diff --git a/.github/old_python_publish_yml b/.github/old_python_publish_yml deleted file mode 100644 index 7c852f1..0000000 --- a/.github/old_python_publish_yml +++ /dev/null @@ -1,26 +0,0 @@ -name: Upload Python Package - -on: - release: - types: [created] - -jobs: - deploy: - runs-on: ubuntu-latest - steps: - - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v5 - with: - python-version: '3.x' - - name: Install dependencies - run: | - pip install --upgrade pip - pip install setuptools wheel twine - - name: Build and publish - env: - TWINE_USERNAME: __token__ - TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }} - run: | - python setup.py sdist bdist_wheel - twine upload dist/* diff --git a/.github/setup.py b/.github/setup.py index a610784..b4771f2 100644 --- a/.github/setup.py +++ b/.github/setup.py @@ -2,7 +2,7 @@ setup( name='stock-analysis-program', - version='1.0.0', + version='1.2.0', packages=find_packages(), include_package_data=True, description='A Python-based toolkit for fetching and visualizing financial data and metrics for stocks.', diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 0000000..49adbff --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,70 @@ +name: CI + +on: + push: + branches: ["main"] + pull_request: + branches: ["main"] + workflow_dispatch: + +permissions: + contents: read + +jobs: + test: + name: Test Python ${{ matrix.python-version }} + runs-on: ubuntu-latest + strategy: + fail-fast: false + matrix: + python-version: ["3.11", "3.12", "3.13"] + + steps: + - name: Checkout + uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: ${{ matrix.python-version }} + cache: "pip" + + - name: Install Poetry + run: | + python -m pip install --upgrade pip + python -m pip install poetry + + - name: Validate package metadata + run: poetry check + + - name: Install dependencies + run: poetry install --with dev + + - name: Run tests + run: poetry run pytest -q + + build: + name: Build package + runs-on: ubuntu-latest + needs: test + + steps: + - name: Checkout + uses: actions/checkout@v6 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "latest" + cache: "pip" + + - name: Install build tooling + run: | + python -m pip install --upgrade pip + python -m pip install poetry twine + + - name: Build distributions + run: poetry build + + - name: Check distributions + run: twine check dist/* diff --git a/.github/workflows/jekyll-gh-pages.yml b/.github/workflows/jekyll-gh-pages.yml index 9cb771a..d8d7e80 100644 --- a/.github/workflows/jekyll-gh-pages.yml +++ b/.github/workflows/jekyll-gh-pages.yml @@ -1,44 +1,43 @@ -# Sample workflow for building and deploying a Jekyll site to GitHub Pages -name: Deploy Jekyll with GitHub Pages dependencies preinstalled +name: Deploy Docs to GitHub Pages on: - # Runs on pushes targeting the default branch push: branches: ["main"] + paths: + - "README.md" + - "docs/**" + - ".github/workflows/jekyll-gh-pages.yml" - # Allows you to run this workflow manually from the Actions tab workflow_dispatch: -# Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages permissions: contents: read pages: write id-token: write -# Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued. -# However, do NOT cancel in-progress runs as we want to allow these production deployments to complete. concurrency: group: "pages" cancel-in-progress: false jobs: - # Build job build: runs-on: ubuntu-latest steps: - name: Checkout uses: actions/checkout@v4 + - name: Setup Pages uses: actions/configure-pages@v4 + - name: Build with Jekyll uses: actions/jekyll-build-pages@v1 with: source: ./ destination: ./_site + - name: Upload artifact uses: actions/upload-pages-artifact@v3 - # Deployment job deploy: environment: name: github-pages diff --git a/.github/workflows/python_publish.yml b/.github/workflows/python_publish.yml index 854f5f1..021a56c 100644 --- a/.github/workflows/python_publish.yml +++ b/.github/workflows/python_publish.yml @@ -1,30 +1,52 @@ -name: Upload Python Package +name: Publish Python Package on: push: tags: - - 'v*' + - "v*" + workflow_dispatch: + +permissions: + contents: read jobs: - deploy: + publish: runs-on: ubuntu-latest + environment: + name: pypi + url: https://pypi.org/project/stock-analysis-program/ + steps: - - uses: actions/checkout@v4 - - - name: Set up Python - uses: actions/setup-python@v5 - with: - python-version: '3.x' - - - name: Install Poetry - run: | - pip install --upgrade pip - pip install poetry - - - name: Build and publish to PyPI - env: - POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_API_TOKEN }} - run: | - poetry config virtualenvs.create false - poetry build - poetry publish + - name: Checkout + uses: actions/checkout@v6 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "latest" + cache: "pip" + + - name: Install release tooling + run: | + python -m pip install --upgrade pip + python -m pip install poetry twine + + - name: Validate package metadata + run: poetry check + + - name: Install dependencies + run: poetry install --with dev + + - name: Run tests + run: poetry run pytest -q + + - name: Build distributions + run: poetry build + + - name: Check distributions + run: twine check dist/* + + - name: Publish to PyPI + env: + POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_API_TOKEN }} + run: poetry publish diff --git a/.gitignore b/.gitignore index 3569283..581f13e 100644 --- a/.gitignore +++ b/.gitignore @@ -225,3 +225,4 @@ $RECYCLE.BIN/ .vscode/ archive/ +pytest-cache-files-*/ diff --git a/README.md b/README.md index f2800cc..15d2267 100644 --- a/README.md +++ b/README.md @@ -15,12 +15,16 @@ The Stock Analysis Program is a Python-based toolkit designed to fetch and visua ## Installation -To use this program, ensure you have Python installed on your system. Clone this repository and install the required dependencies: +Install the package from PyPI: ```bash -git clone https://github.com/visionary-code-works/stock-analysis-program.git -cd stock-analysis-program -pip install -r requirements.txt +pip install stock-analysis-program +``` + +The package also installs a small command-line menu: + +```bash +stock-analysis ``` ## Usage @@ -46,13 +50,24 @@ The program consists of multiple Python classes categorized into Fetchers and Pl ### Example ```python -from plotter.stock_price_plotter import StockPricePlotter +from stock_analysis_program import StockPricePlotter # Plotting stock prices for Apple and Microsoft price_plotter = StockPricePlotter(['AAPL', 'MSFT']) price_plotter.plot_closing_prices('2021-01-01', '2021-12-31') ``` +Plotter methods return Matplotlib figure and axes objects for notebook, +testing, or dashboard usage: + +```python +figures = price_plotter.plot_closing_prices( + '2021-01-01', + '2021-12-31', + show=False, +) +``` + ## Documentation For detailed documentation on each component, please refer to the `docs` directory. diff --git a/docs/CHANGELOG.md b/docs/CHANGELOG.md index b9286da..f56a10e 100644 --- a/docs/CHANGELOG.md +++ b/docs/CHANGELOG.md @@ -1,3 +1,13 @@ +## v1.2.0 + +- Added the `stock-analysis` console command through the package metadata. +- Moved CLI behavior into `stock_analysis_program.cli` and kept root `main.py` as a compatibility wrapper. +- Standardized public imports around `stock_analysis_program`. +- Updated plotter methods to return Matplotlib figure/axes objects and support `show=False`. +- Added ticker normalization and clearer empty-data validation for fetchers and plotters. +- Replaced network-dependent tests with mocked provider tests. +- Updated README and documentation examples for PyPI installation and package imports. + To rewrite the provided code as a set of classes, we need to organize the functionalities into logical units that represent distinct aspects of the operations. The code you provided contains various functions for fetching and analyzing stock data using the `yfinance` library. Here's how we can organize these functionalities into classes: 1. **StockAveragesFetcher**: Handles the fetching and calculation of moving averages and average trading volume for a single stock ticker. diff --git a/docs/documentation.md b/docs/documentation.md index 9d5f43f..42112c6 100644 --- a/docs/documentation.md +++ b/docs/documentation.md @@ -80,7 +80,7 @@ flowchart LR Each fetcher class can be used independently to retrieve specific data. For example: ```python -from fetcher.stock_summary_fetcher import StockSummaryFetcher +from stock_analysis_program import StockSummaryFetcher # Fetching stock summaries summary_fetcher = StockSummaryFetcher(['AAPL', 'MSFT']) @@ -93,7 +93,7 @@ print(summaries) Plotters are used for visualizing data. They often depend on fetchers to get the necessary data. For example: ```python -from plotter.stock_price_plotter import StockPricePlotter +from stock_analysis_program import StockPricePlotter # Plotting stock prices price_plotter = StockPricePlotter(['AAPL', 'MSFT']) @@ -121,8 +121,7 @@ To extend the program: Here's an example of how to integrate multiple components in a larger program: ```python -from fetcher.revenue_growth_fetcher import RevenueGrowthFetcher -from plotter.revenue_growth_plotter import RevenueGrowthPlotter +from stock_analysis_program import RevenueGrowthFetcher, RevenueGrowthPlotter def plot_revenue_growth(tickers): # Fetching revenue growth diff --git a/main.py b/main.py index 42eb6d4..fafba6c 100644 --- a/main.py +++ b/main.py @@ -1,265 +1,6 @@ -""" main.py +"""Compatibility wrapper for the package CLI.""" -This script provides a user interface to interact with various stock analysis -functionalities. It includes options to fetch and plot stock data, summarize -financial metrics, and visualize stock performance. - -The script uses a menu-driven approach to allow users to choose from different -stock analysis options, including data fetching, summary retrieval, and various -plotting capabilities for stocks and financial indices. -""" - -from src.stock_analysis_program import ( - StockDataFetcher, - StockSummaryFetcher, - FinancialMetricsFetcher, - RevenueGrowthFetcher, - StockPricePlotter, - FinancialMetricsPlotter, - RevenueGrowthPlotter, - StockVolatilityPlotter, - StockExchangePerformancePlotter, - CurrentPricesTickerDisplay, -) - - -def use_stock_data_fetcher(): - """ - Interacts with StockDataFetcher to fetch historical data, moving averages, - average volume, and financial metrics for a specific stock ticker. - - Users are prompted to enter a stock ticker. The function then displays - historical data, moving averages, average trading volume, and key financial - metrics for the entered ticker. - """ - ticker = input("Enter a stock ticker (e.g., AAPL, GOOGL): ") - fetcher = StockDataFetcher(ticker) - historical_data = fetcher.fetch_historical_data() - moving_averages = fetcher.calculate_moving_averages(historical_data) - average_volume = fetcher.get_average_volume(historical_data) - financial_metrics = fetcher.get_financial_metrics() - - print(f"Moving Averages for {ticker}: {moving_averages}") - print(f"Average Volume for {ticker}: {average_volume}") - print(f"Financial Metrics for {ticker}: {financial_metrics}") - - -def use_stock_summary_fetcher(): - """ - Utilizes StockSummaryFetcher to retrieve and display summary information - for a list of stock tickers. - - Users can enter multiple stock tickers separated by commas. The function - fetches and displays a summary for each ticker, including name, sector, - industry, and other key details. - """ - tickers = input( - "Enter stock ticker(s) separated by commas (e.g., GOOGL, AAPL): " - ).split(",") - fetcher = StockSummaryFetcher([ticker.strip() for ticker in tickers]) - summaries = fetcher.get_summaries() - - for summary in summaries: - print(f"\nSummary for {summary['Ticker']}:\n") - for key, value in summary.items(): - print(f"{key}: {value if value is not None else 'N/A'}") - - -def use_financial_metrics_fetcher(): - """ - Uses FinancialMetricsFetcher to fetch and display financial metrics for a - list of stock tickers. - - This function allows users to enter multiple tickers and displays financial - metrics such as market cap, PE ratio, forward PE, and profit margins for - each ticker. - """ - tickers = input( - "Enter stock ticker(s) separated by commas for financial metrics (e.g., AAPL, MSFT): " - ).split(",") - fetcher = FinancialMetricsFetcher([ticker.strip() for ticker in tickers]) - financial_metrics = fetcher.fetch_financial_metrics() - - print("\nFinancial Metrics:") - print(financial_metrics) - - -def use_revenue_growth_fetcher(): - """ - Interacts with RevenueGrowthFetcher to fetch and display year-over-year - revenue growth for a list of stock tickers. - - After users input stock tickers, the function calculates and displays the - year-over-year revenue growth percentage for each ticker. - """ - tickers = input( - "Enter stock ticker(s) separated by commas for revenue growth (e.g., AAPL, MSFT): " - ).split(",") - fetcher = RevenueGrowthFetcher([ticker.strip() for ticker in tickers]) - revenue_growth = fetcher.fetch_revenue_growth() - - print("\nYear-over-Year Revenue Growth:") - for ticker, growth in revenue_growth.items(): - print( - f"{ticker}: {growth:.2%}" - if growth is not None - else f"{ticker}: Data not available" - ) - - -def use_stock_price_plotter(): - """ - Uses StockPricePlotter to plot closing prices and moving averages for a - list of stock tickers. - - Users input stock tickers and a date range. The function then plots the - closing prices and moving averages for the selected period for each ticker. - """ - tickers = input( - "Enter stock ticker(s) separated by commas for price plotting (e.g., AAPL, MSFT): " - ).split(",") - start_date = input("Enter start date (YYYY-MM-DD): ") - end_date = input("Enter end date (YYYY-MM-DD): ") - plotter = StockPricePlotter([ticker.strip() for ticker in tickers]) - plotter.plot_closing_prices(start_date, end_date) - plotter.plot_moving_averages(start_date, end_date) - - -def use_financial_metrics_plotter(): - """ - Utilizes FinancialMetricsPlotter to create histograms of financial metrics - for a list of stock tickers. - - After receiving a list of tickers from the user, this function plots - histograms for key financial metrics like market cap and PE ratio for each - ticker. - """ - tickers = input( - "Enter stock ticker(s) separated by commas for financial metrics plotting (e.g., AAPL, MSFT): " - ).split(",") - plotter = FinancialMetricsPlotter([ticker.strip() for ticker in tickers]) - plotter.plot_metrics() - - -def use_revenue_growth_plotter(): - """ - Leverages RevenueGrowthPlotter to plot the revenue growth of a list of - stock tickers. - - Users provide stock tickers, and the function visualizes the year-over-year - revenue growth for each ticker in a bar chart format. - """ - tickers = input( - "Enter stock ticker(s) separated by commas for revenue growth plotting (e.g., AAPL, MSFT): " - ).split(",") - plotter = RevenueGrowthPlotter([ticker.strip() for ticker in tickers]) - plotter.plot_revenue_growth() - - -def use_stock_volatility_plotter(): - """ - Interacts with StockVolatilityPlotter to plot the rolling volatility of a - list of stock tickers. - - Users enter stock tickers and a date range, and the function plots the - calculated rolling volatility for each ticker over the specified period. - """ - tickers = input( - "Enter stock ticker(s) separated by commas for volatility plotting (e.g., AAPL, MSFT): " - ).split(",") - start_date = input("Enter start date (YYYY-MM-DD): ") - end_date = input("Enter end date (YYYY-MM-DD): ") - plotter = StockVolatilityPlotter([ticker.strip() for ticker in tickers]) - plotter.plot_volatility(start_date, end_date) - - -def use_stock_exchange_performance_plotter(): - """ - Uses StockExchangePerformancePlotter to compare and visualize the - performance of different stock indices. - - Users input symbols of stock indices and a date range, and the function - plots the normalized closing prices of these indices for comparative - analysis. - """ - indices = input( - "Enter stock index symbols separated by commas (e.g., ^GSPC, ^DJI): " - ).split(",") - start_date = input("Enter start date (YYYY-MM-DD): ") - end_date = input("Enter end date (YYYY-MM-DD): ") - plotter = StockExchangePerformancePlotter([index.strip() for index in indices]) - plotter.plot_performance(start_date, end_date) - - -def use_current_prices_ticker_display(): - """ - Utilizes CurrentPricesTickerDisplay to show a rolling display of current - stock prices for a list of tickers. - - Users input stock tickers and a display interval, and the function - continuously displays the current prices of these stocks in a ticker-like - format. - """ - tickers = input( - "Enter stock ticker(s) separated by commas for current price display (e.g., AAPL, MSFT): " - ).split(",") - interval = int(input("Enter display interval in seconds: ")) - ticker_display = CurrentPricesTickerDisplay( - [ticker.strip() for ticker in tickers], interval - ) - ticker_display.display_ticker() - - -def main(): - """ - Main function to run