diff --git a/.dockerignore b/.dockerignore index 07143dc..26ad490 100644 --- a/.dockerignore +++ b/.dockerignore @@ -1,61 +1,108 @@ -# Git +# Include any files or directories that you don't want to be copied to your +# container here (e.g., local build artifacts, temporary files, etc.). +# +# For more help, visit the .dockerignore file reference guide at +# https://docs.docker.com/go/build-context-dockerignore/ + +**/.DS_Store +**/__pycache__ +**/.venv +**/.classpath +**/.dockerignore +**/.env +**/.git +**/.gitignore +**/.project +**/.settings +**/.toolstarget +**/.vs +**/.vscode +**/*.*proj.user +**/*.dbmdl +**/*.jfm +**/bin +**/charts +**/docker-compose* +**/compose.y*ml +**/Dockerfile* +**/node_modules +**/npm-debug.log +**/obj +**/secrets.dev.yaml +**/values.dev.yaml +LICENSE +README.md .git .gitignore - -# Python -__pycache__ -*.pyc -*.pyo -*.pyd -.Python -env -venv -pip-log.txt -pip-delete-this-directory.txt -.tox -.coverage -.coverage.* -.cache -nosetests.xml -coverage.xml -*.cover +.venv/ +__pycache__/ *.log +.python-version +data/ + + +# Python-generated files +__pycache__/ .mypy_cache -.pytest_cache -.hypothesis +.ruff_cache +*.py[cod] +*$py.class +*.so +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +*.egg-info/ +.installed.cfg +*.egg -# Environments +# Environment variables .env .venv -env/ venv/ +env/ ENV/ -# IDEs -.vscode -.idea +# IDEs and editors +.idea/ +.vscode/ +*.swp +*.swo +*~ -# OS generated files +# Operating System Files .DS_Store -.DS_Store? -._* -.Spotlight-V100 -.Trashes -ehthumbs.db Thumbs.db -# Project specific -tests/ -*.md -LICENSE -.github/ -docker-compose.yml - -# DuckDB -*.duckdb - # Jupyter Notebook .ipynb_checkpoints +# pytest +.pytest_cache/ + +# Coverage reports +htmlcov/ +.coverage +.coverage.* +.cache + +# Logs +*.log + # uv specific -.uv/ \ No newline at end of file +.uv/ + +# DuckDB +*.duckdb + +# Scratch Pad +scratch.py \ No newline at end of file diff --git a/.github/workflows/ci_cd.yml b/.github/workflows/ci_cd.yml index e69de29..6e59c68 100644 --- a/.github/workflows/ci_cd.yml +++ b/.github/workflows/ci_cd.yml @@ -0,0 +1,34 @@ +name: CI/CD Pipeline + +on: + pull_request: + branches: + - main + +jobs: + ci: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Build and Check (using multi-stage Dockerfile) + run: make docker-check-ci + + cd: + needs: ci + if: github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Build prod image + run: make docker-build-prod + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKERHUB_USERNAME }} + password: ${{ secrets.DOCKERHUB_TOKEN }} + + - name: Push prod image + run: make docker-push \ No newline at end of file diff --git a/.gitignore b/.gitignore index de64abe..4144a1e 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,7 @@ # Python-generated files __pycache__/ +.mypy_cache +.ruff_cache *.py[cod] *$py.class *.so @@ -57,4 +59,7 @@ htmlcov/ .uv/ # DuckDB -*.duckdb \ No newline at end of file +*.duckdb + +# Scratch Pad +scratch.py \ No newline at end of file diff --git a/.streamlit/config.toml b/.streamlit/config.toml new file mode 100644 index 0000000..80a2030 --- /dev/null +++ b/.streamlit/config.toml @@ -0,0 +1,6 @@ +[theme] +base="dark" +backgroundColor="#F5F5F5" +secondaryBackgroundColor="#F0F2F6" +textColor="#333333" +font="sans serif" \ No newline at end of file diff --git a/Dockerfile b/Dockerfile index e69de29..02b6498 100644 --- a/Dockerfile +++ b/Dockerfile @@ -0,0 +1,67 @@ +# ------------------------------- Builder Satge ------------------------------- + + # Build stage (with dev tools for linting, testing, etc.) +FROM python:3.13-slim-bookworm AS builder + +# The installer requires curl (and certificates) to download the release archive +RUN apt-get update && apt-get install -y --no-install-recommends curl ca-certificates && \ + apt-get clean && rm -rf /var/lib/apt/lists/* + +# Download the latest installer, install it, and remove it +ADD https://astral.sh/uv/install.sh /uv-installer.sh +RUN chmod -R 655 /uv-installer.sh && /uv-installer.sh && rm /uv-installer.sh + +# Set up uv environment PATH +ENV PATH="/root/.local/bin/:$PATH" + +WORKDIR /app + +# Prevent Python from writing pyc files and buffering output +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 + +# Copy dependency files first for caching +COPY pyproject.toml /app/ + +# Sync dependencies (includes streamlit, ruff, pytest if in pyproject.toml) +RUN uv sync + +# Copy the rest of the project +COPY . /app + +# ------------------------- Production Stage ------------------------- + +# Final stage (production, lean image) +FROM python:3.13-slim-bookworm AS production +WORKDIR /app + +# Prevent Python from writing pyc files and buffering output +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 + +# Create a non-privileged user +ARG UID=10001 +RUN adduser \ + --disabled-password \ + --gecos "" \ + --home "/nonexistent" \ + --shell "/sbin/nologin" \ + --no-create-home \ + --uid "${UID}" \ + appuser + +# Copy the virtual env and project files +COPY --from=builder /app/.venv /app/.venv +COPY . /app + +# Set PATH to use the virtual env +ENV PATH="/app/.venv/bin:$PATH" + +# Switch to non-privileged user +USER appuser + +# Expose Streamlit's default port +EXPOSE 8501 + +# Run Streamlit app +CMD ["streamlit", "run", "src/app.py"] \ No newline at end of file diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..e3502ad --- /dev/null +++ b/Makefile @@ -0,0 +1,53 @@ +.PHONY: all deps check test docker-build-dev docker-check docker-test docker-check-ci docker-build-prod docker-run docker-push docker-clean + +# Dependency management +deps: + uv sync + +# Linting and formatting +check: + - uv run ruff check . --fix + - uv run ruff format . + +# Testing +test: + uv run pytest -v + +# Dev: Build the builder stage image +docker-build-dev: + docker build --target builder -t stockdataview:dev . + +# Dev: Run linting in container +docker-check: docker-build-dev + docker run --rm -v $(PWD):/app stockdataview:dev uv run ruff check . + +# Dev: Run tests in container +docker-test: docker-build-dev + docker run --rm stockdataview:dev uv run pytest -v + +# CI specific target: Build up to the builder stage and run checks/tests +docker-check-ci: docker-build-dev + - docker run --rm -v $(PWD):/app stockdataview:dev uv run ruff check . + - docker run --rm -v $(PWD):/app stockdataview:dev uv run pytest -v + + +# Prod: Build the production stage image +docker-build-prod: + docker build --target production -t skytics/stockdataview:latest . + +# Prod: Run the app locally +docker-run: docker-build-prod + docker run --rm -e FMP_API_KEY=${FMP_API_KEY} -p 8501:8501 skytics/stockdataview:latest + +# Prod: Push to Docker Hub +docker-push: docker-build-prod + docker push skytics/stockdataview:latest + +# Clean up images +docker-clean: + - docker image rm stockdataview:dev || true + - docker image rm skytics/stockdataview:latest || true + +# All-in-one for local dev +all: check test docker-build-dev + @echo "All checks passed!" \ No newline at end of file diff --git a/README.md b/README.md index b82bf8d..eb56a12 100644 --- a/README.md +++ b/README.md @@ -1,92 +1,96 @@ -# Stock Valuation Dashboard +# StockDataView +StockDataView is a Streamlit application designed to display and visualize stock data fetched from the Financial Modeling Prep (FMP) API. It provides users with bar charts, tables of stock fundamentals, and ratings for a given stock ticker. + +## Features +* **Stock Data Visualization:** Presents stock data in clear and interactive bar charts. +* **Fundamental Data Tables:** Displays key stock fundamentals in easy-to-read tables. +* **Stock Ratings:** Shows ratings information for selected stocks. +* **Containerized Application:** Easily deployable via Docker. +* **API Key Input:** Requires users to provide their FMP API key for data retrieval. +* **Automated CI/CD:** Uses GitHub Actions for continuous integration and deployment. +* **Package Management:** Uses `uv` and `pyproject.toml` for dependency management. +* **Makefile Automation:** Includes a Makefile for streamlined development and deployment workflows. + +## Prerequisites +- **Docker**: Required to build and run the application container +- **FMP API Key**: Obtain a free or paid API key from [Financial Modeling Prep](https://financialmodelingprep.com/developer/docs/) +- **Git**: To clone the repository (optional) + +## Installation + +### Option 1: Use the Pre-Built Image +1. **Pull the Image from Docker Hub**: + ```bash + docker pull skytics/stockdataview:latest + ``` + +2. **Run the Container**: + * Replace `your-api-key` with your FMP API key: + ```bash + docker run -p 8501:8501 -e FMP_API_KEY=your-api-key skytics/stockdataview:latest + ``` + +3. Open `http://localhost:8501` in your browser + + +### Option 2: Build and Run Locally +1. **Clone the Repository**: + ```bash + git clone https://github.com/your-username/StockDataView.git + cd StockDataView + ``` + +2. **Build the Production Image**: + ```bash + make docker-build-prod + ``` + * This builds only the `production` stage of the multi-stage Dockerfile + +3. **Run the Container**: + * Replace `your-api-key` with your FMP API key: + ```bash + docker run -p 8501:8501 -e FMP_API_KEY=your-api-key skytics/stockdataview:latest + ``` + +4. Open `http://localhost:8501` in your browser -## Overview - -This project is a web-based stock valuation dashboard that helps investors analyze dividend growth stocks. It provides insights into stock quality and valuation based on historical financial data. - -Key features: -- Fetches financial data from Financial Modeling Prep API -- Calculates growth rates for revenue, dividends, cash flow, and other metrics -- Determines if a stock is a quality dividend growth stock -- Assesses whether a stock is undervalued or reasonably valued -- Visualizes key metrics and growth rates - -## Tech Stack - -- Python 3.11+ -- FastAPI: Web framework for building APIs -- Dash: React-based framework for building analytical web applications -- Polars: Fast DataFrame library for data manipulation -- Pydantic: Data validation using Python type annotations -- PyArrow: Efficient data interchange format -- DuckDB: Embedded analytical database -- uv: Python packaging and dependency management tool -- Docker: Containerization -- GitHub Actions: CI/CD pipeline - -## Project Structure - -stock_valuation_app/ -├── .github/workflows/ # CI/CD configuration -├── src/ -│ └── stock_valuation_app/ -│ ├── api/ # FastAPI routes -│ ├── data/ # Data fetching and processing -│ ├── models/ # Pydantic models -│ ├── services/ # Business logic -│ └── ui/ # Dash dashboard -├── tests/ # Unit and integration tests -├── Dockerfile -├── docker-compose.yml -├── pyproject.toml # Project metadata and dependencies -├── README.md -└── uv.lock # Dependency lock file - - - -## Setup and Installation - -1. Clone the repository: -git clone https://github.com/dimtics/stock_valuation_app.git -cd stock_valuation_app - -2. Install uv and project dependencies: -pip install uv -uv pip install -e . - -3. Set up environment variables: -Create a `.env` file in the project root and add your Financial Modeling Prep API key: -FMP_API_KEY=your_api_key_here - -4. Run the application: -uvicorn stock_valuation_app:app --reload - -5. Open your browser and navigate to `http://localhost:8000/dashboard` to view the