Grocery Service

A Data Component specializing in loading workspace data from disk into Mantid’s ADS, for use inside algorithm s. The grocery service handles loading neutron scattering data, grouping workspaces, calibration tables, and masking workspaces. The goal of the grocery service is to centralize and minimize loading operations. On the first load of a file, it is cached in its initial condition. Any future operations calling for the same workspace data will clone a copy of the cached workspace, making it safe to deform the clone.

The primary way to interact with the grocery service is to send it a grocery list. A grocery list is a list of GroceryListItem`s. Each item contains the data needed for the grocery service to locate the correct file and load the file into a workspace in the :term:`ADS. Which properties of a GroceryListItem must be set will depend on the kind of data it corresponds to. The service will properly handle loading all the items on the list into the ADS then return to you a list of loaded workspaces.

The GroceryListBuilder is intended to handle constructing grocery lists or dictionaries. These can be be passed to either the fetchGroceryList or the fetchGroceryDict methods inside grocery service.

GroceryListBuilder

Inside most services, this will usually be initialized inside the __init__, called groceryClerk.

Any service methods which need to get workspace data can then create their list using

self.groceryClerk.neutron(<runNumber>).useLiteMode(<useLiteMode>).add()
self.groceryClerk.grouping(<focusGroupName>).fromRun(<runNumber>).useLiteMode(<useLiteMode>).add()
groceryList = self.groceryClerk.buildList()

A preferable alternative, for easier use inside algorithms and recipes, is to create a grocery dictionary, which will assign each loaded workspace a name corresponding to an algorithm’s inputs.

self.groceryClerk.name("InputWorkspace").neutron(<runNumber>).useLiteMode(<useLiteMode>).add()
self.groceryClerk.name("GroupingWorkspace").grouping(<focusGroupName>).fromRun(<runNumber>).useLiteMode(<useLiteMode>).add()
groceryDict = self.groceryClerk.buildDict()

If only a single workspace is needed, then a single GroceryListItem can be created with

groceryItem = self.groceryClerk.neutron(<runNumber>).useLiteMode(<useLiteMode>).build()

fetchGroceryList

Make a list of GroceryListItem s specofying all needed workspaces for an operation, then pass the list. This method will handle finding the correct loders.

Inputs

• groceryList: List[GroceryListItem]

  A list of GroceryListItems , preferably created as above using the builder.

Outputs

Returns a list of WorkspaceName s corresponding to the requested data.

fetchGroceryDict

Make a dictionary that matches a GroceryListItem to a string name. The string name is NOT the workspace name, but should correspond to the property name inside a recipe or algorithm. For instance, “InputWorkspace”, “BackgroundWorkspace”, or “CalibrationWorkspace”.

Inputs

• groceryDict: Dict[str, GroceryListItem]

  A dictionary that matches a property name to a GroceryListItem.

Outputs

Returns a dictionary that matches the original keys from the input, to the loaded workspace names.

All Together Now

The below will illustrate a service that used the grocery service to fetch workspace data, which is used inside of a recipe.

from snapred.backend.dao.ingredients import GroceryListItem
from snapred.backend.data.GroceryService import GroceryService
from snapred.backend.service.Service import Service

@Singleton
class SomeService(Service):

    def __init__(self):
        super().__init__()
        self.groceryClerk = GroceryListItem.builder()
        self.groceryService = GroceryService()


    def someEndpointNeedingGroceries(self, runNumber: str, useLiteMode: bool, focusGroup: FocusGroup):
        # build the dictionary
        self.groceryClerk.name("InputWorkspace").neutron(runNumber).useLiteMode(useLiteMode).add()
        self.groceryClerk.name("GroupingWorkspace").fromRun(runNumber).useLiteMode(useLiteMode).grouping(focusGroup.name).add()

        # fetch the groceries, and tag on an output workspace name
        groceries = self.groceryService.fetchGroceryDict(
            self.groceryClerk.buildDict(),
            OutputWorkspace="output_ws_name",
        )

        # run whatever recipe needed these
        return SomeRecipeNeedingGroceries(
            InputWorkspace = groceries["InputWorkspace"],
            GroupingWorkspace = groceries["GroupingWorkspace"],
            OutputWorkspace = groceries["OutputWorkspace"],
        )

        ## or, alternatively, if the recipe only has workspace inputs
        # return SomeRecipeNeedingGroceries(**groceries)

This illustration is using the dictionary methods. These are recommended, as then the return lists aren’t tied to an order but to a property name.