the stock analysis application. - - Presents a menu-driven interface for users to select various stock analysis - functionalities, including data fetching, plotting, and performance - visualization. The script runs in a loop until the user chooses to exit. - """ - while True: - print( - "\nStock Data Analysis Menu\n", - "1. Use Stock Data Fetcher\n", - "2. Use Stock Summary Fetcher\n", - "3. Use Financial Metrics Fetcher\n", - "4. Use Revenue Growth Fetcher\n", - "5. Use Stock Price Plotter\n", - "6. Use Financial Metrics Plotter\n", - "7. Use Revenue Growth Plotter\n", - "8. Use Stock Volatility Plotter\n", - "9. Use Stock Exchange Performance Plotter\n", - "10. Use Current Prices Ticker Display\n", - "0. Exit\n" - ) - - choice = input("Enter your choice: ") - - if choice == "1": - use_stock_data_fetcher() - elif choice == "2": - use_stock_summary_fetcher() - elif choice == "3": - use_financial_metrics_fetcher() - elif choice == "4": - use_revenue_growth_fetcher() - elif choice == "5": - use_stock_price_plotter() - elif choice == "6": - use_financial_metrics_plotter() - elif choice == "7": - use_revenue_growth_plotter() - elif choice == "8": - use_stock_volatility_plotter() - elif choice == "9": - use_stock_exchange_performance_plotter() - elif choice == "10": - use_current_prices_ticker_display() - elif choice == "0": - break - else: - print("Invalid choice. Please try again.") +from stock_analysis_program.cli import main if __name__ == "__main__": diff --git a/poetry.lock b/poetry.lock index 3cd0438..bce6e23 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,38 +1,1564 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. + +[[package]] +name = "beautifulsoup4" +version = "4.14.3" +description = "Screen-scraping library" +optional = false +python-versions = ">=3.7.0" +groups = ["main"] +files = [ + {file = "beautifulsoup4-4.14.3-py3-none-any.whl", hash = "sha256:0918bfe44902e6ad8d57732ba310582e98da931428d231a5ecb9e7c703a735bb"}, + {file = "beautifulsoup4-4.14.3.tar.gz", hash = "sha256:6292b1c5186d356bba669ef9f7f051757099565ad9ada5dd630bd9de5fa7fb86"}, +] + +[package.dependencies] +soupsieve = ">=1.6.1" +typing-extensions = ">=4.0.0" + +[package.extras] +cchardet = ["cchardet"] +chardet = ["chardet"] 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The examples use common tickers so you can run them as-is, then replace the symbols with your own watchlist.\n", + "\n", + "> These exercises are for educational analysis only and are not financial advice." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setup\n", + "\n", + "Import the package classes used throughout the notebook. If you are running this from an installed PyPI package, use `pip install stock-analysis-program` first." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from stock_analysis_program import (\n", + " CurrentPricesTickerDisplay,\n", + " FinancialMetricsFetcher,\n", + " FinancialMetricsPlotter,\n", + " RevenueGrowthFetcher,\n", + " RevenueGrowthPlotter,\n", + " StockDataFetcher,\n", + " StockExchangePerformancePlotter,\n", + " StockPricePlotter,\n", + " StockSummaryFetcher,\n", + " StockVolatilityPlotter,\n", + ")\n", + "\n", + "WATCHLIST = [\"AAPL\", \"MSFT\", \"GOOGL\"]\n", + "START_DATE = \"2023-01-01\"\n", + "END_DATE = \"2024-01-01\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Quick Stock Price Charting\n", + "\n", + "Practical use: quickly visualize a stock's historical closing price to understand its general trend over a chosen period. This is useful as a first look before doing deeper fundamental or technical analysis." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "price_plotter = StockPricePlotter(\"AAPL\")\n", + "price_plotter.plot_closing_prices(START_DATE, END_DATE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. Moving Average Analysis\n", + "\n", + "Practical use: moving averages smooth price action and help highlight trend direction. A short moving average can show recent momentum, while a longer one can show broader trend strength." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "price_plotter.plot_moving_averages(\n", + " START_DATE,\n", + " END_DATE,\n", + " window_sizes=[20, 50, 200],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3. Basic Stock Screening\n", + "\n", + "Practical use: collect valuation and profitability metrics for a watchlist. This can help identify which companies deserve deeper research based on market cap, P/E ratio, price-to-book, and profit margins." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "metrics_fetcher = FinancialMetricsFetcher(WATCHLIST)\n", + "financial_metrics = metrics_fetcher.fetch_financial_metrics()\n", + "financial_metrics\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4. Portfolio Comparison\n", + "\n", + "Practical use: compare multiple holdings or candidates visually over the same period. This can help you see which stock outperformed and when relative momentum changed." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "portfolio_plotter = StockPricePlotter(WATCHLIST)\n", + "portfolio_plotter.plot_closing_prices(START_DATE, END_DATE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 5. Index Performance Comparison\n", + "\n", + "Practical use: compare broad market indexes such as the S&P 500, Dow Jones Industrial Average, and Nasdaq Composite. Normalized prices make relative performance easier to compare." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "index_plotter = StockExchangePerformancePlotter([\"^GSPC\", \"^DJI\", \"^IXIC\"])\n", + "index_plotter.plot_performance(START_DATE, END_DATE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6. Revenue Growth Checks\n", + "\n", + "Practical use: revenue growth can show whether a company's top line is expanding or slowing. This is useful for comparing business momentum across several companies." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "growth_fetcher = RevenueGrowthFetcher(WATCHLIST)\n", + "revenue_growth = growth_fetcher.fetch_revenue_growth()\n", + "revenue_growth\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 7. Revenue Growth Visualization\n", + "\n", + "Practical use: a chart can make revenue growth comparisons easier to scan than raw numbers, especially when reviewing several companies at once." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "growth_plotter = RevenueGrowthPlotter(WATCHLIST)\n", + "growth_plotter.plot_revenue_growth()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8. Volatility Analysis\n", + "\n", + "Practical use: rolling volatility helps estimate how much a stock's returns fluctuate. This is useful when comparing risk across stocks or deciding whether a position matches your risk tolerance." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "volatility_plotter = StockVolatilityPlotter(WATCHLIST)\n", + "volatility_plotter.plot_volatility(\n", + " START_DATE,\n", + " END_DATE,\n", + " window_size=30,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 9. Watchlist Summaries\n", + "\n", + "Practical use: fetch a quick company overview for each ticker, including name, sector, industry, exchange, country, market cap, and other summary fields." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "summary_fetcher = StockSummaryFetcher(WATCHLIST)\n", + "summaries = summary_fetcher.get_summaries()\n", + "summaries\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 10. Average Volume and Moving Average Data\n", + "\n", + "Practical use: average volume can help judge liquidity, while computed moving average series can be reused in custom models, reports, or dashboards." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "data_fetcher = StockDataFetcher(\"AAPL\")\n", + "historical_data = data_fetcher.fetch_historical_data(period=\"1y\")\n", + "average_volume = data_fetcher.get_average_volume(historical_data)\n", + "moving_averages = data_fetcher.calculate_moving_averages(\n", + " historical_data, window_sizes=[20, 50]\n", + ")\n", + "\n", + "average_volume, moving_averages.keys()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 11. Current Price Checks\n", + "\n", + "Practical use: fetch current prices for a watchlist when you need a simple snapshot. In scripts or dashboards, use `fetch_current_prices()` instead of the continuous CLI-style ticker display." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ticker_display = CurrentPricesTickerDisplay(WATCHLIST, interval=10)\n", + "current_prices = ticker_display.fetch_current_prices()\n", + "current_prices\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 12. Automated Reporting Starter\n", + "\n", + "Practical use: combine metrics, summaries, and charts into a repeatable workflow. This pattern can be scheduled daily, weekly, or monthly to generate a consistent watchlist report." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def build_watchlist_snapshot(tickers):\n", + " metrics = FinancialMetricsFetcher(tickers).fetch_financial_metrics()\n", + " growth = RevenueGrowthFetcher(tickers).fetch_revenue_growth()\n", + " summaries = StockSummaryFetcher(tickers).get_summaries()\n", + " return {\n", + " \"metrics\": metrics,\n", + " \"revenue_growth\": growth,\n", + " \"summaries\": summaries,\n", + " }\n", + "\n", + "\n", + "snapshot = build_watchlist_snapshot(WATCHLIST)\n", + "snapshot[\"metrics\"]\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 13. Sector or Peer Comparison\n", + "\n", + "Practical use: compare companies in the same broad peer group. This example uses large technology companies, but you can swap in banks, energy companies, retailers, healthcare firms, or any custom peer set." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "tech_peers = [\"AAPL\", \"MSFT\", \"GOOGL\", \"META\"]\n", + "peer_metrics = FinancialMetricsFetcher(tech_peers).fetch_financial_metrics()\n", + "peer_metrics\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 14. Report-Friendly Plotting\n", + "\n", + "Practical use: plotter methods can be used inside notebooks or reporting scripts. With the current published package, the methods display plots directly; for saved reports, generate the chart and then save the active Matplotlib figure." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "StockPricePlotter(\"MSFT\").plot_closing_prices(START_DATE, END_DATE)\n", + "plt.gcf().savefig(\"msft_closing_price.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Next Steps\n", + "\n", + "Try replacing `WATCHLIST`, `START_DATE`, and `END_DATE` with your own research universe. For a more advanced project, combine these outputs into a scheduled report, a Streamlit dashboard, or a notebook template for repeated stock reviews." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/pyproject.toml b/pyproject.toml index 04fa42d..70e251d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,41 +1,47 @@ -[tool.poetry] +[project] name = "stock-analysis-program" -version = "1.0.8" +version = "1.2.0" description = "A Python-based toolkit for fetching and visualizing financial data and metrics for stocks." readme = "README.md" +requires-python = ">=3.11,<4.0" authors = [ - "Thaddeus Thomas ", - "Fernando McKenzie " + { name = "Thaddeus Thomas", email = "thaddeus.r.thomas@gmail.com" }, + { name = "Fernando McKenzie", email = "fernando.a.mckenzie@live.com" }, ] license = "MIT" -homepage = "https://vcwtech.com/stock-analysis-program" -repository = "https://github.com/visionary-code-works/stock-analysis-program" -documentation = "https://github.com/visionary-code-works/stock-analysis-program/docs" classifiers = [ "Programming Language :: Python :: 3", - "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Intended Audience :: Financial and Insurance Industry", "Topic :: Office/Business :: Financial :: Investment", "Development Status :: 4 - Beta" ] +dependencies = [ + "yfinance>=0.2.37,<0.3.0", + "matplotlib>=3.8.3,<4.0.0", + "pandas>=2.2.1,<3.0.0", +] + +[project.urls] +Homepage = "https://vcwtech.com/stock-analysis-program" +Repository = "https://github.com/visionary-code-works/stock-analysis-program" +Documentation = "https://github.com/visionary-code-works/stock-analysis-program/tree/main/docs" + +[project.scripts] +stock-analysis = "stock_analysis_program.cli:main" + +[tool.poetry] packages = [ { include = "stock_analysis_program", from = "src" }, ] -[tool.poetry.dependencies] -python = "^3.11" -yfinance = "^0.2.37" -matplotlib = "^3.8.3" -pandas = "^2.2.1" - -[tool.poetry.dev-dependencies] +[tool.poetry.group.dev.dependencies] pytest = "^8.1.1" -[[tool.poetry.source]] -name = "StockAnalysisProgram" -url = "https://github.com/Visionary-Code-Works/StockAnalysisProgram" -priority = "primary" +[tool.pytest.ini_options] +pythonpath = ["src"] +norecursedirs = [".git", ".pytest_cache", "pytest-cache-files-*"] +addopts = "-p no:cacheprovider" [build-system] requires = ["poetry>=1.8.2"] diff --git a/requirements.txt b/requirements.txt index 5a44e5a..36ce2b9 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,5 +1,3 @@ -pytest -pandas>=1.0 -numpy>=1.18 -matplotlib>=3.2 -yfinance \ No newline at end of file +pandas>=2.2.1 +matplotlib>=3.8.3 +yfinance>=0.2.37 diff --git a/src/stock_analysis_program/__init__.py b/src/stock_analysis_program/__init__.py index 995135a..cdf310f 100644 --- a/src/stock_analysis_program/__init__.py +++ b/src/stock_analysis_program/__init__.py @@ -14,3 +14,21 @@ StockExchangePerformancePlotter, CurrentPricesTickerDisplay, ) +from .cli import main +from .exceptions import DataFetchError, StockAnalysisError + +__all__ = [ + "StockDataFetcher", + "StockSummaryFetcher", + "FinancialMetricsFetcher", + "RevenueGrowthFetcher", + "StockPricePlotter", + "FinancialMetricsPlotter", + "RevenueGrowthPlotter", + "StockVolatilityPlotter", + "StockExchangePerformancePlotter", + "CurrentPricesTickerDisplay", + "DataFetchError", + "StockAnalysisError", + "main", +] diff --git a/src/stock_analysis_program/_utils.py b/src/stock_analysis_program/_utils.py new file mode 100644 index 0000000..93b4666 --- /dev/null +++ b/src/stock_analysis_program/_utils.py @@ -0,0 +1,21 @@ +"""Internal helpers shared by fetchers and plotters.""" + +from .exceptions import DataFetchError + + +def normalize_tickers(tickers): + if isinstance(tickers, str): + tickers = [tickers] + + normalized = [str(ticker).strip().upper() for ticker in tickers if str(ticker).strip()] + if not normalized: + raise ValueError("At least one ticker symbol is required.") + + return normalized + + +def require_columns(data, columns, context): + missing = [column for column in columns if column not in data.columns] + if data.empty or missing: + detail = "empty data" if data.empty else f"missing columns: {', '.join(missing)}" + raise DataFetchError(f"No usable data returned for {context} ({detail}).") diff --git a/src/stock_analysis_program/cli.py b/src/stock_analysis_program/cli.py new file mode 100644 index 0000000..02a2bb9 --- /dev/null +++ b/src/stock_analysis_program/cli.py @@ -0,0 +1,161 @@ +"""Command-line interface for stock_analysis_program.""" + +from .fetcher import ( + FinancialMetricsFetcher, + RevenueGrowthFetcher, + StockDataFetcher, + StockSummaryFetcher, +) +from .plotter import ( + CurrentPricesTickerDisplay, + FinancialMetricsPlotter, + RevenueGrowthPlotter, + StockExchangePerformancePlotter, + StockPricePlotter, + StockVolatilityPlotter, +) + + +def _parse_tickers(prompt): + return [ticker.strip().upper() for ticker in input(prompt).split(",") if ticker.strip()] + + +def use_stock_data_fetcher(): + ticker = input("Enter a stock ticker (e.g., AAPL, GOOGL): ").strip().upper() + fetcher = StockDataFetcher(ticker) + historical_data = fetcher.fetch_historical_data() + moving_averages = fetcher.calculate_moving_averages(historical_data) + average_volume = fetcher.get_average_volume(historical_data) + financial_metrics = fetcher.get_financial_metrics() + + print(f"Moving Averages for {ticker}: {moving_averages}") + print(f"Average Volume for {ticker}: {average_volume}") + print(f"Financial Metrics for {ticker}: {financial_metrics}") + + +def use_stock_summary_fetcher(): + tickers = _parse_tickers("Enter stock ticker(s) separated by commas (e.g., GOOGL, AAPL): ") + fetcher = StockSummaryFetcher(tickers) + summaries = fetcher.get_summaries() + + for summary in summaries: + print(f"\nSummary for {summary['Ticker']}:\n") + for key, value in summary.items(): + print(f"{key}: {value if value is not None else 'N/A'}") + + +def use_financial_metrics_fetcher(): + tickers = _parse_tickers( + "Enter stock ticker(s) separated by commas for financial metrics (e.g., AAPL, MSFT): " + ) + fetcher = FinancialMetricsFetcher(tickers) + print("\nFinancial Metrics:") + print(fetcher.fetch_financial_metrics()) + + +def use_revenue_growth_fetcher(): + tickers = _parse_tickers( + "Enter stock ticker(s) separated by commas for revenue growth (e.g., AAPL, MSFT): " + ) + fetcher = RevenueGrowthFetcher(tickers) + revenue_growth = fetcher.fetch_revenue_growth() + + print("\nYear-over-Year Revenue Growth:") + for ticker, growth in