- fixed to work with multiple courses.

- set supported versions of python packages. - changes key 'topics' to 'goals' when setting a course. - fix use of deprecated 'g.node[]' from networkx.

- fixed to work with multiple courses.
- set supported versions of python packages. - changes key 'topics' to 'goals' when setting a course. - fix use of deprecated 'g.node[]' from networkx.
Miguel Barão
1 parent 3dd184c9
Showing 6 changed files with 58 additions and 55 deletions Show diff stats
.gitignore
BUGS.md
aprendizations/__init__.py
aprendizations/learnapp.py
aprendizations/student.py
setup.py
@@ -3,4 +3,7 @@
 /aprendizations/__pycache__/
 /demo/students.db
 /node_modules/
-/.mypy_cache/
 \ No newline at end of file
+/.mypy_cache/
+.DS_Store
+demo/.DS_Store
+demo/solar_system/.DS_Store
  
 # BUGS
  
-- não suporta definition lists em markdown
+- obter rankings por curso GET course=course_id
+- indicar qtos topicos faltam (>=50%) para terminar o curso.
+- permite definir goal, mas nao verifica se esta no grafo. rebenta no start_topic.
 - double click submits twice.
 - nao esta a seguir o max_tries definido no ficheiro de dependencias.
-- obter rankings por curso GET course=course_id
 - impedir que quando students.db não é encontrado, crie um ficheiro vazio.
 - classificacoes so devia mostrar os que ja fizeram alguma coisa
 - QFactory.generate() devia fazer run da gen_async, ou remover.
@@ -30,7 +30,7 @@ are progressively uncovered as the students progress.
 '''
  
 APP_NAME = 'aprendizations'
-APP_VERSION = '2019.07.dev3'
+APP_VERSION = '2019.10.dev1'
 APP_DESCRIPTION = __doc__
  
 __author__ = 'Miguel Barão'
@@ -67,18 +67,24 @@ class LearnApp(object):
  
         config: Dict[str, Any] = load_yaml(courses)
  
-        # courses dict
+        # --- courses dict
         self.courses = config['courses']
         logger.info(f'Courses: {", ".join(self.courses.keys())}')
  
-        # topic dependencies are shared between all courses
+        # --- topic dependencies are shared between all courses
         self.deps = nx.DiGraph(prefix=prefix)
         logger.info('Populating graph:')
-        for f in config['deps']:
-            self.populate_graph(f)
+
+        t = config.get('topics', {})  # topics defined directly in courses file
+        self.populate_graph(t)
+        logger.info(f'{len(t):>6} topics in {courses}')
+        for f in config.get('topics_from', []):
+            c = load_yaml(f)    # course configuration
+            logger.info(f'{len(c["topics"]):>6} topics from {f}')
+            self.populate_graph(c)
         logger.info(f'Graph has {len(self.deps)} topics')
  
-        # factory is a dict with question generators for all topics
+        # --- factory is a dict with question generators for all topics
         self.factory: Dict[str, QFactory] = self.make_factory()
  
         # if graph has topics that are not in the database, add them
@@ -322,29 +328,30 @@ class LearnApp(object):
     # Populates a digraph.
     #
     # Nodes are the topic references e.g. 'my/topic'
-    #   g.node['my/topic']['name']      name of the topic
-    #   g.node['my/topic']['questions'] list of question refs
+    #   g.nodes['my/topic']['name']      name of the topic
+    #   g.nodes['my/topic']['questions'] list of question refs
     #
     # Edges are obtained from the deps defined in the YAML file for each topic.
     # ------------------------------------------------------------------------
-    def populate_graph(self, conffile: str) -> None:
-        config: Dict[str, Any] = load_yaml(conffile)    # course configuration
-
-        # default attributes that apply to the topics
-        default_file: str = config.get('file', 'questions.yaml')
-        default_shuffle_questions: bool = config.get('shuffle_questions', True)
-        default_choose: int = config.get('choose', 9999)
-        default_forgetting_factor: float = config.get('forgetting_factor', 1.0)
-        default_maxtries: int = config.get('max_tries', 1)
-        default_append_wrong: bool = config.get('append_wrong', True)
-        default_min_level: float = config.get('min_level', 0.01)  # to unlock
+    def populate_graph(self, config: Dict[str, Any]) -> None:
+        g = self.deps       # dependency graph
+        defaults = {
+            'type': 'topic',
+            'file': 'questions.yaml',
+            'shuffle_questions': True,
+            'choose': 9999,
+            'forgetting_factor': 1.0,  # no forgetting
+            'max_tries': 1,            # in every question
+            'append_wrong': True,
+            'min_level': 0.01,         # to unlock topic
+        }
+        defaults.update(config.get('defaults', {}))
  
