129 lines
3.0 KiB
Markdown
129 lines
3.0 KiB
Markdown
# cal_heatmap: Yearly Calendar Heatmaps
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This project generates interactive yearly activity heatmaps using calendar data from a specified URL. It utilizes Streamlit for the web interface, Plotly for creating heatmaps, and other supporting libraries for data handling and visualization.
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## Features
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- Load calendar data from a given URL.
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- Save and load different configurations for calendar URL and number of years to display.
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- Generate interactive yearly heatmaps of events.
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- Customize the number of years to visualize.
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## Prerequisites
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- Python 3.9+
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- Required Python packages (listed in `requirements.txt`)!
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## Installation
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1. **Clone the repository:**
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```sh
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git clone https://github.com/yourusername/yearly-activity-heatmaps.git
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cd yearly-activity-heatmaps
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```
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2. **Install the required packages:**
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```sh
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pip install -r requirements.txt
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```
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3. **Run the Streamlit app:**
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```sh
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streamlit run app.py
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```
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## Usage
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1. **Configure Settings:**
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- Enter the calendar export link.
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- Set the number of years to visualize.
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- Save your configuration.
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2. **Generate Heatmaps:**
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- The app will download the calendar data.
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- It will parse the data and count events for each day.
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- Interactive heatmaps will be generated for the specified years.
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## File Structure
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- `app.py`: Main script for running the Streamlit app.
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- `settings.json`: JSON file to store user configurations.
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- `requirements.txt`: List of required Python packages.
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## Project Dependencies
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Make sure you have the following Python libraries installed:
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- pandas
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- vobject
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- requests
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- datetime
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- matplotlib
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- calmap
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- streamlit
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- plotly
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You can install all dependencies using the following command:
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```sh
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pip install -r requirements.txt
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```
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## Docker Deployment
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1. **Build Docker Image:**
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```sh
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docker build -t yearly-activity-heatmaps .
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```
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2. **Run Docker Container:**
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```sh
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docker run -p 8501:8501 yearly-activity-heatmaps
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```
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This will build and run your Streamlit app inside a Docker container, exposing it on port 8501.
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## Example Code
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Below is a snippet of the core functionality in `app.py`:
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```python
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import pandas as pd
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import vobject
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import requests
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from datetime import datetime, date
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import matplotlib.pyplot as plt
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import calmap
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import streamlit as st
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import plotly.express as px
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import plotly.graph_objects as go
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import json
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import os
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# Functions to load and save data, create heatmaps, and update session state...
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# Set webpage title
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st.title("Yearly Activity Heatmaps")
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# Main logic for loading configurations, downloading calendar data, and generating heatmaps...
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# Plot each year's data
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for year in years_to_plot:
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fig = create_calendar_heatmap(event_series, year)
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st.plotly_chart(fig)
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```
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## License
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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## Acknowledgments
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- Streamlit for providing a fantastic framework for building web apps.
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- Plotly for interactive data visualization capabilities.
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- All contributors and users for their support.
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