fix all quality/typing issues

Author: DaltheCow

README.md

@@ -160,6 +160,7 @@ GuideLLM UI is a companion frontend for visualizing the results of a GuideLLM be
 ### 🛠 Generating an HTML report with a benchmark run
 
 Set the output to benchmarks.html for your run:
+
 ```base
 --output-path=benchmarks.html
 ```

pyproject.toml

@@ -53,10 +53,10 @@ dependencies = [
     "protobuf",
     "pydantic>=2.0.0",
     "pydantic-settings>=2.0.0",
+    "pyhumps>=3.8.0",
     "pyyaml>=6.0.0",
     "rich",
     "transformers",
-    "pyhumps>=3.8.0",
 ]
 
 [project.optional-dependencies]

src/guidellm/benchmark/output.py

@@ -6,7 +6,7 @@
 from pathlib import Path
 from typing import Any, Literal, Optional, Union
 
-import humps
+import humps  # type: ignore[import-not-found]
 import yaml
 from pydantic import Field
 from rich.console import Console
@@ -236,14 +236,15 @@ def save_html(self, path: Union[str, Path]) -> Path:
         :param path: The path to create the report at.
         :return: The path to the report.
         """
-        from guidellm.presentation import UIDataBuilder
+
         data_builder = UIDataBuilder(self.benchmarks)
         data = data_builder.to_dict()
         camel_data = humps.camelize(data)
-        ui_api_data = {
-            f"window.{humps.decamelize(k)} = {{}};": f"window.{humps.decamelize(k)} = {json.dumps(v, indent=2)};\n"
-            for k, v in camel_data.items()
-        }
+        ui_api_data = {}
+        for k, v in camel_data.items():
+            key = f"window.{humps.decamelize(k)} = {{}};"
+            value = f"window.{humps.decamelize(k)} = {json.dumps(v, indent=2)};\n"
+            ui_api_data[key] = value
         return create_report(ui_api_data, path)
 
     @staticmethod

src/guidellm/presentation/builder.py

@@ -1,10 +1,11 @@
-from typing import Any, TYPE_CHECKING
+from typing import TYPE_CHECKING, Any
 
 if TYPE_CHECKING:
     from guidellm.benchmark.benchmark import GenerativeBenchmark
 
 from .data_models import BenchmarkDatum, RunInfo, WorkloadDetails
 
+
 class UIDataBuilder:
     def __init__(self, benchmarks: list["GenerativeBenchmark"]):
         self.benchmarks = benchmarks

src/guidellm/presentation/data_models.py

@@ -1,25 +1,26 @@
 import random
 from collections import defaultdict
 from math import ceil
-from typing import List, Optional, Tuple, TYPE_CHECKING, Union
+from typing import TYPE_CHECKING, Optional, Union
 
-from pydantic import BaseModel, computed_field
+from pydantic import BaseModel
 
 if TYPE_CHECKING:
     from guidellm.benchmark.benchmark import GenerativeBenchmark
 
 from guidellm.objects.statistics import DistributionSummary
 
+
 class Bucket(BaseModel):
     value: Union[float, int]
     count: int
 
     @staticmethod
     def from_data(
-        data: Union[List[float], List[int]],
+        data: Union[list[float], list[int]],
         bucket_width: Optional[float] = None,
         n_buckets: Optional[int] = None,
-    ) -> Tuple[List["Bucket"], float]:
+    ) -> tuple[list["Bucket"], float]:
         if not data:
             return [], 1.0
 
@@ -125,10 +126,14 @@ def from_benchmarks(cls, benchmarks: list["GenerativeBenchmark"]):
         ]
 
         prompt_tokens = [
-            float(req.prompt_tokens) for bm in benchmarks for req in bm.requests.successful
+            float(req.prompt_tokens)
+            for bm in benchmarks
+            for req in bm.requests.successful
         ]
         output_tokens = [
-            float(req.output_tokens) for bm in benchmarks for req in bm.requests.successful
+            float(req.output_tokens)
+            for bm in benchmarks
+            for req in bm.requests.successful
         ]
 
         prompt_token_buckets, _prompt_token_bucket_width = Bucket.from_data(
@@ -190,10 +195,9 @@ def percentile_rows(self) -> list[dict[str, float]]:
             {"percentile": name, "value": value}
             for name, value in self.percentiles.model_dump().items()
         ]
-        filtered_rows = list(
+        return list(
             filter(lambda row: row["percentile"] in ["p50", "p90", "p95", "p99"], rows)
         )
-        return filtered_rows
 
     @classmethod
     def from_distribution_summary(

src/guidellm/presentation/injector.py

@@ -37,7 +37,8 @@ def inject_data(
     html: str,
 ) -> str:
     """
-    Injects the json data into the HTML, replacing placeholders only within the <head> section.
+    Injects the json data into the HTML,
+    replacing placeholders only within the <head> section.
 