         # iterate over topics and populate graph
         topics: Dict[str, Dict] = config.get('topics', {})
-        g = self.deps       # dependency graph
-
         g.add_nodes_from(topics.keys())
         for tref, attr in topics.items():
+            logger.debug(f'       + {tref}...')
             for d in attr.get('deps', []):
                 if d not in g.nodes():
                     logger.error(f'Topic "{tref}" depends on "{d}" but it '
@@ -353,22 +360,15 @@ class LearnApp(object):
                 else:
                     g.add_edge(d, tref)
  
-            t = g.node[tref]  # get current topic node
-            t['type'] = attr.get('type', 'topic')
+            t = g.nodes[tref]  # get current topic node
             t['name'] = attr.get('name', tref)
-            t['path'] = path.join(g.graph['prefix'], tref)    # prefix/topic
-            t['file'] = attr.get('file', default_file)        # questions.yaml
-            t['shuffle_questions'] = attr.get('shuffle_questions',
-                                              default_shuffle_questions)
-            t['max_tries'] = attr.get('max_tries', default_maxtries)
-            t['forgetting_factor'] = attr.get('forgetting_factor',
-                                              default_forgetting_factor)
-            t['min_level'] = attr.get('min_level', default_min_level)
-            t['choose'] = attr.get('choose', default_choose)
-            t['append_wrong'] = attr.get('append_wrong', default_append_wrong)
             t['questions'] = attr.get('questions', [])
  
-        logger.info(f'{len(topics):>6} topics in {conffile}')
+            for k, default in defaults.items():
+                t[k] = attr.get(k, default)
+
+            t['path'] = path.join(g.graph['prefix'], tref)    # prefix/topic
+
  
     # ========================================================================
     # methods that do not change state (pure functions)
@@ -378,12 +378,11 @@ class LearnApp(object):
     # Buils dictionary of question factories
     # ------------------------------------------------------------------------
     def make_factory(self) -> Dict[str, QFactory]:
-
         logger.info('Building questions factory:')
         factory: Dict[str, QFactory] = {}
         g = self.deps
         for tref in g.nodes():
-            t = g.node[tref]
+            t = g.nodes[tref]
  
             # load questions as list of dicts
             topicpath: str = path.join(g.graph['prefix'], tref)
@@ -457,13 +456,8 @@ class LearnApp(object):
         return self.online[uid]['state'].get_current_course_id()
  
     # ------------------------------------------------------------------------
-    # def get_title(self) -> str:
-    #     # return self.deps.graph.get('title', '')
-    #     return self.
-
-    # ------------------------------------------------------------------------
     def get_topic_name(self, ref: str) -> str:
-        return self.deps.node[ref]['name']
+        return self.deps.nodes[ref]['name']
  
     # ------------------------------------------------------------------------
     def get_current_public_dir(self, uid: str) -> str:
@@ -53,7 +53,7 @@ class StudentState(object):
         else:
             logger.debug(f'starting course {course}')
             self.current_course = course
-            topics = self.courses[course]['topics']
+            topics = self.courses[course]['goals']
             self.topic_sequence = self.recommend_topic_sequence(topics)
  
     # ------------------------------------------------------------------------
@@ -79,7 +79,7 @@ class StudentState(object):
         self.correct_answers = 0
         self.wrong_answers = 0
  
-        t = self.deps.node[topic]
+        t = self.deps.nodes[topic]
         k = t['choose']
         if t['shuffle_questions']:
             questions = random.sample(t['questions'], k=k)
@@ -174,7 +174,7 @@ class StudentState(object):
         now = datetime.now()
         for tref, s in self.state.items():
             dt = now - s['date']
-            forgetting_factor = self.deps.node[tref]['forgetting_factor']
+            forgetting_factor = self.deps.nodes[tref]['forgetting_factor']
             s['level'] *= forgetting_factor ** dt.days   # forgetting factor
  
