from sqlalchemy import exc, schema, topological, util, sql, types as sqltypes from sqlalchemy.sql import expression, operators, visitors from itertools import chain """Utility functions that build upon SQL and Schema constructs.""" def sort_tables(tables): """sort a collection of Table objects in order of their foreign-key dependency.""" tables = list(tables) tuples = [] def visit_foreign_key(fkey): if fkey.use_alter: return parent_table = fkey.column.table if parent_table in tables: child_table = fkey.parent.table tuples.append( ( parent_table, child_table ) ) for table in tables: visitors.traverse(table, {'schema_visitor':True}, {'foreign_key':visit_foreign_key}) return topological.sort(tuples, tables) def find_join_source(clauses, join_to): """Given a list of FROM clauses and a selectable, return the first index and element from the list of clauses which can be joined against the selectable. returns None, None if no match is found. e.g.:: clause1 = table1.join(table2) clause2 = table4.join(table5) join_to = table2.join(table3) find_join_source([clause1, clause2], join_to) == clause1 """ selectables = list(expression._from_objects(join_to)) for i, f in enumerate(clauses): for s in selectables: if f.is_derived_from(s): return i, f else: return None, None def find_tables(clause, check_columns=False, include_aliases=False, include_joins=False, include_selects=False, include_crud=False): """locate Table objects within the given expression.""" tables = [] _visitors = {} if include_selects: _visitors['select'] = _visitors['compound_select'] = tables.append if include_joins: _visitors['join'] = tables.append if include_aliases: _visitors['alias'] = tables.append if include_crud: _visitors['insert'] = _visitors['update'] = \ _visitors['delete'] = lambda ent: tables.append(ent.table) if check_columns: def visit_column(column): tables.append(column.table) _visitors['column'] = visit_column _visitors['table'] = tables.append visitors.traverse(clause, {'column_collections':False}, _visitors) return tables def find_columns(clause): """locate Column objects within the given expression.""" cols = util.column_set() visitors.traverse(clause, {}, {'column':cols.add}) return cols def _quote_ddl_expr(element): if isinstance(element, basestring): element = element.replace("'", "''") return "'%s'" % element else: return repr(element) def expression_as_ddl(clause): """Given a SQL expression, convert for usage in DDL, such as CREATE INDEX and CHECK CONSTRAINT. Converts bind params into quoted literals, column identifiers into detached column constructs so that the parent table identifier is not included. """ def repl(element): if isinstance(element, expression._BindParamClause): return expression.literal_column(_quote_ddl_expr(element.value)) elif isinstance(element, expression.ColumnClause) and \ element.table is not None: return expression.column(element.name) else: return None return visitors.replacement_traverse(clause, {}, repl) def adapt_criterion_to_null(crit, nulls): """given criterion containing bind params, convert selected elements to IS NULL.""" def visit_binary(binary): if isinstance(binary.left, expression._BindParamClause) and binary.left.key in nulls: # reverse order if the NULL is on the left side binary.left = binary.right binary.right = expression.null() binary.operator = operators.is_ binary.negate = operators.isnot elif isinstance(binary.right, expression._BindParamClause) and binary.right.key in nulls: binary.right = expression.null() binary.operator = operators.is_ binary.negate = operators.isnot return visitors.cloned_traverse(crit, {}, {'binary':visit_binary}) def join_condition(a, b, ignore_nonexistent_tables=False, a_subset=None): """create a join condition between two tables or selectables. e.g.:: join_condition(tablea, tableb) would produce an expression along the lines of:: tablea.c.id==tableb.c.tablea_id The join is determined based on the foreign key relationships between the two selectables. If there are multiple ways to join, or no way to join, an error is raised. :param ignore_nonexistent_tables: This flag will cause the function to silently skip over foreign key resolution errors due to nonexistent tables - the assumption is that these tables have not yet been defined within an initialization process and are not significant to the operation. :param a_subset: An optional expression that is a sub-component of ``a``. An attempt will be made to join to just this sub-component first before looking at the full ``a`` construct, and if found will be successful even if there