For **statistics and data science visuals** in hobby projects (e.g., distributions, regression plots, time series, clustering), here’s the optimal workflow balancing **quality, performance, and ease of use**:

---

### **1. Recommended Tools by Task**
#### **A. Static Visuals (PNG/SVG)**
| Task                  | Best Tool (Python)       | Best Tool (R)          | Output Format |
|-----------------------|--------------------------|------------------------|---------------|
| Distributions         | Seaborn (`histplot`, `kdeplot`) | ggplot2 (`geom_histogram`, `geom_density`) | PNG (if dense data) / SVG (if simple) |
| Scatter/Regression    | Seaborn (`regplot`, `lmplot`) | ggplot2 (`geom_smooth`, `geom_point`) | SVG (for interactivity later) |
| Time Series          | Matplotlib (`plot_date`) + Seaborn | ggplot2 (`geom_line`) | PNG (long series) |
| Heatmaps/Correlation | Seaborn (`heatmap`)       | ggplot2 (`geom_tile`)  | PNG (large matrices) |
| Box/Violin Plots     | Seaborn (`boxplot`, `violinplot`) | ggplot2 (`geom_boxplot`) | SVG |

#### **B. Interactive Visuals (Embeddable in Hugo)**
| Task                  | Best Tool                | Output Format          |
|-----------------------|--------------------------|------------------------|
| Exploratory hover plots | Plotly Express (Python/R) | HTML (embed as `<iframe>`) |
| Linked brushing       | Altair (Python) + Vega   | JSON (via Hugo shortcode) |
| Animated transitions  | Plotly (`animation_frame`) | GIF/MP4 (FFmpeg-optimized) |

---

### **2. File Format Guidelines**
- **Use PNG if:**  
  - Plot has >1,000 data points (e.g., large scatterplots).  
  - You’re using transparency (`plt.savefig(..., transparent=True)`).  
  - Example:  
    ```python
    # Python (Seaborn)
    sns.scatterplot(data=df, x="x", y="y").get_figure().savefig("plot.png", dpi=200, bbox_inches="tight")
    ```

- **Use SVG if:**  
  - Plot is simple (e.g., boxplots, small line charts).  
  - You want to edit colors/text later in Inkscape.  
  - Example:  
    ```r
    # R (ggplot2)
    ggsave("plot.svg", plot, device = svg, width=8, height=6)
    ```

---

### **3. Optimization Pipeline**
#### **For PNGs:**
1. Generate high-res (300dpi) PNGs directly from Python/R.  
2. Compress with `oxipng` (lossless):  
   ```bash
   oxipng -o 4 --strip safe plot.png
   ```
   - (Alternative: Use ImageMagick `-quality 90 -strip`).  

#### **For SVGs:**
1. Export from tool (avoid unnecessary metadata).  
2. Crush with `svgo`:  
   ```bash
   npx svgo plot.svg --config='
   {
     "plugins": [
       "removeXMLProcInst",
       "removeComments",
       "removeDoctype"
     ]
   }'
   ```

---

### **4. Hugo Integration**
- **Static images**: Place in `/static/images/` and reference in Markdown:  
  ```md
  ![Distribution Plot](/images/distplot.png)
  ```
- **Interactive plots**: Use Hugo shortcodes for iframes:  
  ```html
  {{< iframe src="/plots/interactive_plot.html" width="100%" height="500px" >}}
  ```

---

### **5. Example Workflows**
#### **Python (Seaborn + Plotly)**
```python
# Static plot
sns.histplot(data=df, x="value").get_figure().savefig("histogram.png", dpi=300)

# Interactive plot
fig = px.scatter(df, x="x", y="y", hover_data=["label"])
fig.write_html("scatter.html")  # Embed in Hugo
```

#### **R (ggplot2 + Plotly)**
```r
# Static plot
ggsave("boxplot.svg", ggplot(df, aes(x=group, y=value)) + geom_boxplot())

# Interactive plot
ggplotly(p) %>% htmlwidgets::saveWidget("boxplot.html")
```

---

### **6. Tools to Avoid**
- **D3.js**: Overkill unless you need custom interactivity.  
- **Bokeh**: Heavy for static sites; Plotly is simpler.  
- **RAWGraphs**: Better for one-offs, not automation.  

---

### **Final Recommendation**
- **Default to Seaborn (Python) / ggplot2 (R)** → Export as **PNG** for dense plots, **SVG** for simple ones.  
- **Add interactivity sparingly** with Plotly (saved as HTML).  
- **Optimize all files** (`oxipng`/`svgo`) before Hugo deployment.  