     # ------------------------------------------------------------------------
@@ -184,7 +184,7 @@ class StudentState(object):
         for topic in self.deps.nodes():
             if topic not in self.state:  # if locked
                 pred = self.deps.predecessors(topic)
-                min_level = self.deps.node[topic]['min_level']
+                min_level = self.deps.nodes[topic]['min_level']
                 if all(d in self.state and self.state[d]['level'] > min_level
                        for d in pred):  # all deps are greater than min_level
  
@@ -206,12 +206,12 @@ class StudentState(object):
     # ------------------------------------------------------------------------
     # compute recommended sequence of topics  ['a', 'b', ...]
     # ------------------------------------------------------------------------
-    def recommend_topic_sequence(self, targets: List[str] = []) -> List[str]:
+    def recommend_topic_sequence(self, goals: List[str] = []) -> List[str]:
         G = self.deps
-        ts = set(targets)
-        for t in targets:
+        ts = set(goals)
+        for t in goals:
             ts.update(nx.ancestors(G, t))
-
+            # FIXME filter by level done, only level < 50% are included
         tl = list(nx.topological_sort(G.subgraph(ts)))
  
         # sort with unlocked first
@@ -20,8 +20,13 @@ setup(
     include_package_data=True,   # install files from MANIFEST.in
     python_requires='>=3.7.*',
     install_requires=[
-        'tornado', 'mistune', 'pyyaml', 'pygments', 'sqlalchemy', 'bcrypt',
-        'networkx'
+        'tornado>=6.0',
+        'mistune',
+        'pyyaml>=5.1',
+        'pygments',
+        'sqlalchemy',
+        'bcrypt>=3.1',
+        'networkx>=2.4'
         ],
     entry_points={
         'console_scripts': [
...	...	@@ -3,4 +3,7 @@
3	3	/aprendizations/__pycache__/
4	4	/demo/students.db
5	5	/node_modules/
6		-/.mypy_cache/
7	6	\ No newline at end of file
	7	+/.mypy_cache/
	8	+.DS_Store
	9	+demo/.DS_Store
	10	+demo/solar_system/.DS_Store
...	...
1	1
2	2	# BUGS
3	3
4		-- não suporta definition lists em markdown
	4	+- obter rankings por curso GET course=course_id
	5	+- indicar qtos topicos faltam (>=50%) para terminar o curso.
	6	+- permite definir goal, mas nao verifica se esta no grafo. rebenta no start_topic.
5	7	- double click submits twice.
6	8	- nao esta a seguir o max_tries definido no ficheiro de dependencias.
7		-- obter rankings por curso GET course=course_id
8	9	- impedir que quando students.db não é encontrado, crie um ficheiro vazio.
9	10	- classificacoes so devia mostrar os que ja fizeram alguma coisa
10	11	- QFactory.generate() devia fazer run da gen_async, ou remover.
...	...
...	...	@@ -30,7 +30,7 @@ are progressively uncovered as the students progress.
30	30	'''
31	31
32	32	APP_NAME = 'aprendizations'
33		-APP_VERSION = '2019.07.dev3'
	33	+APP_VERSION = '2019.10.dev1'
34	34	APP_DESCRIPTION = __doc__
35	35
36	36	__author__ = 'Miguel Barão'
...	...
...	...	@@ -67,18 +67,24 @@ class LearnApp(object):
67	67
68	68	config: Dict[str, Any] = load_yaml(courses)
69	69
70		- # courses dict
	70	+ # --- courses dict
71	71	self.courses = config['courses']
72	72	logger.info(f'Courses: {", ".join(self.courses.keys())}')
73	73
74		- # topic dependencies are shared between all courses
	74	+ # --- topic dependencies are shared between all courses
75	75	self.deps = nx.DiGraph(prefix=prefix)
76	76	logger.info('Populating graph:')
77		- for f in config['deps']:
78		- self.populate_graph(f)
	77	+
	78	+ t = config.get('topics', {}) # topics defined directly in courses file
	79	+ self.populate_graph(t)
	80	+ logger.info(f'{len(t):>6} topics in {courses}')
	81	+ for f in config.get('topics_from', []):
	82	+ c = load_yaml(f) # course configuration
	83	+ logger.info(f'{len(c["topics"]):>6} topics from {f}')
	84	+ self.populate_graph(c)
79	85	logger.info(f'Graph has {len(self.deps)} topics')
