start = time.time()
try:
conn = utils.persist.connection()
cur = conn.cursor()
sql = 'select description, position_name from company where type != "None"'
cur.execute(sql)
rst = cur.fetchall()
transformer = TfidfTransformer()
vectorizer = CountVectorizer()
stopf = open('stopword', 'r')
stopwords = pickle.load(stopf)
train_data = []
for rs in rst:
desc = utils.discrement_unicode(rs[0])
segs = jieba.cut(desc, cut_all=False)
wordss = []
for seg in segs:
if not stopwords.has_key(seg.lower()):
wordss.append(seg.lower())
segs = jieba.cut(utils.discrement_unicode(rs[1]), cut_all=False)
for seg in segs:
if not stopwords.has_key(seg.lower()):
for i in range(5):
wordss.append(seg.lower())
train_data.append(' '.join(wordss))
tfidf = transformer.fit_transform(vectorizer.fit_transform(train_data))
try:
conn = utils.persist.connection()
cur = conn.cursor()
resume_id = '12227125-2'
sql = 'select resumekeywords, dessalary, latestmajor, latestcollege,\
latestdegree, workyear, latestcompany, latesttitle from profile where \
resume_id = "%s"' % resume_id
cur.execute(sql)
rst = cur.fetchall()
for rs in rst:
for tem in rs:
print utils.discrement_unicode(tem)
sql = 'select unit_name, start_time, end_time, position_name, description from work where\
resume_id = "%s"' % resume_id
cur.execute(sql)
rst = cur.fetchall()
for rs in rst:
for tem in rs:
print utils.discrement_unicode(tem)
conn.close()
except:
traceback.print_exc()
conn.close()
topic_words = pickle.load(topic_word)
topicsx = []
topicsy = []
type_dct = {}
type_dct_r = {}
num = 0
for rs in rst:
if not type_dct.has_key(rs[1].lower()):
type_dct[rs[1].lower()] = num
type_dct_r[num] = rs[1].lower()
num += 1
for rs in rst:
desc = rs[0]
segs = jieba.cut(utils.discrement_unicode(desc), cut_all=False)
tpwords = copy.deepcopy(topic_words)
for seg in segs:
if tpwords.has_key(seg.lower()):
tpwords[seg.lower()] += 1
tpwordl = []
topicsy.append(type_dct[rs[1].lower()])
for key in sorted(tpwords.keys()):
tpwordl.append(tpwords[key])
topicsx.append(tpwordl)
pdb.set_trace()
x = np.array(topicsx)
cur.execute(sql)
stopf = open('stopword', 'rb')
stopword = pickle.load(stopf)
topics = []
topic_words = {}
rst = cur.fetchall()
for rs in rst:
desc = rs[0]
pname = rs[1]
ptype = rs[2]
topics.append(ptype)
topic_word = []
segs = jieba.cut(utils.discrement_unicode(desc))
for seg in segs:
if stopword.has_key(seg):
continue
if not topic_words.has_key(seg.lower()):
topic_words[seg.lower()] = 0
pdb.set_trace()
# print topic_words
for word in topic_words:
print word
topic_word = open('topic_word', 'wb')
pickle.dump(topic_words, topic_word)
except:
traceback.print_exc()
cur.execute(sql)
rst = cur.fetchall()
# pdb.set_trace()
for rs in rst:
print rs[2]
if rs[1] == '[]' or not rs[1]:
continue
# rsff3 = rs[1].replace(u'\u201c', '"')
# rsff2 = rsff3.replace('\n', '')
# rsff3 = utils.discrement_unicode(rs[1])
# pdb.set_trace()
rsff3 = rs[1].replace('\n', '')
rsff3 = rsff3.replace(u'\u201c', '"')
rsff3 = rsff3.replace(u'\u2018', '')
rsff3 = utils.discrement_unicode(rsff3)
rsff2 = utils.convert_code(rsff3)
rsff = eval(rsff2)
# pdb.set_trace()
for rsf in rsff:
for key in rsf.keys():
rsf[key.decode('utf8')] = rsf[key].decode('utf8')
# rsf.pop(key)
for rsf in rsff:
sql = 'insert into projects(name, start, end, description, resume_id, software,\
hardware, developtool, dudescription) values("%s", "%s", "%s", "%s", "%s", "%s",\
"%s", "%s", "%s")' % (rsf.get('name', ''), rsf.get('start_time', ''), rsf.get('end_time', ''),\
rsf.get(u'项目描述', ''), rs[0], rsf.get(u'软件环境', ''), rsf.get(u'硬件环境', ''), \
rsf.get(u'开发工具', ''), rsf.get(u'责任描述', ''))
cur.execute(sql)
rst = cur.fetchall()
