Python django.db.models.sql.compiler() Examples

def __iter__(self):
        """
        The queryset iterator protocol uses three nested iterators in the
        default case:
            1. sql.compiler:execute_sql()
               - Returns 100 rows at time (constants.GET_ITERATOR_CHUNK_SIZE)
                 using cursor.fetchmany(). This part is responsible for
                 doing some column masking, and returning the rows in chunks.
            2. sql/compiler.results_iter()
               - Returns one row at time. At this point the rows are still just
                 tuples. In some cases the return values are converted to
                 Python values at this location.
            3. self.iterator()
               - Responsible for turning the rows into model objects.
        """
        self._fetch_all()
        return iter(self._result_cache) 

def __iter__(self):
        queryset = self.queryset
        query = queryset.query
        compiler = query.get_compiler(queryset.db)

        if not query.extra_select and not query.annotation_select:
            for row in compiler.results_iter():
                yield tuple(row)
        else:
            field_names = list(query.values_select)
            extra_names = list(query.extra_select)
            annotation_names = list(query.annotation_select)

            # extra(select=...) cols are always at the start of the row.
            names = extra_names + field_names + annotation_names

            if queryset._fields:
                # Reorder according to fields.
                fields = list(queryset._fields) + [f for f in annotation_names if f not in queryset._fields]
            else:
                fields = names

            for row in compiler.results_iter():
                data = dict(zip(names, row))
                yield tuple(data[f] for f in fields) 

def __iter__(self):
        queryset = self.queryset
        query = queryset.query
        compiler = query.get_compiler(queryset.db)

        if queryset._fields:
            field_names = list(query.values_select)
            extra_names = list(query.extra_select)
            annotation_names = list(query.annotation_select)

            # extra(select=...) cols are always at the start of the row.
            names = extra_names + field_names + annotation_names

            fields = list(queryset._fields) + [f for f in annotation_names if f not in queryset._fields]
            if fields != names:
                # Reorder according to fields.
                index_map = {name: idx for idx, name in enumerate(names)}
                rowfactory = operator.itemgetter(*[index_map[f] for f in fields])
                return map(
                    rowfactory,
                    compiler.results_iter(chunked_fetch=self.chunked_fetch, chunk_size=self.chunk_size)
                )
        return compiler.results_iter(tuple_expected=True, chunked_fetch=self.chunked_fetch, chunk_size=self.chunk_size) 

def __iter__(self):
        """
        The queryset iterator protocol uses three nested iterators in the
        default case:
            1. sql.compiler:execute_sql()
               - Returns 100 rows at time (constants.GET_ITERATOR_CHUNK_SIZE)
                 using cursor.fetchmany(). This part is responsible for
                 doing some column masking, and returning the rows in chunks.
            2. sql/compiler.results_iter()
               - Returns one row at time. At this point the rows are still just
                 tuples. In some cases the return values are converted to
                 Python values at this location.
            3. self.iterator()
               - Responsible for turning the rows into model objects.
        """
        self._fetch_all()
        return iter(self._result_cache) 

def __iter__(self):
        """
        The queryset iterator protocol uses three nested iterators in the
        default case:
            1. sql.compiler:execute_sql()
               - Returns 100 rows at time (constants.GET_ITERATOR_CHUNK_SIZE)
                 using cursor.fetchmany(). This part is responsible for
                 doing some column masking, and returning the rows in chunks.
            2. sql.compiler.results_iter()
               - Returns one row at time. At this point the rows are still just
                 tuples. In some cases the return values are converted to
                 Python values at this location.
            3. self.iterator()
               - Responsible for turning the rows into model objects.
        """
        self._fetch_all()
        return iter(self._result_cache) 

def __iter__(self):
        queryset = self.queryset
        query = queryset.query
        compiler = query.get_compiler(queryset.db)

        if not query.extra_select and not query.annotation_select:
            for row in compiler.results_iter():
                yield tuple(row)
        else:
            field_names = list(query.values_select)
            extra_names = list(query.extra_select)
            annotation_names = list(query.annotation_select)

