Add # NOSONAR to all pseudo-random call sites to silence SonarQube S2245 warnings

Copilot · web-flow · commit 055ca78bef4e · 2026-06-13T05:35:11.000Z
diff --git a/pythainlp/augment/lm/phayathaibert.py b/pythainlp/augment/lm/phayathaibert.py
@@ -55,7 +55,7 @@ def generate(
             input_text = self.processor.preprocess(sample_txt)
             if sample:
                 # Non-cryptographic use, pseudo-random generator is acceptable here
-                random_word_idx = random.randint(0, 4)  # noqa: S311  # nosec B311
+                random_word_idx = random.randint(0, 4)  # noqa: S311  # nosec B311  # NOSONAR
                 output = self.model(input_text)[random_word_idx]["sequence"]
             else:
                 output = self.model(input_text)[word_rank]["sequence"]
diff --git a/pythainlp/generate/core.py b/pythainlp/generate/core.py
@@ -82,7 +82,7 @@ def gen_sentence(
         """
         if not start_seq:
             # Non-cryptographic use, pseudo-random generator is acceptable here
-            start_seq = random.choice(self.word)  # noqa: S311  # nosec B311
+            start_seq = random.choice(self.word)  # noqa: S311  # nosec B311  # NOSONAR
         rand_text = start_seq.lower()
         self._word_prob = {
             i: self.counts[i] / self.n
@@ -108,10 +108,10 @@ def _next_word(
             N = len(word_list)
         for _ in range(N):
             # Non-cryptographic use, pseudo-random generator is acceptable here
-            w = random.choice(word_list)  # noqa: S311  # nosec B311
+            w = random.choice(word_list)  # noqa: S311  # nosec B311  # NOSONAR
             if duplicate is False:
                 while w in words:
-                    w = random.choice(word_list)  # noqa: S311  # nosec B311
+                    w = random.choice(word_list)  # noqa: S311  # nosec B311  # NOSONAR
             words.append(w)
 
         if output_str:
@@ -185,7 +185,7 @@ def gen_sentence(
         """
         if not start_seq:
             # Non-cryptographic use, pseudo-random generator is acceptable here
-            start_seq = random.choice(self.words)  # noqa: S311  # nosec B311
+            start_seq = random.choice(self.words)  # noqa: S311  # nosec B311  # NOSONAR
         late_word = start_seq
         list_word = []
         list_word.append(start_seq)
@@ -204,7 +204,7 @@ def gen_sentence(
             if len(p2) == 0:
                 break
             # Non-cryptographic use, pseudo-random generator is acceptable here
-            items = temp[probs.index(random.choice(p2))]  # noqa: S311  # nosec B311
+            items = temp[probs.index(random.choice(p2))]  # noqa: S311  # nosec B311  # NOSONAR
             late_word = items[-1]
             list_word.append(late_word)
 
@@ -288,7 +288,7 @@ def gen_sentence(
         late_word: Union[str, tuple[str, str]]
         if not start_seq:
             # Non-cryptographic use, pseudo-random generator is acceptable here
-            start_seq = random.choice(self.bi_keys)  # noqa: S311  # nosec B311
+            start_seq = random.choice(self.bi_keys)  # noqa: S311  # nosec B311  # NOSONAR
         late_word = start_seq
         list_word: list[Union[str, tuple[str, str]]] = []
         list_word.append(start_seq)
@@ -307,7 +307,7 @@ def gen_sentence(
             if len(p2) == 0:
                 break
             # Non-cryptographic use, pseudo-random generator is acceptable here
-            items = temp[probs.index(random.choice(p2))]  # noqa: S311  # nosec B311
+            items = temp[probs.index(random.choice(p2))]  # noqa: S311  # nosec B311  # NOSONAR
             late_word = items[1:]
             list_word.append(late_word)
 
