Moving random EM generation methods in a dedicated file

Creating a class RandomEm in EditorialModel/randomem.py

EditorialModel/model.py

@@ -3,9 +3,6 @@
 ## @file editorialmodel.py
 # Manage instance of an editorial model
 
-import random
-import time
-
 import EditorialModel
 from EditorialModel.migrationhandler.dummy import DummyMigrationHandler
 from EditorialModel.backend.dummy_backend import EmBackendDummy
@@ -13,8 +10,6 @@ from EditorialModel.classes import EmClass
 from EditorialModel.fieldgroups import EmFieldGroup
 from EditorialModel.fields import EmField
 from EditorialModel.types import EmType
-from EditorialModel.classtypes import EmClassType
-from Lodel.utils.mlstring import MlString
 from EditorialModel.exceptions import EmComponentCheckError, EmComponentNotExistError, MigrationHandlerChangeError
 import hashlib
 
@@ -278,161 +273,3 @@ class Model(object):
         del new_me
 
         self.migration_handler = new_mh
-
-    @classmethod
-    ## @brief Generate a random editorial model
-    # 
-    # The random generator can be tuned with integer parameters
-    # that represent probability or maximum numbers of items.
-    # The probability (chances) works like 1/x chances to append
-    # with x the tunable parameter
-    # Tunable generator parameters :
-    # - classtype : Chances for a classtype to be empty (default 0)
-    # - nclass : Maximum number of classes per classtypes (default 5)
-    # - nofg : Chances for a classe to have no fieldgroup associated to it (default 10)
-    # - notype : Chances for a classe to have no type associated to it (default 5)
-    # - seltype : Chances for a type to select an optionnal field (default 2)
-    # - ntypesuperiors : Chances for a type to link with a superiors (default 3)
-    # - nofields : Chances for a fieldgroup to be empty (default 10)
-    # - nfields : Maximum number of field per fieldgroups (default 8)
-    # - rfields : Maximum number of relation_to_type attributes fields (default 5)
-    # - optfield : Chances for a field to be optionnal (default 2)
-    # @param backend : A backend to use with the new EM
-    # @param **kwargs dict : Provide tunable generation parameter
-    # @return A randomly generate EM
-    def random(cls, backend, **kwargs):
-        em = Model(backend)
-
-        chances = {
-            'classtype' : 0, # a class in classtype
-            'nclass': 5, #max number of classes per classtype
-            'nofg': 10, #no fieldgroup in a class
-            'nfg': 5, #max number of fieldgroups per classes
-            'notype': 10, # no types in a class
-            'ntype': 8,  # max number of types in a class
-            'seltype': 2, #chances to select an optional field
-            'ntypesuperiors': 2, #chances to link with a superior
-            'nofields': 10, # no fields in a fieldgroup
-            'nfields' : 8, #max number of fields per fieldgroups
-            'rfields': 5,#max number of attributes relation fields
-            'optfield': 2, #chances to be optionnal
-        }
-
-        for name,value in kwargs.items():
-            if name not in chances:
-                #warning
-                pass
-            else:
-                chances[name] = value
-
-        #classes creation
-        for classtype in EmClassType.getall():
-            if random.randint(0,chances['classtype']) == 0:
-                for _ in range(random.randint(1,chances['nclass'])):
-                    cdats = cls._rnd_component_datas()
-                    cdats['classtype'] = classtype['name']
-                    em.create_component('EmClass', cdats)
-
-        for emclass in em.classes():
-            #fieldgroups creation
-            if random.randint(0, chances['nofg']) != 0:
-                for _ in range(random.randint(1, chances['nfg'])):
-                    fgdats = cls._rnd_component_datas()
-                    fgdats['class_id'] = emclass.uid
-                    em.create_component('EmFieldGroup', fgdats)
-
-            #types creation