revenue_growth.items(): + print(f"{ticker}: {growth:.2%}" if growth is not None else f"{ticker}: Data not available") + + +def use_stock_price_plotter(): + tickers = _parse_tickers( + "Enter stock ticker(s) separated by commas for price plotting (e.g., AAPL, MSFT): " + ) + start_date = input("Enter start date (YYYY-MM-DD): ") + end_date = input("Enter end date (YYYY-MM-DD): ") + plotter = StockPricePlotter(tickers) + plotter.plot_closing_prices(start_date, end_date) + plotter.plot_moving_averages(start_date, end_date) + + +def use_financial_metrics_plotter(): + tickers = _parse_tickers( + "Enter stock ticker(s) separated by commas for financial metrics plotting (e.g., AAPL, MSFT): " + ) + FinancialMetricsPlotter(tickers).plot_metrics() + + +def use_revenue_growth_plotter(): + tickers = _parse_tickers( + "Enter stock ticker(s) separated by commas for revenue growth plotting (e.g., AAPL, MSFT): " + ) + RevenueGrowthPlotter(tickers).plot_revenue_growth() + + +def use_stock_volatility_plotter(): + tickers = _parse_tickers( + "Enter stock ticker(s) separated by commas for volatility plotting (e.g., AAPL, MSFT): " + ) + start_date = input("Enter start date (YYYY-MM-DD): ") + end_date = input("Enter end date (YYYY-MM-DD): ") + StockVolatilityPlotter(tickers).plot_volatility(start_date, end_date) + + +def use_stock_exchange_performance_plotter(): + indices = _parse_tickers( + "Enter stock index symbols separated by commas (e.g., ^GSPC, ^DJI): " + ) + start_date = input("Enter start date (YYYY-MM-DD): ") + end_date = input("Enter end date (YYYY-MM-DD): ") + StockExchangePerformancePlotter(indices).plot_performance(start_date, end_date) + + +def use_current_prices_ticker_display(): + tickers = _parse_tickers( + "Enter stock ticker(s) separated by commas for current price display (e.g., AAPL, MSFT): " + ) + interval = int(input("Enter display interval in seconds: ")) + CurrentPricesTickerDisplay(tickers, interval).display_ticker() + + +def main(): + actions = { + "1": use_stock_data_fetcher, + "2": use_stock_summary_fetcher, + "3": use_financial_metrics_fetcher, + "4": use_revenue_growth_fetcher, + "5": use_stock_price_plotter, + "6": use_financial_metrics_plotter, + "7": use_revenue_growth_plotter, + "8": use_stock_volatility_plotter, + "9": use_stock_exchange_performance_plotter, + "10": use_current_prices_ticker_display, + } + + while True: + print( + "\nStock Data Analysis Menu\n" + "1. Use Stock Data Fetcher\n" + "2. Use Stock Summary Fetcher\n" + "3. Use Financial Metrics Fetcher\n" + "4. Use Revenue Growth Fetcher\n" + "5. Use Stock Price Plotter\n" + "6. Use Financial Metrics Plotter\n" + "7. Use Revenue Growth Plotter\n" + "8. Use Stock Volatility Plotter\n" + "9. Use Stock Exchange Performance Plotter\n" + "10. Use Current Prices Ticker Display\n" + "0. Exit\n" + ) + + choice = input("Enter your choice: ") + if choice == "0": + break + + action = actions.get(choice) + if action is None: + print("Invalid choice. Please try again.") + continue + + try: + action() + except Exception as exc: + print(f"Error: {exc}") diff --git a/src/stock_analysis_program/exceptions.py b/src/stock_analysis_program/exceptions.py new file mode 100644 index 0000000..8bf93b8 --- /dev/null +++ b/src/stock_analysis_program/exceptions.py @@ -0,0 +1,9 @@ +"""Custom exceptions for stock_analysis_program.""" + + +class StockAnalysisError(Exception): + """Base exception for package-specific errors.""" + + +class DataFetchError(StockAnalysisError): + """Raised when a data provider returns no usable data.""" diff --git a/src/stock_analysis_program/fetcher/financial_metrics_fetcher.py b/src/stock_analysis_program/fetcher/financial_metrics_fetcher.py index 873fb61..385a212 100644 --- a/src/stock_analysis_program/fetcher/financial_metrics_fetcher.py +++ b/src/stock_analysis_program/fetcher/financial_metrics_fetcher.py @@ -13,6 +13,8 @@ import yfinance as yf import pandas as pd +from .._utils import normalize_tickers + class FinancialMetricsFetcher: """ A class that fetches financial metrics for a list of stock tickers. @@ -33,7 +35,7 @@ def __init__(self, tickers): tickers (list of str): A list of stock ticker symbols (e.g., ['AAPL', 'MSFT']) for which financial metrics are to be fetched. """ - self.tickers = tickers if isinstance(tickers, list) else [tickers] + self.tickers = normalize_tickers(tickers) def fetch_financial_metrics(self): """ @@ -49,8 +51,6 @@ def fetch_financial_metrics(self): for each financial metric. """ financial_data_list = [] - - financial_data = pd.DataFrame() for ticker in self.tickers: stock = yf.Ticker(ticker) info = stock.info diff --git a/src/stock_analysis_program/fetcher/revenue_growth_fetcher.py b/src/stock_analysis_program/fetcher/revenue_growth_fetcher.py index 64ee77c..5ef9f1e 100644 --- a/src/stock_analysis_program/fetcher/revenue_growth_fetcher.py +++ b/src/stock_analysis_program/fetcher/revenue_growth_fetcher.py @@ -12,6 +12,8 @@ import yfinance as yf +from .._utils import normalize_tickers + class RevenueGrowthFetcher: """ @@ -29,7 +31,7 @@ def __init__(self, tickers): tickers (list of str): Stock tickers to fetch the revenue growth for. """ - self.tickers = tickers if isinstance(tickers, list) else [tickers] + self.tickers = normalize_tickers(tickers) def fetch_revenue_growth(self): """ @@ -44,14 +46,15 @@ def fetch_revenue_growth(self): for ticker in self.tickers: company = yf.Ticker(ticker) income_statement = company.financials - if "Total Revenue" in income_statement.index: + if not income_statement.empty and "Total Revenue" in income_statement.index: revenue = income_statement.loc["Total Revenue"] revenue_growth = revenue.pct_change( periods=-1 ) # Negative periods for year-over-year growth - growth_data[ticker] = revenue_growth.dropna().iloc[ - 0 - ] # Most recent growth value + revenue_growth = revenue_growth.dropna() + growth_data[ticker] = ( + revenue_growth.iloc[0] if not revenue_growth.empty else None + ) else: growth_data[ticker] = None return growth_data diff --git a/src/stock_analysis_program/fetcher/stock_data_fetcher.py b/src/stock_analysis_program/fetcher/stock_data_fetcher.py index fe854a5..6509be0 100644 --- a/src/stock_analysis_program/fetcher/stock_data_fetcher.py +++ b/src/stock_analysis_program/fetcher/stock_data_fetcher.py @@ -12,6 +12,8 @@ import yfinance as yf +from .._utils import require_columns + class StockDataFetcher: """ @@ -30,8 +32,10 @@ def __init__(self, ticker): ticker (str): The stock ticker symbol for which the data is to be fetched. """ - self.ticker = ticker - self.stock = yf.Ticker(ticker) + self.ticker = str(ticker).strip().upper() + if not self.ticker: + raise ValueError("A ticker symbol is required.") + self.stock = yf.Ticker(self.ticker) def fetch_historical_data(self, period="1y"): """ @@ -45,9 +49,11 @@ def fetch_historical_data(self, period="1y"): pandas.DataFrame: A DataFrame containing historical stock data for the specified period. """ - return self.stock.history(period=period) + data = self.stock.history(period=period) + require_columns(data, ["Close", "Volume"], self.ticker) + return data - def calculate_moving_averages(self, data, window_sizes=[20, 50, 200]): + def calculate_moving_averages(self, data, window_sizes=None): """ Calculates and returns moving averages for given window sizes. @@ -60,6 +66,8 @@ def calculate_moving_averages(self, data, window_sizes=[20, 50, 200]): dict: A dictionary with keys as window sizes and values as the corresponding moving averages. """ + window_sizes = window_sizes or [20, 50, 200] + require_columns(data, ["Close"], self.ticker) moving_averages = {} for window in window_sizes: ma = data["Close"].rolling(window=window).mean() @@ -76,6 +84,7 @@ def get_average_volume(self, data): Returns: float: The average trading volume for the stock. """ + require_columns(data, ["Volume"], self.ticker) return data["Volume"].mean() def get_financial_metrics(self): diff --git a/src/stock_analysis_program/fetcher/stock_summary_fetcher.py b/src/stock_analysis_program/fetcher/stock_summary_fetcher.py index 1781c41..972a185 100644 --- a/src/stock_analysis_program/fetcher/stock_summary_fetcher.py +++ b/src/stock_analysis_program/fetcher/stock_summary_fetcher.py @@ -12,6 +12,8 @@ import yfinance as yf +from .._utils import normalize_tickers + class StockSummaryFetcher: """ A class that fetches summary information for a list of stock tickers. @@ -34,7 +36,7 @@ def __init__(self, tickers): summary information is to be fetched. Can be a single ticker (str) or a list of tickers. """ - self.tickers = tickers if