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- Examples
- ========
- To run this code, store it in a file (*e.g.*, test.alc), and execute the following commands::
- python scripts/run_local_modelverse.py 8001 &
- python scripts/make_parallel.py http://localhost:8001 test test.alc bootstrap/primitives.alc
- python scripts/prompt.py
- In the prompt, log on to http://localhost:8001 as user *test*.
- Now, all input you send, will be caught in the *input()* calls seen in the code.
- Results will also be printed.
- Note that all content will, by default, be typed as string.
- If you want to send integers or so, prepend the input with a backslash (\\), which allows you to directly input the JSON code.
- For example, input *5* will be received as the string "5".
- To send the integer 5, the input should be *\\5*.
- Fibonacci Server
- ----------------
- The first example is a simple Fibonacci server.
- The code is identical to the action language example from before, as this already included the *server* part (*i.e.*, the while loop).
- Now we will just connect to it using *prompt.py* and try out the code directly.
- The code is repeated below::
- include "primitives.alh"
- Integer function fib(param : Integer):
- if (param <= 2):
- return 1!
- else:
- return fib(param - 1) + fib(param - 2)!
- Void function main():
- while(True):
- output(fib(input()))
- To run this code, save it to a file (*e.g.*, fibonacci.alc) and execute the following command::
- python scripts/run_local_modelverse.py 8001
-
- Now, the Modelverse is running, but we still need to upload our code.
- To compile the file, together with the primitives.alc file, execute the following command::
- python scripts/make_parallel.py http://localhost:8001 test fibonacci.alc bootstrap/primitives.alc
- When this finishes, the Modelverse now stores a copy of our code in its own format.
- The Modelverse will automatically create the user *test* and start executing the *main* function as this user.
- We can therefore simply connect to the Modelverse as the *test* user and start seeing the responses.
- To start the prompt, execute the following command::
- python scripts/prompt.py
-
- In this prompt tool, you first have to configure the location of the Modelverse and the username.
- The defaults should be fine, so just press <return> twice.
- After that, you are in direct connection with the Modelverse.
- Each message you type in, is made available in the *input()* function of the code.
- Remember that, to send integers, you have to prefix this with a backslash (\\).
- To get, for example, the 1st Fibonacci number, type in the command::
- \1
- You will now see the following.
- .. image:: img/prompt_fibonacci.png
- Since we are in an unconditional loop, you can send as many requests as you want, as long as they are understandable by the *fib* function.
- .. image:: img/prompt_fibonacci_more.png
- Inputting a string directly, such as *1* instead of *\\1*, will make the Modelverse crash on the execution of this code.
- This is normal, though in the future the Modelverse will keep running for other users: only the current user's code will be interrupted.
- Modelling Server
- ----------------
- The simple Fibonacci server is not very relevant to the primary concern of the Modelverse: (meta-)modelling.
- But since we can create whatever kind of server we want, a simple (meta-)modelling server is created.
- The code offers an interface for users to execute modelling operations.
- The interface itself mostly just relays the incoming messages and operations to the internal modelling library.
- The full code is seen below::
- include "primitives.alh"
- include "constructors.alh"
- include "object_operations.alh"
- include "library.alh"
- include "conformance_scd.alh"
- include "io.alh"
- include "metamodels.alh"
- include "modelling.alh"
- include "compilation_manager.alh"
- Element function model_loaded(model : Element):
- String cmd
- Element attr_list_pn
- Element attr_keys_pn
- String attr_key_pn
- Element metamodel_element_pn
- String typename
- Boolean bottom
- Element other_metamodel
- bottom = False
- other_metamodel = create_node()
- dict_add(other_metamodel, "model", model["model"])
- dict_add(other_metamodel, "type_mapping", create_node())
- dict_add(other_metamodel, "metamodel", import_node("models/LTM_bottom"))
- dict_add(other_metamodel, "inheritance", other_metamodel["metamodel"]["model"]["__Inheritance"])
- output("Model loaded, ready for commands!")
- output("Use 'help' command for a list of possible commands")
- while (True):
- output("Please give your command.")
