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Running
on
Zero
Running
on
Zero
# -*- coding: UTF-8 -*- | |
import os, json,re,copy | |
import pandas as pd | |
current_file_path = os.path.dirname(os.path.abspath(__file__)) | |
TBL = pd.read_csv(os.path.join(current_file_path, "res/schools.csv"), sep="\t", header=0).fillna("") | |
TBL["name_en"] = TBL["name_en"].map(lambda x: x.lower().strip()) | |
GOOD_SCH = json.load(open(os.path.join(current_file_path, "res/good_sch.json"), "r")) | |
GOOD_SCH = set([re.sub(r"[,. &()()]+", "", c) for c in GOOD_SCH]) | |
def loadRank(fnm): | |
global TBL | |
TBL["rank"] = 1000000 | |
with open(fnm, "r",encoding='UTF-8') as f: | |
while True: | |
l = f.readline() | |
if not l:break | |
l = l.strip("\n").split(",") | |
try: | |
nm,rk = l[0].strip(),int(l[1]) | |
#assert len(TBL[((TBL.name_cn == nm) | (TBL.name_en == nm))]),f"<{nm}>" | |
TBL.loc[((TBL.name_cn == nm) | (TBL.name_en == nm)), "rank"] = rk | |
except Exception as e: | |
pass | |
loadRank(os.path.join(current_file_path, "res/school.rank.csv")) | |
def split(txt): | |
tks = [] | |
for t in re.sub(r"[ \t]+", " ",txt).split(" "): | |
if tks and re.match(r".*[a-zA-Z]$", tks[-1]) and \ | |
re.match(r"[a-zA-Z]", t) and tks: | |
tks[-1] = tks[-1] + " " + t | |
else:tks.append(t) | |
return tks | |
def select(nm): | |
global TBL | |
if not nm:return | |
if isinstance(nm, list):nm = str(nm[0]) | |
nm = split(nm)[0] | |
nm = str(nm).lower().strip() | |
nm = re.sub(r"[((][^()()]+[))]", "", nm.lower()) | |
nm = re.sub(r"(^the |[,.&()();;·]+|^(英国|美国|瑞士))", "", nm) | |
nm = re.sub(r"大学.*学院", "大学", nm) | |
tbl = copy.deepcopy(TBL) | |
tbl["hit_alias"] = tbl["alias"].map(lambda x:nm in set(x.split("+"))) | |
res = tbl[((tbl.name_cn == nm) | (tbl.name_en == nm) | (tbl.hit_alias == True))] | |
if res.empty:return | |
return json.loads(res.to_json(orient="records"))[0] | |
def is_good(nm): | |
global GOOD_SCH | |
nm = re.sub(r"[((][^()()]+[))]", "", nm.lower()) | |
nm = re.sub(r"[''`‘’“”,. &()();;]+", "", nm) | |
return nm in GOOD_SCH | |