sqlalchemy.sql.lambdas.AnalyzedFunction

class documentation

class AnalyzedFunction(object):

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Undocumented

Method __init__ Undocumented
Method ​_coerce​_expression Run the tracker-generated expression through coercion rules.
Method ​_instrument​_and​_run​_function Undocumented
Method ​_rewrite​_code​_obj Return a copy of f, with a new closure and new globals
Class Variable __slots__ Undocumented
Instance Variable analyzed​_code Undocumented
Instance Variable bindparam​_trackers Undocumented
Instance Variable closure​_pywrappers Undocumented
Instance Variable expected​_expr Undocumented
Instance Variable expr Undocumented
Instance Variable fn Undocumented
Instance Variable is​_sequence Undocumented
Instance Variable propagate​_attrs Undocumented
Instance Variable tracker​_instrumented​_fn Undocumented
def __init__(self, analyzed_code, lambda_element, apply_propagate_attrs, fn):

Undocumented

def _coerce_expression(self, lambda_element, apply_propagate_attrs):

Run the tracker-generated expression through coercion rules.

After the user-defined lambda has been invoked to produce a statement for re-use, run it through coercion rules to both check that it's the correct type of object and also to coerce it to its useful form.

def _instrument_and_run_function(self, lambda_element):

Undocumented

def _rewrite_code_obj(self, f, cell_values, globals_):

Return a copy of f, with a new closure and new globals

yes it works in pypy :P

__slots__: tuple[str, ...] =

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analyzed_code =

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bindparam_trackers =

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closure_pywrappers: list =

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expected_expr =

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expr =

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fn =

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is_sequence: bool =

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propagate_attrs =

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tracker_instrumented_fn =

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