- cmd = input()
- if (cmd == "help"):
- output("Generic model operations:")
- output(" instantiate -- Create a new model element")
- output(" delete -- Delete an existing element")
- output(" attr_add -- Add an attribute to an element")
- output(" attr_del -- Delete an attribute of an element")
- output(" constrain -- Add a constraint function to the model")
- output(" rename -- Rename an existing element")
- output(" modify -- Modify the attributes of an element")
- output(" list -- Prints the list of elements in the model")
- output(" types -- Prints the list of elements that can be instantiated")
- output(" read -- Prints the current state of a model element")
- output(" verify -- Check whether the model conforms to the metamodel")
- output(" retype -- Change the type of an element")
- output(" switch -- Switch between conformance bottom and the linguistic metamodel")
- output(" exit -- Unload the model and go back to the loading prompt")
- elif (cmd == "exit"):
- return model!
- elif (cmd == "instantiate"):
- String mm_type_name
- output("Type to instantiate?")
- mm_type_name = input()
- if (dict_in(model["metamodel"]["model"], mm_type_name)):
- String element_name
- output("Name of new element?")
- element_name = input()
- if (dict_in(model["model"], element_name)):
- output("Element already exists; aborting")
- else:
- if (is_edge(model["metamodel"]["model"][mm_type_name])):
- output("Source name?")
- String src_name
- src_name = input()
- if (dict_in(model["model"], src_name)):
- output("Destination name?")
- String dst_name
- dst_name = input()
- if (dict_in(model["model"], dst_name)):
- instantiate_link(model, mm_type_name, element_name, src_name, dst_name)
- output("Instantiation successful!")
- else:
- output("Unknown destination; aborting")
- else:
- output("Unknown source; aborting")
- else:
- instantiate_node(model, mm_type_name, element_name)
- output("Instantiation successful!")
- else:
- output("Unknown type specified; aborting")
- elif (cmd == "set_inheritance"):
- String inh_name
- output("Which link in the metamodel is the inheritance link?")
- inh_name = input()
- if (dict_in(model["metamodel"]["model"], inh_name)):
- dict_add(model, "inheritance", model["metamodel"]["model"][inh_name])
- output("Set inheritance link!")
- else:
- output("Element not found in metamodel; aborting")
- elif (cmd == "constrain"):
- output("Element to constrain (empty for global)?")
- String model_name
- model_name = input()
- if (model_name == ""):
- // Global constraint
- output("Give input to function constructors for GLOBAL constraint!")
- set_model_constraints(model, construct_function())
- elif (dict_in(model["model"], model_name)):
- // Local constraint for this model
- output("Give input to function constructors for LOCAL constraint!")
- add_constraint(model, model_name, construct_function())
- output("Added constraint to model!")
- else:
- // Local constraint, but model not found
- output("Unknown model; aborting")
- elif (cmd == "modify"):
- String model_name
- output("Element to modify?")
- model_name = input()
- if (dict_in(model["model"], model_name)):
- Element attrs
- attrs = getAttributeList(model, model_name)
- String attr_name
- output("Attribute to modify?")
- attr_name = input()
- if (set_in(dict_keys(attrs), attr_name)):
- output("New value?")
- unset_attribute(model, model_name, attr_name)
- instantiate_attribute(model, model_name, attr_name, input())
- output("Modified!")
- else:
- output("No such attribute!")
- else:
- output("No such model!")
- elif (cmd == "attr_add"):
- String model_name
- output("Which model do you want to assign an attribute to?")
- model_name = input()
- if (dict_in(model["model"], model_name)):
- Element attrs
- attrs = getAttributeList(model, model_name)
- String attr_name
- output("Which attribute do you wish to assign?")
- attr_name = input()
- if (set_in(dict_keys(attrs), attr_name)):
- output("Value of attribute?")
- instantiate_attribute(model, model_name, attr_name, input())
- output("Added attribute!")
- else:
- output("No such attribute!")
- else:
- output("No such model!")
- elif (cmd == "attr_del"):
- String model_name
- output("Which model do you want to remove an attribute of?")
- model_name = input()
- if (dict_in(model["model"], model_name)):
- Element attrs
- attrs = getAttributeList(model, model_name)
- String attr_name
- output("Which attribute do you want to delete?")