-            if random.randint(0, chances['notype']) != 0:
-                for _ in range(random.randint(1, chances['ntype'])):
-                    tdats = cls._rnd_component_datas()
-                    tdats['class_id'] = emclass.uid
-                    em.create_component('EmType', tdats)
-
-        #random type hierarchy
-        for emtype in em.components(EmType):
-            possible = emtype.possible_superiors()
-            for nat in possible:
-                if len(possible[nat]) > 0 and random.randint(0, chances['ntypesuperiors']) == 0:
-                    random.shuffle(possible[nat])
-                    for i in range(random.randint(1, len(possible[nat]))):
-                        emtype.add_superior(possible[nat][i], nat)
-
-
-        #fields creation
-        ft_l = EmField.fieldtypes_list()
-        for emfg in em.components(EmFieldGroup):
-            if random.randint(0, chances['nofields']) != 0:
-                for _ in range(random.randint(1, chances['nfields'])):
-                    ft = ft_l[random.randint(0,len(ft_l)-1)]
-                    fdats = cls._rnd_component_datas()
-                    fdats['fieldtype']=ft
-                    fdats['fieldgroup_id'] = emfg.uid
-                    if ft == 'rel2type':
-                        emtypes = em.components(EmType)
-                        fdats['rel_to_type_id'] = emtypes[random.randint(0,len(emtypes)-1)].uid
-                    if random.randint(0,chances['optfield']) == 0:
-                        fdats['optional'] = True
-                    em.create_component('EmField', fdats)
-
-        #relationnal fiels creation
-        ft_l = [ ft for ft in EmField.fieldtypes_list() if ft != 'rel2type' ]
-        for emrelf in [ f for f in em.components(EmField) if f.ftype == 'rel2type' ]:
-            for _ in range(0,chances['rfields']):
-                ft = ft_l[random.randint(0, len(ft_l)-1)]
-                fdats = cls._rnd_component_datas()
-                fdats['fieldtype'] = ft
-                fdats['fieldgroup_id'] = emrelf.fieldgroup_id
-                if random.randint(0, chances['optfield']) == 0:
-                    fdats['optional'] = True
-                em.create_component('EmField', fdats)
-                
-
-        #selection optionnal fields
-        for emtype in em.components(EmType):
-            selectable = [field for fieldgroup in emtype.fieldgroups() for field in fieldgroup.fields() if field.optional ]
-            for field in selectable:
-                if random.randint(0,chances['seltype']) == 0:
-                    emtype.select_field(field)
-                    
-
-        return em
-
-                
-    
-    @staticmethod
-    ## @brief Generate a random string
-    # @warning dirty cache trick with globals()
-    # @return a randomly selected string
-    def _rnd_str(words_src='/usr/share/dict/words'):
-        if '_words' not in globals() or globals()['_words_fname'] != words_src:
-            globals()['_words_fname'] = words_src
-            with open(words_src, 'r') as fpw:
-                globals()['_words'] = [ l.strip() for l in fpw ]
-        words = globals()['_words']
-        return words[random.randint(0,len(words)-1)]
-        
-    @classmethod
-    ## @brief Generate a random MlString
-    # @param nlng : Number of langs in the MlString
-    # @return a random MlString with nlng translations
-    # @todo use a dict to generated langages
-    def _rnd_mlstr(cls, nlng):
-        ret = MlString()
-        for _ in range(nlng):
-            ret.set(cls._rnd_str(), cls._rnd_str())
-        return ret
-
-    @classmethod
-    ## @brief returns randomly generated datas for an EmComponent
-    # @return a dict with name, string and help_text
-    def _rnd_component_datas(cls):
-        mlstr_nlang = 2;
-        ret = dict()
-        ret['name'] = cls._rnd_str()
-        ret['string'] = cls._rnd_mlstr(mlstr_nlang)
-        ret['help_text'] = cls._rnd_mlstr(mlstr_nlang)
-
-        return ret
-        
-        
-        