For hobby projects, this balances **speed, quality, and fun**! Want a sample Hugo project structure with automation scripts?

---

To get started with your data visualization project using Hugo, Bootstrap, and Chart.js, follow these steps:

1. Project Setup:
   - Install Hugo on your local machine
   - Create a new Hugo site using the command `hugo new site <project-name>`
   - Choose and integrate a Bootstrap theme into your project
   - Organize your project structure by creating directories for content, layouts, and static files

2. Content Creation:
   - Identify the main sections or categories for your reports
   - Create content sections within the `content/` directory for each report category
   - Write Markdown files for each individual report within the respective sections

3. Layout and Templates:
   - Create a base template in `layouts/_default/baseof.html` with Bootstrap CSS and JS included
   - Design a single report template in `layouts/<section>/single.html` for rendering individual report pages
   - Customize the templates to match your desired layout and design

4. Data Visualization:
   - Integrate Chart.js into your project by including the necessary JavaScript files
   - Create shortcodes or partials for defining Chart.js configurations within your Markdown files
   - Customize the charts to display your data effectively, choosing appropriate chart types and styles

5. Static Files:
   - Add any custom CSS styles in the `static/css/` directory to enhance the visual appearance of your reports
   - Include any custom JavaScript files in the `static/js/` directory for additional functionality or interactivity

6. Testing and Refinement:
   - Run the Hugo server locally using `hugo server` to preview your site and test the report pages
   - Iterate and refine the content, layouts, and visualizations based on feedback and requirements

7. Deployment:
   - Build your Hugo site using `hugo` command, which generates the static files in the `public/` directory
   - Deploy the generated files to a hosting platform of your choice, such as GitHub Pages, Netlify, or AWS S3

Deliverables:
1. A fully functional Hugo site with integrated Bootstrap theme and organized project structure
2. Markdown files for each report, containing the report content and Chart.js configurations
3. Custom templates for the base layout and individual report pages
4. Interactive data visualizations using Chart.js, embedded within the report pages
5. Custom CSS and JavaScript files for styling and additional functionality
6. Deployed website accessible via a public URL, showcasing the data visualization reports

By following these steps and delivering the mentioned artifacts, you will have a complete data visualization project using Hugo, Bootstrap, and Chart.js. The project will provide a structured way to present your reports, incorporate engaging data visualizations, and create a professional-looking website to showcase your findings.

Remember to iterate and refine your project based on feedback and requirements, ensuring that the visualizations effectively communicate the insights from your data. Additionally, consider optimizing the site's performance, responsiveness, and accessibility to provide a smooth user experience across different devices and audiences.

---

To organize the information you provided, I would suggest the following structure:

1. Introduction
   - Brief overview of the project
   - Purpose and goals of the project

2. Prerequisites
   - Installing Hugo
   - Familiarity with Markdown, HTML, CSS, and JavaScript

3. Project Setup
   - Creating a new Hugo site
   - Choosing and integrating a Bootstrap theme
   - Organizing the project structure

4. Content Creation
   - Creating content sections for different reports
   - Writing Markdown files for each report

5. Layout and Templates
   - Creating a base template with Bootstrap CSS and JS
   - Designing a single report template for rendering report pages

6. Static Files
   - Adding custom CSS for additional styling
   - Including custom JavaScript for enhanced functionality

7. Integrating HTMX (if applicable)
   - Adding HTMX via CDN
   - Creating server-side endpoints for handling HTMX requests
   - Implementing HTMX features for interactivity

8. Data Visualization with Chart.js
   - Configuring Chart.js in Markdown files using shortcodes or partials
   - Creating different types of charts (bar, line, pie, etc.)
   - Customizing chart options and styling

9. Building and Deployment
   - Running the Hugo server for local development
   - Building the site for production
   - Deploying the site to a hosting platform (e.g., GitHub Pages, Netlify)

10. Conclusion
    - Recap of the project and its components
    - Benefits of using Hugo, Bootstrap, and Chart.js for data visualization
    - Future enhancements and considerations

11. Appendices (if needed)
    - Additional resources and references
    - Troubleshooting guide
    - FAQ

By organizing the information into these sections, you can create a comprehensive and easy-to-follow guide for your data visualization project using Hugo, Bootstrap, and Chart.js. This structure allows readers to understand the project's purpose, set up their environment, create content, integrate visualization components, and deploy the site successfully.

Remember to provide clear instructions, code examples, and explanations for each section to ensure a smooth learning experience for your audience.

