apache_beam.dataframe.expressions module

class apache_beam.dataframe.expressions.Session(bindings=None)

Bases: object

A session represents a mapping of expressions to concrete values.

The bindings typically include required placeholders, but may be any intermediate expression as well.

evaluate(expr)

lookup(expr)

class apache_beam.dataframe.expressions.Expression(name, proxy, _id=None)

Bases: object

An expression is an operation bound to a set of arguments.

An expression represents a deferred tree of operations, which can be evaluated at a specific bindings of root expressions to values.

proxy()

placeholders()

Returns all the placeholders that self depends on.

evaluate_at(session)

Returns the result of self with the bindings given in session.

requires_partition_by_index()

Whether this expression requires its argument(s) to be partitioned by index.

preserves_partition_by_index()

Whether the result of this expression will be partitioned by index whenever all of its inputs are partitioned by index.

class apache_beam.dataframe.expressions.PlaceholderExpression(proxy, reference=None)

Bases: apache_beam.dataframe.expressions.Expression

An expression whose value must be explicitly bound in the session.

Initialize a placeholder expression.

Parameters:proxy – A proxy object with the type expected to be bound to this expression. Used for type checking at pipeline construction time.

placeholders()

args()

evaluate_at(session)

requires_partition_by_index()

preserves_partition_by_index()

class apache_beam.dataframe.expressions.ConstantExpression(value, proxy=None)

Bases: apache_beam.dataframe.expressions.Expression

An expression whose value is known at pipeline construction time.

Initialize a constant expression.

Parameters:

• value – The constant value to be produced by this expression.
• proxy – (Optional) a proxy object with same type as value to use for rapid type checking at pipeline construction time. If not provided, value will be used directly.

placeholders()

args()

evaluate_at(session)

requires_partition_by_index()

preserves_partition_by_index()

class apache_beam.dataframe.expressions.ComputedExpression(name, func, args, proxy=None, _id=None, requires_partition_by_index=True, preserves_partition_by_index=False)

Bases: apache_beam.dataframe.expressions.Expression

An expression whose value must be computed at pipeline execution time.

Initialize a computed expression.

Parameters:

• name – The name of this expression.
• func – The function that will be used to compute the value of this expression. Should accept arguments of the types returned when evaluating the args expressions.
• args – The list of expressions that will be used to produce inputs to func.
• proxy – (Optional) a proxy object with same type as the objects that this ComputedExpression will produce at execution time. If not provided, a proxy will be generated using func and the proxies of args.
• _id – (Optional) a string to uniquely identify this expression.
• requires_partition_by_index – Whether this expression requires its argument(s) to be partitioned by index.
• preserves_partition_by_index – Whether the result of this expression will be partitioned by index whenever all of its inputs are partitioned by index.

placeholders()

args()

evaluate_at(session)

requires_partition_by_index()

preserves_partition_by_index()

apache_beam.dataframe.expressions.elementwise_expression(name, func, args)