- attr_name = input()
- if (set_in(dict_keys(attrs), attr_name)):
- unset_attribute(model, model_name, attr_name)
- output("Attribute deleted!")
- else:
- output("No such attribute!")
- else:
- output("No such model!")
- elif (cmd == "delete"):
- output("What is the name of the element you want to delete?")
- cmd = input()
- if (dict_in(model["model"], cmd)):
- model_delete_element(model, cmd)
- output("Deleted!")
- else:
- output("No such element; aborting")
- elif (cmd == "rename"):
- output("Old name?")
- String old_name_e
- old_name_e = input()
- if (dict_in(model["model"], old_name_e)):
- output("New name?")
- String new_name_e
- new_name_e = input()
- if (dict_in(model["model"], new_name_e)):
- output("New name already used; aborting")
- else:
- dict_add(model["model"], new_name_e, model["model"][old_name_e])
- dict_delete(model["model"], old_name_e)
- output("Rename complete!")
- else:
- output("Unknown element; aborting")
- elif (cmd == "list"):
- Element keys_m
- keys_m = dict_keys(model["model"])
- output("List of all elements:")
- String v_m
- while (read_nr_out(keys_m) > 0):
- v_m = set_pop(keys_m)
- // Filter out anonymous objects
- if (bool_not(string_startswith(v_m, "__"))):
- typename = reverseKeyLookup(model["metamodel"]["model"], dict_read_node(model["type_mapping"], model["model"][v_m]))
- output(((" " + v_m) + " : ") + typename)
- elif (cmd == "read"):
- output("Element to read?")
- cmd = input()
- if (dict_in(model["model"], cmd)):
- Element read_elem
- read_elem = model["model"][cmd]
- metamodel_element_pn = dict_read_node(model["type_mapping"], read_elem)
- output("Name: " + cmd)
- output("Type: " + reverseKeyLookup(model["metamodel"]["model"], metamodel_element_pn))
- if (is_edge(read_elem)):
- output("Source: " + reverseKeyLookup(model["model"], read_edge_src(read_elem)))
- output("Destination: " + reverseKeyLookup(model["model"], read_edge_dst(read_elem)))
- if (cast_v2s(read_elem) != "None"):
- output("Value: " + cast_v2s(read_elem))
- output("Defines attributes:")
- attr_list_pn = getInstantiatableAttributes(model, read_elem)
- attr_keys_pn = dict_keys(attr_list_pn)
- while (0 < read_nr_out(attr_keys_pn)):
- attr_key_pn = set_pop(attr_keys_pn)
- output((((" " + attr_key_pn) + " : ") + cast_v2s(attr_list_pn[attr_key_pn])))
- output("Attributes:")
- attr_list_pn = getAttributeList(model, cmd)
- attr_keys_pn = dict_keys(attr_list_pn)
- while (0 < read_nr_out(attr_keys_pn)):
- attr_key_pn = set_pop(attr_keys_pn)
- output(((((" " + cast_v2s(attr_key_pn)) + " : ") + cast_v2s(attr_list_pn[attr_key_pn])) + " = ") + cast_v2s(read_attribute(model, reverseKeyLookup(model["model"], read_elem), attr_key_pn)))
- else:
- output("Unknown element; aborting")
- elif (cmd == "verify"):
- output(conformance_scd(model))
- elif (cmd == "types"):
- Element keys_t
- keys_t = dict_keys(model["metamodel"]["model"])
- output("List of types:")
- String v_t
- while (read_nr_out(keys_t) > 0):
- v_t = set_pop(keys_t)
- if (bool_not(string_startswith(v_t, "__"))):
- output(string_join((" " + v_t) + " : ", reverseKeyLookup(model["metamodel"]["metamodel"]["model"], dict_read_node(model["metamodel"]["type_mapping"], model["metamodel"]["model"][v_t]))))
- elif (cmd == "retype"):
- output("Element to retype?")
- String elementname
- elementname = input()
- if (dict_in(model["model"], elementname)):
- output("New type")
- typename = input()
- if (dict_in(model["metamodel"]["model"], typename)):
- // OK, do the retyping
- // First try removing the previous type if it exists
- dict_delete(model["type_mapping"], model["model"][elementname])
- // Now add the new type
- dict_add(model["type_mapping"], model["model"][elementname], model["metamodel"]["model"][typename])
- output("Retyped!")