---

It looks like the main structure and details are solid, but a few crucial elements are missing or could use some refinement. Here’s what to add or clarify:

### Missing or Refined Steps

1. **Dynamic Data Loading with HTMX**:
    - Ensure HTMX requests are correctly integrated to load dynamic data.

2. **Error Handling and Fallbacks**:
    - Add error handling for dynamic content loading to ensure the site degrades gracefully if the data cannot be loaded.

3. **Enhanced User Experience**:
    - Include loading indicators or feedback for users while the data is being fetched.

### Detailed Missing Elements:

#### 1. Enhanced HTMX Integration

**Modify the HTML to handle dynamic loading and data visualization correctly**:

**layouts/_default/baseof.html**:
```html
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>{{ .Title }}</title>
    <meta name="description" content="{{ .Description }}">
    <link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css">
    <link rel="stylesheet" href="{{ "css/styles.css" | relURL }}">
    <script src="https://unpkg.com/htmx.org@1.5.0"></script>
</head>
<body>
    <nav class="navbar navbar-expand-lg navbar-light bg-light">
        <a class="navbar-brand" href="{{ "/" | relURL }}">{{ .Site.Title }}</a>
        <button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation">
            <span class="navbar-toggler-icon"></span>
        </button>
        <div class="collapse navbar-collapse" id="navbarNav">
            <ul class="navbar-nav">
                <li class="nav-item">
                    <a class="nav-link" href="{{ "/" | relURL }}">Home</a>
                </li>
                <li class="nav-item">
                    <a class="nav-link" href="{{ "/clients/" | relURL }}">Clients</a>
                </li>
            </ul>
        </div>
    </nav>
    <main class="container mt-4">
        {{ block "main" . }}{{ end }}
    </main>
    <footer class="footer bg-light text-center py-3">
        <p>&copy; {{ now.Format "2006" }} {{ .Site.Title }}</p>
    </footer>
    <script src="https://code.jquery.com/jquery-3.5.1.slim.min.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/@popperjs/core@2.9.2/dist/umd/popper.min.js"></script>
    <script src="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/js/bootstrap.min.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
    <script src="{{ "js/scripts.js" | relURL }}"></script>
</body>
</html>
```

#### 2. Dynamic Data Loading Button

**Add the HTMX button and loading indicator**:

**content/clients/client1.md**:
```markdown
---
title: "Client 1"
date: 2024-05-23
---

# Client 1 Ads Telemetry

<div class="card mb-3">
  <div class="card-body">
    <h5 class="card-title">Ads Data Visualization</h5>
    <canvas id="adsChart" width="400" height="200"></canvas>
  </div>
</div>

<div id="loading" style="display: none;">Loading...</div>
<button hx-get="/clients/client1-data" hx-target="#adsChart" hx-trigger="loadstart">Load Data</button>

<script>
  document.addEventListener('htmx:loadstart', function() {
    document.getElementById('loading').style.display = 'block';
  });
  document.addEventListener('htmx:afterOnLoad', function() {
    document.getElementById('loading').style.display = 'none';
    const data = {{ .Site.Data.clients.client1.ads_data | jsonify }};
    const ctx = document.getElementById('adsChart').getContext('2d');
    const labels = data.map(item => item.date);
    const googleAds = data.map(item => item.google_ads);
    const metaAds = data.map(item => item.meta_ads);
    new Chart(ctx, {
      type: 'line',
      data: {
        labels: labels,
        datasets: [
          {
            label: 'Google Ads',
            data: googleAds,
            borderColor: 'rgba(75, 192, 192, 1)',
            backgroundColor: 'rgba(75, 192, 192, 0.2)',
            fill: false
          },
          {
            label: 'Meta Ads',
            data: metaAds,
            borderColor: 'rgba(153, 102, 255, 1)',
            backgroundColor: 'rgba(153, 102, 255, 0.2)',
            fill: false
          }
        ]
      },
      options: {
        scales: {
          y: {
            beginAtZero: true
          }
        }
      }
    });
  });
</script>
```

#### 3. Error Handling

**Add error handling for HTMX requests**:

**layouts/_default/baseof.html** (or relevant HTML file):
```html
...
<div id="error" style="display: none; color: red;">An error occurred while loading data.</div>
<script>
  document.addEventListener('htmx:error', function() {
    document.getElementById('loading').style.display = 'none';
    document.getElementById('error').style.display = 'block';
  });
</script>
...
```

#### 4. Complete Deployment Steps

**Ensure you deploy the Flask app if using a server for dynamic data**.

### Complete Summary

**Tech Stack**:
- **Hugo**: Static site generation.
- **Markdown**: Content creation.
- **Bootstrap**: Responsive design.
- **Chart.js**: Data visualization.
- **HTMX**: Dynamic interactivity.
- **Python/Flask**: Server-side data handling.