            # extra(select=...) cols are always at the start of the row.
            names = extra_names + field_names + annotation_names

            if queryset._fields:
                # Reorder according to fields.
                fields = list(queryset._fields) + [f for f in annotation_names if f not in queryset._fields]
            else:
                fields = names

            for row in compiler.results_iter():
                data = dict(zip(names, row))
                yield tuple(data[f] for f in fields) 

def __iter__(self):
        queryset = self.queryset
        query = queryset.query
        compiler = query.get_compiler(queryset.db)

        if not query.extra_select and not query.annotation_select:
            for row in compiler.results_iter():
                yield tuple(row)
        else:
            field_names = list(query.values_select)
            extra_names = list(query.extra_select)
            annotation_names = list(query.annotation_select)

            # extra(select=...) cols are always at the start of the row.
            names = extra_names + field_names + annotation_names

            if queryset._fields:
                # Reorder according to fields.
                fields = list(queryset._fields) + [f for f in annotation_names if f not in queryset._fields]
            else:
                fields = names

            for row in compiler.results_iter():
                data = dict(zip(names, row))
                yield tuple(data[f] for f in fields) 

def __iter__(self):
        """
        The queryset iterator protocol uses three nested iterators in the
        default case:
            1. sql.compiler:execute_sql()
               - Returns 100 rows at time (constants.GET_ITERATOR_CHUNK_SIZE)
                 using cursor.fetchmany(). This part is responsible for
                 doing some column masking, and returning the rows in chunks.
            2. sql/compiler.results_iter()
               - Returns one row at time. At this point the rows are still just
                 tuples. In some cases the return values are converted to
                 Python values at this location.
            3. self.iterator()
               - Responsible for turning the rows into model objects.
        """
        self._fetch_all()
        return iter(self._result_cache) 

def __iter__(self):
        """
        The queryset iterator protocol uses three nested iterators in the
        default case:
            1. sql.compiler:execute_sql()
               - Returns 100 rows at time (constants.GET_ITERATOR_CHUNK_SIZE)
                 using cursor.fetchmany(). This part is responsible for
                 doing some column masking, and returning the rows in chunks.
            2. sql/compiler.results_iter()
               - Returns one row at time. At this point the rows are still just
                 tuples. In some cases the return values are converted to
                 Python values at this location.
            3. self.iterator()
               - Responsible for turning the rows into model objects.
        """
        self._fetch_all()
        return iter(self._result_cache) 

def __iter__(self):
        queryset = self.queryset
        compiler = queryset.query.get_compiler(queryset.db)
        for row in compiler.results_iter():
            yield row[0] 

def __iter__(self):
        queryset = self.queryset
        compiler = queryset.query.get_compiler(queryset.db)
        for row in compiler.results_iter():
            yield row[0] 

def __iter__(self):
        queryset = self.queryset
        query = queryset.query
        compiler = query.get_compiler(queryset.db)

        field_names = list(query.values_select)
        extra_names = list(query.extra_select)
        annotation_names = list(query.annotation_select)

        # extra(select=...) cols are always at the start of the row.
        names = extra_names + field_names + annotation_names

        for row in compiler.results_iter():
            yield dict(zip(names, row)) 

def __iter__(self):
        queryset = self.queryset
        db = queryset.db
        compiler = queryset.query.get_compiler(using=db)
        # Execute the query. This will also fill compiler.select, klass_info,
        # and annotations.
        results = compiler.execute_sql(chunked_fetch=self.chunked_fetch)
        select, klass_info, annotation_col_map = (compiler.select, compiler.klass_info,
                                                  compiler.annotation_col_map)
        model_cls = klass_info['model']
        select_fields = klass_info['select_fields']
        model_fields_start, model_fields_end = select_fields[0], select_fields[-1] + 1
        init_list = [f[0].target.attname
                     for f in select[model_fields_start:model_fields_end]]
        related_populators = get_related_populators(klass_info, select, db)
        for row in compiler.results_iter(results):
            obj = model_cls.from_db(db, init_list, row[model_fields_start:model_fields_end])
            if related_populators:
                for rel_populator in related_populators:
                    rel_populator.populate(row, obj)
            if annotation_col_map:
                for attr_name, col_pos in annotation_col_map.items():
                    setattr(obj, attr_name, row[col_pos])

            # Add the known related objects to the model, if there are any
            if queryset._known_related_objects:
                for field, rel_objs in queryset._known_related_objects.items():
                    # Avoid overwriting objects loaded e.g. by select_related
                    if hasattr(obj, field.get_cache_name()):
                        continue
                    pk = getattr(obj, field.get_attname())
                    try:
                        rel_obj = rel_objs[pk]
                    except KeyError:
                        pass  # may happen in qs1 | qs2 scenarios
                    else:
                        setattr(obj, field.name, rel_obj)

            yield obj 

def __iter__(self):
        queryset = self.queryset
        compiler = queryset.query.get_compiler(queryset.db)
        for row in compiler.results_iter():
            yield row[0] 

def __iter__(self):
        queryset = self.queryset
        query = queryset.query
        compiler = query.get_compiler(queryset.db)

        field_names = list(query.values_select)
        extra_names = list(query.extra_select)
        annotation_names = list(query.annotation_select)

        # extra(select=...) cols are always at the start of the row.
        names = extra_names + field_names + annotation_names

        for row in compiler.results_iter():
            yield dict(zip(names, row)) 

def __iter__(self):
        queryset = self.queryset
        query = queryset.query
        compiler = query.get_compiler(queryset.db)

        field_names = list(query.values_select)
        extra_names = list(query.extra_select)
        annotation_names = list(query.annotation_select)

        # extra(select=...) cols are always at the start of the row.
        names = extra_names + field_names + annotation_names

        for row in compiler.results_iter():
            yield dict(zip(names, row)) 

def __iter__(self):
        queryset = self.queryset
        db = queryset.db
        compiler = queryset.query.get_compiler(using=db)
        # Execute the query. This will also fill compiler.select, klass_info,
        # and annotations.
        results = compiler.execute_sql(chunked_fetch=self.chunked_fetch)
        select, klass_info, annotation_col_map = (compiler.select, compiler.klass_info,
                                                  compiler.annotation_col_map)
        model_cls = klass_info['model']
        select_fields = klass_info['select_fields']
        model_fields_start, model_fields_end = select_fields[0], select_fields[-1] + 1
        init_list = [f[0].target.attname
                     for f in select[model_fields_start:model_fields_end]]
        related_populators = get_related_populators(klass_info, select, db)
        for row in compiler.results_iter(results):
            obj = model_cls.from_db(db, init_list, row[model_fields_start:model_fields_end])
            if related_populators:
                for rel_populator in related_populators:
                    rel_populator.populate(row, obj)
            if annotation_col_map:
                for attr_name, col_pos in annotation_col_map.items():
                    setattr(obj, attr_name, row[col_pos])

            # Add the known related objects to the model, if there are any
            if queryset._known_related_objects:
                for field, rel_objs in queryset._known_related_objects.items():
                    # Avoid overwriting objects loaded e.g. by select_related
                    if hasattr(obj, field.get_cache_name()):
                        continue
                    pk = getattr(obj, field.get_attname())
                    try:
                        rel_obj = rel_objs[pk]
                    except KeyError:
                        pass  # may happen in qs1 | qs2 scenarios
                    else:
                        setattr(obj, field.name, rel_obj)

            yield obj 

def __iter__(self):
        queryset = self.queryset
        compiler = queryset.query.get_compiler(queryset.db)
        return chain.from_iterable(compiler.results_iter(chunked_fetch=self.chunked_fetch, chunk_size=self.chunk_size)) 

def __iter__(self):
        queryset = self.queryset
        query = queryset.query
        compiler = query.get_compiler(queryset.db)

        field_names = list(query.values_select)
        extra_names = list(query.extra_select)
        annotation_names = list(query.annotation_select)

