Index: /framspy/frams-test.py
===================================================================
--- /framspy/frams-test.py	(revision 1088)
+++ /framspy/frams-test.py	(revision 1089)
@@ -1,2 +1,9 @@
+"""Simple examples of using the "frams" module to communicate directly with the Framsticks library (dll/so).
+
+For an introduction to Framsticks, its usage and scripting, see https://www.youtube.com/playlist?list=PLkPlXm7pOPatTl3_Gecx8ZaCVGeH4UV1L
+For a list of available classes, objects, methods and fields, see http://www.framsticks.com/files/classdoc/
+For a number of examples of scripting, see the "scripts" directory in Framsticks distribution.
+"""
+
 import sys
 import frams
@@ -13,20 +20,65 @@
 
 def extValueDetails(v):
-	return '"' + str(v) + '"    frams type=' + str(v._type()) + '    frams class=' + str(v._class()) + '    python type=' + str(type(v._value()))
+	"""A helper function to display basic information about a variable of type ExtValue."""
+	return '\t"' + str(v) + '"    frams type=' + str(v._type()) + '    frams class=' + str(v._class()) + '    python type=' + str(type(v._value()))
 
 
-v = frams.String.deserialize('[100,2.2,"abc",[null,[]],XYZ[9,8,7]]')
+dic_as_string = '[100,2.2,"abc",[null,[],{}],XYZ[9,8,7]]'
+print("We have the following string:\n\t'%s'" % dic_as_string)
+print("Looks like a serialized dictionary, let's ask Framsticks String.deserialize() to do its job.")
+v = frams.String.deserialize(dic_as_string)
+print("Framsticks String.deserialize() returned\n\t", type(v))
+print("More specifically, it is:")
 print(extValueDetails(v))
+print("Even though it is ExtValue (Framsticks' Vector), it supports iteration like a python vector, so let's inspect its elements:")
 for e in v:
 	print(extValueDetails(e))
 
+print("Now let's play with the Framsticks simulator. Let's create a Genotype object and set fields in its custom 'data' dictionary.")
 g = frams.GenePools[0].add('X')
-g.name = "py!"
+g.name = "Snakis Py"
 g.data['custom'] = 123.456
-g.data['a'] = 'b'
+g.data['a'] = 'b'  # implicit conversion, looks like python dictionary but still converts '3' and '4' to ExtValue
+dic = frams.Dictionary.new()  # let's create a Dictionary object from Framsticks
+dic.set('1', '2')  # calling set() from Framsticks Dictionary
+dic['3'] = '4'  # implicit conversion, looks like python dictionary but still converts '3' and '4' to ExtValue
+g.data['d'] = dic
+print(extValueDetails(g))
 
+print("Let's add a few mutants and display their data:")
 for more in range(5):
 	frams.GenePools[0].add(frams.GenMan.mutate(g.geno))
 
 for g in frams.GenePools[0]:
-	print(str(g.index) + '. "' + str(g.name) + '"  ' + str(g.genotype) + '  data=' + str(g.data))
+	print("\t%d. name='%s'\tgenotype='%s'\tdata=%s" % (g.index._value(), str(g.name), str(g.genotype), str(g.data)))
+
+print("Let's now change some property of the simulation. Current water level is", frams.World.wrldwat)
+frams.World.wrldwat = 0.5
+print("Now water level is", frams.World.wrldwat)
+frams.World.wrldwat = frams.World.wrldwat._value() + 0.7
+print("Now water level is", frams.World.wrldwat)
+
+initial_genotype = 'X(X,RX(X[T],X[G]))'  # simple body with gyroscope and touch sensors
+print("Let's perform a few simulation steps of the initial genotype:", initial_genotype)
+frams.ExpProperties.initialgen = initial_genotype
+frams.ExpProperties.p_mut = 0  # no mutation (the selection procedure will clone our initial genotype)
+frams.ExpProperties.p_xov = 0  # no crossover (the selection procedure will clone our initial genotype)
+frams.Populations[0].initial_nn_active = 1  # immediate simulation of neural network - no "waiting for stabilization" period
+frams.World.wrldg = 5  # gravity=5x default, let it fall quickly
+
+frams.Simulator.init()  # adds initial_genotype to gene pool (calls onInit() from standard.expdef)
+frams.Simulator.start()  # this does not actually start the simulation, just sets the "Simulator.running" status variable
+step = frams.Simulator.step  # cache reference to avoid repeated lookup in the loop (just for performance)
+for s in range(15):
+	step()  # first step performs selection and revives one genotype according to standard.expdef rules
+	creature = frams.Populations[0][0]  # FramScript Creature object
+	mechpart0 = creature.getMechPart(0)
+	print('Step# = %d' % frams.Simulator.stepNumber._value(),
+	      '\tSimulated_creatures =', frams.Populations[0].size._value(),
+	      "\tpart0_xyz = (% .2f,% .2f,% .2f)" % (mechpart0.x._value(), mechpart0.y._value(), mechpart0.z._value()),
+	      "\ttouch = % .3f\tgyro = % .3f" % (creature.getNeuro(0).state._value(), creature.getNeuro(1).state._value()))
+frams.Simulator.stop()
+
+# Note that implementing a complete expdef, especially a complex one, entirely in python may be inconvenient or impractical
+# because you do not have access to "event handlers" like you have in FramScript - onStep(), onBorn(), onDied(), onCollision() etc.,
+# so you would have to check various conditions in python in each simulation step to achieve the same effect.