**Implementation**:
- Set up Hugo and configure the project structure.
- Create data and content files for each client.
- Use Bootstrap for styling and Chart.js for visualizations.
- Enhance interactivity with HTMX for dynamic data loading.
- Add error handling for better UX.
- Use Python/Flask for server-side data handling if needed.
- Deploy the Hugo site and Flask app.

**Deliverables**:
1. Hugo site with Bootstrap integration.
2. Organized content structure for reports.
3. Base template and report-specific templates.
4. Static assets: custom CSS and JS files.
5. Chart integration with shortcodes/partials.
6. Reports with various chart types.
7. Deployment of Hugo site and server-side Flask app if required.

By incorporating these steps, you ensure a robust, scalable, and interactive data visualization site using Hugo, Bootstrap, Chart.js, and HTMX. If you have any further questions or need more detailed guidance, feel free to ask!

---

It looks like you have a solid plan for integrating HTMX into your Hugo project to enhance interactivity. Let's structure your data visualization project into clear components and deliverables. Here’s a refined and detailed approach:

### 1. **Project Setup**
   - **Install Hugo**: Make sure Hugo is installed. Follow the [Hugo installation guide](https://gohugo.io/getting-started/installing/).
   - **Create a New Hugo Site**:
     ```sh
     hugo new site smma-telemetry
     cd smma-telemetry
     ```

### 2. **Initialize Git and Add a Bootstrap Theme**
   ```sh
   git init
   git submodule add https://github.com/razonyang/hugo-theme-bootstrap themes/hugo-theme-bootstrap
   ```

   Update `config.toml`:
   ```toml
   baseURL = 'https://example.org/'
   languageCode = 'en-us'
   title = 'SMMA Telemetry'
   theme = 'hugo-theme-bootstrap'
   ```

### 3. **Organize Project Structure**
   ```sh
   mkdir -p content/clients
   mkdir -p data/clients
   mkdir -p static/css
   mkdir -p static/js
   ```

### 4. **Add HTMX to Your Project**
   **layouts/_default/baseof.html**:
   ```html
   <!DOCTYPE html>
   <html lang="en">
   <head>
       <meta charset="UTF-8">
       <meta name="viewport" content="width=device-width, initial-scale=1.0">
       <title>{{ .Title }}</title>
       <meta name="description" content="{{ .Description }}">
       <link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css">
       <link rel="stylesheet" href="{{ "css/styles.css" | relURL }}">
       <script src="https://unpkg.com/htmx.org@1.5.0"></script>
   </head>
   <body>
       <nav class="navbar navbar-expand-lg navbar-light bg-light">
           <a class="navbar-brand" href="{{ "/" | relURL }}">{{ .Site.Title }}</a>
           <button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation">
               <span class="navbar-toggler-icon"></span>
           </button>
           <div class="collapse navbar-collapse" id="navbarNav">
               <ul class="navbar-nav">
                   <li class="nav-item">
                       <a class="nav-link" href="{{ "/" | relURL }}">Home</a>
                   </li>
                   <li class="nav-item">
                       <a class="nav-link" href="{{ "/clients/" | relURL }}">Clients</a>
                   </li>
               </ul>
           </div>
       </nav>
       <main class="container mt-4">
           {{ block "main" . }}{{ end }}
       </main>
       <footer class="footer bg-light text-center py-3">
           <p>&copy; {{ now.Format "2006" }} {{ .Site.Title }}</p>
       </footer>
       <script src="https://code.jquery.com/jquery-3.5.1.slim.min.js"></script>
       <script src="https://cdn.jsdelivr.net/npm/@popperjs/core@2.9.2/dist/umd/popper.min.js"></script>
       <script src="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/js/bootstrap.min.js"></script>
       <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
       <script src="{{ "js/scripts.js" | relURL }}"></script>
   </body>
   </html>
   ```

### 5. **Create Data Files**
   **data/clients/client1.json**:
   ```json
   {
     "name": "Client 1",
     "ads_data": [
       { "date": "2024-05-01", "google_ads": 500, "meta_ads": 300 },
       { "date": "2024-05-02", "google_ads": 700, "meta_ads": 400 },
       { "date": "2024-05-03", "google_ads": 600, "meta_ads": 350 }
     ]
   }
   ```