# topic_word = open('topic_word', 'r')
topic_word = open('tfidfwords', 'r')
topic_words = pickle.load(topic_word)
topicsx = []
topicsy = []
type_dct = {}
type_dct_r = {}
train_data = []
train_tags = []
for rs in rst:
desc = rs[0]
segs = jieba.cut(utils.discrement_unicode(desc).lower(), cut_all=False)
tpword = copy.deepcopy(topic_words)
train_words = []
for seg in segs:
if tpword.has_key(seg.lower()):
tpword[seg.lower()] += 1
segs = jieba.cut(utils.discrement_unicode(rs[2]).lower(),
cut_all=False)
for seg in segs:
if tpword.has_key(seg.lower()):
tpword[seg.lower()] += 1
# pdb.set_trace()
# for key in sorted(tpword.keys()):
for key in tpword.keys():
train_words.append(tpword[key])
def generate_test_feature(cur, pos_id, resume_id):
sql = 'select position_id, low_income, description, low_workage, position_name,\
workage, degree from companytest where position_id = %d' % pos_id
cur.execute(sql)
rst = cur.fetchall()
for term in rst:
com_low_income = term[1]
pro_low_income = 0
com_position = utils.discrement_unicode(term[4])
com_workage = term[5]
com_degree = term[6]
pro_position = ''
com_description = utils.discrement_unicode(term[2])
pro_decription = ''
pro_hisprojects = ''
pro_otherinfo = ''
com_lst = []
if com_low_income < 500 and com_low_income > 0:
com_low_income = (com_low_income * 8000) / 12
com_low_income = com_low_income / 5000
low_workage = term[5]
if not low_workage:
low_workage = 0
com_lst.append(low_workage)
com_workage = term[5]
com_degree = term[6]
keywords = get_keywords(utils.discrement_unicode(term[2]))
com_description = utils.discrement_unicode(term[2])
try:
sqlp = 'select dessalary, skills, destitle, hisprojects, otherinfo, resume_id, workyear, latestdegree \
from profiletest where resume_id = "%s" limit 5' % (
resume_id)
cur.execute(sqlp)
profile = cur.fetchall()
except:
pdb.set_trace()
for pro in profile:
if not pro[0]:
incomes = salaryp.search('0')
else:
incomes = salaryp.search(pro[0])
try:
if not resume_id:
continue
pos_sql = 'select position_name from worktest where resume_id = "%s" order by end_time desc' % resume_id
cur.execute(pos_sql)
pos_rst = cur.fetchall()
pro_position = pos_rst[0][0]
except:
pro_position = pro[2]
if incomes:
low_income = incomes.group(0)
else:
low_income = 0
pro_low_income = int(low_income) / 5000
pro_hisprojects = utils.discrement_unicode(pro[3])
pro_otherinfo = utils.discrement_unicode(pro[4])
pro_skills = utils.discrement_unicode(pro[1])
try:
sql_work = 'select description from worktest where resume_id = "%s"' % resume_id
except:
traceback.print_exc()
pdb.set_trace()
cur.execute(sql_work)
pro_decription = cur.fetchall()
position_feature = get_position_feature(com_position, pro_position)
com_feature = []
descrip_feature = get_description_feature(com_description, pro_hisprojects, \
pro_decription, pro_otherinfo, pro_skills)
com_feature.append(com_low_income)
com_feature.append(pro_low_income)
pro_workage = pro[6]
workage = salaryp.search(pro_workage)
if workage:
pro_workage = int(workage.group(0))
else:
pro_workage = 0
pro_degree = pro[7]
if '科' in pro_degree or '学' in pro_degree:
pro_degree = 1
elif '硕' in pro_degree or '士' in pro_degree:
pro_degree = 2
else:
pro_degree = 0
com_feature.append(com_workage)
com_feature.append(pro_workage - com_workage)
com_feature.append(com_degree)
com_feature.append(pro_degree - com_degree)
com_feature.append(round(position_feature, 3))
com_feature += descrip_feature
return com_feature
def generate_test_feature(cur, pos_id, resume_id):
sql = 'select position_id, low_income, description, low_workage, position_name,\
workage, degree from companytest where position_id = %d' % pos_id
cur.execute(sql)
rst = cur.fetchall()
for term in rst:
