The application side: generated files as malli registries, plus helpers that need malli. Generated files are read from the classpath as pgmalli/<schema>.edn.
The application side: generated files as malli registries, plus helpers that need malli. Generated files are read from the classpath as pgmalli/<schema>.edn.
[:pg/bytes {:min n :max n}]: a byte array of bounded length, generated as such (malli's bytes? has no length).
[:pg/bytes {:min n :max n}]: a byte array of bounded length, generated as such (malli's bytes?
has no length).[:pg/check expr]: a row passes when the CHECK expression data does (pgmalli.impl.eval). A column missing from the row is NULL, or its value in the :pg/defaults property.
[:pg/check expr]: a row passes when the CHECK expression data does (pgmalli.impl.eval). A column missing from the row is NULL, or its value in the :pg/defaults property.
[:pg/check-value expr]: a domain CHECK, the value standing for VALUE.
[:pg/check-value expr]: a domain CHECK, the value standing for VALUE.
(columns registry name)The [:map ...] of a row or insert schema, without the table-level constraints.
The [:map ...] of a row or insert schema, without the table-level constraints.
(dataset-generator registry)(dataset-generator registry {:keys [rows except] :or {rows 5}})test.check generator of datasets that satisfy dataset-schema: tables are generated in foreign-key order and referencing columns are pointed at rows generated before them (a self-reference at the same table); a reference that finds no fitting row grows its target table by one row that fits, whose own references may grow their targets in turn. :rows is the number of rows wanted per table, out of many more candidates; a table that comes out short (a CHECK random rows cannot satisfy, a parent that came out empty) is recorded in the dataset's metadata under :pgmalli/short with the reasons, and its children come out short too. :except names tables ("schema.table") to leave out; a kept table may not reference one of them.
test.check generator of datasets that satisfy dataset-schema: tables are generated in
foreign-key order and referencing columns are pointed at rows generated before them (a
self-reference at the same table); a reference that finds no fitting row grows its target
table by one row that fits, whose own references may grow their targets in turn. :rows is
the number of rows wanted per table, out of many more candidates; a table that comes out
short (a CHECK random rows cannot satisfy, a parent that came out empty) is recorded in
the dataset's metadata under :pgmalli/short with the reasons, and its children come out
short too. :except names tables ("schema.table") to leave out; a kept table may not
reference one of them.(dataset-schema registry)Schema for {"schema.table" [row ...] ...} covering every table of the registry: rows validate against their row schemas, and every primary key, unique constraint and foreign key is a check of its own, named in its error. The result contains functions, so it is built at runtime.
Schema for {"schema.table" [row ...] ...} covering every table of the registry: rows validate
against their row schemas, and every primary key, unique constraint and foreign key is a
check of its own, named in its error. The result contains functions, so it is built at runtime.(read-generated schema)The generated data for a schema name, from the classpath (pgmalli/<schema>.edn).
The generated data for a schema name, from the classpath (pgmalli/<schema>.edn).
(registry & schemas)The registry pgmalli.core/registry documents.
The registry pgmalli.core/registry documents.
(transformer)(transformer {:keys [zone] :or {zone (java.time.ZoneId/systemDefault)}})Decodes JDBC and string values into the registry's types: java.sql.Timestamp and java.util.Date -> Instant, java.sql.Date -> LocalDate, an Instant or java.util.Date landing in a date or timestamp (without time zone) column is read in :zone, default the JVM's; JSON text in a json or jsonb column is parsed.
Decodes JDBC and string values into the registry's types: java.sql.Timestamp and java.util.Date -> Instant, java.sql.Date -> LocalDate, an Instant or java.util.Date landing in a date or timestamp (without time zone) column is read in :zone, default the JVM's; JSON text in a json or jsonb column is parsed.
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