lint fixes

.github/workflows/test.yml

@@ -52,4 +52,3 @@ jobs:
         uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
-        shell: bash

Makefile

@@ -29,7 +29,7 @@ lint_diff: PYTHON_FILES=$(shell git diff --name-only --diff-filter=d master | gr
 
 lint lint_diff:
 	poetry run mypy $(PYTHON_FILES)
-	poetry run black $(PYTHON_FILES) --check
+	poetry run ruff format
 	poetry run ruff .
 
 TEST_FILE ?= tests/

pyproject.toml

@@ -25,6 +25,19 @@ pytest = "^8.3.4"
 pytest-asyncio = "^0.25.0"
 pytest-cov = "^6.0.0"
 mypy = "^1.14.0"
+poetry-types = "^0.6.0"
+
+[tool.poetry.group.lint.dependencies]
+black = "^23.7.0"
+mypy = "^1.5.1"
+ruff = "^0.0.286"
+types-chardet = "^5.0.4.6"
+poetry-types = "^0.6.0"
+
+
+[tool.poetry.group.types.dependencies]
+types-beautifulsoup4 = "^4.12.0.20241020"
+
 
 [build-system]
 requires = ["poetry-core"]

tests/test_db.py

@@ -1,6 +1,5 @@
 import pytest
 import sqlite3
-import json
 from yaart.db import JobDatabase
 from yaart.models import JobDescription, JobRequirements
 

tests/test_llm.py

@@ -1,10 +1,7 @@
 import pytest
 from unittest.mock import Mock, patch, MagicMock
 from yaart.llm import ResumeAssistant
-from yaart.models import JobDescription, JobRequirements, TailoredResume
-from langchain.schema import HumanMessage, AIMessage
-from langchain_core.outputs import LLMResult
-from langchain.schema.runnable import RunnableParallel
+from yaart.models import JobDescription, JobRequirements
 from langchain.output_parsers import PydanticOutputParser
 import json
 
@@ -139,7 +136,11 @@ def test_parse_jd_invalid_response(mock_llm):
 
 @patch('yaart.llm.PydanticOutputParser')
 @patch('yaart.llm.PromptTemplate')
-def test_tailor_resume_success(mock_prompt, mock_parser, mock_llm, sample_job_description, sample_tailored_resume_dict):
+def test_tailor_resume_success(mock_prompt, 
+                               mock_parser, 
+                               mock_llm, 
+                               sample_job_description, 
+                               sample_tailored_resume_dict):
     mock_tailored_resume = MagicMock()
     mock_tailored_resume.to_markdown.return_value = "# Tailored Resume"
     mock_tailored_resume.model_dump.return_value = sample_tailored_resume_dict

tests/test_models.py

@@ -1,4 +1,3 @@
-import pytest
 from yaart.models import (
     JobRequirements,
     JobDescription,

tests/test_resume_optimizer.py

@@ -1,7 +1,6 @@
 import pytest
 from pathlib import Path
-import json
-from unittest.mock import Mock, patch, AsyncMock, MagicMock
+from unittest.mock import patch, AsyncMock, MagicMock
 from yaart.optimizer import ResumeOptimizer
 from yaart.models import JobDescription, JobRequirements
 from yaart.scraper import JobScraper
@@ -30,7 +29,7 @@ def mock_optimizer():
     with patch('yaart.optimizer.ResumeAssistant') as mock_assistant, \
          patch('yaart.optimizer.JobScraper') as mock_scraper, \
          patch('yaart.optimizer.JobDatabase') as mock_db, \
-         patch('yaart.optimizer.md2pdf') as mock_md2pdf:
+         patch('yaart.optimizer.md2pdf'):
 
         optimizer = ResumeOptimizer(api_key="test-key")
         optimizer.assistant = mock_assistant
@@ -132,7 +131,8 @@ def test_generate_documents_pdf_error(mock_optimizer, tmp_path):
     markdown_dir.mkdir()
     pdf_dir.mkdir()
 
-    with patch('yaart.optimizer.md2pdf', side_effect=Exception("PDF generation failed")):
+    with patch('yaart.optimizer.md2pdf', 
+               side_effect=Exception("PDF generation failed")):
         with pytest.raises(ValueError) as exc_info:
             mock_optimizer.generate_documents(
                 "# Test Resume",
@@ -143,7 +143,9 @@ def test_generate_documents_pdf_error(mock_optimizer, tmp_path):
     assert "Failed to generate PDF" in str(exc_info.value)
 