- else:
- output("Unknown type; aborting")
- else:
- output("Unknown element; aborting")
- elif (cmd == "switch"):
- bottom = bool_not(bottom)
- Element tmp_model
- tmp_model = model
- model = other_metamodel
- other_metamodel = tmp_model
- if (bottom):
- // The type mapping we are using is probably not complete for our model
- // so we completely recreate it from the model we have.
- output("Switching to conformance bottom mode!")
- generate_bottom_type_mapping(model)
- else:
- // We already switched the models and such, so we are already done!
- output("Switching to linguistic metamodel!")
- else:
- output("Unknown command: " + cast_v2s(cmd))
- output("Use command 'help' to get a list of available commands")
- Element function main():
- output("Welcome to the Model Management Interface, running live on the Modelverse!")
- output("Use 'help' command for a list of possible commands")
- String command
- Element root
- Element metamodel
- String name
- Element my_model
- String mm_name
- root = create_metamodels()
- while (True):
- output("Please give your command.")
- command = input()
- if (command == "help"):
- output("Currently no model is loaded, so your operations are limited to:")
- output(" new -- Create a new model and save it for future use")
- output(" load -- Load a previously made model")
- output(" rename -- Rename a previously made model")
- output(" delete -- Delete a previously made model")
- output(" list -- Show a list of all stored models")
- output(" help -- Show a list of possible commands")
- elif (command == "new"):
- output("Metamodel to instantiate?")
- mm_name = input()
- if (dict_in(root, mm_name)):
- output("Name of model?")
- name = input()
- if (dict_in(root, name)):
- output("Model exists; aborting")
- else:
- my_model = instantiate_model(root[mm_name])
- dict_add(root, name, my_model)
- model_loaded(my_model)
- else:
- output("Unknown metamodel; aborting")
- elif (command == "load"):
- output("Model to load?")
- name = input()
- if (dict_in(root, name)):
- my_model = root[name]
- model_loaded(my_model)
- else:
- output("Model not found; aborting")
- elif (command == "list"):
- Element keys
- String m_menu_list
- keys = dict_keys(root)
- output("Found models:")
- while (read_nr_out(keys) > 0):
- m_menu_list = set_pop(keys)
- output(((" " + m_menu_list) + " : ") + reverseKeyLookup(root, root[m_menu_list]["metamodel"]))
- elif (command == "delete"):
- output("Model to delete?")
- name = input()
- if (dict_in(root, name)):
- dict_delete(root, name)
- output("Deleted!")
- else:
- output("Model not found; aborting")
- elif (command == "rename"):
- output("Old name?")
- String old_name
- old_name = input()
- if (dict_in(root, old_name)):
- output("New name?")
- String new_name
- new_name = input()
- if (dict_in(root, new_name)):
- output("Model exists; aborting")
- else:
- dict_add(root, new_name, root[old_name])
- dict_delete(root, old_name)
- output("Rename complete!")
- else:
- output("Model not found; aborting")
- elif (command == "actions"):
- output("Switching to compilation manager!")
- compilation_manager()
- output("Back in model manager!")
- else:
- output("Command not recognized, use 'help' for a list of possible commands")
- This code implements a very simple (meta-)modelling tool.
- Its use is documented with the provided *help* function.
- A simple example of its use is shown below.
- .. image:: img/prompt_pn_interface.png
- In this case, note that the value of tokens is the string 3 instead of the integer (or natural) 3.
- Therefore, the conformance check will flag this value as incorrectly typed.
- Upload model
- ------------
- Uploading a model, and using it, is very similar to what you usually do.
- The exception is that your model will be added before any code is executed.
- That way, you can just execute the same modelling server, but include a model in it.
- Doing that, your interface will see additional models with the *list* command.
- The command for this is (instead of the *make_all.py* script)::
- python scripts/execute_model.py http://localhost:8001 test bootstrap/*.alc integration/code/pn_interface.alc integration/code/rpgame.mvc
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