80	86
81		- # factory is a dict with question generators for all topics
	87	+ # --- factory is a dict with question generators for all topics
82	88	self.factory: Dict[str, QFactory] = self.make_factory()
83	89
84	90	# if graph has topics that are not in the database, add them
...	...	@@ -322,29 +328,30 @@ class LearnApp(object):
322	328	# Populates a digraph.
323	329	#
324	330	# Nodes are the topic references e.g. 'my/topic'
325		- # g.node['my/topic']['name'] name of the topic
326		- # g.node['my/topic']['questions'] list of question refs
	331	+ # g.nodes['my/topic']['name'] name of the topic
	332	+ # g.nodes['my/topic']['questions'] list of question refs
327	333	#
328	334	# Edges are obtained from the deps defined in the YAML file for each topic.
329	335	# ------------------------------------------------------------------------
330		- def populate_graph(self, conffile: str) -> None:
331		- config: Dict[str, Any] = load_yaml(conffile) # course configuration
332		-
333		- # default attributes that apply to the topics
334		- default_file: str = config.get('file', 'questions.yaml')
335		- default_shuffle_questions: bool = config.get('shuffle_questions', True)
336		- default_choose: int = config.get('choose', 9999)
337		- default_forgetting_factor: float = config.get('forgetting_factor', 1.0)
338		- default_maxtries: int = config.get('max_tries', 1)
339		- default_append_wrong: bool = config.get('append_wrong', True)
340		- default_min_level: float = config.get('min_level', 0.01) # to unlock
	336	+ def populate_graph(self, config: Dict[str, Any]) -> None:
	337	+ g = self.deps # dependency graph
	338	+ defaults = {
	339	+ 'type': 'topic',
	340	+ 'file': 'questions.yaml',
	341	+ 'shuffle_questions': True,
	342	+ 'choose': 9999,
	343	+ 'forgetting_factor': 1.0, # no forgetting
	344	+ 'max_tries': 1, # in every question
	345	+ 'append_wrong': True,
	346	+ 'min_level': 0.01, # to unlock topic
	347	+ }
	348	+ defaults.update(config.get('defaults', {}))
341	349
342	350	# iterate over topics and populate graph
343	351	topics: Dict[str, Dict] = config.get('topics', {})
344		- g = self.deps # dependency graph
345		-
346	352	g.add_nodes_from(topics.keys())
347	353	for tref, attr in topics.items():
	354	+ logger.debug(f' + {tref}...')
348	355	for d in attr.get('deps', []):
349	356	if d not in g.nodes():
350	357	logger.error(f'Topic "{tref}" depends on "{d}" but it '
...	...	@@ -353,22 +360,15 @@ class LearnApp(object):
353	360	else:
354	361	g.add_edge(d, tref)
355	362
356		- t = g.node[tref] # get current topic node
357		- t['type'] = attr.get('type', 'topic')
	363	+ t = g.nodes[tref] # get current topic node
358	364	t['name'] = attr.get('name', tref)
359		- t['path'] = path.join(g.graph['prefix'], tref) # prefix/topic
360		- t['file'] = attr.get('file', default_file) # questions.yaml
361		- t['shuffle_questions'] = attr.get('shuffle_questions',
362		- default_shuffle_questions)
363		- t['max_tries'] = attr.get('max_tries', default_maxtries)
364		- t['forgetting_factor'] = attr.get('forgetting_factor',
365		- default_forgetting_factor)
366		- t['min_level'] = attr.get('min_level', default_min_level)
367		- t['choose'] = attr.get('choose', default_choose)
368		- t['append_wrong'] = attr.get('append_wrong', default_append_wrong)
369	365	t['questions'] = attr.get('questions', [])
370	366
371		- logger.info(f'{len(topics):>6} topics in {conffile}')
	367	+ for k, default in defaults.items():
	368	+ t[k] = attr.get(k, default)
	369	+
	370	+ t['path'] = path.join(g.graph['prefix'], tref) # prefix/topic
	371	+
372	372
373	373	# ========================================================================
374	374	# methods that do not change state (pure functions)
...	...	@@ -378,12 +378,11 @@ class LearnApp(object):
378	378	# Buils dictionary of question factories
379	379	# ------------------------------------------------------------------------