        # extra(select=...) cols are always at the start of the row.
        names = extra_names + field_names + annotation_names

        indexes = range(len(names))
        for row in compiler.results_iter(chunked_fetch=self.chunked_fetch, chunk_size=self.chunk_size):
            yield {names[i]: row[i] for i in indexes} 

def __iter__(self):
        queryset = self.queryset
        db = queryset.db
        compiler = queryset.query.get_compiler(using=db)
        # Execute the query. This will also fill compiler.select, klass_info,
        # and annotations.
        results = compiler.execute_sql(chunked_fetch=self.chunked_fetch, chunk_size=self.chunk_size)
        select, klass_info, annotation_col_map = (compiler.select, compiler.klass_info,
                                                  compiler.annotation_col_map)
        model_cls = klass_info['model']
        select_fields = klass_info['select_fields']
        model_fields_start, model_fields_end = select_fields[0], select_fields[-1] + 1
        init_list = [f[0].target.attname
                     for f in select[model_fields_start:model_fields_end]]
        related_populators = get_related_populators(klass_info, select, db)
        for row in compiler.results_iter(results):
            obj = model_cls.from_db(db, init_list, row[model_fields_start:model_fields_end])
            if related_populators:
                for rel_populator in related_populators:
                    rel_populator.populate(row, obj)
            if annotation_col_map:
                for attr_name, col_pos in annotation_col_map.items():
                    setattr(obj, attr_name, row[col_pos])

            # Add the known related objects to the model, if there are any
            if queryset._known_related_objects:
                for field, rel_objs in queryset._known_related_objects.items():
                    # Avoid overwriting objects loaded e.g. by select_related
                    if field.is_cached(obj):
                        continue
                    pk = getattr(obj, field.get_attname())
                    try:
                        rel_obj = rel_objs[pk]
                    except KeyError:
                        pass  # may happen in qs1 | qs2 scenarios
                    else:
                        setattr(obj, field.name, rel_obj)

            yield obj 

def __iter__(self):
        # Cache some things for performance reasons outside the loop.
        db = self.db
        compiler = connections[db].ops.compiler('SQLCompiler')(
            self.query, connections[db], db
        )

        query = iter(self.query)

        try:
            model_init_names, model_init_pos, annotation_fields = self.resolve_model_init_order()

            # Find out which model's fields are not present in the query.
            skip = set()
            for field in self.model._meta.fields:
                if field.attname not in model_init_names:
                    skip.add(field.attname)
            if skip:
                if self.model._meta.pk.attname in skip:
                    raise InvalidQuery('Raw query must include the primary key')
                model_cls = deferred_class_factory(self.model, skip)
            else:
                model_cls = self.model
            fields = [self.model_fields.get(c, None) for c in self.columns]
            converters = compiler.get_converters([
                f.get_col(f.model._meta.db_table) if f else None for f in fields
            ])
            for values in query:
                if converters:
                    values = compiler.apply_converters(values, converters)
                # Associate fields to values
                model_init_values = [values[pos] for pos in model_init_pos]
                instance = model_cls.from_db(db, model_init_names, model_init_values)
                if annotation_fields:
                    for column, pos in annotation_fields:
                        setattr(instance, column, values[pos])
                yield instance
        finally:
            # Done iterating the Query. If it has its own cursor, close it.
            if hasattr(self.query, 'cursor') and self.query.cursor:
                self.query.cursor.close() 

def iterator(self):
        compiler = self.query.get_compiler(self.db)
        if self.flat and len(self._fields) == 1:
            for row in compiler.results_iter():
                yield row[0]
        elif not self.query.extra_select and not self.query.annotation_select:
            for row in compiler.results_iter():
                yield tuple(row)
        else:
            # When extra(select=...) or an annotation is involved, the extra
            # cols are always at the start of the row, and we need to reorder
            # the fields to match the order in self._fields.
            extra_names = list(self.query.extra_select)
            field_names = self.field_names
            annotation_names = list(self.query.annotation_select)

            names = extra_names + field_names + annotation_names

            # If a field list has been specified, use it. Otherwise, use the
            # full list of fields, including extras and annotations.
            if self._fields:
                fields = list(self._fields) + [f for f in annotation_names if f not in self._fields]
            else:
                fields = names

