A Lua system utilities package extended for OpenCog cognitive architecture needs.
Note: some functions only work on UNIX systems.
- Lua 5.4 (or compatible version)
- GCC or compatible C compiler
- Standard UNIX utilities (for some functions)
- Make (optional, for easier building)
# Build the library
make
# Run tests
make test
# Clean build artifacts
make clean# Build the native library manually
gcc -shared -fPIC -I/usr/include/lua5.4 sys.c -o libsys.so -llua5.4
# Run tests
lua5.4 test_opencog_functions.luaCurrently, the package should be used from its source directory:
# Use in your project from the ocsys directory
cd /path/to/ocsys
lua5.4
> require 'init'For system-wide installation, you can use LuaRocks:
luarocks make sys-1.1-0.rockspecRun the example script to see the OpenCog system functions in action:
./example.luaOr run the comprehensive test suite:
make test
# or
./test_opencog_functions.lua> require 'sys'> t = sys.clock() -- high precision clock (us precision)
> sys.tic()
> -- do something
> t = sys.toc() -- high precision tic/toc
> sys.sleep(1.5) -- sleep 1.5 seconds> path,fname = sys.fpath()Always returns the path of the file in which this call is made. Useful to access local resources (non-lua files).
By default, Lua's os.execute doesn't pipe its results (stdout). This
function uses popen to pipe its results into a Lua string:
> res = sys.execute('ls -l')
> print(res)Derived from this, a few commands:
> print(sys.uname())
linuxUNIX-only: shortcuts to run bash commands:
> ls()
> ll()
> lla()-- Monitor memory usage for AtomSpace operations
> memory_info = sys.monitor_memory()
> print("RSS:", memory_info.process_rss_mb, "MB")
> print("System pressure:", memory_info.memory_pressure, "%")
-- AtomSpace-aware garbage collection
> gc_stats = sys.atomspace_gc()
> print("Freed:", gc_stats.rss_freed_kb, "KB")-- Get comprehensive process statistics
> stats = sys.cognitive_stats()
> print("CPU time:", stats.cpu_time_total, "s")
> print("Memory:", stats.memory_mb, "MB")
-- Adjust process priority based on system load
> result = sys.adjust_cognitive_priority(80) -- 80% memory pressure threshold
> print("Priority adjustment:", result)-- Benchmark OpenCog operations
> result = sys.benchmark_operation("my_operation", function(n)
-- Your cognitive processing code here
return compute_something(n)
end, 1000)
> print("Duration:", result.duration, "s")
> print("Memory delta:", result.memory_delta_mb, "MB")-- Network and node identification
> network = sys.get_network_info()
> print("Hostname:", network.hostname)
> node_id = sys.create_node_id()
> print("Unique node ID:", node_id)
-- Atomic file operations for AtomSpace synchronization
> success = sys.atomic_write_file("/path/to/atomspace.dat", data)-- OpenCog parameter management
> sys.set_opencog_param("max_atoms", 1000000)
> sys.set_opencog_param("learning_rate", 0.01)
> max_atoms = sys.get_opencog_param("max_atoms", 100000)-- Check system resource limits
> limits = sys.check_resource_limits()
> print("Memory OK:", limits.memory_ok)
> print("Overall OK:", limits.overall_ok)-- Cognitive event logging with context
> sys.log_cognitive_event("INFO", "ATOMSPACE", "Created new atom", {type="ConceptNode"})
-- Output: [timestamp] INFO [PID:1234] [ATOMSPACE] Created new atom [MEM:45MB] [CPU:1.23s]If you'd like print in colours, follow the following snippets of code. Let start by listing the available colours
$ torch
> for k in pairs(sys.COLORS) do print(k) endThen, we can generate a shortcut c = sys.COLORS and use it within a print
> c = sys.COLORS
> print(c.magenta .. 'This ' .. c.red .. 'is ' .. c.yellow .. 'a ' .. c.green .. 'rainbow' .. c.cyan .. '!')