dashboard. +## Usage +* Once the app is running, enter a stock ticker (e.g., AAPL) in the Streamlit interface. +* View the displayed bar charts, tables, stock fundamentals, and ratings fetched from the FMP API. -## Docker Deployment -To run the application using Docker: +## Development -1. Build the Docker image: -docker build -t stock-valuation-app . -docker run -p 8000:8000 -e FMP_API_KEY=your_api_key_here stock-valuation-app +### Package Management (uv) +* This project uses `uv` for package management. Dependencies are defined in `pyproject.toml`. +* Sync dependencies from `pyproject.toml`. -Alternatively, use Docker Compose: -docker-compose up +To install dependencies: +```bash +uv sync +``` +### Makefile Commands +* `make docker-build-prod`: Build the production image +* `make docker-run`: Run the production image +* `make docker-build-dev`: Build the dev image (for linting/testing) +* `make docker-check`: Run linting in the dev image +* `make docker-test`: Run tests in the dev image +* `make docker-clean`: Remove all images -## Usage +### Multi-Stage Dockerfile +* `builder` stage: Used for development (linting, testing) +* `production` stage: Final app image for running StockDataView -1. Enter a stock symbol in the input field on the dashboard. -2. Click the "Analyze" button to fetch and analyze the stock data. -3. View the growth rates, quality assessment, and valuation results. +## CI/CD Workflow +* GitHub Actions automates building the `production` image and pushing it to Docker Hub (`skytics/stockdataview:latest`) on `main` branch updates +* The `builder` stage is used for linting and testing in CI +* See `.github/workflows/ci-cd.yml` for details ## Contributing - -Contributions are welcome! Please feel free to submit a Pull Request. +Contributions are welcome! Please feel free to submit a pull request. ## License - -This project is licensed under the MIT License - see the LICENSE file for details. \ No newline at end of file +This project is licensed under the MIT License - see the `LICENSE` file for details. \ No newline at end of file diff --git a/config.yml b/config.yml deleted file mode 100644 index 2e7a46a..0000000 --- a/config.yml +++ /dev/null @@ -1,19 +0,0 @@ -api: - base_url: "https://financialmodelingprep.com/api/v3" - -valuation: - default_pe_ratio: 15 - quality_threshold: - revenue_growth: 0.05 - dividend_growth: 0.05 - -dashboard: - refresh_interval: 300 # in seconds - -database: - type: "duckdb" - file: "stock_data.duckdb" - -logging: - level: "INFO" - file: "app.log" \ No newline at end of file diff --git a/docker-compose.yml b/docker-compose.yml deleted file mode 100644 index e69de29..0000000 diff --git a/pyproject.toml b/pyproject.toml index 1539d18..b7206c9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,33 +1,31 @@ [project] -name = "stock-valuation-app" +name = "stockdataview" version = "0.1.0" -description = "A single-page web app displaying stock data, growth charts, and valuation insights." +description = "A containerized application for visualizing stock fundamentals, ratings, and historical data using the Financial Modeling Prep (FMP) API." readme = "README.md" authors = [ { name = "Dimeji Salau", email = "dimejisalau@protonmail.com" } ] requires-python = ">=3.12" + dependencies = [ - "dash>=2.18.2", - "duckdb>=1.1.3", - "fastapi>=0.115.4", + "asyncio>=3.4.3", "httpx>=0.27.2", + "plotly>=5.24.1", "polars>=1.12.0", - "pyarrow>=18.0.0", - "pydantic>=2.9.2", + "pydantic-settings>=2.8.1", + "streamlit>=1.40.1", ] -[project.scripts] -stock-valuation-app = "stock_valuation_app:main" - -[build-system] -requires = ["hatchling"] -build-backend = "hatchling.build" - [dependency-groups] dev = [ - "ipykernel>=6.29.5", - "mypy>=1.13.0", "pytest>=8.3.3", "ruff>=0.7.3", ] + +[tool.pytest.ini_options] +pythonpath = ["src"] +testpaths = ["tests"] +python_files = ["test_*.py"] +python_classes = ["Test*"] +python_functions = ["test_*"] \ No newline at end of file diff --git a/src/app.py b/src/app.py new file mode 100644 index 0000000..f79abca --- /dev/null +++ b/src/app.py @@ -0,0 +1,669 @@ +from typing import Any + +import plotly.graph_objects as go +import polars as pl +import streamlit as st +import streamlit.components.v1 as components + +from data_validation import get_validated_stock_data + + +def display_profile(profile_data: dict[str, Any]) -> None: + """Displays company profile in sidebar""" + try: + if profile_data: + st.sidebar.write("## Company Profile") + st.sidebar.image(profile_data["image"], width=180) + st.sidebar.write(f"## {profile_data['company_name']}") + st.sidebar.write(f"**Sector**: {profile_data['sector']}") + st.sidebar.write(f"**Industry**: {profile_data['industry']}") + st.sidebar.write(f"**Description**: {profile_data['description']}") + except IndexError: + st.write("Couldn't find company profile.") + + +def display_quotes(quote_data: dict[str, Any], profile_data: dict[str, Any]) -> None: + """Displays company quotes in main area""" + + def display_stock_metric(header, value) -> None: + """Displays quotes in capsule at the top of the page""" + + html_content = f""" + +
+
{header}
+
{value}
+