com_low_income = term[1]
pro_low_income = 0
com_position = utils.discrement_unicode(term[4])
com_workage = term[5]
com_degree = term[6]
pro_position = ''
com_description = utils.discrement_unicode(term[2])
pro_decription = ''
pro_hisprojects = ''
pro_otherinfo = ''
com_lst = []
if com_low_income < 500 and com_low_income > 0:
com_low_income = (com_low_income * 8000) / 12
com_low_income = com_low_income / 5000
low_workage = term[5]
if not low_workage:
low_workage = 0
com_lst.append(low_workage)
com_workage = term[5]
com_degree = term[6]
keywords = get_keywords( utils.discrement_unicode(term[2]))
com_description = utils.discrement_unicode(term[2])
try:
sqlp = 'select dessalary, skills, destitle, hisprojects, otherinfo, resume_id, workyear, latestdegree \
from profiletest where resume_id = "%s" limit 5' % (resume_id)
cur.execute(sqlp)
profile = cur.fetchall()
except:
pdb.set_trace()
for pro in profile:
if not pro[0]:
incomes = salaryp.search('0')
else:
incomes = salaryp.search(pro[0])
try:
if not resume_id:
continue
pos_sql = 'select position_name from worktest where resume_id = "%s" order by end_time desc' % resume_id
cur.execute(pos_sql)
pos_rst = cur.fetchall()
pro_position = pos_rst[0][0]
except:
pro_position = pro[2]
if incomes:
low_income = incomes.group(0)
else:
low_income = 0
pro_low_income = int(low_income) / 5000
pro_hisprojects = utils.discrement_unicode(pro[3])
pro_otherinfo = utils.discrement_unicode(pro[4])
pro_skills = utils.discrement_unicode(pro[1])
try:
sql_work = 'select description from worktest where resume_id = "%s"' % resume_id
except:
traceback.print_exc()
pdb.set_trace()
cur.execute(sql_work)
pro_decription = cur.fetchall()
position_feature = get_position_feature(com_position, pro_position)
com_feature = []
descrip_feature = get_description_feature(com_description, pro_hisprojects, \
pro_decription, pro_otherinfo, pro_skills)
com_feature.append(com_low_income)
com_feature.append(pro_low_income)
pro_workage = pro[6]
workage = salaryp.search(pro_workage)
if workage:
pro_workage = int(workage.group(0))
else:
pro_workage = 0
pro_degree = pro[7]
if '科' in pro_degree or '学' in pro_degree:
pro_degree = 1
elif '硕' in pro_degree or '士' in pro_degree:
pro_degree = 2
else:
pro_degree = 0
com_feature.append(com_workage)
com_feature.append(pro_workage - com_workage)
com_feature.append(com_degree)
com_feature.append(pro_degree - com_degree)
com_feature.append(round(position_feature, 3))
com_feature += descrip_feature
return com_feature
try:
conn = utils.persist.connection()
cur = conn.cursor()
# sql = 'select low_income, high_income, low_workage, high_workage, description, \
# position_name, naren_created from company where id > %d' % 459
sql = "select id, description from company where id > %d " % 624
cur.execute(sql)
rst = cur.fetchall()
pdb.set_trace()
for rs in rst:
# print utils.discrement_unicode(rs[1])
print rs[0]
try:
usql = """update company set description = "%s" where id = %d""" % (utils.discrement_unicode(rs[1]), rs[0])
cur.execute(usql)
except:
pdb.set_trace()
traceback.print_exc()
conn.commit()
conn.close()
except:
traceback.print_exc()
pdb.set_trace()
conn.close()
lu = time.time()
print lu - start
topic_words = pickle.load(topic_word)
topicsx = []
topicsy = []
type_dct = {}
type_dct_r = {}
num = 0
for rs in rst:
if not type_dct.has_key(rs[1].lower()):
type_dct[rs[1].lower()] = num
type_dct_r[num] = rs[1].lower()
num += 1
for rs in rst:
desc = rs[0]
segs = jieba.cut(utils.discrement_unicode(desc), cut_all=False)
tpwords = copy.deepcopy(topic_words)
for seg in segs:
if tpwords.has_key(seg.lower()):
tpwords[seg.lower()] += 1
tpwordl = []
topicsy.append(type_dct[rs[1].lower()])
