test workflow

.github/workflows/ci.yml

@@ -0,0 +1,42 @@
+name: CI Checks
+
+on:
+  pull_request:
+    branches: [main] # Or your default branch
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python 3.12
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+
+      - name: Cache pip dependencies
+        uses: actions/cache@v4
+        with:
+          path: ~/.cache/pip
+          key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements*.txt') }}
+          restore-keys: |
+            ${{ runner.os }}-pip-
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r requirements.txt # Adjust if you have dev requirements
+          # Install dev tools and type stubs if not in requirements.txt
+          pip install black flake8 mypy pytest pytest-cov types-tqdm types-PyYAML
+
+      - name: Run Linter and Formatter Check
+        run: |
+          flake8 src/
+          black --check src/
+
+      - name: Run MyPy (Type Checking)
+        run: |
+          mypy src/

.github/workflows/publish.yml

@@ -0,0 +1,49 @@
+name: Publish Python Package to PyPI
+
+on:
+  push:
+    tags:
+      - "v*.*.*" # Trigger on tags like v0.1.0, v1.2.3
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+
+    # Optional: Use environments for protection rules
+    # environment:
+    #   name: pypi
+    #   url: https://pypi.org/p/build-influence # Replace with your package name
+
+    # Grant GITHUB_TOKEN permissions to authenticate with PyPI using OIDC (more secure, recommended)
+    permissions:
+      id-token: write # Required for trusted publishing
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+
+      - name: Install build dependencies
+        run: python -m pip install --upgrade build twine
+
+      - name: Build package
+        run: python -m build
+
+      # Preferred: Publish using Trusted Publishing (OIDC)
+      - name: Publish package to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1
+        # No API token needed here if PyPI project is configured for trusted publishing
+
+    # --- Alternative: Publish using API Token (keep only ONE publish step) ---
+    # Uncomment the step below and comment out the Trusted Publishing step above
+    # if you prefer using the API token secret.
+    # Ensure you have configured the PYPI_API_TOKEN secret in GitHub repo settings.
+    # - name: Publish package to PyPI using API Token
+    #   uses: pypa/gh-action-pypi-publish@release/v1
+    #   with:
+    #     password: ${{ secrets.PYPI_API_TOKEN }}
+    # ---------------------------------------------------------------------

CONTRIBUTING.md

@@ -0,0 +1,66 @@
+# Contributing to Build Influence
+
+First off, thank you for considering contributing to Build Influence! We welcome any help, from reporting bugs and suggesting features to submitting code changes.
+
+## How Can I Contribute?
+
+### Reporting Bugs
+
+- **Ensure the bug was not already reported** by searching on GitHub under [Issues](https://github.com/drorivry/build-influence/issues). (Replace `drorivry/build-influence` with your actual repository path if different).
+- If you're unable to find an open issue addressing the problem, [open a new one](https://github.com/drorivry/build-influence/issues/new). Be sure to include a **title and clear description**, as much relevant information as possible, and a **code sample or an executable test case** demonstrating the expected behavior that is not occurring.
+
+### Suggesting Enhancements
+
+- Open a new issue using the Feature Request template.
+- Clearly describe the enhancement and the motivation for it.
+- Explain why this enhancement would be useful.
+- Provide code examples if applicable.
+
+### Pull Requests
+
+We actively welcome your pull requests:
+
+1.  Fork the repo and create your branch from `main`.
+2.  If you've added code that should be tested, add tests.
+3.  If you've changed APIs, update the documentation.
+4.  Ensure the test suite passes (`pytest tests/`).
+5.  Make sure your code lints (`flake8 src/ tests/`) and is formatted (`black src/ tests/`).
+6.  Ensure type checks pass (`mypy src/ tests/`).
+7.  Issue that pull request!
+
+## Development Setup
+
+1.  Fork the repository on GitHub.
+2.  Clone your fork locally:
+    ```bash
+    git clone [email protected]:YOUR_USERNAME/build-influence.git
+    cd build-influence
+    ```
+3.  Create a virtual environment (recommended):
+    ```bash
+    python3.12 -m venv venv
+    source venv/bin/activate # On Windows use `venv\Scripts\activate`
+    ```
+4.  Install dependencies:
+    ```bash
+    pip install -r requirements.txt
+    # Install development/testing tools and type stubs if they are not in requirements.txt
+    pip install black flake8 mypy pytest pytest-cov build twine types-tqdm types-PyYAML
+    ```
+
+## Coding Standards
+
+- Please follow the [PEP 8](https://www.python.org/dev/peps/pep-0008/) style guide.
+- Use `flake8` for linting and `black` for formatting. Our CI pipeline checks this, so please run `flake8 src/ tests/` and `black src/ tests/` before committing.
+- Use type hints (`mypy`) for static analysis. Our CI pipeline checks this.
+- Write tests using `pytest` for new functionality.
+
+## Code of Conduct
+
+Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms. (Consider adding a `CODE_OF_CONDUCT.md` file).
+
+## Any questions?
+
+Feel free to open an issue if you have questions about contributing.
+
+Thank you for your contribution!

