Schemas

Table Schemas

schema

ibis.schema(pairs=None, names=None, types=None)

Validate and return a Schema object.

Parameters

Name	Type	Description	Default
pairs	SchemaLike | None	List or dictionary of name, type pairs. Mutually exclusive with names and types arguments.	None
names	Iterable[str] | None	Field names. Mutually exclusive with pairs.	None
types	Iterable[str | dt.DataType] | None	Field types. Mutually exclusive with pairs.	None

Returns

Name	Type	Description
	Schema	An ibis schema

Examples

>>> from ibis import schema, Schema
>>> sc = schema([("foo", "string"), ("bar", "int64"), ("baz", "boolean")])
>>> sc = schema(names=["foo", "bar", "baz"], types=["string", "int64", "boolean"])
>>> sc = schema(dict(foo="string"))
>>> sc = schema(Schema(dict(foo="string")))  # no-op

Schema

Schema(self, **kwargs)

An ordered mapping of str -> datatype, used to hold a Table’s schema.

Attributes

Name	Description
fields	A mapping of str to

Methods

Name	Description
equals	Return whether other is equal to self.
from_numpy	Return the equivalent ibis schema.
from_pandas	Return the equivalent ibis schema.
from_polars	Return the equivalent ibis schema.
from_pyarrow	Return the equivalent ibis schema.
from_tuples	Construct a Schema from an iterable of pairs.
name_at_position	Return the name of a schema column at position i.
to_numpy	Return the equivalent numpy dtypes.
to_pandas	Return the equivalent pandas datatypes.
to_polars	Return the equivalent polars schema.
to_pyarrow	Return the equivalent pyarrow schema.
to_sqlglot	Convert the schema to a list of SQL column definitions.

equals

equals(other)

Return whether other is equal to self.

The order of fields in the schema is taken into account when computing equality.

Parameters

Name	Type	Description	Default
other	Schema	Schema to compare self to.	required

Examples

>>> import ibis
>>> xy = ibis.schema({"x": int, "y": str})
>>> xy2 = ibis.schema({"x": int, "y": str})
>>> yx = ibis.schema({"y": str, "x": int})
>>> xy_float = ibis.schema({"x": float, "y": str})
>>> assert xy.equals(xy2)
>>> assert not xy.equals(yx)
>>> assert not xy.equals(xy_float)

from_numpy

from_numpy(numpy_schema)

Return the equivalent ibis schema.

from_pandas

from_pandas(pandas_schema)

Return the equivalent ibis schema.

from_polars

from_polars(polars_schema)

Return the equivalent ibis schema.

from_pyarrow

from_pyarrow(pyarrow_schema)

Return the equivalent ibis schema.

from_tuples

from_tuples(values)

Construct a Schema from an iterable of pairs.

Parameters

Name	Type	Description	Default
values	Iterable[tuple[str, str | dt.DataType]]	An iterable of pairs of name and type.	required

Returns

Name	Type	Description
	Schema	A new schema

Examples

>>> import ibis
>>> ibis.Schema.from_tuples([("a", "int"), ("b", "string")])

ibis.Schema {
  a  int64
  b  string
}

name_at_position

name_at_position(i)

Return the name of a schema column at position i.

Parameters

Name	Type	Description	Default
i	int	The position of the column	required

Returns

Name	Type	Description
	str	The name of the column in the schema at position i.

Examples

>>> import ibis
>>> sch = ibis.Schema({"a": "int", "b": "string"})
>>> sch.name_at_position(0)

'a'

>>> sch.name_at_position(1)

'b'

to_numpy

to_numpy()

Return the equivalent numpy dtypes.

to_pandas

to_pandas()

Return the equivalent pandas datatypes.

to_polars

to_polars()

Return the equivalent polars schema.

to_pyarrow

to_pyarrow()

Return the equivalent pyarrow schema.

to_sqlglot

to_sqlglot(dialect)

Convert the schema to a list of SQL column definitions.

Parameters

Name	Type	Description	Default
dialect	str | sg.Dialect	The SQL dialect to use.	required

Returns

Name	Type	Description
	list[sqlglot.expressions.ColumnDef]	A list of SQL column definitions.

Examples

>>> import ibis
>>> sch = ibis.schema({"a": "int", "b": "!string"})
>>> sch

ibis.Schema {
  a  int64
  b  !string
}

>>> columns = sch.to_sqlglot(dialect="duckdb")
>>> columns

[ColumnDef(
   this=Identifier(this=a, quoted=True),
   kind=DataType(this=Type.BIGINT)),
 ColumnDef(
   this=Identifier(this=b, quoted=True),
   kind=DataType(this=Type.VARCHAR),
   constraints=[
     ColumnConstraint(
       kind=NotNullColumnConstraint())])]

One use case for this method is to embed its output into a SQLGlot CREATE TABLE expression.

>>> import sqlglot as sg
>>> import sqlglot.expressions as sge
>>> table = sg.table("t", quoted=True)
>>> ct = sge.Create(
...     kind="TABLE",
...     this=sge.Schema(
...         this=table,
...         expressions=columns,
...     ),
... )
>>> ct.sql(dialect="duckdb")

'CREATE TABLE "t" ("a" BIGINT, "b" TEXT NOT NULL)'