No Description

Yentl Van Tendeloo 592282cbcf Massive cleanup 4 years ago
bootstrap 46dfcb1bc6 Fixed bootstrap file: everything loads 4 years ago
doc a66ad33dca Updated documentation on MvC and mini_modify 4 years ago
hybrid_server aa3e4742db Fix constructor_AL to not time out on a test 4 years ago
integration 592282cbcf Massive cleanup 4 years ago
interface 46dfcb1bc6 Fixed bootstrap file: everything loads 4 years ago
kernel 5df214ee18 Updated test_MvC to use the wrapper for the parts that already work 4 years ago
model b2f0bc0469 Naively changed user to task in all files 4 years ago
models 2762a48807 Add model transformations to the Python API 4 years ago
performance 00b48a6948 Fixes to make everything work 4 years ago
scripts 592282cbcf Massive cleanup 4 years ago
state e120d53144 Added test file for Simon 4 years ago
wrappers 5c4db8b7fb Fix wrapper for init to keep trying for some time (until Mv has loaded 4 years ago
.gitattributes b3d374390d Make .gz files merge properly 4 years ago
.gitignore cc7e5822aa Merge remote-tracking branch 'upstream/master' into jit 4 years ago
README.md 592282cbcf Massive cleanup 4 years ago
sum_times.py eee6f1ce47 Minor optimizations 4 years ago

README.md

Installation

Installing the Modelverse is unnecessary, as it is mere Python code and doesn't use installation scripts. All scripts which are generally useful are found in the 'scripts' directory, and are written in OS-independent Python code.

You will, however, need to install a dependency: the SCCD compiler and runtime.

Starting up the Modelverse

Starting up the Modelverse is easy: simply execute the scripts/run_local_modelverse.py script, with as parameter the port you want to use. By default, port 8001 is used.

Communicating with the Modelverse

Now that the Modelverse is running, you will want to communicate with it! To do this, you can use whatever tool you want, as long as it can send and receive XML/HTTPRequests. For example, a mere internet browser can already communicate with the Modelverse, though not in the most user-friendly way.

A nicer way is through the Python prompt script scripts/prompt.py. After that, it will print out all the output of the Modelverse, and send in all your queries directly to the Modelverse.

Python wrapper

To automatically communicate with the Modelverse in a programmatic way, a Python wrapper is provided. This wrapper is found in wrappers/modelverse.py, and provides Python functions that make the necessary Modelverse requests. At the moment, not all functions are implemented in the wrapper yet.

Performance

Performance of the Modelverse is currently rather low. This is primarily caused by the reliance on the action language, which is an explicitly modelled (and interpreted) language. Additionally, the Modelverse runs remotely, meaning that all requests have to pass over the network. Even when this is executed on the same machine, this causes quite some overhead.

Additional documentation

Some additional documentation can be found online in the Modelverse techreport, describing the internal workings of the Modelverse, as well as a brief introduction on how to use it. There is also in-depth documentation describing how to use the Modelverse and its various languages.

Tests

Running the tests is easy: simply execute scripts/run_tests.py in the main modelverse folder. This will invoke the necessary build commands (to create bootstrapping code etc.) and call the tests for each individual aspect of the Modelverse. Note that testing is done using py.test, which is the only dependency of the Modelverse (and only for tests, of course).

Using PyPy

Since all scripts chain the invocation with the same interpreter as originally invoking the script, you will need to install py.test for PyPy. Assuming that you already have PyPy installed, you can simply install py.test using these commands:

wget https://msdl.uantwerpen.be/files/get-pip.py
pypy get-pip.py --user
pypy -m pip install pytest --user

From then on, you can simply invoke all tests in PyPy using:

pypy scripts/run_tests.py