def state_helper(def_state: dict, path: dict, log) -> tuple:
no_ini = not os.path.isfile(path['settings'])
no_state = not os.path.isfile(path['state'])
if no_state and no_ini:
return def_state, True, True
ini_version, merge, state_save = 0, 0, True
if not no_state:
try:
state = dict_from_file(path['state'])
ini_version = state['system']['ini_version']
merge = state['system']['merge']
except RuntimeError as e:
log('Broken {}, reset'.format(path['state']), logger.WARN)
state = def_state
else:
state['system'] = def_state['system']
else:
state = def_state
m = _Merge(merge, state, path, log)
state_save = ini_version != m.state['system']['ini_version']
return m.state, m.state['system'][
'ini_version'] > ini_version, state_save or m.state_save
def build_student_dict(student_data, **kwargs):
# returns dict of student objs, complete with course work.
student_dict = {}
used_ids = set()
crs_type_look_up = utils.dict_from_file(
"/Users/thomasolson/Documents/workspace/advising_revamp/course_type_lookup.csv", 3, 4, "\n", ",", True)
for data in student_data:
data = sf_coder.translate_sfsu_data(data)
student_id = data[kwargs["student_id"]]
i = 0
if len(kwargs) < 3: #less than 3 means no special type.
course = Course(data[kwargs["class_int"]], int(data[kwargs["grade_int"]])*10, data[kwargs["year_int"]], 0,
0, 0)
else:
name_check = data[kwargs["crs_abbr"]]+str(data[kwargs["crs_num"]])
# if "CSC" not in name_check:
# if "CSC" not in name_check and "PHYS" not in name_check and "MATH" not in name_check:
# continue
course_id = student_id + str(i)
while course_id in used_ids:
i += 1
course_id = student_id + str(i)
used_ids.add(course_id)
course = Course(data[kwargs["crs_abbr"]] + str(data[kwargs["crs_num"]]), data[kwargs["grade_str"]],
int(data[kwargs["year_int"]]),int(data[kwargs["age"]]), int(data[kwargs["standing"]]),
course_id, student_id, float(data[kwargs["term_gpa"]]), float(data[kwargs["sfsu_gpa"]]),
crs_type_look_up[data[kwargs["crs_abbr"]]+str(data[kwargs["crs_num"]])],
data[kwargs["grad_flag"]], float(data[kwargs["term_units"]]),
float(data[kwargs["sfsu_units"]]), data[kwargs["spring_19_flag"]],
data[kwargs["crs_college_long"]], data[kwargs["crs_dept_long"]],
float(data[kwargs["total_units"]]))
add_to_student_obj(student_id, course, student_dict, data, kwargs)
return student_dict
def merge_1(self):
for key in ('backup', 'update'):
file_path = os.path.join(self.path['data'], key + '.json')
if os.path.isfile(file_path):
data = dict_from_file(file_path)
os.remove(file_path)
if data and isinstance(data, dict):
if key == 'update':
key = 'updater'
self.state[key] = data
def load_dict(self, name: str, format_='json') -> dict or None:
file_path = os.path.join(self.path['data'],
name + DATA_FORMATS.get(format_, '.json'))
if not os.path.isfile(file_path):
self.log(F('Файл не найден (это нормально): {}', file_path))
return None
try:
return utils.dict_from_file(file_path)
except RuntimeError as e:
self.log(F('Ошибка загрузки {}: {}', file_path, str(e)),
logger.ERROR)
return None
def score_series_set(path, outpath, add_412, add_211, class_type):
#score maps are built from sequence analysis and I have included examples of their format in git.
if class_type.lower() == "transfer":
seq_score_map = utils.dict_from_file("/Users/thomasolson/Documents/workspace/advising_revamp/group analysis runs/subset_transfer_sequence_score_map_25.csv",
0,1,"\n", ",", True)
equiv_score_map = utils.dict_from_file("/Users/thomasolson/Documents/workspace/advising_revamp/group analysis runs/subset_transfer_concurrent_score_map_25.csv",
0,1,"\n", ",", True)
elif class_type.lower() == "49_set":#This was some testing work I did
seq_score_map = utils.dict_from_file(
"/Users/thomasolson/Documents/workspace/advising_revamp/group analysis runs/49_cs_sequence_score_map_25.csv",
0, 1, "\n", ",", True)
equiv_score_map = utils.dict_from_file(
"/Users/thomasolson/Documents/workspace/advising_revamp/group analysis runs/49_cs_concurrent_score_map_25.csv",
0, 1, "\n", ",", True)
else:
seq_score_map = utils.dict_from_file(
"/Users/thomasolson/Documents/workspace/advising_revamp/group analysis runs/combo_score_seq_mod_bonus.csv",
0, 1, "\n", ",", True)
equiv_score_map = utils.dict_from_file(
"/Users/thomasolson/Documents/workspace/advising_revamp/group analysis runs/combo_score_equiv_mod_bonus.csv",
0, 1, "\n", ",", True)
i = 0
top_100 = []
with open(path, "r") as x:
data = x.readline()
while data:
if i % 10000 == 0:
print(i)
i+=1
#if "10_" in data or "9_" in data:
# data = x.readline()
# continue
line = data.strip().replace(" ", "").replace("[","").replace("]","").replace("'","").split(",")
if add_412 or add_211:
for sem_x in range(0,len(line)):
if "CSC340" in line[sem_x] and add_412:
sem = line[sem_x].split("_")[0]
line.insert(sem_x+1, sem+"_CSC412")
break
if "CSC210" in line[sem_x] and add_211:
sem = line[sem_x].split("_")[0]
line.insert(sem_x+1, sem+"_CSC211")
#if "PHYS220" in line[sem_x]: #Typically unneeded due to presence of PHYS230/222 scores that capture same info.
# sem = line[sem_x].split("_")[0]
# line.insert(sem_x+1, sem+"_PHYS222")
#if "PHYS230" in line[sem_x]:
# sem = line[sem_x].split("_")[0]
# line.insert(sem_x+1, sem+"_PHYS232")
score_line = []
for crs in line:
if crs.startswith("0"):
continue
score_line.append(crs)
sem_dict = build_seq_sem_dict(score_line)
score = score_seq(sem_dict, equiv_score_map, seq_score_map)
top_100 = update_top_100([score, score_line], top_100)
data = x.readline()
print(i)
if add_412:
split_path = outpath.split(".")
prefix = split_path[0]
split_path[0] = prefix + "_412add"
outpath = ".".join(split_path)
if add_211:
split_path = outpath.split(".")
prefix = split_path[0]
split_path[0] = prefix + "_211add"
outpath = ".".join(split_path)
utils.list_to_file(outpath, top_100)
def get_new_build_numbers(fn):
d = dict_from_file(fn)
return int(d['js']), int(d['css'])