+ """ + st.html(html_content) + + try: + stock_price = f"${quote_data['price']:,.2f}" + change_price = f"{quote_data['change_percent']:,.2f}%" + year_low = f"${quote_data['year_low']:,.2f}" + year_high = f"${quote_data['year_high']:,.2f}" + market_cap = f"{quote_data['market_cap']/1_000_000_000:.2f}B" + vol_avg = f"{quote_data['vol_avg']/1_000_000:.2f}M" + earning_date = quote_data["earning_date"][:10] + eps = f"{quote_data['eps']:.2f}" + shares_outstanding = f"{quote_data["shares_outstanding"]/1_000_000_000:.2f}B" + + # Set page top quotes layout + col1, col2, col3, col4, col5, col6, col7, col8, col9 = st.columns(9) + + with col1: + display_stock_metric("Price", stock_price) + with col2: + display_stock_metric("Change Percent", change_price) + with col3: + display_stock_metric("52w Low", year_low) + with col4: + display_stock_metric("52w High", year_high) + with col5: + display_stock_metric("Avg Volume", vol_avg) + with col6: + display_stock_metric("Market Cap", market_cap) + with col7: + display_stock_metric("EPS", eps) + with col8: + display_stock_metric("Shares", shares_outstanding) + with col9: + display_stock_metric("Earning Date", earning_date) + except Exception as e: + print(e) + + +def display_metric_tables(data: list[dict[str, Any]]): + """Displays metric tables in main area""" + + def generate_table_rows(data: dict[str, Any]): # table_name: str + rows_html = "" + for metric, value in data.items(): + row = f""" + +
+ {metric}: + {value} +
+ """ + rows_html += row + return rows_html + + def display_table(data: dict[str, Any], header_name: str): + table_html = f""" + +
+
{header_name}
+ {generate_table_rows(data)} +
+ """ + return components.html(table_html, height=185) # 210 + + # Get data and generate tables + quote_data, key_metrics_ttm_data, growth_data, ratings_data = data + latest_growth_data = growth_data[0] + latest_ratings_data = ratings_data[0] + + valuation_data = { + "PE Ratio (TTM)": f"{quote_data['pe']:,.2f}", + "EV/EBITDA (TTM)": f"{key_metrics_ttm_data['ev_over_ebitda_ttm']:,.2f}", + "Price/Sales (TTM)": f"{key_metrics_ttm_data['pts_ratio_ttm']:,.2f}", + "Price/Book (TTM)": f"{key_metrics_ttm_data['ptb_ratio_ttm']:,.2f}", + } + + freecashflow_data = { + "FCF Yield (TTM)": f"{key_metrics_ttm_data['fcf_yield_ttm'] * 100:,.2f}%", + "Price/FCF (TTM)": f"{key_metrics_ttm_data['pfcf_ratio_ttm']:,.2f}", + "EV/FCF (TTM)": f"{key_metrics_ttm_data['ev_to_fcf_ttm']:,.2f}", + "FCF/Share (TTM)": f"{key_metrics_ttm_data['fcf_per_share_ttm']:,.2f}", + } + + growth_metric_data = { + "5Y Rev Growth/Share": f"{latest_growth_data['fiveY_rev_growth_per_share'] * 100:,.2f}%", + "5Y NI Growth/Share": f"{latest_growth_data['fiveY_ni_growth_per_share'] * 100:,.2f}%", + "5Y Div Growth/Share": f"{latest_growth_data['fiveY_dps_growth_per_share'] * 100:,.2f}%", + "5Y OCF Growth/Share": f"{latest_growth_data['fiveY_opcf_growth_per_share'] * 100:,.2f}%", + } + + dividend_data = { + "Div Yield (TTM)": f"{key_metrics_ttm_data['dvd_yield_pct_ttm']:,.2f}%", + "Div/Share (TTM)": f"{key_metrics_ttm_data['dvd_per_share_ttm']:,.2f}", + "Payout Ratio (TTM)": f"{key_metrics_ttm_data['payout_ratio_ttm'] * 100:,.2f}%", + } + + rating_data = { + "Date": f"{latest_ratings_data['date']}", + "Rating": f"{latest_ratings_data['rating']}", + "Score": f"{latest_ratings_data['score']}", + "Recommendation": f"{latest_ratings_data['recommendation']}", + } + + # Define tables layout + container = st.empty() + col1, col2, col3, col4, col5 = st.columns(5) + with col1: + container.markdown( + display_table(valuation_data, "Valuation"), unsafe_allow_html=True + ) + container.empty() + + with col2: + container.markdown( + display_table(freecashflow_data, "Cash Flow"), unsafe_allow_html=True + ) + container.empty() + + with col3: + container.markdown( + display_table(growth_metric_data, "Growth"), unsafe_allow_html=True + ) + container.empty() + + with col4: + container.markdown( + display_table(dividend_data, "Dividend"), unsafe_allow_html=True + ) + container.empty() + + with col5: + container.markdown(display_table(rating_data, "Rating"), unsafe_allow_html=True) + container.empty() + + +def display_metrics_charts( + metrics_data: list[dict[str, Any]], key_metrics_ttm_data: dict[str, Any] +): + """Displays metrics charts in main area""" + + def create_compact_bar_chart(data: pl.DataFrame, x_col, y_col, title, ttm_value): + fig = go.Figure() + + # Historical data bars + fig.add_trace( + go.Bar( + x=data[x_col], + y=data[y_col], + name="Historical", + marker=dict( + color="#4C78A8", # Modern blue + line=dict(width=1, color="#2E2E2E"), # Dark outline + ), + width=0.75, + opacity=0.9, + hovertemplate="%{x}: %{y:.2f}", + ) + ) + + # TTM value with high-contrast marker + latest_date = data[x_col].dt.max() + fig.add_trace( + go.Scatter( + x=[latest_date], + y=[ttm_value], + mode="markers+text", + marker=dict( + size=12, + color="#F28C38", # Vibrant orange + symbol="diamond", + line=dict(width=2, color="#D76F1E"), # Darker orange outline + ), + name="TTM", + text=[f"{ttm_value:.2f}"], + textposition="top center", + textfont=dict( + size=12, color="#2E2E2E", weight="bold" + ), # Dark gray for visibility + hovertemplate="TTM: %{y:.2f}", + ) + ) + + # TTM reference line + fig.add_shape( + type="line", + x0=data[x_col].dt.min(), + y0=ttm_value, + x1=latest_date, + y1=ttm_value, + line=dict( + color="#F28C38", + width=1.5, + dash="dash", + ), + ) + + # Adaptive layout + fig.update_layout( + title=dict( + text=title, + font=dict(size=16, color="#2E2E2E"), # Darker gray for contrast + x=0.5, + xanchor="center", + y=0.95, + yanchor="top", + ), + xaxis_title="Year", + yaxis_title=title, + plot_bgcolor="rgba(0,0,0,0)", # Transparent plot + paper_bgcolor="rgba(0,0,0,0)", # Transparent paper + height=450, + margin=dict(l=60, r=40, t=80, b=60), + font=dict( + family="Inter, Arial, sans-serif", + size=13, + color="#2E2E2E", # Dark gray text + ), + showlegend=True, + legend=dict( + orientation="h", + yanchor="bottom", + y=1.02, + xanchor="right", + x=1, + font=dict(size=12), + bgcolor="rgba(255,255,255,0.8)", # Light background for legend on white + ), + hovermode="x unified", + transition_duration=500, + ) + + # Enhanced axes + fig.update_xaxes( + tickmode="array", + tickvals=data[x_col], + ticktext=data[x_col].dt.strftime("%Y"), + gridcolor="rgba(0,0,0,0.2)", # Darker gridlines for white background + linecolor="#666666", + linewidth=1, + ticks="outside", + tickfont=dict(size=12), + title_font=dict(size=14), + zeroline=False, + ) + + fig.update_yaxes( + gridcolor="rgba(0,0,0,0.2)", # Darker gridlines + linecolor="#666666", + linewidth=1, + tickfont=dict(size=12), + title_font=dict(size=14), + zeroline=False, + showline=True, + ) + + # Enhanced hover + fig.update_traces( + hoverlabel=dict( + bgcolor="#FFFFFF", # White hover background + font_size=12, + font_color="#2E2E2E", # Dark gray text + bordercolor="#666666", + ), + ) + return fig + + # Create dataframe to use for charts + df = ( + pl.DataFrame(metrics_data) + .with_columns( + pl.col("date") + .str.strptime(pl.Date, format="%Y-%m-%d") + .alias("FYDateEnding") + ) + .sort("date") + .drop("date") + ) + + if df is None or df.is_empty(): + print("Dataframe is empty") + return None + + def plot_chart(metrics: list[tuple[str, str]]): + """Plots charts for each metric in the list""" + for metric, title in metrics: + ttm_value = key_metrics_ttm_data[f"{metric}_ttm"] + dfx = df.select("FYDateEnding", f"{metric}") + + st.plotly_chart( + create_compact_bar_chart( + dfx, + x_col="FYDateEnding", + y_col=f"{metric}", + title=f"{title}", + ttm_value=ttm_value, + ), + use_container_width=True, + ) + + col1, col2 = st.columns(2) + col3, col4 = st.columns(2) + col5, col6 = st.columns(2) + + with col1: + col1_metrics = [ + ("rev_per_share", "Rev/Share"), + ] + plot_chart(col1_metrics) + with col2: + col2_metrics = [ + ("pe_ratio", "PE Ratio"), + ] + plot_chart(col2_metrics) + with col3: + col3_metrics = [ + ("fcf_per_share", "FCF/Share"), + ] + plot_chart(col3_metrics) + with col4: + col4_metrics = [ + ("ev_over_ebitda", "EV/EBITDA"), + ] + plot_chart(col4_metrics) + with col5: + col5_metrics = [ + ("ev_to_fcf", "EV/FCF"), + ] + plot_chart(col5_metrics) + with col6: + col6_metrics = [ + ("fcf_yield", "FCF Yield"), + ] + plot_chart(col6_metrics) + + +def display_growth_charts(growth_data: list[dict[str, Any]]): + """Displays growth charts in main area""" + + def create_compact_bar_chart(data: pl.DataFrame, x_col, y_col, title): + fig = go.Figure() + + fig.add_trace( + go.Bar( + x=data[x_col], + y=data[y_col], + name="", + marker=dict( + color="#54A24B", # Modern green + line=dict(width=1, color="#2E2E2E"), # Dark outline + ), + width=0.7, + hovertemplate="%{x}: %{y:.2f}%", + ) + ) + + fig.update_layout( + title=dict( + text=title, + font=dict(size=18, color="#2E2E2E"), # Darker gray + x=0.5, + xanchor="center", + y=0.95, + yanchor="top", + ), + xaxis_title="Year", + yaxis_title="Growth Rate (%)", + plot_bgcolor="rgba(0,0,0,0)", + paper_bgcolor="rgba(0,0,0,0)", + height=450, + margin=dict(l=50, r=50, t=80, b=60), + font=dict( + family="Inter, Arial, sans-serif", + size=13, + color="#2E2E2E", # Dark gray text + ), + showlegend=False, + hovermode="x unified", + barmode="group", + transition_duration=400, + ) + + fig.update_xaxes( + tickmode="array", + tickvals=data[x_col], + ticktext=data[x_col].dt.strftime("%Y"), + gridcolor="rgba(0,0,0,0.2)", # Darker gridlines + linecolor="#666666", + linewidth=1, + ticks="outside", + tickfont=dict(size=12), + title_font=dict(size=14), + zeroline=False, + ) + + fig.update_yaxes( + gridcolor="rgba(0,0,0,0.2)", + linecolor="#666666", + linewidth=1, + ticksuffix="%", + tickfont=dict(size=12), + title_font=dict(size=14), + zeroline=False, + showline=True, + ) + + fig.update_traces( + opacity=0.95, + hoverlabel=dict( + bgcolor="#FFFFFF", + font_size=12, + font_color="#2E2E2E", + bordercolor="#666666", + ), + ) + + return fig + + # Create charts + df = ( + pl.DataFrame(growth_data) + .with_columns( + pl.exclude(["symbol", "date"]).map_elements( + lambda x: round(x * 100, 2), return_dtype=pl.Float64 + ), + pl.col("date").str.strptime(pl.Date, format="%Y-%m-%d").alias("Year"), + ) + .sort("date") + .drop("date") + ) + + if df is None or df.is_empty(): + print("Dataframe is empty") + return None + + def plot_chart(metrics: list[tuple[str, str]]): + for metric, title in metrics: + dfx = df.select("Year", f"{metric}") + + st.plotly_chart( + create_compact_bar_chart( + dfx, + x_col="Year", + y_col=f"{metric}", + title=f"{title}", + ), + use_container_width=True, + ) + + col1, col2 = st.columns(2) + col3, col4 = st.columns(2) + col5, _ = st.columns(2) + + with col1: + col1_metrics = [ + ("rev_growth", "Rev Growth"), + ] + plot_chart(col1_metrics) + with col2: + col2_metrics = [ + ("eps_growth", "EPS Growth"), + ] + plot_chart(col2_metrics) + with col3: + col3_metrics = [ + ("dps_growth", "DPS Growth"), + ] + plot_chart(col3_metrics) + with col4: + col4_metrics = [ + ("fcf_growth", "FCF Growth"), + ] + plot_chart(col4_metrics) + with col5: + col5_metrics = [ + ("debt_growth", "Debt Growth"), + ] + plot_chart(col5_metrics) + + +def main(): + """Main function to run StockDataView app""" + + # Set main page config + st.set_page_config( + page_title="Stock Data View", + layout="wide", + ) + + # Custom CSS for styling main page + st.markdown( + """ + + """, + unsafe_allow_html=True, + ) + + # Custom CSS for styling sidebar + st.sidebar.markdown( + """ + + """, + unsafe_allow_html=True, + ) + + # Set main page title and description + st.title("StockDataView") + st.subheader( + "Visualize stock fundamentals, ratings, and historical data using the Financial Modeling Prep (FMP) API", + divider="gray", + ) + st.markdown('