for key in sorted(tpwords.keys()):
tpwordl.append(tpwords[key])
topicsx.append(tpwordl)
pdb.set_trace()
x = np.array(topicsx)
def get_feature(cur, feature_lines, flag, pos_id):
if not pos_id:
sql = 'select position_id, low_income, description, low_workage, position_name,\
workage, degree from company'
else:
sql = 'select position_id, low_income, description, low_workage, position_name,\
workage, degree from company where position_id = %d' % pos_id
cur.execute(sql)
rst = cur.fetchall()
nummn = 0
for term in rst:
com_low_income = term[1]
pro_low_income = 0
com_position = utils.discrement_unicode(term[4])
pro_position = ''
com_description = utils.discrement_unicode(term[2])
pro_decription = ''
pro_hisprojects = ''
pro_otherinfo = ''
com_lst = []
if com_low_income < 500 and com_low_income > 0:
com_low_income = (com_low_income * 8000) / 12
com_low_income = com_low_income / 5000
low_workage = term[5]
if not low_workage:
low_workage = 0
com_lst.append(low_workage)
com_workage = term[5]
com_degree = term[6]
keywords = get_keywords(utils.discrement_unicode(term[2]))
com_description = utils.discrement_unicode(term[2])
try:
sqlp = 'select dessalary, skills, latesttitle, hisprojects, otherinfo, pf.resume_id, workyear, latestdegree, \
pr.pos_id, pr.resume_id from pos_resume as pr left join profile as pf on pr.resume_id = pf.resume_id \
where pr.train_flag = 0 and pr.pos_id = %d and pr.hr_confirm = %d' % (term[0], flag)
cur.execute(sqlp)
profile = cur.fetchall()
except:
pdb.set_trace()
for pro in profile:
nummn += 1
print nummn
if not pro[0]:
incomes = salaryp.search('0')
else:
incomes = salaryp.search(pro[0])
try:
resume_id = pro[5]
if not resume_id:
continue
pos_sql = 'select position_name from work where resume_id = %d order by end_time desc' % resume_id
cur.execute(pos_sql)
pos_rst = cur.fetchall()
pro_position = utils.discrement_unicode(pos_rst[0][0])
except:
pro_position = utils.discrement_unicode(pro[2])
if incomes:
low_income = incomes.group(0)
else:
low_income = 0
pro_low_income = int(low_income) / 5000
pro_hisprojects = utils.discrement_unicode(pro[3])
pro_otherinfo = utils.discrement_unicode(pro[4])
pro_skills = utils.discrement_unicode(pro[1])
try:
sql_work = 'select description from work where resume_id = "%s"' % resume_id
except:
traceback.print_exc()
pdb.set_trace()
cur.execute(sql_work)
pro_decription = cur.fetchall()
position_feature = get_position_feature(com_position, pro_position)
com_feature = []
descrip_feature = get_description_feature(com_description, pro_hisprojects, \
pro_decription, pro_otherinfo, pro_skills)
com_feature.append(com_low_income)
com_feature.append(pro_low_income)
pro_workage = pro[6]
workage = salaryp.search(pro_workage)
if workage:
pro_workage = int(workage.group(0))
else:
pro_workage = 0
pro_degree = utils.discrement_unicode(pro[7])
if '科' in pro_degree or '学' in pro_degree:
pro_degree = 1
elif '硕' in pro_degree or '士' in pro_degree:
pro_degree = 2
else:
pro_degree = 0
com_feature.append(com_workage)
com_feature.append(pro_workage - com_workage)
com_feature.append(com_degree)
com_feature.append(pro_degree - com_degree)
com_feature.append(round(position_feature, 3))
com_feature += descrip_feature
# pdb.set_trace()
feature = utils.get_work_feature(cur, resume_id)
com_feature = com_feature + feature
com_feature.append(flag)
feature_lines.append(','.join(map(lambda x: str(x), com_feature)))
rst = cur.fetchall()
# topic_word = open('topic_word', 'r')
topic_word = open('tfidfwords', 'r')
topic_words = pickle.load(topic_word)
topicsx = []
topicsy = []
type_dct = {}
type_dct_r = {}
train_data = []
train_tags = []
for rs in rst:
desc = rs[0]
