def _loadRecipe(self, troveSpec, label, findInstalled):
        loader = ChainedRecipeLoader(troveSpec, label, findInstalled,
                                     self.subloadData.cfg,
                                     self.subloadData.repos,
                                     self.subloadData.branch,
                                     self.subloadData.parentPackageName,
                                     self.subloadData.parentDir,
                                     self.subloadData.buildFlavor,
                                     self.subloadData.ignoreInstalled,
                                     self.subloadData.overrides,
                                     self.subloadData.db)

        for name, recipe in loader.allRecipes().items():
            # hide all recipes from RecipeLoader - we don't want to return
            # a recipe that has been loaded by loadRecipe, so we treat them
            # for these purposes as if they are abstract base classes
            recipe.internalAbstractBaseClass = 1

            self.module.__dict__[name] = recipe
            if recipe._trove:
                # create a tuple with the version and flavor information needed to
                # load this trove again.   You might be able to rely on the
                # flavor that the trove was built with, but when you load a
                # recipe that is not a superclass of the current recipe,
                # its flavor is not assumed to be relevant to the resulting
                # package (otherwise you might have completely irrelevant flavors
                # showing up for any package that loads the python recipe, e.g.)
                troveTuple = (recipe._trove.getName(), recipe._trove.getVersion(),
                              recipe._usedFlavor)
                log.info('Loaded %s from %s=%s[%s]' % ((name,) + troveTuple))
                self.loadedTroves.extend(loader.getLoadedTroves())
                self.loadedTroves.append(troveTuple)
                self.loadedSpecs[troveSpec] = (troveTuple,
                                               loader.getLoadedSpecs())

        # stash a reference to the module in the namespace
        # of the recipe that loaded it, or else it will be destroyed
        self.module.__dict__[loader.recipe.__module__] = loader
        return loader.getRecipe()
:param keep_recent: see `tf.train.Saver` documentation.
dataset/ETHPy150Open sassoftware/conary/conary/build/loadrecipe.py/Importer._loadRecipe--crossover with--dataset/ETHPy150Open ppwwyyxx/tensorpack/tensorpack/callbacks/common.py/ModelSaver.__init__