EditorialModel/randomem.py

@@ -0,0 +1,177 @@
+#-*- coding: utf-8 -*-
+
+## @package EditorialModel.randomem
+#
+# Provide methods for random EM generation
+
+import random
+from EditorialModel.backend.dummy_backend import EmBackendDummy
+from EditorialModel.model import Model
+from EditorialModel.fieldgroups import EmFieldGroup
+from EditorialModel.fields import EmField
+from EditorialModel.types import EmType
+from EditorialModel.classtypes import EmClassType
+from Lodel.utils.mlstring import MlString
+
+
+class RandomEm(object):
+    
+    ## @brief Instanciate a class allowing to generate random EM
+    # @see RandomEm::random_em()
+    def __init__(self, backend=None, **kwargs):
+        self.backend = backend
+        self.kwargs = kwargs
+
+    ## @brief Return a random EM
+    # @return A random EM
+    def gen(self):
+        return self.random_em(self.backend, **self.kwargs)
+
+    @classmethod
+    ## @brief Generate a random editorial model
+    #
+    # The random generator can be tuned with integer parameters
+    # that represent probability or maximum numbers of items.
+    # The probability (chances) works like 1/x chances to append
+    # with x the tunable parameter
+    # Tunable generator parameters :
+    # - classtype : Chances for a classtype to be empty (default 0)
+    # - nclass : Maximum number of classes per classtypes (default 5)
+    # - nofg : Chances for a classe to have no fieldgroup associated to it (default 10)
+    # - notype : Chances for a classe to have no type associated to it (default 5)
+    # - seltype : Chances for a type to select an optionnal field (default 2)
+    # - ntypesuperiors : Chances for a type to link with a superiors (default 3)
+    # - nofields : Chances for a fieldgroup to be empty (default 10)
+    # - nfields : Maximum number of field per fieldgroups (default 8)
+    # - rfields : Maximum number of relation_to_type attributes fields (default 5)
+    # - optfield : Chances for a field to be optionnal (default 2)
+    # @param backend : A backend to use with the new EM
+    # @param **kwargs dict : Provide tunable generation parameter
+    # @return A randomly generate EM
+    def random_em(cls, backend=None, **kwargs):
+        ed_mod = Model(EmBackendDummy if backend is None else backend)
+
+        chances = {
+            'classtype': 0,         # a class in classtype
+            'nclass': 5,            # max number of classes per classtype
+            'nofg': 10,             # no fieldgroup in a class
+            'nfg': 5,               # max number of fieldgroups per classes
+            'notype': 10,           # no types in a class
+            'ntype': 8,             # max number of types in a class
+            'seltype': 2,           # chances to select an optional field
+            'ntypesuperiors': 2,    # chances to link with a superior
+            'nofields': 10,         # no fields in a fieldgroup
+            'nfields': 8,           # max number of fields per fieldgroups
+            'rfields': 5,           # max number of attributes relation fields
+            'optfield': 2,          # chances to be optionnal
+        }
+
+        for name, value in kwargs.items():
+            if name not in chances:
+                #warning
+                pass
+            else:
+                chances[name] = value
+
+        #classes creation
+        for classtype in EmClassType.getall():
+            if random.randint(0, chances['classtype']) == 0:
+                for _ in range(random.randint(1, chances['nclass'])):
+                    cdats = cls._rnd_component_datas()
+                    cdats['classtype'] = classtype['name']
+                    ed_mod.create_component('EmClass', cdats)
+
+        for emclass in ed_mod.classes():
+            #fieldgroups creation
+            if random.randint(0, chances['nofg']) != 0:
+                for _ in range(random.randint(1, chances['nfg'])):
+                    fgdats = cls._rnd_component_datas()
+                    fgdats['class_id'] = emclass.uid
+                    ed_mod.create_component('EmFieldGroup', fgdats)
+
+            #types creation
+            if random.randint(0, chances['notype']) != 0:
+                for _ in range(random.randint(1, chances['ntype'])):
+                    tdats = cls._rnd_component_datas()
+                    tdats['class_id'] = emclass.uid
+                    ed_mod.create_component('EmType', tdats)