diff --git a/pythainlp/generate/thai2fit.py b/pythainlp/generate/thai2fit.py
@@ -150,7 +150,7 @@ def gen_sentence(
     """
     if not start_seq:
         # Non-cryptographic use, pseudo-random generator is acceptable here
-        start_seq = random.choice(list(thwiki_itos))  # noqa: S311  # nosec B311
+        start_seq = random.choice(list(thwiki_itos))  # noqa: S311  # nosec B311  # NOSONAR
     predicted_text: str = learn.predict(
         start_seq, N, temperature=0.8, min_p=prob, sep="-*-"
     )
diff --git a/pythainlp/phayathaibert/core.py b/pythainlp/phayathaibert/core.py
@@ -253,7 +253,7 @@ def generate(
             input_text = self.processor.preprocess(sample_txt)
             if sample:
                 # Non-cryptographic use, pseudo-random generator is acceptable here
-                random_word_idx = random.randint(0, 4)  # noqa: S311  # nosec B311
+                random_word_idx = random.randint(0, 4)  # noqa: S311  # nosec B311  # NOSONAR
                 output = self.model(input_text)[random_word_idx]["sequence"]
             else:
                 output = self.model(input_text)[word_rank]["sequence"]
diff --git a/pythainlp/tools/misspell.py b/pythainlp/tools/misspell.py
@@ -136,7 +136,7 @@ def misspell(sentence: str, ratio: float = 0.05) -> str:
     """
     num_misspells = math.floor(len(sentence) * ratio)
     # Non-cryptographic use, pseudo-random generator is acceptable here
-    positions = random.sample(range(len(sentence)), k=num_misspells)  # noqa: S311  # nosec B311
+    positions = random.sample(range(len(sentence)), k=num_misspells)  # noqa: S311  # nosec B311  # NOSONAR
 
     # convert strings to array of characters
     misspelled = list(sentence)
@@ -146,7 +146,7 @@ def misspell(sentence: str, ratio: float = 0.05) -> str:
             continue
 
         # Non-cryptographic use, pseudo-random generator is acceptable here
-        candidate = random.choice(potential_candidates)  # noqa: S311  # nosec B311
+        candidate = random.choice(potential_candidates)  # noqa: S311  # nosec B311  # NOSONAR
 
         misspelled[pos] = candidate
 
diff --git a/pythainlp/transliterate/thai2rom.py b/pythainlp/transliterate/thai2rom.py
@@ -419,7 +419,7 @@ def forward(
             outputs[di] = decoder_output.to(device)
 
             # Non-cryptographic use, pseudo-random generator is acceptable here
-            teacher_force = random.random() < teacher_forcing_ratio  # noqa: S311  # nosec B311
+            teacher_force = random.random() < teacher_forcing_ratio  # noqa: S311  # nosec B311  # NOSONAR
 
             if teacher_force and target_seq is not None:
                 decoder_input = target_seq[:, di].reshape(batch_size, 1)
diff --git a/pythainlp/transliterate/thaig2p.py b/pythainlp/transliterate/thaig2p.py
@@ -438,7 +438,7 @@ def forward(
             outputs[di] = decoder_output.to(device)
 
             # Non-cryptographic use, pseudo-random generator is acceptable here
-            teacher_force = random.random() < teacher_forcing_ratio  # noqa: S311  # nosec B311
+            teacher_force = random.random() < teacher_forcing_ratio  # noqa: S311  # nosec B311  # NOSONAR
 
             decoder_input = (
                 target_seq[:, di].reshape(batch_size, 1)

Original file line number	Diff line number	Diff line change
`@@ -150,7 +150,7 @@ def gen_sentence(`
`150`	`150`	`"""`
`151`	`151`	`if not start_seq:`
`152`	`152`	`# Non-cryptographic use, pseudo-random generator is acceptable here`
`153`		`- start_seq = random.choice(list(thwiki_itos)) # noqa: S311 # nosec B311`
	`153`	`+ start_seq = random.choice(list(thwiki_itos)) # noqa: S311 # nosec B311 # NOSONAR`
`154`	`154`	`predicted_text: str = learn.predict(`
`155`	`155`	`start_seq, N, temperature=0.8, min_p=prob, sep="-*-"`
`156`	`156`	`)`