DISCLAIMER: This is not an official TLA+ tool and isn't a prototype for one. I'm not making any guarantees of backwards compatibility or non-breaking changes or whatever. It's just a script I find useful.
tlacli
is a tool for running the TLC model checker from the command line. You can already run TLC from the command line, anyway, using tlc2.TLC
, and tlacli
only provides a subset of the functionality. It still has a few UX improvements, though:
tlacli check specfile.tla
. Spec
as your temporal formula, defaults to using a worker per CPU core, gives terse output, etc.tlacli
will automatically build the proper config file for that run. You can also save the configuration as a template for future runs. You can also use both a config file and flags, where the config is a template and the flags are specializations.Just run pip install tlacli
. You will need Java and Python 3.7.
The requirements.txt
is only needed for testing.
tlacli translate specfile.tla
NOTE: By default this includes the -nocfg
flag, which prevents the tool from overwritting your copy of specfile.cfg
. Right now no other flags are supported. If you need flags, you can put them directly in the module file. See page 67 of the PlusCal manual.
tlacli check specfile.tla
By default, this runs specfile.tla
with the specification Spec
. You can change the run specification with the --spec
flag. By default, this runs TLC with the -terse
and -cleanup
flags. The config file will be saved as temporary.cfg
. You can change the filename with --out-cfg {name}
.
BUG: Currently you cannot pass in an absolute path for the specfile, at least on windows. You can pass in a relative path. See this tlatools issue. This is not an issue for pluscal translation.
You can specify invariants and properties from the command line. Use the --invariant {inv}
flag and the --property {prop}
flag, respectively. Both accept multiple operators.
NOTE: If --invariant
or --property
are the last flags passed in, the script will assume your specfile is an invariant! You can prevent this by adding a --
.
tlacli check --invariant Inv1 Inv2 -- specfile.tla
You can also use --inv
and --prop
, but this may change in the future.
You can assign constants with --constant {name} {value}
. Each constant must be a separate flag. You can put in sets, tuples, etc by putting {value}
in quotes. Use single quotes if you want to put in strings.
tlacli check --constant Max 4 --constant Threads '{1, 2}' specfile.tla
tlacli check --constant Colors '{\"red\", \"green\"}' specfile.tla
If you need several model values, you can specify them all in a single --model-values {m1} {m2} ...
flag.
tlacli check --model_values A B C Null Server -- specfile.tla
Use an ordinary assignment. You don't need a --model-values
flag first.
# Wrong
tlacli check --model-values m1 m2 m3 --constant ModelSet "{m1, m2, m3}" specfile.tla
# Right
tlacli check --constant ModelSet "{m1, m2, m3}" specfile.tla
Symmetry sets are not yet supported.
You can specify a template configuration with --cfg template.cfg
:
tlacli check --cfg foo.cfg specfile.tla
tlacli
can only read things that are also expressible as flags. Currently, this means invariants, properties, specification, and (most) constants. Everything else is ignored. It's a simple text parser and may miss things formated in an unexpected way. The one guarantee: If you write a file a config with --out-cfg
and later read it with --cfg
, the whole config will be read properly.
A template can be used in conjunction with the other flags. Currently this adds the additional flags on top of the template. The plan is that if the flags and the template conflict, the flags take priority. This will let us specialize a template.
--show-script
will print the command-line script passing to tla2tools
. --show-cfg
will print the cfg used for model-checking.
Eh make a PR or something
Use pytest
. This is currently broken because I need to add fixtures
temporary.cfg
EXTENDS
, I think)pkg_resources
kludge for accessing the jar