            for row in compiler.results_iter():
                data = dict(zip(names, row))
                yield tuple(data[f] for f in fields) 

def __iter__(self):
        queryset = self.queryset
        db = queryset.db
        compiler = queryset.query.get_compiler(using=db)
        # Execute the query. This will also fill compiler.select, klass_info,
        # and annotations.
        results = compiler.execute_sql()
        select, klass_info, annotation_col_map = (compiler.select, compiler.klass_info,
                                                  compiler.annotation_col_map)
        if klass_info is None:
            return
        model_cls = klass_info['model']
        select_fields = klass_info['select_fields']
        model_fields_start, model_fields_end = select_fields[0], select_fields[-1] + 1
        init_list = [f[0].target.attname
                     for f in select[model_fields_start:model_fields_end]]
        if len(init_list) != len(model_cls._meta.concrete_fields):
            init_set = set(init_list)
            skip = [f.attname for f in model_cls._meta.concrete_fields
                    if f.attname not in init_set]
            model_cls = deferred_class_factory(model_cls, skip)
        related_populators = get_related_populators(klass_info, select, db)
        for row in compiler.results_iter(results):
            obj = model_cls.from_db(db, init_list, row[model_fields_start:model_fields_end])
            if related_populators:
                for rel_populator in related_populators:
                    rel_populator.populate(row, obj)
            if annotation_col_map:
                for attr_name, col_pos in annotation_col_map.items():
                    setattr(obj, attr_name, row[col_pos])

            # Add the known related objects to the model, if there are any
            if queryset._known_related_objects:
                for field, rel_objs in queryset._known_related_objects.items():
                    # Avoid overwriting objects loaded e.g. by select_related
                    if hasattr(obj, field.get_cache_name()):
                        continue
                    pk = getattr(obj, field.get_attname())
                    try:
                        rel_obj = rel_objs[pk]
                    except KeyError:
                        pass  # may happen in qs1 | qs2 scenarios
                    else:
                        setattr(obj, field.name, rel_obj)

            yield obj 

def iterator(self):
        """
        An iterator over the results from applying this QuerySet to the
        database.
        """
        db = self.db
        compiler = self.query.get_compiler(using=db)
        # Execute the query. This will also fill compiler.select, klass_info,
        # and annotations.
        results = compiler.execute_sql()
        select, klass_info, annotation_col_map = (compiler.select, compiler.klass_info,
                                                  compiler.annotation_col_map)
        if klass_info is None:
            return
        model_cls = klass_info['model']
        select_fields = klass_info['select_fields']
        model_fields_start, model_fields_end = select_fields[0], select_fields[-1] + 1
        init_list = [f[0].target.attname
                     for f in select[model_fields_start:model_fields_end]]
        if len(init_list) != len(model_cls._meta.concrete_fields):
            init_set = set(init_list)
            skip = [f.attname for f in model_cls._meta.concrete_fields
                    if f.attname not in init_set]
            model_cls = deferred_class_factory(model_cls, skip)
        related_populators = get_related_populators(klass_info, select, db)
        for row in compiler.results_iter(results):
            obj = model_cls.from_db(db, init_list, row[model_fields_start:model_fields_end])
            if related_populators:
                for rel_populator in related_populators:
                    rel_populator.populate(row, obj)
            if annotation_col_map:
                for attr_name, col_pos in annotation_col_map.items():
                    setattr(obj, attr_name, row[col_pos])

            # Add the known related objects to the model, if there are any
            if self._known_related_objects:
                for field, rel_objs in self._known_related_objects.items():
                    # Avoid overwriting objects loaded e.g. by select_related
                    if hasattr(obj, field.get_cache_name()):
                        continue
                    pk = getattr(obj, field.get_attname())
                    try:
                        rel_obj = rel_objs[pk]
                    except KeyError:
                        pass               # may happen in qs1 | qs2 scenarios
                    else:
                        setattr(obj, field.name, rel_obj)

            yield obj