isinstance(tickers, list) else [tickers] + self.tickers = normalize_tickers(tickers) def fetch_summary(self, ticker): """ diff --git a/src/stock_analysis_program/plotter/current_prices_ticker_display.py b/src/stock_analysis_program/plotter/current_prices_ticker_display.py index 582ba6d..a8e2e4c 100644 --- a/src/stock_analysis_program/plotter/current_prices_ticker_display.py +++ b/src/stock_analysis_program/plotter/current_prices_ticker_display.py @@ -13,6 +13,8 @@ import time import yfinance as yf +from .._utils import normalize_tickers + class CurrentPricesTickerDisplay: """ A class for displaying current prices of a list of stock tickers in a @@ -34,7 +36,7 @@ def __init__(self, tickers, interval=10): interval (int, optional): Time interval in seconds between updates of the ticker display. Defaults to 10 seconds. """ - self.tickers = tickers if isinstance(tickers, list) else [tickers] + self.tickers = normalize_tickers(tickers) self.interval = interval def fetch_current_prices(self): diff --git a/src/stock_analysis_program/plotter/financial_metrics_plotter.py b/src/stock_analysis_program/plotter/financial_metrics_plotter.py index b405ad9..5f105fb 100644 --- a/src/stock_analysis_program/plotter/financial_metrics_plotter.py +++ b/src/stock_analysis_program/plotter/financial_metrics_plotter.py @@ -12,7 +12,7 @@ class to fetch financial data and then plots these metrics in a histogram import matplotlib.pyplot as plt import pandas as pd -from src.stock_analysis_program.fetcher.financial_metrics_fetcher import FinancialMetricsFetcher +from ..fetcher.financial_metrics_fetcher import FinancialMetricsFetcher class FinancialMetricsPlotter: """A class for plotting financial metrics of stocks. @@ -35,7 +35,7 @@ def __init__(self, tickers): """ self.fetcher = FinancialMetricsFetcher(tickers) - def plot_metrics(self): + def plot_metrics(self, show=True): """Plots histograms of financial metrics for the given tickers. Fetches financial metrics using the FinancialMetricsFetcher instance @@ -47,15 +47,20 @@ def plot_metrics(self): """ financial_data = self.fetcher.fetch_financial_metrics() + figures = [] for column in financial_data.columns[1:]: # Skip the 'Ticker' column - plt.figure(figsize=(10, 6)) - # Check if the data is numeric and not empty - if pd.to_numeric(financial_data[column], errors='coerce').notnull().all(): - plt.hist(financial_data[column].dropna(), bins=15, alpha=0.7) - plt.title(f'Histogram of {column} for Selected Stocks') - plt.xlabel(column) - plt.ylabel('Frequency') - plt.grid(True) + numeric_values = pd.to_numeric(financial_data[column], errors="coerce").dropna() + if numeric_values.empty: + continue + + fig, ax = plt.subplots(figsize=(10, 6)) + ax.hist(numeric_values, bins=15, alpha=0.7) + ax.set_title(f"Histogram of {column} for Selected Stocks") + ax.set_xlabel(column) + ax.set_ylabel("Frequency") + ax.grid(True) + figures.append((fig, ax)) + if show: plt.show() - else: - print(f"Skipping histogram for {column} as it contains non-numeric data.") + + return figures diff --git a/src/stock_analysis_program/plotter/revenue_growth_plotter.py b/src/stock_analysis_program/plotter/revenue_growth_plotter.py index fb0960e..f37e228 100644 --- a/src/stock_analysis_program/plotter/revenue_growth_plotter.py +++ b/src/stock_analysis_program/plotter/revenue_growth_plotter.py @@ -32,7 +32,7 @@ def __init__(self, tickers): """ self.fetcher = RevenueGrowthFetcher(tickers) - def plot_revenue_growth(self): + def plot_revenue_growth(self, show=True): """ Plots the year-over-year revenue growth for each ticker. @@ -42,14 +42,20 @@ def plot_revenue_growth(self): """ revenue_growth = self.fetcher.fetch_revenue_growth() - # Prepare data for plotting - tickers = list(revenue_growth.keys()) - growth_values = list(revenue_growth.values()) - - plt.figure(figsize=(10, 6)) - plt.bar(tickers, growth_values, color='green') - plt.title('Year-over-Year Revenue Growth') - plt.xlabel('Ticker') - plt.ylabel('Growth (%)') - plt.grid(True) - plt.show() + filtered = { + ticker: growth + for ticker, growth in revenue_growth.items() + if growth is not None + } + tickers = list(filtered.keys()) + growth_values = list(filtered.values()) + + fig, ax = plt.subplots(figsize=(10, 6)) + ax.bar(tickers, growth_values, color="green") + ax.set_title("Year-over-Year Revenue Growth") + ax.set_xlabel("Ticker") + ax.set_ylabel("Growth (%)") + ax.grid(True) + if show: + plt.show() + return fig, ax diff --git a/src/stock_analysis_program/plotter/stock_exchange_performance_plotter.py b/src/stock_analysis_program/plotter/stock_exchange_performance_plotter.py index 78f157b..07c1a87 100644 --- a/src/stock_analysis_program/plotter/stock_exchange_performance_plotter.py +++ b/src/stock_analysis_program/plotter/stock_exchange_performance_plotter.py @@ -12,6 +12,8 @@ import yfinance as yf import matplotlib.pyplot as plt +from .._utils import normalize_tickers, require_columns + class StockExchangePerformancePlotter: """A class for comparing the performance of different stock indices. @@ -31,9 +33,9 @@ def __init__(self, indices): Args: indices (list of str): Stock index symbols for comparison. """ - self.indices = indices if isinstance(indices, list) else [indices] + self.indices = normalize_tickers(indices) - def plot_performance(self, start_date, end_date): + def plot_performance(self, start_date, end_date, show=True): """Plots the normalized closing prices of the indices for comparison. Args: @@ -46,15 +48,18 @@ def plot_performance(self, start_date, end_date): to visualize and compare their performance over the specified time period. """ - plt.figure(figsize=(14, 8)) + fig, ax = plt.subplots(figsize=(14, 8)) for index in self.indices: data = yf.download(index, start=start_date, end=end_date) + require_columns(data, ["Close"], index) normalized_data = data['Close'] / data['Close'].iloc[0] - plt.plot(normalized_data, label=index) - - plt.title('Comparative Performance of Stock Indices') - plt.xlabel('Date') - plt.ylabel('Normalized Closing Price') - plt.legend() - plt.grid(True) - plt.show() + ax.plot(normalized_data, label=index) + + ax.set_title('Comparative Performance of Stock Indices') + ax.set_xlabel('Date') + ax.set_ylabel('Normalized Closing Price') + ax.legend() + ax.grid(True) + if show: + plt.show() + return fig, ax diff --git a/src/stock_analysis_program/plotter/stock_price_plotter.py b/src/stock_analysis_program/plotter/stock_price_plotter.py index 264534a..dfab191 100644 --- a/src/stock_analysis_program/plotter/stock_price_plotter.py +++ b/src/stock_analysis_program/plotter/stock_price_plotter.py @@ -10,6 +10,8 @@ import yfinance as yf import matplotlib.pyplot as plt +from .._utils import normalize_tickers, require_columns + class StockPricePlotter: """ A class for plotting stock prices and moving averages. @@ -27,9 +29,9 @@ def __init__(self, tickers): tickers (list of str): Stock tickers to plot prices and moving averages for. """ - self.tickers = tickers if isinstance(tickers, list) else [tickers] + self.tickers = normalize_tickers(tickers) - def plot_closing_prices(self, start_date, end_date): + def plot_closing_prices(self, start_date, end_date, show=True): """ Plots the closing prices of the stocks over a specified period. @@ -37,18 +39,23 @@ def plot_closing_prices(self, start_date, end_date): start_date (str): Start date for the data in 'YYYY-MM-DD' format. end_date (str): End date for the data in 'YYYY-MM-DD' format. """ + figures = [] for ticker in self.tickers: data = yf.download(ticker, start=start_date, end=end_date) - plt.figure(figsize=(10, 6)) - plt.plot(data['Close'], label=f'{ticker} Close Price') - plt.title(f'{ticker} Closing Prices') - plt.xlabel('Date') - plt.ylabel('Price') - plt.legend() - plt.grid(True) - plt.show() + require_columns(data, ["Close"], ticker) + fig, ax = plt.subplots(figsize=(10, 6)) + ax.plot(data["Close"], label=f"{ticker} Close Price") + ax.set_title(f"{ticker} Closing Prices") + ax.set_xlabel("Date") + ax.set_ylabel("Price") + ax.legend() + ax.grid(True) + figures.append((fig, ax)) + if show: + plt.show() + return figures - def plot_moving_averages(self, start_date, end_date, window_sizes=[20, 50]): + def plot_moving_averages(self, start_date, end_date, window_sizes=None, show=True): """ Plots moving averages along with closing prices for the stocks. @@ -58,16 +65,22 @@ def plot_moving_averages(self, start_date, end_date, window_sizes=[20, 50]): window_sizes (list of int, optional): Window sizes for calculating moving averages. Defaults to [20, 50]. """ + window_sizes = window_sizes or [20, 50] + figures = [] for ticker in self.tickers: data = yf.download(ticker, start=start_date, end=end_date) - plt.figure(figsize=(10, 6)) - plt.plot(data['Close'], label=f'{ticker} Closing Prices', alpha=0.5) + require_columns(data, ["Close"], ticker) + fig, ax = plt.subplots(figsize=(10, 6)) + ax.plot(data["Close"], label=f"{ticker} Closing Prices", alpha=0.5) for window in window_sizes: - ma = data['Close'].rolling(window=window).mean() - plt.plot(ma, label=f'{window}-Day MA') - plt.title(f'{ticker} Closing Prices and Moving Averages') - plt.xlabel('Date') - plt.ylabel('Price') - plt.legend() - plt.grid(True) - plt.show() + ma = data["Close"].rolling(window=window).mean() + ax.plot(ma, label=f"{window}-Day MA") + ax.set_title(f"{ticker} Closing Prices and Moving Averages") + ax.set_xlabel("Date") + ax.set_ylabel("Price") + ax.legend() + ax.grid(True) + figures.append((fig, ax)) + if show: + plt.show() + return figures diff --git a/src/stock_analysis_program/plotter/stock_volatility_plotter.py b/src/stock_analysis_program/plotter/stock_volatility_plotter.py index 207075d..581d342 100644 --- a/src/stock_analysis_program/plotter/stock_volatility_plotter.py +++ b/src/stock_analysis_program/plotter/stock_volatility_plotter.py @@ -10,6 +10,8 @@ import yfinance as yf import matplotlib.pyplot as plt +from .._utils import normalize_tickers, require_columns + class StockVolatilityPlotter: """ @@ -26,9 +28,9 @@ def __init__(self, tickers): Args: tickers (list of str): Stock tickers to analyze for volatility. """ - self.tickers = tickers if isinstance(tickers, list) else [tickers] + self.tickers = normalize_tickers(tickers) - def plot_volatility(self, start_date, end_date, window_size=30): + def plot_volatility(self, start_date, end_date, window_size=30, show=True): """ Calculates and plots the rolling volatility for each ticker. @@ -38,20 +40,23 @@ def plot_volatility(self, start_date, end_date, window_size=30): window_size (int, optional): Window size in days for calculating rolling volatility. Defaults to 30. """ - plt.figure(figsize=(12, 8)) + fig, ax = plt.subplots(figsize=(12, 8)) for ticker in self.tickers: data = yf.download(ticker, start=start_date, end=end_date) + require_columns(data, ["Close"], ticker) # Calculate daily returns daily_returns = data['Close'].pct_change() # Calculate rolling standard deviation (volatility) rolling_volatility = daily_returns.rolling(window=window_size).std() * (252 ** 0.5) # Annualized - plt.plot(rolling_volatility, label=f'{ticker} Volatility') + ax.plot(rolling_volatility, label=f'{ticker} Volatility') - plt.title(f'{window_size}-Day Rolling Volatility (Annualized)') - plt.xlabel('Date') - plt.ylabel('Volatility') - plt.legend() - plt.grid(True) - plt.show() + ax.set_title(f'{window_size}-Day Rolling Volatility (Annualized)') + ax.set_xlabel('Date') + ax.set_ylabel('Volatility') + ax.legend() + ax.grid(True) + if show: + plt.show() + return fig, ax diff --git a/tests/__init__.py b/tests/__init__.py index af4e1a2..8b13789 100644 --- a/tests/__init__.py +++ b/tests/__init__.py @@ -1,17 +1 @@ -# tests/__init__.py -from .test_fetcher import ( - test_financial_metrics_fetcher, - test_revenue_growth_fetcher_initialization, - test_stock_data_fetcher, - test_stock_summary_fetcher_initialization -) -from .test_plotter import ( - test_current_prices_ticker_display_initialization, - test_financial_metrics_plotter, - test_revenue_growth_plotter_initialization, - test_stock_exchange_performance_plotter, - test_stock_price_plotter_initialization, - test_stock_volatility_plotter_initialization -) -from .test_main import test_main_exists diff --git a/tests/test_fetcher/__init__.py b/tests/test_fetcher/__init__.py index da51016..8b13789 100644 --- a/tests/test_fetcher/__init__.py +++ b/tests/test_fetcher/__init__.py @@ -1,6 +1 @@ -# tests/test_fetcher/__init__.py -from .test_financial_metrics_fetcher import test_financial_metrics_fetcher -from .test_revenue_growth_fetcher import test_revenue_growth_fetcher_initialization -from .test_stock_data_fetcher import test_stock_data_fetcher -from .test_stock_summary_fetcher import test_stock_summary_fetcher_initialization diff --git a/tests/test_fetcher/test_financial_metrics_fetcher.py b/tests/test_fetcher/test_financial_metrics_fetcher.py index 7beabee..8334c8d 100644 --- a/tests/test_fetcher/test_financial_metrics_fetcher.py +++ b/tests/test_fetcher/test_financial_metrics_fetcher.py @@ -1,9 +1,20 @@ -# tests/test_fetcher/test_financial_metrics_fetcher.py +from unittest.mock import Mock, patch -import pytest -from src.stock_analysis_program.fetcher import FinancialMetricsFetcher +from stock_analysis_program.fetcher import FinancialMetricsFetcher def test_financial_metrics_fetcher(): - fetcher = FinancialMetricsFetcher(['AAPL']) - metrics = fetcher.fetch_financial_metrics() - assert 'AAPL' in metrics['Ticker'].values, "AAPL should be in the fetched financial metrics." + stock = Mock() + stock.info = { + "marketCap": 100, + "trailingPE": 20, + "forwardPE": 18, + "priceToBook": 3, + "profitMargins": 0.25, + } + + with patch("stock_analysis_program.fetcher.financial_metrics_fetcher.yf.Ticker", return_value=stock): + fetcher = FinancialMetricsFetcher(["aapl"]) + metrics = fetcher.fetch_financial_metrics() + + assert "AAPL" in metrics["Ticker"].values + assert metrics.loc[0, "Market Cap"] == 100 diff --git a/tests/test_fetcher/test_revenue_growth_fetcher.py b/tests/test_fetcher/test_revenue_growth_fetcher.py index d40c531..88acae2 100644 --- a/tests/test_fetcher/test_revenue_growth_fetcher.py +++ b/tests/test_fetcher/test_revenue_growth_fetcher.py @@ -1,8 +1,20 @@ -# tests/test_fetcher/test_revenue_growth_fetcher.py +from unittest.mock import Mock, patch +import pandas as pd import pytest -from src.stock_analysis_program import RevenueGrowthFetcher -def test_revenue_growth_fetcher_initialization(): - fetcher = RevenueGrowthFetcher(["AAPL"]) - assert fetcher is not None, "RevenueGrowthFetcher should be initialized." +from stock_analysis_program import RevenueGrowthFetcher + +def test_revenue_growth_fetcher_returns_latest_growth(): + stock = Mock() + stock.financials = pd.DataFrame( + [[120, 100]], + index=["Total Revenue"], + columns=["2024", "2023"], + ) + + with patch("stock_analysis_program.fetcher.revenue_growth_fetcher.yf.Ticker", return_value=stock): + fetcher = RevenueGrowthFetcher(["aapl"]) + growth = fetcher.fetch_revenue_growth() + + assert growth["AAPL"] == pytest.approx(0.2) diff --git a/tests/test_fetcher/test_stock_data_fetcher.py b/tests/test_fetcher/test_stock_data_fetcher.py index 00e9dad..4129cd7 100644 --- a/tests/test_fetcher/test_stock_data_fetcher.py +++ b/tests/test_fetcher/test_stock_data_fetcher.py @@ -1,8 +1,25 @@ -# tests/test_fetcher/test_stock_data_fetcher.py +from unittest.mock import Mock, patch -import pytest -from src.stock_analysis_program import StockDataFetcher +import pandas as pd + +from stock_analysis_program import StockDataFetcher def test_stock_data_fetcher(): - fetcher = StockDataFetcher("AAPL") - assert fetcher is not None, "StockDataFetcher should be initialized." + with patch("stock_analysis_program.fetcher.stock_data_fetcher.yf.Ticker") as ticker: + ticker.return_value = Mock() + fetcher = StockDataFetcher("aapl") + + assert fetcher.ticker == "AAPL" + ticker.assert_called_once_with("AAPL") + + +def test_stock_data_fetcher_calculates_moving_averages(): + fetcher = StockDataFetcher.