+
+        #random type hierarchy
+        for emtype in ed_mod.components(EmType):
+            possible = emtype.possible_superiors()
+            for nat in possible:
+                if len(possible[nat]) > 0 and random.randint(0, chances['ntypesuperiors']) == 0:
+                    random.shuffle(possible[nat])
+                    for i in range(random.randint(1, len(possible[nat]))):
+                        emtype.add_superior(possible[nat][i], nat)
+
+        #fields creation
+        ft_l = EmField.fieldtypes_list()
+        for emfg in ed_mod.components(EmFieldGroup):
+            if random.randint(0, chances['nofields']) != 0:
+                for _ in range(random.randint(1, chances['nfields'])):
+                    field_type = ft_l[random.randint(0, len(ft_l) - 1)]
+                    fdats = cls._rnd_component_datas()
+                    fdats['fieldtype'] = field_type
+                    fdats['fieldgroup_id'] = emfg.uid
+                    if field_type == 'rel2type':
+                        emtypes = ed_mod.components(EmType)
+                        fdats['rel_to_type_id'] = emtypes[random.randint(0, len(emtypes) - 1)].uid
+                    if random.randint(0, chances['optfield']) == 0:
+                        fdats['optional'] = True
+                    ed_mod.create_component('EmField', fdats)
+
+        #relationnal fiels creation
+        ft_l = [field_type for field_type in EmField.fieldtypes_list() if field_type != 'rel2type']
+        for emrelf in [f for f in ed_mod.components(EmField) if f.ftype == 'rel2type']:
+            for _ in range(0, chances['rfields']):
+                field_type = ft_l[random.randint(0, len(ft_l) - 1)]
+                fdats = cls._rnd_component_datas()
+                fdats['fieldtype'] = field_type
+                fdats['fieldgroup_id'] = emrelf.fieldgroup_id
+                if random.randint(0, chances['optfield']) == 0:
+                    fdats['optional'] = True
+                ed_mod.create_component('EmField', fdats)
+
+        #selection optionnal fields
+        for emtype in ed_mod.components(EmType):
+            selectable = [field for fieldgroup in emtype.fieldgroups() for field in fieldgroup.fields() if field.optional]
+            for field in selectable:
+                if random.randint(0, chances['seltype']) == 0:
+                    emtype.select_field(field)
+        return ed_mod
+
+    @staticmethod
+    ## @brief Generate a random string
+    # @warning dirty cache trick with globals()
+    # @return a randomly selected string
+    def _rnd_str(words_src='/usr/share/dict/words'):
+        if '_words' not in globals() or globals()['_words_fname'] != words_src:
+            globals()['_words_fname'] = words_src
+            with open(words_src, 'r') as fpw:
+                globals()['_words'] = [l.strip() for l in fpw]
+        words = globals()['_words']
+        return words[random.randint(0, len(words) - 1)]
+
+    @classmethod
+    ## @brief Generate a random MlString
+    # @param nlng : Number of langs in the MlString
+    # @return a random MlString with nlng translations
+    # @todo use a dict to generated langages
+    def _rnd_mlstr(cls, nlng):
+        ret = MlString()
+        for _ in range(nlng):
+            ret.set(cls._rnd_str(), cls._rnd_str())
+        return ret
+
+    @classmethod
+    ## @brief returns randomly generated datas for an EmComponent
+    # @return a dict with name, string and help_text
+    def _rnd_component_datas(cls):
+        mlstr_nlang = 2
+        ret = dict()
+        ret['name'] = cls._rnd_str()
+        ret['string'] = cls._rnd_mlstr(mlstr_nlang)
+        ret['help_text'] = cls._rnd_mlstr(mlstr_nlang)
+
+        return ret

Lodel/management/commands/emgen.py

@@ -1,6 +1,6 @@
 from django.core.management.base import BaseCommand, CommandError
 from optparse import make_option
-from EditorialModel.model import Model
+from EditorialModel.randomem import RandomEm
 from EditorialModel.backend.json_backend import EmBackendJson
 from EditorialModel.backend.dummy_backend import EmBackendDummy
 from EditorialModel.backend.graphviz import EmBackendGraphviz
@@ -127,7 +127,7 @@ class Command(BaseCommand):
         
         bj = EmBackendJson(options['output'])
 
-        em = Model.random(EmBackendDummy())
+        em = RandomEm.random_em(EmBackendDummy())
         bj.save(em)
 
         if options['dotout']: