Embedding Code from Your GitHub Repositories

This guide shows practical examples of how to embed and reference code from your GitHub repositories in your documentation.

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Example 1: Arduino Bioreactor Code

Referencing with Link

You can reference specific files from your repositories:

The pH sensor code is available in the [bioreactor.ino](https://github.com/bio-info/advanced-bioreactor/blob/main/bioreactor.ino) file.

Embedding Code Snippet

Copy relevant sections from your GitHub repos:

// From: https://github.com/bio-info/advanced-bioreactor
// pH Sensor Reading Function

float readPH() {
  int sensorValue = analogRead(PH_PIN);
  float voltage = sensorValue * (5.0 / 1024.0);
  float pH = 3.5 * voltage + CALIBRATION_OFFSET;
  return pH;
}

void logData(float pH, float temp) {
  Serial.print("pH: ");
  Serial.print(pH);
  Serial.print(" | Temp: ");
  Serial.println(temp);
  
  // Save to SD card
  dataFile.print(millis());
  dataFile.print(",");
  dataFile.print(pH);
  dataFile.print(",");
  dataFile.println(temp);
}

Source: View full code on GitHub →

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Example 2: Python Air Quality Analysis

PM2.5 Data Analysis

From your air-quality-analysis repository:

# Source: https://github.com/bio-info/air-quality-analysis
# PM2.5 Data Analysis

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

def analyze_pm25_trends(data_file):
    """
    Analyze PM2.5 trends from sensor data
    
    Args:
        data_file: Path to CSV file with PM2.5 measurements
    
    Returns:
        DataFrame with statistical summary
    """
    # Load data
    df = pd.read_csv(data_file)
    df['timestamp'] = pd.to_datetime(df['timestamp'])
    
    # Calculate daily averages
    daily_avg = df.groupby(df['timestamp'].dt.date)['pm25'].mean()
    
    # Statistical summary
    stats = {
        'mean': df['pm25'].mean(),
        'median': df['pm25'].median(),
        'std': df['pm25'].std(),
        'max': df['pm25'].max(),
        'days_above_who_limit': (daily_avg > 25).sum()
    }
    
    return pd.DataFrame([stats])

# Visualization function
def plot_pm25_timeseries(df):
    plt.figure(figsize=(12, 6))
    plt.plot(df['timestamp'], df['pm25'], label='PM2.5', alpha=0.7)
    plt.axhline(y=25, color='r', linestyle='--', label='WHO 24h Limit')
    plt.xlabel('Time')
    plt.ylabel('PM2.5 (μg/m³)')
    plt.title('PM2.5 Concentration Over Time')
    plt.legend()
    plt.grid(True, alpha=0.3)
    plt.tight_layout()
    plt.savefig('pm25_timeseries.png', dpi=300)

Explore more: View Jupyter notebooks →

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Example 3: ESP8266 Weather Station Code

MQTT Data Transmission

// Source: https://github.com/bio-info/weatherstation
// ESP8266 Weather Station - MQTT Client

#include <ESP8266WiFi.h>
#include <PubSubClient.h>
#include <DHT.h>

#define DHTPIN D4
#define DHTTYPE DHT22

const char* ssid = "YOUR_WIFI";
const char* password = "YOUR_PASSWORD";
const char* mqtt_server = "broker.hivemq.com";

DHT dht(DHTPIN, DHTTYPE);
WiFiClient espClient;
PubSubClient client(espClient);

void publishSensorData() {
  float temp = dht.readTemperature();
  float humidity = dht.readHumidity();
  int light = analogRead(A0);
  
  if (isnan(temp) || isnan(humidity)) {
    Serial.println("Failed to read from DHT sensor!");
    return;
  }
  
  // Create JSON payload
  String payload = "{\"temperature\":" + String(temp) + 
                   ",\"humidity\":" + String(humidity) +
                   ",\"light\":" + String(light) + "}";
  
  // Publish to MQTT topic
  client.publish("weather/station/data", payload.c_str());
  
  Serial.println("Data published: " + payload);
}

void setup() {
  Serial.begin(115200);
  dht.begin();
  
  // Connect to WiFi
  WiFi.begin(ssid, password);
  while (WiFi.status() != WL_CONNECTED) {
    delay(500);
    Serial.print(".");
  }
  