### 6. **Create Content Files**
   **content/clients/client1.md**:
   ```markdown
   ---
   title: "Client 1"
   date: 2024-05-23
   ---

   # Client 1 Ads Telemetry

   <div class="card mb-3">
     <div class="card-body">
       <h5 class="card-title">Ads Data Visualization</h5>
       <canvas id="adsChart" width="400" height="200"></canvas>
     </div>
   </div>

   <button hx-get="/clients/client1-data" hx-target="#adsChart" hx-trigger="load">Load Data</button>

   <script>
     document.addEventListener('DOMContentLoaded', function () {
       const data = {{ .Site.Data.clients.client1.ads_data | jsonify }};
       const ctx = document.getElementById('adsChart').getContext('2d');
       const labels = data.map(item => item.date);
       const googleAds = data.map(item => item.google_ads);
       const metaAds = data.map(item => item.meta_ads);
       new Chart(ctx, {
         type: 'line',
         data: {
           labels: labels,
           datasets: [
             {
               label: 'Google Ads',
               data: googleAds,
               borderColor: 'rgba(75, 192, 192, 1)',
               backgroundColor: 'rgba(75, 192, 192, 0.2)',
               fill: false
             },
             {
               label: 'Meta Ads',
               data: metaAds,
               borderColor: 'rgba(153, 102, 255, 1)',
               backgroundColor: 'rgba(153, 102, 255, 0.2)',
               fill: false
             }
           ]
         },
         options: {
           scales: {
             y: {
               beginAtZero: true
             }
           }
         }
       });
     });
   </script>
   ```

### 7. **Add Custom JavaScript and CSS**
   **static/js/scripts.js**:
   ```js
   document.addEventListener('DOMContentLoaded', function () {
       console.log('Custom JS Loaded');
   });
   ```

   **static/css/styles.css**:
   ```css
   body {
       font-family: Arial, sans-serif;
       line-height: 1.6;
       margin: 0;
       padding: 0;
       background: #f4f4f4;
   }

   #adsChart {
       max-width: 600px;
       margin: 50px auto;
   }
   ```

### 8. **Create a Server-Side Endpoint**
   **Example Python Flask Endpoint (app.py)**:
   ```python
   from flask import Flask, jsonify
   import json

   app = Flask(__name__)

   @app.route('/clients/client1-data')
   def client1_data():
       with open('data/clients/client1.json') as f:
           data = json.load(f)
       return jsonify(data['ads_data'])

   if __name__ == '__main__':
       app.run(debug=True)
   ```

### 9. **Run the Hugo Server**
   ```sh
   hugo server -D
   ```

### Summary
1. **Project Setup**: Hugo site created with Bootstrap theme.
2. **Organized Content**: Structure for clients and data files.
3. **Integrated HTMX**: HTMX included for enhanced interactivity.
4. **Data Visualization**: Charts implemented using Chart.js.
5. **Dynamic Data Loading**: Server-side endpoint for dynamic data.

By following this structured approach, you can create a robust and interactive data visualization site using Hugo, Bootstrap, and Chart.js. If you have any further questions or need additional details, feel free to ask!

---

Integrating HTMX into your Hugo project can enhance the interactivity of your site without requiring a full-fledged JavaScript framework. HTMX allows you to make your static site more dynamic by enabling AJAX, CSS Transitions, WebSockets, and Server Sent Events (SSE) directly in HTML. This can be particularly useful for enhancing user experience without the complexity of traditional JavaScript frameworks.

### When to Use HTMX

HTMX is useful for:
- **Enhancing Interactivity:** Adding dynamic features like in-place content updates, form submissions, and interactive elements without a full JavaScript framework.
- **AJAX Requests:** Making asynchronous requests to the server to update parts of your page without reloading.
- **Progressive Enhancement:** Gradually enhancing your static site with more interactive features.

### Integrating HTMX into Hugo

Here's how you can integrate HTMX into your Hugo site, especially for data visualization and client reports.