 @pytest.mark.asyncio
-async def test_optimize_resume_tailor_error(mock_optimizer, mock_job_description, tmp_path):
+async def test_optimize_resume_tailor_error(mock_optimizer, 
+                                            mock_job_description, 
+                                            tmp_path):
     base_resume = tmp_path / "base_resume.md"
     base_resume.write_text("# Test Resume")
 
@@ -167,7 +169,8 @@ async def test_optimize_resume_tailor_error(mock_optimizer, mock_job_description
 @pytest.mark.asyncio
 async def test_get_job_description_from_scraper(mock_optimizer, mock_job_description):
     mock_optimizer.db.get_job_description.return_value = None
-    mock_optimizer.scraper.scrape_job_description = AsyncMock(return_value=mock_job_description)
+    mock_optimizer.scraper.scrape_job_description = AsyncMock(
+        return_value=mock_job_description)
 
     result = await mock_optimizer.get_job_description("https://example.com/job")
 
@@ -193,7 +196,9 @@ def test_generate_documents(mock_optimizer, tmp_path):
     assert markdown_path.read_text() == "# Test Resume"
 
 @pytest.mark.asyncio
-async def test_optimize_resume_with_new_jd(mock_optimizer, mock_job_description, tmp_path):
+async def test_optimize_resume_with_new_jd(mock_optimizer, 
+                                           mock_job_description, 
+                                           tmp_path):
     base_resume = tmp_path / "base_resume.md"
     base_resume.write_text("# Test Resume")
 
@@ -203,7 +208,8 @@ async def test_optimize_resume_with_new_jd(mock_optimizer, mock_job_description,
     (output_dir / "PDF").mkdir()
 
     mock_optimizer.db.get_job_description.side_effect = [None, mock_job_description]
-    mock_optimizer.scraper.scrape_job_description = AsyncMock(return_value=mock_job_description)
+    mock_optimizer.scraper.scrape_job_description = AsyncMock(
+        return_value=mock_job_description)
     mock_optimizer.assistant.tailor_resume.return_value = "# Tailored Resume"
 
     result = await mock_optimizer.optimize_resume(

tests/test_scraper.py

@@ -87,7 +87,8 @@ async def test_scrape_job_description_html_parsing(mock_assistant):
 async def test_scrape_job_description_http_error(mock_assistant):
     # Setup mock client to raise HTTPError
     mock_client = AsyncMock()
-    mock_client.__aenter__.return_value.get.side_effect = httpx.HTTPError("Failed to fetch")
+    mock_client.__aenter__.return_value.get.side_effect = httpx.HTTPError(
+        "Failed to fetch")
 
     # Create scraper instance
     scraper = JobScraper(assistant=mock_assistant)

yaart/llm.py

@@ -1,14 +1,16 @@
-from typing import Dict, Optional
+from typing import Optional
 from langchain.output_parsers import PydanticOutputParser
 from langchain.prompts import PromptTemplate
 from langchain_openai import ChatOpenAI
 from langchain.base_language import BaseLanguageModel
+from pydantic import SecretStr
 from yaart.models import JobDescription, TailoredResume
 from yaart.prompts import PARSE_JD_PROMPT, TAILOR_RESUME_PROMPT
 import json
 
 class ResumeAssistant:
-    def __init__(self, llm: Optional[BaseLanguageModel] = None, api_key: Optional[str] = None):
+    def __init__(self, llm: Optional[BaseLanguageModel] = None, 
+                 api_key: Optional[SecretStr] = None):
         if llm:
             self.llm = llm
         elif api_key:
@@ -23,7 +25,9 @@ def parse_jd(self, text: str, url: str) -> JobDescription:
         prompt = PromptTemplate(
             template=PARSE_JD_PROMPT,
             input_variables=["text"],
-            partial_variables={"format_instructions": self.jd_parser.get_format_instructions()}
+            partial_variables={
+                "format_instructions": self.jd_parser.get_format_instructions()
+                }
         )
 
         try:
@@ -38,12 +42,15 @@ def parse_jd(self, text: str, url: str) -> JobDescription:
         except Exception as e:
             raise ValueError(f"Failed to parse job description: {str(e)}")
 
-    def tailor_resume(self, resume_content: str, job_description: JobDescription) -> str:
+    def tailor_resume(self, resume_content: str, 
+                      job_description: JobDescription) -> str:
         """Tailor resume content to match job description"""
         prompt = PromptTemplate(
             template=TAILOR_RESUME_PROMPT,
             input_variables=["resume", "job_description"],
-            partial_variables={"format_instructions": self.resume_parser.get_format_instructions()}
+            partial_variables={
+                "format_instructions": self.resume_parser.get_format_instructions()
+                }
         )
 
         try: