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SpotOnDocker is a utility which exposes some of spot (spot.lrde.epita.fr) functionality as a dockerized service.

Project description

SpotOnDocker

SpotOnDocker is a utility which exposes some of spot's functions as a dockerized service. The functions can be called using client API provided in C++, Python, VB.NET and C#.

Note: In v0.1.0, only Python client API is available.

Supported spot Functions:

  • mp_class: Returns class of LTL formula in Manna-Pnueli hierarchy.
  • translate: Translates LTL formula to Buchi automaton.
  • contains: Checks if the language of an LTL formula is contained within another's.
  • equiv: Checks of the language of two LTL formulas is equivalent.
  • rand_ltl: Generates a random LTL formula.
  • get_ap: Gets the atomic propositions from given LTL formula.
  • to_string_latex: LaTeX-friendly writing of LTL formula.

Installation Instructions

Server Setup

  1. Install Docker. Skip if already installed.

  2. Get the latest version of spotondocker image.

    docker pull abhibp1993/spotondocker
    

Python Client Setup

The following packages are required.

  • networkx
  • docker
  • thrift (Apache)
pip3 install docker networkx thrift
pip3 install spotondocker

Example (Python Client API)

It is advisable to check if spot is available on system, if not use spotondocker.

try:
    import spot
except ImportError:
    import spotondocker.client as client
    spot = client.SpotOnDockerClient()

SpotOnDockerClient() creates a docker container and sets up the server to send requests to

Call the spot functions (only the supported ones!) as usual. For example, to get the class of formula G(a -> Fb) in Manna Pnueli hierarchy, we can call

spot.mp_class('G(a -> Fb)')

which will return a verbose like safety, guarantee, ...

In case of translation, the SpotClient.translate(..) function returns a networkx.MultiDiGraph.

nx_graph = spot.translate("(p1 W 0) | Gp2")

The returned graph has several graph properties. See spotondocker.thrift to see a list of properties associated with graph. The node and edge attributes of nx_graph contains information like id and label.

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