are other ways to join to ``a``. This allows the "right side" of a join to be passed thereby providing a "natural join". """ crit = [] constraints = set() for left in (a_subset, a): if left is None: continue for fk in b.foreign_keys: try: col = fk.get_referent(left) except exc.NoReferencedTableError: if ignore_nonexistent_tables: continue else: raise if col is not None: crit.append(col == fk.parent) constraints.add(fk.constraint) if left is not b: for fk in left.foreign_keys: try: col = fk.get_referent(b) except exc.NoReferencedTableError: if ignore_nonexistent_tables: continue else: raise if col is not None: crit.append(col == fk.parent) constraints.add(fk.constraint) if crit: break if len(crit) == 0: if isinstance(b, expression._FromGrouping): hint = " Perhaps you meant to convert the right side to a subquery using alias()?" else: hint = "" raise exc.ArgumentError( "Can't find any foreign key relationships " "between '%s' and '%s'.%s" % (a.description, b.description, hint)) elif len(constraints) > 1: raise exc.ArgumentError( "Can't determine join between '%s' and '%s'; " "tables have more than one foreign key " "constraint relationship between them. " "Please specify the 'onclause' of this " "join explicitly." % (a.description, b.description)) elif len(crit) == 1: return (crit[0]) else: return sql.and_(*crit) class Annotated(object): """clones a ClauseElement and applies an 'annotations' dictionary. Unlike regular clones, this clone also mimics __hash__() and __cmp__() of the original element so that it takes its place in hashed collections. A reference to the original element is maintained, for the important reason of keeping its hash value current. When GC'ed, the hash value may be reused, causing conflicts. """ def __new__(cls, *args): if not args: # clone constructor return object.__new__(cls) else: element, values = args # pull appropriate subclass from registry of annotated # classes try: cls = annotated_classes[element.__class__] except KeyError: cls = annotated_classes[element.__class__] = type.__new__(type, "Annotated%s" % element.__class__.__name__, (Annotated, element.__class__), {}) return object.__new__(cls) def __init__(self, element, values): # force FromClause to generate their internal # collections into __dict__ if isinstance(element, expression.FromClause): element.c self.__dict__ = element.__dict__.copy() self.__element = element self._annotations = values def _annotate(self, values): _values = self._annotations.copy() _values.update(values) clone = self.__class__.__new__(self.__class__) clone.__dict__ = self.__dict__.copy() clone._annotations = _values return clone def _deannotate(self): return self.__element def _clone(self): clone = self.__element._clone() if clone is self.__element: # detect immutable, don't change anything return self else: # update the clone with any changes that have occured # to this object's __dict__. clone.__dict__.update(self.__dict__) return Annotated(clone, self._annotations) def __hash__(self): return hash(self.__element) def __cmp__(self, other): return cmp(hash(self.__element), hash(other)) # hard-generate Annotated subclasses. this technique # is used instead of on-the-fly types (i.e. type.__new__()) # so that the resulting objects are pickleable. annotated_classes = {} from sqlalchemy.sql import expression for cls in expression.__dict__.values() + [schema.Column, schema.Table]: if isinstance(cls, type) and issubclass(cls, expression.ClauseElement): exec "class Annotated%s(Annotated, cls):\n" \ " __visit_name__ = cls.__visit_name__\n"\ " pass" % (cls.__name__, ) in locals() exec "annotated_classes[cls] = Annotated%s" % (cls.__name__) def _deep_annotate(element, annotations, exclude=None): """Deep copy the given ClauseElement, annotating each element with the given annotations dictionary. Elements within the exclude collection will be cloned but not annotated. """ def clone(elem): # check if element is present in the exclude list. # take into account proxying relationships. if exclude and \ hasattr(elem, 'proxy_set') and \ elem.proxy_set.intersection(exclude): elem = elem._clone() elif annotations != elem._annotations: elem = elem._annotate(annotations.copy()) elem._copy_internals(clone=clone) return elem if element is not None: element = clone(element) return element def _deep_deannotate(element): """Deep copy the given element, removing all annotations.""" def clone(elem): elem = elem._deannotate() elem._copy_internals(clone=clone) return elem if element is not None: element = clone(element) return element def