def p_name_def_array(p):
''' array_def : ID '[' INTEGER ']' '''
global local_symbol_table
a = symbol()
a.var_name = p[1]
is_duplicate(a.var_name)
a.var_type = scanner.last_type_met
a.var_is_ptr = True
local_symbol_table[a.var_name] = a
p[0] = '%s=[]' % (a.var_name)
def p_para_item(p):
'''para_item : TYPE ID
| TYPE '*' ID '''
a = symbol()
a.var_type = p[1]
a.var_name = p[2] if len(p) == 3 else p[3]
a.var_is_ptr = len(p) > 3 #如果包含*则为指针类型
#参数列表中的元素插入符号表中
is_duplicate(a.var_name)
local_symbol_table[a.var_name] = a
p[0] = a
def p_init_expr_str(p):
'''init_expr : '*' ID '=' STRING '''
is_duplicate(p[2])
if not scanner.last_type_met == "char":
raise Exception("strings shall only be used with char type")
p[0] = "%s=%s" % (p[2], p[4])
a = symbol()
a.var_name = p[2]
a.var_type = 'char'
a.var_is_ptr = True
global local_symbol_table
local_symbol_table[a.var_name] = a
def p_name_def(p):
''' name_def : ID
| '*' ID'''
global local_symbol_table
#检查变量定义是否重复
a = symbol()
a.var_name = p[1] if len(p) == 2 else p[2]
is_duplicate(a.var_name)
a.var_type = scanner.last_type_met
a.var_is_ptr = len(p) == 3
local_symbol_table[a.var_name] = a
p[0] = a.var_name
def get_characters():
# open the excel file
file = open("pickles/dictionary-n.xlsx", 'rb')
wb = pyxl.load_workbook(file)
ws = wb.active
# store characters and words
words = []
characters = []
characters_dict = {}
symbols = []
symbols_dict = {}
lines = []
for row in ws.iter_rows():
if "BCI-AV#" not in str(row[0].value) and row[0].value is not None:
lines.append((row[0].value, str(row[2].value), str(row[3].value)))
#print(lines[-1])
# for row in ws.iter_rows():
# if "BCI-AV#" not in str(row[0].value) and row[0].value is not None:
# if str(row[2].value) is not "":
# lines.append((row[0].value, str(row[1].value), str(row[2].value)))
# else:
# lines.append((row[0].value, str(row[1].value), str(row[3].value)))
#print(lines[-1])
# create dicts
num_to_def_dict = {}
for line in lines:
words_non_filtered = str(line[1]).split(',')
words_filtered = []
# print(words_non_filtered)
for word in words_non_filtered:
regex = re.compile(".*?\((.*?)\)")
remove_string = re.findall(regex, word)
if len(remove_string) > 0:
word = word.replace(remove_string[0], '')
word = word.replace('(', '')
word = word.replace(')', '')
if len(word) > 0 and word[-1] is '_':
word_list = list(word)
word_list[-1] = ''
word = "".join(word_list[:-1])
word = word.replace('_', ' ')
words_filtered.append(word)
# print(words_filtered)
num_to_def_dict[line[0]] = ()
# "BCI-AV#"
# for i in range(1000, 1005):
# print(lines[i])
#
# print(lines[-1])
id_to_words_dict = {}
for line in lines:
id_to_words_dict[line[0]] = line[1]
def_dict = {}
id_to_character_dict = {}
for line in lines:
def_dict[line[0]] = line[2]
composition = ""
# assume it is a word, unless it expresses that it is a character
is_character = False
# get the description/composition
if " - Character" in str(line[2]):
id_to_character_dict[line[0]] = [line[1], line[2]]
is_character = True
if "+" in str(line[2]):
regex = re.compile(r"\(.+\)")
composition = str(re.findall(regex,
str(line[2]).replace('\n', '')))
composition = composition.replace('(', '')
composition = composition.replace(')', '')
composition = composition.replace('\'', '')
composition = composition.replace('"', '')
# composition = composition.replace('_', ' ')
# remove [ first bracket
composition = composition[1:-1]
#print("Comp: ", composition)
regex_2 = re.compile(r":.*")
remove_string = re.findall(regex_2, str(composition))
while len(remove_string) > 0:
for i in range(len(remove_string)):
composition = composition.replace(remove_string[0], '')
remove_string = re.findall(regex_2, composition)
# print("parts removed: ", remove_string[0])
regex_2 = re.compile(r": .*")
remove_string = re.findall(regex_2, str(composition))
while len(remove_string) > 0:
for i in range(len(remove_string)):
composition = composition.replace(remove_string[i], '')
remove_string = re.findall(regex_2, composition)
#print("parts removed: ", remove_string[0])
while ',' in composition:
regex = re.compile(r"(,\w*_*\w*)*")
remove_string = re.findall(regex, composition)
for i in range(len(remove_string)):
composition = composition.replace(remove_string[i], '')
#print("remove string:", remove_string)
regex = re.compile(r"\[[^\+]*\]")
remove_string = re.findall(regex, composition)
reg2 = re.compile(r"\-.*[cC]haracter.*")
remove = re.findall(reg2, composition)
while len(remove_string) > 0:
for i in range(len(remove_string)):
composition = composition.replace(remove_string[i], '')
remove_string = re.findall(regex, composition)
while len(remove) > 0:
for i in range(len(remove)):
composition = composition.replace(remove[i], '')
remove = re.findall(reg2, composition)
print("Comp: ", composition)
# print("final string: ", composition)
# print("part 1: ", line[0], '\n', "part 2: ", line[1], '\n', "part 3: ", line[2], '\n')
# if composition == "":
# print('wtf', line[0], line[1], line[2])
# print(line[0], ": ", composition, " ; ", line)
if (is_character):
t_is_word = not is_character
t_char = symbol(line[1], composition.split(" + "), line[0],
t_is_word)
characters.append(t_char)
characters_dict[t_char.id] = t_char
sym = symbol(line[1], composition.split(" + "), line[0],
not is_character)
symbols.append(sym)
symbols_dict[sym.id] = sym
#print(len(id_to_character_dict.keys()))
pickle.dump(id_to_character_dict, open("bliss_chars.p", 'wb'))
word_to_id_dict = {}
ambiguous_words = {}
for key in id_to_words_dict.keys():
words = str(id_to_words_dict[key]).split(',')
for word in words:
if word in word_to_id_dict.keys():
# add it to the ambigous words dictionary
if word in ambiguous_words.keys():
ambiguous_words[word].append(key)
else:
ambiguous_words[word] = [key]
ambiguous_words[word].append(word_to_id_dict[word][0])
word_to_id_dict[word].append(key)
#print(word, " ", word_to_id_dict[word])
else:
word_to_id_dict[word] = [key]
#print(len(word_to_id_dict.keys()))
pickle.dump(word_to_id_dict, open("word_to_char_id.p", "wb"))
pickle.dump(characters, open(CHARS_LIST_NAME, 'wb'))
pickle.dump(symbols, open(SYMBOLS_LIST_NAME, 'wb'))
pickle.dump(symbols_dict, open(SYMBOL_DICT_NAME, 'wb'))
pickle.dump(id_to_words_dict, open("id_to_words.p", 'wb'))