Fix errors detected by Ruff (#3918)

### What problem does this PR solve?

Fix errors detected by Ruff

### Type of change

- [x] Refactoring

deepdoc/parser/resume/entities/corporations.py

@@ -21,13 +21,18 @@ from . import regions
 
 
 current_file_path = os.path.dirname(os.path.abspath(__file__))
-GOODS = pd.read_csv(os.path.join(current_file_path, "res/corp_baike_len.csv"), sep="\t", header=0).fillna(0)
+GOODS = pd.read_csv(
+    os.path.join(current_file_path, "res/corp_baike_len.csv"), sep="\t", header=0
+).fillna(0)
 GOODS["cid"] = GOODS["cid"].astype(str)
 GOODS = GOODS.set_index(["cid"])
-CORP_TKS = json.load(open(os.path.join(current_file_path, "res/corp.tks.freq.json"), "r"))
+CORP_TKS = json.load(
+    open(os.path.join(current_file_path, "res/corp.tks.freq.json"), "r")
+)
 GOOD_CORP = json.load(open(os.path.join(current_file_path, "res/good_corp.json"), "r"))
 CORP_TAG = json.load(open(os.path.join(current_file_path, "res/corp_tag.json"), "r"))
 
+
 def baike(cid, default_v=0):
     global GOODS
     try:
@@ -39,27 +44,41 @@ def baike(cid, default_v=0):
 
 def corpNorm(nm, add_region=True):
     global CORP_TKS
-    if not nm or type(nm)!=type(""):return ""
+    if not nm or isinstance(nm, str):
+        return ""
     nm = rag_tokenizer.tradi2simp(rag_tokenizer.strQ2B(nm)).lower()
     nm = re.sub(r"&", "&", nm)
     nm = re.sub(r"[\(\)（）\+'\"\t \*\\【】-]+", " ", nm)
-    nm = re.sub(r"([—-]+.*| +co\..*|corp\..*| +inc\..*| +ltd.*)", "", nm, 10000, re.IGNORECASE)
-    nm = re.sub(r"(计算机|技术|(技术|科技|网络)*有限公司|公司|有限|研发中心|中国|总部)$", "", nm, 10000, re.IGNORECASE)
-    if not nm or (len(nm)<5 and not regions.isName(nm[0:2])):return nm
+    nm = re.sub(
+        r"([—-]+.*| +co\..*|corp\..*| +inc\..*| +ltd.*)", "", nm, 10000, re.IGNORECASE
+    )
+    nm = re.sub(
+        r"(计算机|技术|(技术|科技|网络)*有限公司|公司|有限|研发中心|中国|总部)$",
+        "",
+        nm,
+        10000,
+        re.IGNORECASE,
+    )
+    if not nm or (len(nm) < 5 and not regions.isName(nm[0:2])):
+        return nm
 
     tks = rag_tokenizer.tokenize(nm).split()
-    reg = [t for i,t in enumerate(tks) if regions.isName(t) and (t != "中国" or i > 0)]
+    reg = [t for i, t in enumerate(tks) if regions.isName(t) and (t != "中国" or i > 0)]
     nm = ""
     for t in tks:
-        if regions.isName(t) or t in CORP_TKS:continue
-        if re.match(r"[0-9a-zA-Z\\,.]+", t) and re.match(r".*[0-9a-zA-Z\,.]+$", nm):nm += " "
+        if regions.isName(t) or t in CORP_TKS:
+            continue
+        if re.match(r"[0-9a-zA-Z\\,.]+", t) and re.match(r".*[0-9a-zA-Z\,.]+$", nm):
+            nm += " "
         nm += t
 
     r = re.search(r"^([^a-z0-9 \(\)&]{2,})[a-z ]{4,}$", nm.strip())
-    if r:nm = r.group(1)
+    if r:
+        nm = r.group(1)
     r = re.search(r"^([a-z ]{3,})[^a-z0-9 \(\)&]{2,}$", nm.strip())
-    if r:nm = r.group(1)
-    return nm.strip() + (("" if not reg else "(%s)"%reg[0]) if add_region else "")
+    if r:
+        nm = r.group(1)
+    return nm.strip() + (("" if not reg else "(%s)" % reg[0]) if add_region else "")
 
 
 def rmNoise(n):
@@ -67,33 +86,40 @@ def rmNoise(n):
     n = re.sub(r"[,. &（）()]+", "", n)
     return n
 
+
 GOOD_CORP = set([corpNorm(rmNoise(c), False) for c in GOOD_CORP])
-for c,v in CORP_TAG.items():
+for c, v in CORP_TAG.items():
     cc = corpNorm(rmNoise(c), False)
     if not cc:
         logging.debug(c)
-CORP_TAG = {corpNorm(rmNoise(c), False):v for c,v in CORP_TAG.items()}
+CORP_TAG = {corpNorm(rmNoise(c), False): v for c, v in CORP_TAG.items()}
+
 
 def is_good(nm):
     global GOOD_CORP
-    if nm.find("外派")>=0:return False
+    if nm.find("外派") >= 0:
+        return False
     nm = rmNoise(nm)
     nm = corpNorm(nm, False)
     for n in GOOD_CORP:
         if re.match(r"[0-9a-zA-Z]+$", n):
-            if n == nm: return True
-        elif nm.find(n)>=0:return True
+            if n == nm:
+                return True
+        elif nm.find(n) >= 0:
+            return True
     return False
 
+
 def corp_tag(nm):
     global CORP_TAG
     nm = rmNoise(nm)
     nm = corpNorm(nm, False)
     for n in CORP_TAG.keys():
         if re.match(r"[0-9a-zA-Z., ]+$", n):
-            if n == nm: return CORP_TAG[n]
-        elif nm.find(n)>=0:
-            if len(n)<3 and len(nm)/len(n)>=2:continue
+            if n == nm:
+                return CORP_TAG[n]
+        elif nm.find(n) >= 0:
+            if len(n) < 3 and len(nm) / len(n) >= 2:
+                continue
             return CORP_TAG[n]
     return []
-