  // Connect to MQTT
  client.setServer(mqtt_server, 1883);
}

void loop() {
  if (!client.connected()) {
    reconnect();
  }
  client.loop();
  
  publishSensorData();
  delay(60000); // Send data every minute
}

Complete implementation: View on GitHub →

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Example 4: Linking to Datasets

Reference CSV Data Files

You can link directly to raw data files:

Download sample PM2.5 dataset:
[hanoi_pm25_2024.csv](https://raw.githubusercontent.com/bio-info/air-quality-analysis/main/data/hanoi_pm25_2024.csv)

Embed Data Tables

Show sample data in tables:

Timestamp	PM2.5 (μg/m³)	Temperature (°C)	Humidity (%)
2024-01-01 00:00	45.2	18.5	75
2024-01-01 01:00	52.8	18.2	78
2024-01-01 02:00	48.6	18.0	80

Full dataset: Download →

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Example 5: Interactive Jupyter Notebooks

Linking to Notebooks

View the complete analysis in Jupyter Notebook:
- [PM2.5 Analysis Notebook](https://github.com/bio-info/air-quality-analysis/blob/main/notebooks/pm25_analysis.ipynb)
- [Sensor Calibration](https://github.com/bio-info/air-quality-analysis/blob/main/notebooks/calibration.ipynb)

Using nbviewer

For better notebook viewing:

[View interactive notebook on nbviewer](https://nbviewer.org/github/bio-info/air-quality-analysis/blob/main/notebooks/pm25_analysis.ipynb)

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Example 6: Images and Diagrams

Circuit Diagrams

![Bioreactor Circuit Diagram](https://raw.githubusercontent.com/bio-info/advanced-bioreactor/main/docs/circuit_diagram.png)

*Figure 1: Complete circuit diagram for the bioreactor monitoring system*

Sensor Setup Photos

![Weather Station Setup](https://raw.githubusercontent.com/bio-info/weatherstation/main/images/setup.jpg)

*Weather station deployed in Hanoi, Vietnam*

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Example 7: README Sections

You can embed sections from your repository READMEs:

From Advanced Bioreactor README

Features:

• Real-time pH and temperature monitoring
• Automatic data logging to SD card
• Turbidostat control for maintaining cell density
• LED pattern control mimicking natural sunlight
• Python simulation tools for growth prediction

Read full documentation →

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Best Practices for Your Site

1. Always Attribute Source

# Source: https://github.com/bio-info/REPO/blob/main/file.py
# Author: Binh Ng. (@bio-info)
# License: MIT

2. Keep Code Snippets Focused

Show only relevant parts, link to full code:

// ... setup code omitted ...

void loop() {
  float pH = readPHSensor();
  float temp = readTempSensor();
  logToSD(pH, temp);
  delay(5000);
}

// See full code: https://github.com/bio-info/advanced-bioreactor

3. Update Links When Code Changes

If you refactor code, update the links in your documentation.

4. Use Relative Links for This Site

<!-- Within this site -->
[Getting Started](getting-started.html)

<!-- External GitHub links -->
[View Code](https://github.com/bio-info/REPO)

5. Provide Context

Explain what the code does before showing it:

## pH Sensor Calibration

The following function calibrates the pH sensor using a two-point calibration method:

[code snippet here]

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Your Repository Structure

Quick reference to your main repositories:

bio-info (GitHub Profile)
├── advanced-bioreactor/
│   ├── bioreactor.ino          # Main Arduino code
│   ├── simulation.py           # Growth simulation
│   └── docs/                   # Documentation
│
├── air-quality-analysis/
│   ├── analysis.py             # Main analysis script
│   ├── notebooks/              # Jupyter notebooks
│   └── data/                   # Sample datasets
│
├── weatherstation/
│   ├── esp8266_weather.ino     # ESP8266 code
│   ├── web/                    # Web interface
│   └── sql/                    # Database schemas
│
└── arduinos/
    ├── led_control/            # LED projects
    ├── motion_sensor/          # Motion detection
    └── power_meter/            # Power monitoring

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Next Steps

1. Create content pages linking to your actual code
2. Add code examples from your repositories with proper attribution
3. Include datasets for others to download and use
4. Write tutorials explaining how to use your projects
5. Add images of your setups and results

Your Jekyll site will serve as a central hub for all your research projects! 🚀