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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def copy(self, with_time=True, ignore_standard_types=False):
 """ Returns a deep copy of the Network object with all components and time-dependent data. Returns -------- network : pypsa.Network Parameters with_time : boolean, default True Copy snapshots and time-varying network.component_names_t data too. ignore_standard_types : boolean, default False Ignore the PyPSA standard types. Examples -------- """


        override_components, override_component_attrs = self._retrieve_overridden_components()

        network = self.__class__(ignore_standard_types=ignore_standard_types,
                                 override_components=override_components,
                                 override_component_attrs=override_component_attrs)

        for component in self.iterate_components(["Bus", "Carrier"] + sorted(self.all_components - {"Bus","Carrier"})):
            df = component.df
            #drop the standard types to avoid them being read in twice
            if not ignore_standard_types and component.name in self.standard_type_components:
                df = component.df.drop(network.components[component.name]["standard_types"].index)

            import_components_from_dataframe(network, df, component.name)

        if with_time:
            network.set_snapshots(self.snapshots)
            for component in self.iterate_components():
                pnl = getattr(network, component.list_name+"_t")
                for k in iterkeys(component.pnl):
                    pnl[k] = component.pnl[k].copy()

        #catch all remaining attributes of network
        for attr in ["name", "srid"]:
            setattr(network,attr,getattr(self,attr))

        network.snapshot_weightings = self.snapshot_weightings.copy()

        return network