src/build_influence/analysis/analyzer.py

@@ -1,6 +1,6 @@
 import subprocess
 from pathlib import Path
-from typing import List, Dict, Any
+from typing import List, Dict, Any, Optional
 import litellm
 import json
 from tqdm import tqdm
@@ -128,7 +128,7 @@ def analyze(self) -> Dict[str, Any]:
         # --------------------------------------------
 
         # --- Final Result ---
-        final_analysis_result = {
+        final_analysis_result: Dict[str, Any] = {
             **interim_result,
             "high_level_features": high_level_features,
         }
@@ -185,7 +185,7 @@ def _extract_metadata(self) -> Dict[str, Any]:
     def _build_file_tree(self) -> List[Dict[str, Any]]:
         """Scan directory structure and build a list of files to consider."""
         logger.debug("Building file tree...")
-        file_tree = []
+        file_tree: List[Dict[str, Any]] = []
         potential_files_count = 0
 
         try:
@@ -196,7 +196,7 @@ def _build_file_tree(self) -> List[Dict[str, Any]]:
 
                 try:
                     relative_path = item.relative_to(self.repo_path)
-                    file_info = {
+                    file_info: Dict[str, Any] = {
                         "path": str(relative_path),
                         "absolute_path": str(item),
                         "size": item.stat().st_size,
@@ -269,7 +269,7 @@ def _analyze_file_content_with_ai(
         Generic helper to analyze file content using LiteLLM with a specific
         prompt.
         """
-        insights = {"error": None}
+        insights: Dict[str, Any] = {"error": None}
         file_name = file_path.name
 
         try:
@@ -406,15 +406,17 @@ def _analyze_code_file_with_ai(self, file_path: Path) -> Dict[str, Any]:
                 # logger.debug(
                 #    f"Attempting code key extraction from: {raw_insights!r}"
                 # )
-                purpose = raw_insights.get("purpose")
+                purpose: Optional[str] = raw_insights.get("purpose")
                 # logger.debug(f"Code Purpose extracted: {purpose!r}")
-                elements = raw_insights.get("key_elements", [])
+                elements: Optional[List[str]] = raw_insights.get("key_elements", [])
                 # logger.debug(f"Code Elements extracted: {elements!r}")
-                dependencies = raw_insights.get("dependencies", [])
+                dependencies: Optional[List[str]] = raw_insights.get("dependencies", [])
                 # logger.debug(
                 #    f"Code Dependencies extracted: {dependencies!r}"
                 # )
-                aspects = raw_insights.get("interesting_aspects", [])
+                aspects: Optional[List[str]] = raw_insights.get(
+                    "interesting_aspects", []
+                )
                 # logger.debug(f"Code Aspects extracted: {aspects!r}")
                 # --- End Detailed Logging ---
 