splice_joins(left, right, stop_on=None): if left is None: return right stack = [(right, None)] adapter = ClauseAdapter(left) ret = None while stack: (right, prevright) = stack.pop() if isinstance(right, expression.Join) and right is not stop_on: right = right._clone() right._reset_exported() right.onclause = adapter.traverse(right.onclause) stack.append((right.left, right)) else: right = adapter.traverse(right) if prevright is not None: prevright.left = right if ret is None: ret = right return ret def reduce_columns(columns, *clauses, **kw): """given a list of columns, return a 'reduced' set based on natural equivalents. the set is reduced to the smallest list of columns which have no natural equivalent present in the list. A "natural equivalent" means that two columns will ultimately represent the same value because they are related by a foreign key. \*clauses is an optional list of join clauses which will be traversed to further identify columns that are "equivalent". \**kw may specify 'ignore_nonexistent_tables' to ignore foreign keys whose tables are not yet configured. This function is primarily used to determine the most minimal "primary key" from a selectable, by reducing the set of primary key columns present in the the selectable to just those that are not repeated. """ ignore_nonexistent_tables = kw.pop('ignore_nonexistent_tables', False) columns = util.ordered_column_set(columns) omit = util.column_set() for col in columns: for fk in chain(*[c.foreign_keys for c in col.proxy_set]): for c in columns: if c is col: continue try: fk_col = fk.column except exc.NoReferencedTableError: if ignore_nonexistent_tables: continue else: raise if fk_col.shares_lineage(c): omit.add(col) break if clauses: def visit_binary(binary): if binary.operator == operators.eq: cols = util.column_set(chain(*[c.proxy_set for c in columns.difference(omit)])) if binary.left in cols and binary.right in cols: for c in columns: if c.shares_lineage(binary.right): omit.add(c) break for clause in clauses: visitors.traverse(clause, {}, {'binary':visit_binary}) return expression.ColumnSet(columns.difference(omit)) def criterion_as_pairs(expression, consider_as_foreign_keys=None, consider_as_referenced_keys=None, any_operator=False): """traverse an expression and locate binary criterion pairs.""" if consider_as_foreign_keys and consider_as_referenced_keys: raise exc.ArgumentError("Can only specify one of " "'consider_as_foreign_keys' or " "'consider_as_referenced_keys'") def visit_binary(binary): if not any_operator and binary.operator is not operators.eq: return if not isinstance(binary.left, sql.ColumnElement) or \ not isinstance(binary.right, sql.ColumnElement): return if consider_as_foreign_keys: if binary.left in consider_as_foreign_keys and \ (binary.right is binary.left or binary.right not in consider_as_foreign_keys): pairs.append((binary.right, binary.left)) elif binary.right in consider_as_foreign_keys and \ (binary.left is binary.right or binary.left not in consider_as_foreign_keys): pairs.append((binary.left, binary.right)) elif consider_as_referenced_keys: if binary.left in consider_as_referenced_keys and \ (binary.right is binary.left or binary.right not in consider_as_referenced_keys): pairs.append((binary.left, binary.right)) elif binary.right in consider_as_referenced_keys and \ (binary.left is binary.right or binary.left not in consider_as_referenced_keys): pairs.append((binary.right, binary.left)) else: if isinstance(binary.left, schema.Column) and \ isinstance(binary.right, schema.Column): if binary.left.references(binary.right): pairs.append((binary.right, binary.left)) elif binary.right.references(binary.left): pairs.append((binary.left, binary.right)) pairs = [] visitors.traverse(expression, {}, {'binary':visit_binary}) return pairs def folded_equivalents(join, equivs=None): """Return a list of uniquely named columns. The column list of the given Join will be narrowed down to a list of all equivalently-named, equated columns folded into one column, where 'equated' means they are equated to each other in the ON clause of this join. This function is used by Join.select(fold_equivalents=True). Deprecated. This function is used for a certain kind of "polymorphic_union" which is designed to achieve joined table inheritance where the base table has no "discriminator" column; [ticket:1131] will provide a better way to achieve this. """ if equivs is None: equivs = set() def visit_binary(binary): if binary.operator == operators.eq and binary.left.name == binary.right.name: equivs.add(binary.right) equivs.add(binary.left) visitors.traverse(join.onclause, {}, {'binary':visit_binary}) collist = [] if isinstance(join.left, expression.Join): left = folded_equivalents(join.left, equivs) else: left = list(join.left.columns) if isinstance(join.right, expression.Join): right = folded_equivalents(join.right, equivs) else: right = list(join.right.columns) used = set() for c in left + right: if c in equivs: if c.name not in used: collist.append(c) used.add(c.name) else: collist.append(c) return collist class AliasedRow(object): """Wrap a RowProxy with a translation map. This object allows a set of keys to be translated to those present in a RowProxy. """ def __init__(self, row, map): # AliasedRow objects don't nest, so un-nest # if another AliasedRow was passed if isinstance(row, AliasedRow): self.row = row.row else: self.row = row self.map = map def __contains__(self, key): return self.map[key] in self.row def has_key(self, key): return key in self def __getitem__(self, key): return self.row[self.map[key]] def keys(self): return self.row.keys() class ClauseAdapter(visitors.ReplacingCloningVisitor): """Clones and modifies clauses based on column correspondence. E.g.:: table1 = Table('sometable', metadata, Column('col1', Integer), Column('col2', Integer) ) table2 = Table('someothertable', metadata, Column('col1', Integer), Column('col2', Integer) ) condition = table1.c.col1 == table2.c.col1 make an alias of table1:: s = table1.alias('foo') calling ``ClauseAdapter(s).traverse(condition)`` converts condition to read:: s.c.col1 == table2.c.col1 """ def __init__(self, selectable, equivalents=None, include=None, exclude=None): self.__traverse_options__ = {'column_collections':False, 'stop_on':[selectable]} self.selectable = selectable self.include = include self.exclude = exclude self.equivalents = util.column_dict(equivalents or {}) def _corresponding_column(self, col, require_embedded, _seen=util.EMPTY_SET): newcol = self.selectable.corresponding_column(col, require_embedded=require_embedded) if newcol is None and col in self.equivalents and col not in _seen: for equiv in self.equivalents[col]: newcol = self._corresponding_column(equiv, require_embedded=require_embedded, _seen=_seen.union([col])) if newcol is not None: return newcol return newcol def replace(self, col): if isinstance(col, expression.FromClause): if self.selectable.is_derived_from(col): return self.selectable if not isinstance(col, expression.ColumnElement): return None if self.include and col not in self.include: return None elif self.exclude and col in self.exclude: return None return self._corresponding_column(col, True) class ColumnAdapter(ClauseAdapter): """Extends ClauseAdapter with extra utility functions. Provides the ability to "wrap" this ClauseAdapter around another, a columns dictionary which returns adapted elements given an original, and an adapted_row() factory. """ def __init__(self, selectable, equivalents=None, chain_to=None, include=None, exclude=None, adapt_required=False): ClauseAdapter.__init__(self, selectable, equivalents, include, exclude) if chain_to: self.chain(chain_to) self.columns = util.populate_column_dict(self._locate_col) self.adapt_required = adapt_required def wrap(self, adapter): ac = self.__class__.__new__(self.__class__) ac.__dict__ = self.__dict__.copy() ac._locate_col = ac._wrap(ac._locate_col, adapter._locate_col) ac.adapt_clause = ac._wrap(ac.adapt_clause, adapter.adapt_clause) ac.adapt_list = ac._wrap(ac.adapt_list, adapter.adapt_list) ac.columns = util.populate_column_dict(ac._locate_col) return ac adapt_clause = ClauseAdapter.traverse adapt_list = ClauseAdapter.copy_and_process def _wrap(self, local, wrapped): def locate(col): col = local(col) return wrapped(col) return locate def _locate_col(self, col): c = self._corresponding_column(col, True) if c is None: c = self.adapt_clause(col) # anonymize labels in case they have a hardcoded name if isinstance(c, expression._Label): c = c.label(None) # adapt_required indicates that if we got the same column # back which we put in (i.e. it passed through), # it's not correct. this is used by eagerloading which # knows that all columns and expressions need to be adapted # to a result row, and a "passthrough" is definitely targeting # the wrong column. if self.adapt_required and c is col: return None return c def adapted_row(self, row): return AliasedRow(row, self.columns) def __getstate__(self): d = self.__dict__.copy() del d['columns'] return d def __setstate__(self, state): self.__dict__.update(state) self.columns = util.PopulateDict(self._locate_col)