segs = jieba.cut(utils.discrement_unicode(desc).lower(), cut_all=False)
tpword = copy.deepcopy(topic_words)
train_words = []
for seg in segs:
if tpword.has_key(seg.lower()):
tpword[seg.lower()] += 1
segs = jieba.cut(utils.discrement_unicode(rs[2]).lower(), cut_all=False)
for seg in segs:
if tpword.has_key(seg.lower()):
tpword[seg.lower()] += 1
# pdb.set_trace()
# for key in sorted(tpword.keys()):
for key in tpword.keys():
train_words.append(tpword[key])
start = time.time()
try:
conn = utils.persist.connection()
cur = conn.cursor()
sql = 'select description, position_name from company where type != "None"'
cur.execute(sql)
rst = cur.fetchall()
transformer=TfidfTransformer()
vectorizer=CountVectorizer()
stopf = open('stopword', 'r')
stopwords = pickle.load(stopf)
train_data = []
for rs in rst:
desc = utils.discrement_unicode(rs[0])
segs = jieba.cut(desc, cut_all=False)
wordss = []
for seg in segs:
if not stopwords.has_key(seg.lower()):
wordss.append(seg.lower())
segs = jieba.cut(utils.discrement_unicode(rs[1]), cut_all=False)
for seg in segs:
if not stopwords.has_key(seg.lower()):
for i in range(5):
wordss.append(seg.lower())
train_data.append(' '.join(wordss))
tfidf=transformer.fit_transform(vectorizer.fit_transform(train_data))
try:
conn = utils.persist.connection()
cur = conn.cursor()
# sql = 'select low_income, high_income, low_workage, high_workage, description, \
# position_name, naren_created from company where id > %d' % 459
sql = 'select id, description from company where id > %d ' % 624
cur.execute(sql)
rst = cur.fetchall()
pdb.set_trace()
for rs in rst:
# print utils.discrement_unicode(rs[1])
print rs[0]
try:
usql = '''update company set description = "%s" where id = %d''' % (
utils.discrement_unicode(rs[1]), rs[0])
cur.execute(usql)
except:
pdb.set_trace()
traceback.print_exc()
conn.commit()
conn.close()
except:
traceback.print_exc()
pdb.set_trace()
conn.close()
lu = time.time()
print lu - start
sql = 'select description, type from company where type != "None"'
cur.execute(sql)
rst = cur.fetchall()
topic_word = open('topic_word', 'r')
topic_words = pickle.load(topic_word)
topicsx = []
topicsy = []
type_dct = {}
type_dct_r = {}
train_words = []
train_tags = []
for rs in rst:
desc = rs[0]
train_words.append(utils.discrement_unicode(desc))
train_tags.append(utils.discrement_unicode(rs[1]))
pdb.set_trace()
train_data = vectorize(train_words)
clf = MultinomialNB(alpha=0.01)
clf.fit(train_data, train_tags)
sqll = 'select description, position_name, id from company where type = "None"'
cur.execute(sqll)
rst = cur.fetchall()
test_words = []
pdb.set_trace()
for rs in rst:
def get_feature(cur, feature_lines, flag):
sql = 'select position_id, low_income, description, low_workage, position_name,\
workage, degree from company'
cur.execute(sql)
rst = cur.fetchall()
nummn = 0
for term in rst:
com_low_income = term[1]
pro_low_income = 0
com_position = utils.discrement_unicode(term[4])
pro_position = ''
com_description = utils.discrement_unicode(term[2])
pro_decription = ''
pro_hisprojects = ''
pro_otherinfo = ''
com_lst = []
if com_low_income < 500 and com_low_income > 0:
com_low_income = (com_low_income * 8000) / 12
com_low_income = com_low_income / 5000
low_workage = term[5]
if not low_workage:
low_workage = 0
com_lst.append(low_workage)
com_workage = term[5]
com_degree = term[6]
keywords = get_keywords(utils.discrement_unicode(term[2]))
com_description = utils.discrement_unicode(term[2])
try:
sqlp = 'select dessalary, skills, latesttitle, hisprojects, otherinfo, pf.resume_id, workyear, latestdegree, \
pr.pos_id, pr.resume_id from pos_resume as pr left join profile as pf on pr.resume_id = pf.resume_id \