', unsafe_allow_html=True) + + # Sidebar for user input + ticker = st.sidebar.text_input(r"$\textsf{\Large Enter stock symbol:}$") + analyze_button = st.sidebar.button("Analyze") + + if ticker and analyze_button: + # Get stock ticker data + stock_data = get_validated_stock_data(ticker) + if stock_data is None: + st.write(f"No data found for stock ticker: {ticker}") + else: + profile_data = stock_data["profile"][0] + quote_data = stock_data["quote"][0] + ratings_data = stock_data["ratings"] + key_metrics_ttm_data = stock_data["key_metrics_ttm"][0] + key_metrics_data = stock_data["key_metrics"] + growth_data = stock_data["growth"] + + table_data = [ + quote_data, + key_metrics_ttm_data, + growth_data, + ratings_data, + ] + + # Display ticker profile + display_profile(profile_data) + + # Display ticker quotes + display_quotes(quote_data, profile_data) + st.markdown('
', unsafe_allow_html=True) + st.markdown('
', unsafe_allow_html=True) + + # Display metric tables + display_metric_tables(table_data) + + # Define layout for metrics and growth charts + st.markdown('
', unsafe_allow_html=True) + st.markdown('
', unsafe_allow_html=True) + + left, right = st.columns(2) + with left: + st.markdown( + """

Valuation Metrics

""", + unsafe_allow_html=True, + ) + # Display valuation charts + display_metrics_charts(key_metrics_data, key_metrics_ttm_data) + with right: + st.markdown( + """

Growth Metrics

""", + unsafe_allow_html=True, + ) + # Display growth charts + display_growth_charts(growth_data) + + st.divider() + + +if __name__ == "__main__": + main() diff --git a/src/config.py b/src/config.py new file mode 100644 index 0000000..e567b89 --- /dev/null +++ b/src/config.py @@ -0,0 +1,14 @@ +from pydantic_settings import BaseSettings, SettingsConfigDict + + +class Settings(BaseSettings): + base_url: str = "https://financialmodelingprep.com/api/v3" + annual_ratios: str = "ratios" + annual_financial_growth: str = "financial-growth" + rating: str = "rating" + fmp_api_key: str + + model_config = SettingsConfigDict(env_file=".env", env_file_encoding="utf-8") + + +settings = Settings() diff --git a/src/data_validation.py b/src/data_validation.py new file mode 100644 index 0000000..6c26fb9 --- /dev/null +++ b/src/data_validation.py @@ -0,0 +1,63 @@ +# data_validation.py + +import asyncio +from typing import Any, Optional + +from pydantic import ValidationError + +from stock_models import CombinedModel +from utils import FMPClient, StockData + + +async def extract_stock_data(ticker: str) -> Optional[StockData]: + """Pulls source data from Financial Modeling Prep (FMP) API endpoints for a given ticker""" + # Get stock data + stock_data = await FMPClient().fetch_data(ticker) + + if stock_data: + # Get metric types + metric_types = FMPClient().metric_types + + # Rename some metric types to match with fields defined in the validation + rename_metric_types: dict[Any, Any] = { + "rating": "ratings", + "key-metrics": "key_metrics", + "key-metrics-ttm": "key_metrics_ttm", + "financial-growth": "growth", + } + new_metric_types = [ + rename_metric_types.get(item, item) for item in metric_types + ] + + # Create combined records dict + records = dict(zip(new_metric_types, stock_data)) + return records + + +class DataValidationError(Exception): + """Custom exception for validation error""" + + +def get_validated_stock_data(ticker: str) -> Optional[StockData]: + """Validates stock data against the CombinedModel schema""" + + # Keep validation errors here + errors: list[str] = [] + + # Extract stock data + data = asyncio.run(extract_stock_data(ticker)) + + if data is None: + return None + else: + # Validate stock data + try: + validated_data = CombinedModel(**data).model_dump() + except ValidationError as e: + errors.append(f"Failed validation: {str(e)}") + if errors: + error_message = "\n".join(errors) + raise DataValidationError( + f"Data validation failed with following errors: \n{error_message}" + ) + return validated_data diff --git a/src/stock_models.py b/src/stock_models.py new file mode 100644 index 0000000..bc20d4d --- /dev/null +++ b/src/stock_models.py @@ -0,0 +1,106 @@ +from typing import Optional + +from pydantic import BaseModel, Field + + +class CompanyProfile(BaseModel): + symbol: str + beta: float + range: str + company_name: str = Field(..., alias="companyName") + sector: Optional[str] = None + industry: Optional[str] = None + description: Optional[str] = None + image: Optional[str] = None + + +class Quote(BaseModel): + symbol: str + price: float + change_percent: Optional[float] = Field(..., alias="changesPercentage") + year_high: float = Field(..., alias="yearHigh") + year_low: float = Field(..., alias="yearLow") + market_cap: float = Field(..., alias="marketCap") + vol_avg: int | float | None = Field(..., alias="avgVolume") + eps: float | None + pe: float | None + earning_date: str = Field(..., alias="earningsAnnouncement") + shares_outstanding: int = Field(..., alias="sharesOutstanding") + + +class Ratings(BaseModel): + symbol: str + date: str + rating: str + score: int = Field(..., alias="ratingScore") + recommendation: str = Field(..., alias="ratingRecommendation") + dcf_score: int = Field(..., alias="ratingDetailsDCFScore") + dcf_rec: str = Field(..., alias="ratingDetailsDCFRecommendation") + roe_score: int = Field(..., alias="ratingDetailsROEScore") + roe_rec: str = Field(..., alias="ratingDetailsROERecommendation") + roa_score: int = Field(..., alias="ratingDetailsROAScore") + roa_rec: str = Field(..., alias="ratingDetailsROARecommendation") + de_score: int = Field(..., alias="ratingDetailsDEScore") + de_rec: str = Field(..., alias="ratingDetailsDERecommendation") + pe_score: int = Field(..., alias="ratingDetailsPEScore") + pe_rec: str = Field(..., alias="ratingDetailsPERecommendation") + pb_score: int = Field(..., alias="ratingDetailsPBScore") + pb_rec: str = Field(..., alias="ratingDetailsPBRecommendation") + + +class KeyMetricsTTM(BaseModel): + rev_per_share_ttm: float | None = Field(..., alias="revenuePerShareTTM") + net_income_per_share_ttm: float | None = Field(..., alias="netIncomePerShareTTM") + fcf_per_share_ttm: float | None = Field(..., alias="freeCashFlowPerShareTTM") + pe_ratio_ttm: float | None = Field(..., alias="peRatioTTM") + ev_over_ebitda_ttm: float | None = Field(..., alias="enterpriseValueOverEBITDATTM") + ev_to_fcf_ttm: float | None = Field(..., alias="evToFreeCashFlowTTM") + fcf_yield_ttm: float | None = Field(..., alias="freeCashFlowYieldTTM") + pts_ratio_ttm: float | None = Field(..., alias="priceToSalesRatioTTM") + ptb_ratio_ttm: float | None = Field(..., alias="ptbRatioTTM") + pfcf_ratio_ttm: float | None = Field(..., alias="pfcfRatioTTM") + dvd_yield_pct_ttm: float | None = Field(..., alias="dividendYieldPercentageTTM") + dvd_per_share_ttm: float | None = Field(..., alias="dividendPerShareTTM") + payout_ratio_ttm: float | None = Field(..., alias="payoutRatioTTM") + + +class KeyMetrics(BaseModel): + symbol: str + date: str + rev_per_share: float | None = Field(..., alias="revenuePerShare") + fcf_per_share: float | None = Field(..., alias="freeCashFlowPerShare") + pe_ratio: float | None = Field(..., alias="peRatio") + ev_over_ebitda: float | None = Field(..., alias="enterpriseValueOverEBITDA") + ev_to_fcf: float | None = Field(..., alias="evToFreeCashFlow") + fcf_yield: float | None = Field(..., alias="freeCashFlowYield") + + +class Growth(BaseModel): + symbol: str + date: str + rev_growth: float | None = Field(..., alias="revenueGrowth") + eps_growth: float | None = Field(..., alias="epsdilutedGrowth") + dps_growth: float | None = Field(..., alias="dividendsperShareGrowth") + fcf_growth: float | None = Field(..., alias="freeCashFlowGrowth") + debt_growth: float | None = Field(..., alias="debtGrowth") + fiveY_rev_growth_per_share: float | None = Field( + ..., alias="fiveYRevenueGrowthPerShare" + ) + fiveY_ni_growth_per_share: float | None = Field( + ..., alias="fiveYNetIncomeGrowthPerShare" + ) + fiveY_dps_growth_per_share: float | None = Field( + ..., alias="fiveYDividendperShareGrowthPerShare" + ) + fiveY_opcf_growth_per_share: float | None = Field( + ..., alias="fiveYOperatingCFGrowthPerShare" + ) + + +class CombinedModel(BaseModel): + profile: list[CompanyProfile] + quote: list[Quote] + ratings: list[Ratings] + key_metrics_ttm: list[KeyMetricsTTM] + key_metrics: list[KeyMetrics] + growth: list[Growth] diff --git a/src/stock_valuation_app/__init__.py b/src/stock_valuation_app/__init__.py deleted file mode 100644 index e4a8c91..0000000 --- a/src/stock_valuation_app/__init__.py +++ /dev/null @@ -1,2 +0,0 @@ -def main() -> None: - print("Hello from stock-valuation-app!") diff --git a/src/stock_valuation_app/api/__init__.py b/src/stock_valuation_app/api/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/stock_valuation_app/api/routes.py b/src/stock_valuation_app/api/routes.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/stock_valuation_app/data/__init__.py b/src/stock_valuation_app/data/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/stock_valuation_app/data/fmp_client.py b/src/stock_valuation_app/data/fmp_client.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/stock_valuation_app/models/__init__.py b/src/stock_valuation_app/models/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/stock_valuation_app/models/stock.py b/src/stock_valuation_app/models/stock.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/stock_valuation_app/services/__init__.py b/src/stock_valuation_app/services/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/stock_valuation_app/services/valuation.py b/src/stock_valuation_app/services/valuation.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/stock_valuation_app/ui/__init__.py b/src/stock_valuation_app/ui/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/stock_valuation_app/ui/dashboard.py b/src/stock_valuation_app/ui/dashboard.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/utils.py b/src/utils.py new file mode 100644 index 0000000..b504fe7 --- /dev/null +++ b/src/utils.py @@ -0,0 +1,81 @@ +import asyncio +import logging +import sys +from dataclasses import dataclass, field +from typing import Any, Optional + +import httpx + +from config import settings + +# Define stock data type +StockData = dict[str, list[dict[str, Any]]] + + +def stock_logger(): + """Configures logging for stock data dashboard project""" + logging.basicConfig( + level=logging.INFO, + format="%(asctime)s - %(levelname)s - %(message)s", + datefmt="%Y-%m-%d %H:%M:%S", + stream=sys.stdout, + force=True, # Ensures unbuffered output + ) + return logging.getLogger(__name__) + + +@dataclass +class FMPClient: + """A client for interacting with the Financial Modeling Prep API.""" + + base_url: str = settings.base_url + api_key: str = settings.fmp_api_key + metric_types: list[str] = field( + default_factory=lambda: [ + "profile", + "rating", + "quote", + "key-metrics-ttm", + "key-metrics", + "financial-growth", + ] + ) # + + async def get_data( + self, client: httpx.Client, url: str + ) -> Optional[dict[str, Any]]: + """Call API endpoint asynchronously""" + try: + response = await client.get(url) + data = response.json() + return data + except Exception as e: + stock_logger().error(f"Error fetching data from {url}: {e}") + return None + + async def fetch_data(self, ticker: str) -> Optional[StockData]: + """Extracts data asynchronously from multiple FMP endpoints""" + urls = [] + for metric in self.metric_types: + if metric in ["profile", "quote", "rating", "key-metrics-ttm"]: + endpoint = f"{self.base_url}/{metric}/{ticker}?apikey={self.api_key}" + else: + endpoint = f"{self.base_url}/{metric}/{ticker}?period=annual&apikey={self.api_key}" + urls.append(endpoint) + + async with httpx.AsyncClient() as client: + tasks = [] + for url in urls: + tasks.append(asyncio.create_task(self.get_data(client, url))) + results = await asyncio.gather(*tasks) + + # Check if results are empty or contain error messages + if isinstance(results[0], list) and len(results[0]) == 0: + return None + elif ( + isinstance(results[0], dict) + and list(results[0].keys())[0] == "Error Message" + ): + return None + else: + return results diff --git a/tests/test_data_validation.py b/tests/test_data_validation.py new file mode 100644 index 0000000..ac9e457 --- /dev/null +++ b/tests/test_data_validation.py @@ -0,0 +1,13 @@ +from src.data_validation import get_validated_stock_data + + +def test_get_validated_stock_data_valid_ticker(): + """Test data validation with valid ticker""" + ticker = "AAPL" + data = get_validated_stock_data(ticker) + + assert data is not None + assert "profile" in data + assert "quote" in data + assert "ratings" in data + assert "key_metrics_ttm" in data diff --git a/tests/test_stock_models.py b/tests/test_stock_models.py new file mode 100644 index 0000000..971fad5 --- /dev/null +++ b/tests/test_stock_models.py @@ -0,0 +1,173 @@ +from src.stock_models import ( + Growth, + KeyMetricsTTM, + Quote, + Ratings, +) + + +class TestQuote: + def test_valid_quote(self): + """Test creating a valid Quote instance""" + data = { + "symbol": "AAPL", + "price": 175.84, + "changesPercentage": 0.75, + "yearHigh": 198.23, + "yearLow": 124.17, + "marketCap": 2750000000000, + "avgVolume": 55000000, + "eps": 6.13, + "pe": 28.7, + "earningsAnnouncement": "2024-01-25", + "sharesOutstanding": 15600000000, + } + + quote = Quote(**data) + assert quote.symbol == "AAPL" + assert quote.price == 175.84 + assert quote.change_percent == 0.75 + assert quote.market_cap == 2750000000000 + + def test_quote_with_null_values(self): + """Test Quote with null values for optional fields""" + data = { + "symbol": "AAPL", + "price": 175.84, + "changesPercentage": None, + "yearHigh": 198.23, + "yearLow": 124.17, + "marketCap": 2750000000000, + "avgVolume": None, + "eps": None, + "pe": None, + "earningsAnnouncement": "2024-01-25", + "sharesOutstanding": 15600000000, + } + + quote = Quote(**data) + assert quote.change_percent is None + assert quote.eps is None + assert quote.pe is None + + +class TestRatings: + def test_valid_ratings(self): + """Test creating a valid Ratings instance""" + data = { + "symbol": "AAPL", + "date": "2024-01-15", + "rating": "Strong Buy", + "ratingScore": 5, + "ratingRecommendation": "Strong Buy", + "ratingDetailsDCFScore": 4, + "ratingDetailsDCFRecommendation": "Buy", + "ratingDetailsROEScore": 5, + "ratingDetailsROERecommendation": "Strong Buy", + "ratingDetailsROAScore": 4, + "ratingDetailsROARecommendation": "Buy", + "ratingDetailsDEScore": 5, + "ratingDetailsDERecommendation": "Strong Buy", + "ratingDetailsPEScore": 3, + "ratingDetailsPERecommendation": "Neutral", + "ratingDetailsPBScore": 4, + "ratingDetailsPBRecommendation": "Buy", + } + + ratings = Ratings(**data) + assert ratings.symbol == "AAPL" + assert ratings.score == 5 + assert ratings.dcf_score == 4 + assert ratings.pe_rec == "Neutral" + + +class TestKeyMetricsTTM: + def test_valid_key_metrics_ttm(self): + """Test creating a valid KeyMetricsTTM instance""" + data = { + "revenuePerShareTTM": 24.87, + "netIncomePerShareTTM": 6.13, + "freeCashFlowPerShareTTM": 6.85, + "peRatioTTM": 28.7, + "enterpriseValueOverEBITDATTM": 22.5, + "evToFreeCashFlowTTM": 25.3, + "freeCashFlowYieldTTM": 0.039, + "priceToSalesRatioTTM": 7.1, + "ptbRatioTTM": 45.8, + "pfcfRatioTTM": 25.7, + "dividendYieldPercentageTTM": 0.0051, + "dividendPerShareTTM": 0.92, + "payoutRatioTTM": 0.15, + } + + metrics = KeyMetricsTTM(**data) + assert metrics.rev_per_share_ttm == 24.87 + assert metrics.pe_ratio_ttm == 28.7 + assert metrics.dvd_yield_pct_ttm == 0.0051 + + def test_key_metrics_ttm_with_nulls(self): + """Test KeyMetricsTTM with null values""" + data = { + "revenuePerShareTTM": None, + "netIncomePerShareTTM": None, + "freeCashFlowPerShareTTM": 6.85, + "peRatioTTM": 28.7, + "enterpriseValueOverEBITDATTM": None, + "evToFreeCashFlowTTM": None, + "freeCashFlowYieldTTM": 0.039, + "priceToSalesRatioTTM": None, + "ptbRatioTTM": None, + "pfcfRatioTTM": None, + "dividendYieldPercentageTTM": None, + "dividendPerShareTTM": None, + "payoutRatioTTM": None, + } + + metrics = KeyMetricsTTM(**data) + assert metrics.rev_per_share_ttm is None + assert metrics.net_income_per_share_ttm is None + assert metrics.fcf_per_share_ttm == 6.85 + + +class TestGrowth: + def test_valid_growth(self): + """Test creating a valid Growth instance""" + data = { + "symbol": "AAPL", + "date": "2023-12-31", + "revenueGrowth": 0.08, + "epsdilutedGrowth": 0.09, + "dividendsperShareGrowth": 0.05, + "freeCashFlowGrowth": 0.07, + "debtGrowth": -0.02, + "fiveYRevenueGrowthPerShare": 0.15, + "fiveYNetIncomeGrowthPerShare": 0.18, + "fiveYDividendperShareGrowthPerShare": 0.08, + "fiveYOperatingCFGrowthPerShare": 0.12, + } + + growth = Growth(**data) + assert growth.symbol == "AAPL" + assert growth.rev_growth == 0.08 + assert growth.fiveY_rev_growth_per_share == 0.15 + + def test_growth_with_nulls(self): + """Test Growth with null values""" + data = { + "symbol": "AAPL", + "date": "2023-12-31", + "revenueGrowth": None, + "epsdilutedGrowth": None, + "dividendsperShareGrowth": None, + 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