     :param js_data: the json data to inject
     :type js_data: dict
@@ -58,6 +59,4 @@ def inject_data(
 
     # Rebuild the HTML
     new_head = f"<head>{head_content}</head>"
-    html = html[: head_match.start()] + new_head + html[head_match.end() :]
-
-    return html
+    return html[: head_match.start()] + new_head + html[head_match.end() :]

tests/unit/presentation/__init__.py

@@ -15,8 +15,16 @@ class ExampleModel(BaseModel):
 @pytest.mark.smoke
 def test_inject_data():
     html = "<head><script>window.run_info = {};</script></head>"
-    expected_html = '<head><script>window.run_info = { \"model\": { \"name\": \"neuralmagic/Qwen2.5-7B-quantized.w8a8\" } };</script></head>'
-    js_data = { "window.run_info = {};": "window.run_info = { \"model\": { \"name\": \"neuralmagic/Qwen2.5-7B-quantized.w8a8\" } };" }
+    expected_html = (
+        "<head><script>"
+        "window.run_info ="
+        '{ "model": { "name": "neuralmagic/Qwen2.5-7B-quantized.w8a8" } };'
+        "</script></head>"
+    )
+    js_data = {
+        "window.run_info = {};": "window.run_info ="
+        '{ "model": { "name": "neuralmagic/Qwen2.5-7B-quantized.w8a8" } };'
+    }
     result = inject_data(
         js_data,
         html,
@@ -26,9 +34,17 @@ def test_inject_data():
 
 @pytest.mark.smoke
 def test_create_report_to_file(tmpdir):
-    js_data = { "window.run_info = {};": "window.run_info = { \"model\": { \"name\": \"neuralmagic/Qwen2.5-7B-quantized.w8a8\" } };" }
+    js_data = {
+        "window.run_info = {};": "window.run_info ="
+        '{ "model": { "name": "neuralmagic/Qwen2.5-7B-quantized.w8a8" } };'
+    }
     html_content = "<head><script>window.run_info = {};</script></head>"
-    expected_html_content = '<head><script>window.run_info = { \"model\": { \"name\": \"neuralmagic/Qwen2.5-7B-quantized.w8a8\" } };</script></head>'
+    expected_html_content = (
+        "<head><script>"
+        "window.run_info ="
+        '{ "model": { "name": "neuralmagic/Qwen2.5-7B-quantized.w8a8" } };'
+        "</script></head>"
+    )
 
     mock_html_path = tmpdir.join("template.html")
     mock_html_path.write(html_content)
@@ -44,9 +60,17 @@ def test_create_report_to_file(tmpdir):
 
 @pytest.mark.smoke
 def test_create_report_with_file_nested_in_dir(tmpdir):
-    js_data = { "window.run_info = {};": "window.run_info = { \"model\": { \"name\": \"neuralmagic/Qwen2.5-7B-quantized.w8a8\" } };" }
+    js_data = {
+        "window.run_info = {};": "window.run_info ="
+        '{ "model": { "name": "neuralmagic/Qwen2.5-7B-quantized.w8a8" } };'
+    }
     html_content = "<head><script>window.run_info = {};</script></head>"
-    expected_html_content = '<head><script>window.run_info = { \"model\": { \"name\": \"neuralmagic/Qwen2.5-7B-quantized.w8a8\" } };</script></head>'
+    expected_html_content = (
+        "<head><script>"
+        "window.run_info ="
+        '{ "model": { "name": "neuralmagic/Qwen2.5-7B-quantized.w8a8" } };'
+        "</script></head>"
+    )
 
     output_dir = tmpdir.mkdir("output_dir")
     mock_html_path = tmpdir.join("template.html")

tests/unit/presentation/test_injector.py

@@ -49,10 +49,7 @@ def test_settings_from_env_variables(mocker):
 @pytest.mark.smoke
 def test_report_generation_default_source():
     settings = Settings(env=Environment.LOCAL)
-    assert (
-        settings.report_generation.source
-        == "http://localhost:3000/index.html"
-    )
+    assert settings.report_generation.source == "http://localhost:3000/index.html"
 
     settings = Settings(env=Environment.DEV)
     assert (