__new__(StockDataFetcher) + fetcher.ticker = "AAPL" + data = pd.DataFrame({"Close": [1, 2, 3], "Volume": [10, 20, 30]}) + + moving_averages = fetcher.calculate_moving_averages(data, window_sizes=[2]) + + assert "2-day MA" in moving_averages + assert moving_averages["2-day MA"].iloc[-1] == 2.5 + assert fetcher.get_average_volume(data) == 20 diff --git a/tests/test_fetcher/test_stock_summary_fetcher.py b/tests/test_fetcher/test_stock_summary_fetcher.py index c44d685..d2de929 100644 --- a/tests/test_fetcher/test_stock_summary_fetcher.py +++ b/tests/test_fetcher/test_stock_summary_fetcher.py @@ -1,8 +1,14 @@ -# tests/test_fetcher/test_stock_summary_fetcher.py +from unittest.mock import Mock, patch -import pytest -from src.stock_analysis_program import StockSummaryFetcher +from stock_analysis_program import StockSummaryFetcher -def test_stock_summary_fetcher_initialization(): - fetcher = StockSummaryFetcher(["AAPL"]) - assert fetcher is not None, "StockSummaryFetcher should be initialized." +def test_stock_summary_fetcher_returns_summary(): + stock = Mock() + stock.info = {"longName": "Apple Inc.", "sector": "Technology"} + + with patch("stock_analysis_program.fetcher.stock_summary_fetcher.yf.Ticker", return_value=stock): + fetcher = StockSummaryFetcher(["aapl"]) + summaries = fetcher.get_summaries() + + assert summaries[0]["Ticker"] == "AAPL" + assert summaries[0]["Name"] == "Apple Inc." diff --git a/tests/test_main.py b/tests/test_main.py index 96b6d4d..97345c4 100644 --- a/tests/test_main.py +++ b/tests/test_main.py @@ -1,7 +1,4 @@ -# tests/test_main.py - -import pytest -from src.stock_analysis_program import main +from stock_analysis_program import main def test_main_exists(): - assert main is not None, "Main module should exist." + assert callable(main) diff --git a/tests/test_plotter/__init__.py b/tests/test_plotter/__init__.py index cc7a898..8b13789 100644 --- a/tests/test_plotter/__init__.py +++ b/tests/test_plotter/__init__.py @@ -1,8 +1 @@ -# tests/test_fetcher/__init__.py -from .test_current_prices_ticker_display import test_current_prices_ticker_display_initialization -from .test_financial_metrics_plotter import test_financial_metrics_plotter -from .test_revenue_growth_plotter import test_revenue_growth_plotter_initialization -from .test_stock_exchange_performance_plotter import test_stock_exchange_performance_plotter -from .test_stock_price_plotter import test_stock_price_plotter_initialization -from .test_stock_volatility_plotter import test_stock_volatility_plotter_initialization diff --git a/tests/test_plotter/test_current_prices_ticker_display.py b/tests/test_plotter/test_current_prices_ticker_display.py index 3608b45..d18fc76 100644 --- a/tests/test_plotter/test_current_prices_ticker_display.py +++ b/tests/test_plotter/test_current_prices_ticker_display.py @@ -1,8 +1,18 @@ -# tests/test_plotter/test_current_prices_ticker_display.py +from unittest.mock import Mock, patch -import pytest -from src.stock_analysis_program import CurrentPricesTickerDisplay +from stock_analysis_program import CurrentPricesTickerDisplay def test_current_prices_ticker_display_initialization(): - display = CurrentPricesTickerDisplay(["AAPL"], 10) - assert display is not None, "CurrentPricesTickerDisplay should be initialized." + display = CurrentPricesTickerDisplay(["aapl"], 10) + assert display.tickers == ["AAPL"] + + +def test_current_prices_ticker_display_fetches_prices(): + stock = Mock() + stock.info = {"currentPrice": 123.45} + + with patch("stock_analysis_program.plotter.current_prices_ticker_display.yf.Ticker", return_value=stock): + display = CurrentPricesTickerDisplay(["AAPL"], 10) + prices = display.fetch_current_prices() + + assert prices == {"AAPL": 123.45} diff --git a/tests/test_plotter/test_financial_metrics_plotter.py b/tests/test_plotter/test_financial_metrics_plotter.py index 3bb7334..26a04c8 100644 --- a/tests/test_plotter/test_financial_metrics_plotter.py +++ b/tests/test_plotter/test_financial_metrics_plotter.py @@ -1,9 +1,9 @@ -# tests/test_fetcher/test_financial_metrics_fetcher.py - from unittest.mock import patch -import pytest + import pandas as pd -from src.stock_analysis_program.plotter.financial_metrics_plotter import ( +import pytest + +from stock_analysis_program.plotter.financial_metrics_plotter import ( FinancialMetricsPlotter, ) @@ -24,9 +24,7 @@ def mock_fetcher_return(): return sample_financial_data -@patch( - "src.stock_analysis_program.plotter.financial_metrics_plotter.FinancialMetricsFetcher" -) +@patch("stock_analysis_program.plotter.financial_metrics_plotter.FinancialMetricsFetcher") def test_financial_metrics_plotter(mock_FinancialMetricsFetcher, mock_fetcher_return): """Test the FinancialMetricsPlotter's plot_metrics method.""" # Setup mock to return the sample financial data as a DataFrame @@ -36,8 +34,8 @@ def test_financial_metrics_plotter(mock_FinancialMetricsFetcher, mock_fetcher_re # Initialize the plotter with mock data plotter = FinancialMetricsPlotter(["AAPL", "MSFT"]) - with patch("matplotlib.pyplot.show"): - plotter.plot_metrics() + figures = plotter.plot_metrics(show=False) # Assert fetch_financial_metrics was called mock_instance.fetch_financial_metrics.assert_called_once() + assert len(figures) == 2 diff --git a/tests/test_plotter/test_revenue_growth_plotter.py b/tests/test_plotter/test_revenue_growth_plotter.py index b9af2c1..dc6109a 100644 --- a/tests/test_plotter/test_revenue_growth_plotter.py +++ b/tests/test_plotter/test_revenue_growth_plotter.py @@ -1,8 +1,14 @@ -# tests/test_plotter/test_revenue_growth_plotter.py +from unittest.mock import patch -import pytest -from src.stock_analysis_program import RevenueGrowthPlotter +from stock_analysis_program import RevenueGrowthPlotter -def test_revenue_growth_plotter_initialization(): - plotter = RevenueGrowthPlotter(["AAPL"]) - assert plotter is not None, "RevenueGrowthPlotter should be initialized." +def test_revenue_growth_plotter_returns_figure(): + with patch( + "stock_analysis_program.plotter.revenue_growth_plotter.RevenueGrowthFetcher" + ) as fetcher: + fetcher.return_value.fetch_revenue_growth.return_value = {"AAPL": 0.2} + plotter = RevenueGrowthPlotter(["AAPL"]) + fig, ax = plotter.plot_revenue_growth(show=False) + + assert fig is not None + assert len(ax.patches) == 1 diff --git a/tests/test_plotter/test_stock_exchange_performance_plotter.py b/tests/test_plotter/test_stock_exchange_performance_plotter.py index 13ad31c..a4e19c7 100644 --- a/tests/test_plotter/test_stock_exchange_performance_plotter.py +++ b/tests/test_plotter/test_stock_exchange_performance_plotter.py @@ -1,8 +1,17 @@ -# tests/test_plotter/test_stock_exchange_performance_plotter.py +from unittest.mock import patch -import pytest -from src.stock_analysis_program import StockExchangePerformancePlotter +import pandas as pd + +from stock_analysis_program import StockExchangePerformancePlotter def test_stock_exchange_performance_plotter(): - plotter = StockExchangePerformancePlotter(["^GSPC"]) - assert plotter is not None, "StockExchangePerformancePlotter should be initialized." + data = pd.DataFrame({"Close": [100, 110, 121]}) + with patch( + "stock_analysis_program.plotter.stock_exchange_performance_plotter.yf.download", + return_value=data, + ): + plotter = StockExchangePerformancePlotter(["^GSPC"]) + fig, ax = plotter.plot_performance("2024-01-01", "2024-01-03", show=False) + + assert fig is not None + assert len(ax.lines) == 1 diff --git a/tests/test_plotter/test_stock_price_plotter.py b/tests/test_plotter/test_stock_price_plotter.py index 5b5720f..ac39a37 100644 --- a/tests/test_plotter/test_stock_price_plotter.py +++ b/tests/test_plotter/test_stock_price_plotter.py @@ -1,8 +1,19 @@ -# tests/test_plotter/test_stock_price_plotter.py +from unittest.mock import patch -import pytest -from src.stock_analysis_program import StockPricePlotter +import pandas as pd + +from stock_analysis_program import StockPricePlotter def test_stock_price_plotter_initialization(): - plotter = StockPricePlotter(['AAPL']) - assert plotter is not None, "StockPricePlotter should be initialized." + plotter = StockPricePlotter(["aapl"]) + assert plotter.tickers == ["AAPL"] + + +def test_stock_price_plotter_returns_figures(): + data = pd.DataFrame({"Close": [1, 2, 3]}) + with patch("stock_analysis_program.plotter.stock_price_plotter.yf.download", return_value=data): + plotter = StockPricePlotter(["AAPL"]) + figures = plotter.plot_closing_prices("2024-01-01", "2024-01-03", show=False) + + assert len(figures) == 1 + assert figures[0][0] is not None diff --git a/tests/test_plotter/test_stock_volatility_plotter.py b/tests/test_plotter/test_stock_volatility_plotter.py index 6e47f35..f0e6cb0 100644 --- a/tests/test_plotter/test_stock_volatility_plotter.py +++ b/tests/test_plotter/test_stock_volatility_plotter.py @@ -1,8 +1,17 @@ -# tests/test_plotter/test_stock_volatility_plotter.py +from unittest.mock import patch -import pytest -from src.stock_analysis_program import StockVolatilityPlotter +import pandas as pd + +from stock_analysis_program import StockVolatilityPlotter def test_stock_volatility_plotter_initialization(): - plotter = StockVolatilityPlotter(["AAPL"]) - assert plotter is not None, "StockVolatilityPlotter should be initialized." + data = pd.DataFrame({"Close": [100, 101, 103, 102]}) + with patch( + "stock_analysis_program.plotter.stock_volatility_plotter.yf.download", + return_value=data, + ): + plotter = StockVolatilityPlotter(["AAPL"]) + fig, ax = plotter.plot_volatility("2024-01-01", "2024-01-04", show=False) + + assert fig is not None + assert len(ax.lines) == 1