where pr.train_flag = 0 and pr.pos_id = %d and pr.hr_confirm = %d limit 5' % (
term[0], flag)
cur.execute(sqlp)
profile = cur.fetchall()
except:
pdb.set_trace()
for pro in profile:
nummn += 1
print nummn
if not pro[0]:
incomes = salaryp.search('0')
else:
incomes = salaryp.search(pro[0])
try:
resume_id = pro[5]
if not resume_id:
continue
pos_sql = 'select position_name from work where resume_id = %d order by end_time desc' % resume_id
cur.execute(pos_sql)
pos_rst = cur.fetchall()
pro_position = utils.discrement_unicode(pos_rst[0][0])
except:
pro_position = utils.discrement_unicode(pro[2])
if incomes:
low_income = incomes.group(0)
else:
low_income = 0
pro_low_income = int(low_income) / 5000
pro_hisprojects = utils.discrement_unicode(pro[3])
pro_otherinfo = utils.discrement_unicode(pro[4])
pro_skills = utils.discrement_unicode(pro[1])
try:
sql_work = 'select description from work where resume_id = "%s"' % resume_id
except:
traceback.print_exc()
pdb.set_trace()
cur.execute(sql_work)
pro_decription = cur.fetchall()
position_feature = get_position_feature(com_position, pro_position)
com_feature = []
descrip_feature = get_description_feature(com_description, pro_hisprojects, \
pro_decription, pro_otherinfo, pro_skills)
com_feature.append(com_low_income)
com_feature.append(pro_low_income)
pro_workage = pro[6]
workage = salaryp.search(pro_workage)
if workage:
pro_workage = int(workage.group(0))
else:
pro_workage = 0
pro_degree = utils.discrement_unicode(pro[7])
if '科' in pro_degree or '学' in pro_degree:
pro_degree = 1
elif '硕' in pro_degree or '士' in pro_degree:
pro_degree = 2
else:
pro_degree = 0
com_feature.append(com_workage)
com_feature.append(pro_workage - com_workage)
com_feature.append(com_degree)
com_feature.append(pro_degree - com_degree)
com_feature.append(round(position_feature, 3))
com_feature += descrip_feature
com_feature.append(flag)
feature_lines.append(','.join(map(lambda x: str(x), com_feature)))
set_train_flg(cur, term[0], resume_id)
sql = 'select description, type from company where type != "None"'
cur.execute(sql)
rst = cur.fetchall()
topic_word = open('topic_word', 'r')
topic_words = pickle.load(topic_word)
topicsx = []
topicsy = []
type_dct = {}
type_dct_r = {}
train_words = []
train_tags = []
for rs in rst:
desc = rs[0]
train_words.append(utils.discrement_unicode(desc))
train_tags.append(utils.discrement_unicode(rs[1]))
pdb.set_trace()
train_data = vectorize(train_words)
clf = MultinomialNB(alpha=0.01)
clf.fit(train_data, train_tags)
sqll = 'select description, position_name, id from company where type = "None"'
cur.execute(sqll)
rst = cur.fetchall()
test_words = []
pdb.set_trace()
for rs in rst:
cur.execute(sql)
rst = cur.fetchall()
# pdb.set_trace()
for rs in rst:
print rs[2]
if rs[1] == '[]' or not rs[1]:
continue
# rsff3 = rs[1].replace(u'\u201c', '"')
# rsff2 = rsff3.replace('\n', '')
# rsff3 = utils.discrement_unicode(rs[1])
# pdb.set_trace()
rsff3 = rs[1].replace('\n', '')
rsff3 = rsff3.replace(u'\u201c', '"')
rsff3 = rsff3.replace(u'\u2018', '')
rsff3 = utils.discrement_unicode(rsff3)
rsff2 = utils.convert_code(rsff3)
rsff = eval(rsff2)
# pdb.set_trace()
for rsf in rsff:
for key in rsf.keys():
rsf[key.decode('utf8')] = rsf[key].decode('utf8')
# rsf.pop(key)
for rsf in rsff:
sql = 'insert into projects(name, start, end, description, resume_id, software,\
hardware, developtool, dudescription) values("%s", "%s", "%s", "%s", "%s", "%s",\
"%s", "%s", "%s")' % (rsf.get('name', ''), rsf.get('start_time', ''), rsf.get('end_time', ''),\
rsf.get(u'项目描述', ''), rs[0], rsf.get(u'软件环境', ''), rsf.get(u'硬件环境', ''), \
rsf.get(u'开发工具', ''), rsf.get(u'责任描述', ''))
cur.execute(sql)
