Filters and validation

Filters are used anywhere you want ZangTable to select matching rows instead of working with every row in a table. The most common places are:

Listing records, for example “only active recipes” or “orders for customer 42”.
Bulk updating records, for example “archive every draft older than January 1”.
Bulk deleting records, for example “delete rows where deleted_at is already set”.
Creating exports that include only matching rows.

Shared validation

Field	Rule
`{project}`	Project slug / Project ID: `^[a-z0-9_-]+$`, normalized to lowercase
`{table}` / `{column}` / `{index}`	Names use `^[A-Za-z][A-Za-z0-9_]*$`; some endpoints also accept numeric IDs where documented
`column_type`	`INTEGER`, `REAL`, `TEXT`, `BLOB`, `ANY`; omitted column types default to `TEXT`
Boolean-like fields	booleans, integer `1`, or strings `1`, `true`, `yes`, `on` count as true; other values count as false

Simple filter object

Use this when every condition is an exact match.

{"status":"active","owner_id":42}

Common usage:

curl "$BASE_URL/projects/$PROJECT/records/recipes?filters=%7B%22status%22%3A%22active%22%7D" \
  -H "Authorization: Bearer $ZANGTABLE_TOKEN"

Condition array

Use this when you need operators like greater-than, like, in, or null checks.

[
  {"column":"status","op":"=","value":"active"},
  {"column":"created_at","op":">=","value":"2026-01-01"},
  {"column":"tag","op":"in","value":["dinner","dessert"]},
  {"column":"deleted_at","op":"is_null"}
]

Supported operators: =, eq_ci, !=, >, >=, <, <=, like, in, is_null, not_null. Use eq_ci for exact text equality ignoring ASCII case, such as a handle lookup. It treats _ and % as ordinary characters, unlike like. SQLite’s NOCASE comparison is ASCII-oriented; normalize non-ASCII identifiers in your application if you need broader Unicode case folding.

[{"column":"handle","op":"eq_ci","value":"raul_name"}]

Bulk update example

curl -X PATCH "$BASE_URL/projects/$PROJECT/records/recipes" \
  -H "Authorization: Bearer $ZANGTABLE_TOKEN" \
  -H "Content-Type: application/json" \
  --data '{
    "data": {"status":"archived"},
    "where": [
      {"column":"status","op":"=","value":"draft"},
      {"column":"updated_at","op":"<","value":"2026-01-01"}
    ]
  }'

Use condition arrays for precise updates/deletes. Use the simple object format for everyday exact-match filtering.

Get started

Essentials

Filters and validation

Shared validation

Simple filter object

Condition array

Bulk update example

​Shared validation

​Simple filter object

​Condition array

​Bulk update example

Shared validation

Simple filter object

Condition array

Bulk update example