380	380	def make_factory(self) -> Dict[str, QFactory]:
381		-
382	381	logger.info('Building questions factory:')
383	382	factory: Dict[str, QFactory] = {}
384	383	g = self.deps
385	384	for tref in g.nodes():
386		- t = g.node[tref]
	385	+ t = g.nodes[tref]
387	386
388	387	# load questions as list of dicts
389	388	topicpath: str = path.join(g.graph['prefix'], tref)
...	...	@@ -457,13 +456,8 @@ class LearnApp(object):
457	456	return self.online[uid]['state'].get_current_course_id()
458	457
459	458	# ------------------------------------------------------------------------
460		- # def get_title(self) -> str:
461		- # # return self.deps.graph.get('title', '')
462		- # return self.
463		-
464		- # ------------------------------------------------------------------------
465	459	def get_topic_name(self, ref: str) -> str:
466		- return self.deps.node[ref]['name']
	460	+ return self.deps.nodes[ref]['name']
467	461
468	462	# ------------------------------------------------------------------------
469	463	def get_current_public_dir(self, uid: str) -> str:
...	...
...	...	@@ -53,7 +53,7 @@ class StudentState(object):
53	53	else:
54	54	logger.debug(f'starting course {course}')
55	55	self.current_course = course
56		- topics = self.courses[course]['topics']
	56	+ topics = self.courses[course]['goals']
57	57	self.topic_sequence = self.recommend_topic_sequence(topics)
58	58
59	59	# ------------------------------------------------------------------------
...	...	@@ -79,7 +79,7 @@ class StudentState(object):
79	79	self.correct_answers = 0
80	80	self.wrong_answers = 0
81	81
82		- t = self.deps.node[topic]
	82	+ t = self.deps.nodes[topic]
83	83	k = t['choose']
84	84	if t['shuffle_questions']:
85	85	questions = random.sample(t['questions'], k=k)
...	...	@@ -174,7 +174,7 @@ class StudentState(object):
174	174	now = datetime.now()
175	175	for tref, s in self.state.items():
176	176	dt = now - s['date']
177		- forgetting_factor = self.deps.node[tref]['forgetting_factor']
	177	+ forgetting_factor = self.deps.nodes[tref]['forgetting_factor']
178	178	s['level'] = forgetting_factor * dt.days # forgetting factor
179	179
180	180	# ------------------------------------------------------------------------
...	...	@@ -184,7 +184,7 @@ class StudentState(object):
184	184	for topic in self.deps.nodes():
185	185	if topic not in self.state: # if locked
186	186	pred = self.deps.predecessors(topic)
187		- min_level = self.deps.node[topic]['min_level']
	187	+ min_level = self.deps.nodes[topic]['min_level']
188	188	if all(d in self.state and self.state[d]['level'] > min_level
189	189	for d in pred): # all deps are greater than min_level
190	190
...	...	@@ -206,12 +206,12 @@ class StudentState(object):
206	206	# ------------------------------------------------------------------------
207	207	# compute recommended sequence of topics ['a', 'b', ...]
208	208	# ------------------------------------------------------------------------
209		- def recommend_topic_sequence(self, targets: List[str] = []) -> List[str]:
	209	+ def recommend_topic_sequence(self, goals: List[str] = []) -> List[str]:
210	210	G = self.deps
211		- ts = set(targets)
212		- for t in targets:
	211	+ ts = set(goals)
	212	+ for t in goals:
213	213	ts.update(nx.ancestors(G, t))
214		-
	214	+ # FIXME filter by level done, only level < 50% are included
215	215	tl = list(nx.topological_sort(G.subgraph(ts)))
216	216
217	217	# sort with unlocked first
...	...
...	...	@@ -20,8 +20,13 @@ setup(
20	20	include_package_data=True, # install files from MANIFEST.in
21	21	python_requires='>=3.7.*',
22	22	install_requires=[
23		- 'tornado', 'mistune', 'pyyaml', 'pygments', 'sqlalchemy', 'bcrypt',
24		- 'networkx'
	23	+ 'tornado>=6.0',
	24	+ 'mistune',
	25	+ 'pyyaml>=5.1',
	26	+ 'pygments',
	27	+ 'sqlalchemy',
	28	+ 'bcrypt>=3.1',
	29	+ 'networkx>=2.4'
25	30	],
26	31	entry_points={
27	32	'console_scripts': [
...	...