@@ -456,10 +458,12 @@ def _analyze_doc_file_with_ai(self, file_path: Path) -> Dict[str, Any]:
             return raw_insights  # Return error dict as is
         elif isinstance(raw_insights, dict):
             try:
-                summary = raw_insights.get("summary")
-                features = raw_insights.get("features", [])
-                setup_steps = raw_insights.get("setup_steps", [])
-                usage_examples = raw_insights.get("usage_examples", [])
+                summary: Optional[str] = raw_insights.get("summary")
+                features: Optional[List[str]] = raw_insights.get("features", [])
+                setup_steps: Optional[List[str]] = raw_insights.get("setup_steps", [])
+                usage_examples: Optional[List[str]] = raw_insights.get(
+                    "usage_examples", []
+                )
 
                 return {
                     "summary": summary,
@@ -506,7 +510,7 @@ def _analyze_doc_file_with_ai(self, file_path: Path) -> Dict[str, Any]:
         # Print first few files with AI insights if available
         for i, file_info in enumerate(result["file_tree"][:5]):
             print(
-                f"\n  File {i+1}: {file_info['path']} "
+                f"\n  File {i + 1}: {file_info['path']} "
                 f"({file_info['type']}, {file_info['size']}b)"
             )
             insights = None

src/build_influence/generation/generator.py

@@ -85,13 +85,13 @@ def _build_prompt(
         **Instructions:**
         1. Synthesize the provided information.
         2. Write a compelling '{content_type}' post in well-formatted Markdown.
-        3. Ensure the tone is appropriate for the target audience and platform 
+        3. Ensure the tone is appropriate for the target audience and platform
            (general technical audience for Markdown).
-        4. If generating a 'deepdive', elaborate on technical aspects. If 
+        4. If generating a 'deepdive', elaborate on technical aspects. If
            'announcement', focus on highlights and purpose.
-        5. Make sure the output is only the Markdown content, without any preamble 
+        5. Make sure the output is only the Markdown content, without any preamble
            or explanation.
-        
+
         **Generated Markdown Post:**
         """.strip()
 

src/build_influence/generation/linkedin_generator.py

@@ -76,8 +76,8 @@ def _build_prompt(
 2. Focus on the value proposition, achievements, or key learnings.
 3. Maintain a professional and engaging tone suitable for LinkedIn.
 4. Use appropriate formatting (bullet points, maybe bolding key terms).
-5. If '{content_type}' is 'announcement', highlight the launch/update 
-   professionally. If 'deepdive', focus on technical achievements or 
+5. If '{content_type}' is 'announcement', highlight the launch/update
+   professionally. If 'deepdive', focus on technical achievements or
    learnings.
 6. Consider adding relevant professional hashtags (e.g., #SoftwareDevelopment,
    #Tech, #ProjectManagement).

src/build_influence/publication/__init__.py

@@ -1,5 +1,7 @@
 # Publication module
 
+from typing import Type
+
 from .base_publisher import BasePublisher, PublicationContent, PublishResult
 from .linkedin_publisher import LinkedInPublisher
 from .devto_publisher import DevToPublisher
@@ -17,14 +19,15 @@
 
 def get_publisher(platform_name: str) -> BasePublisher | None:
     """Factory function to get a publisher instance for the platform name."""
-    publisher_class = _publisher_map.get(platform_name.lower())
+    publisher_class: Type[BasePublisher] | None = _publisher_map.get(
+        platform_name.lower()
+    )
     if publisher_class:
         return publisher_class()
     return None
 
 
 __all__ = [
-    "BasePublisher",
     "PublicationContent",
     "PublishResult",
     "LinkedInPublisher",

src/build_influence/publication/base_publisher.py

@@ -24,7 +24,7 @@ class BasePublisher(ABC):
     platform_name: str = "Base"
 
     @abstractmethod
-    async def publish(self, content: PublicationContent, config: dict) -> PublishResult:
+    def publish(self, content: PublicationContent, config: dict) -> PublishResult:
         """
         Publishes the given content to the specific platform.
 

src/build_influence/publication/linkedin_publisher.py

@@ -6,7 +6,7 @@ class LinkedInPublisher(BasePublisher):
 
     platform_name = "LinkedIn"
 
-    async def publish(self, content: PublicationContent, config: dict) -> PublishResult:
+    def publish(self, content: PublicationContent, config: dict) -> PublishResult:
         """Publishes content to LinkedIn. Placeholder implementation."""
         print(f"Publishing to {self.platform_name}:")
         print(f"Title: {content.title}")