS tier
FROM users WHERE id = $1;

tier is nullable because the implicit ELSE returns NULL.

The IS NOT NULL guard exception

A branch that returns a nullable column is not counted as nullable if its condition is exactly WHEN <col> IS NOT NULL THEN <col> – guarding a column with its own null check proves that branch’s result cannot be NULL:

SELECT
    CASE WHEN bio IS NOT NULL THEN bio ELSE 'No bio' END AS bio_display
FROM users WHERE id = $1;

bio_display is non-nullable: the bio branch is exempted by the guard, and the ELSE branch is a non-null literal. This exception only matches the exact col IS NOT NULL THEN col shape (same expression on both sides); it does not generalize to other guard conditions.

Nullability from Expressions

Binary operators fall into three groups:

• Arithmetic (+, -, *, /, %) and string concatenation (||) propagate nullability: if either operand is nullable, the result is nullable.

  SELECT a + b AS sum FROM t;

  If either a or b is nullable, sum is nullable.

• Comparison (=, <>, <, <=, >, >=) and boolean (AND, OR) always produce a non-nullable bool, regardless of operand nullability.

• JSON operators (->, ->>, #>, #>>) are always nullable, regardless of operand nullability – a missing key or path segment naturally produces SQL NULL.

Scalar subqueries

A scalar subquery (a subquery used as a single expression value) is nullable if it can return zero rows, because a zero-row result evaluates to SQL NULL regardless of the projected column’s own nullability. The one exception is an ungrouped aggregate query with no HAVING clause and a single projected column (e.g. (SELECT COUNT(*) FROM ...)) – that shape always returns exactly one row, so its nullability is the aggregate’s own nullability from the tables above, not forced to nullable.

Manual Overrides

When the analyzer cannot determine nullability correctly, use annotations:

-- @name GetUser
-- @returns :one
-- @nullable bio
-- @nonnull computed_status
SELECT id, bio, some_complex_expression() AS computed_status
FROM users WHERE id = $1;

See Annotations for details on @nullable and @nonnull.