### Step-by-Step Integration

#### 1. Install Hugo and Create a New Site

If you haven't already, install Hugo and create a new site:

```sh
hugo new site smma-telemetry
cd smma-telemetry
```

#### 2. Initialize Git and Add a Bootstrap Theme

```sh
git init
git submodule add https://github.com/razonyang/hugo-theme-bootstrap themes/hugo-theme-bootstrap
```

Update your `config.toml` to use the theme:

```toml
baseURL = 'https://example.org/'
languageCode = 'en-us'
title = 'SMMA Telemetry'
theme = 'hugo-theme-bootstrap'
```

#### 3. Set Up Project Structure

```sh
mkdir -p content/clients
mkdir -p data/clients
mkdir -p static/css
mkdir -p static/js
```

#### 4. Add HTMX to Your Project

Add HTMX via a CDN in your base layout file.

**layouts/_default/baseof.html:**

```html
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>{{ .Title }}</title>
    <meta name="description" content="{{ .Description }}">
    <link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css">
    <link rel="stylesheet" href="{{ "css/styles.css" | relURL }}">
    <script src="https://unpkg.com/htmx.org@1.5.0"></script>
</head>
<body>
    <nav class="navbar navbar-expand-lg navbar-light bg-light">
        <a class="navbar-brand" href="{{ "/" | relURL }}">{{ .Site.Title }}</a>
        <button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation">
            <span class="navbar-toggler-icon"></span>
        </button>
        <div class="collapse navbar-collapse" id="navbarNav">
            <ul class="navbar-nav">
                <li class="nav-item">
                    <a class="nav-link" href="{{ "/" | relURL }}">Home</a>
                </li>
                <li class="nav-item">
                    <a class="nav-link" href="{{ "/clients/" | relURL }}">Clients</a>
                </li>
            </ul>
        </div>
    </nav>
    <main class="container mt-4">
        {{ block "main" . }}{{ end }}
    </main>
    <footer class="footer bg-light text-center py-3">
        <p>&copy; {{ now.Format "2006" }} {{ .Site.Title }}</p>
    </footer>
    <script src="https://code.jquery.com/jquery-3.5.1.slim.min.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/@popperjs/core@2.9.2/dist/umd/popper.min.js"></script>
    <script src="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/js/bootstrap.min.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
    <script src="{{ "js/scripts.js" | relURL }}"></script>
</body>
</html>
```

#### 5. Create Data Files

Store ads telemetry data for each client in JSON format. For example:

**data/clients/client1.json:**

```json
{
  "name": "Client 1",
  "ads_data": [
    { "date": "2024-05-01", "google_ads": 500, "meta_ads": 300 },
    { "date": "2024-05-02", "google_ads": 700, "meta_ads": 400 },
    { "date": "2024-05-03", "google_ads": 600, "meta_ads": 350 }
  ]
}
```

#### 6. Create Content Files

Create a content file for each client. For example:

**content/clients/client1.md:**

```markdown
---
title: "Client 1"
date: 2024-05-23
---

# Client 1 Ads Telemetry

<div class="card mb-3">
  <div class="card-body">
    <h5 class="card-title">Ads Data Visualization</h5>
    <canvas id="adsChart" width="400" height="200"></canvas>
  </div>
</div>

<button hx-get="/clients/client1-data" hx-target="#adsChart" hx-trigger="load">Load Data</button>

<script>
  document.addEventListener('DOMContentLoaded', function () {
    const data = {{ .Site.Data.clients.client1.ads_data | jsonify }};
    const ctx = document.getElementById('adsChart').getContext('2d');
    const labels = data.map(item => item.date);
    const googleAds = data.map(item => item.google_ads);
    const metaAds = data.map(item => item.meta_ads);
    new Chart(ctx, {
      type: 'line',
      data: {
        labels: labels,
        datasets: [
          {
            label: 'Google Ads',
            data: googleAds,
            borderColor: 'rgba(75, 192, 192, 1)',
            backgroundColor: 'rgba(75, 192, 192, 0.2)',
            fill: false
          },
          {
            label: 'Meta Ads',
            data: metaAds,
            borderColor: 'rgba(153, 102, 255, 1)',
            backgroundColor: 'rgba(153, 102, 255, 0.2)',
            fill: false
          }
        ]
      },
      options: {
        scales: {
          y: {
            beginAtZero: true
          }
        }
      }
    });
  });
</script>
```

#### 7. Add Custom JavaScript and CSS

**static/js/scripts.js:**

```js
document.addEventListener('DOMContentLoaded', function () {
    console.log('Custom JS Loaded');
});
```

**static/css/styles.css:**

```css
body {
    font-family: Arial, sans-serif;
    line-height: 1.6;
    margin: 0;
    padding: 0;
    background: #f4f4f4;
}

#adsChart {
    max-width: 600px;
    margin: 50px auto;
}
```

#### 8. Create a Server-side Endpoint

To handle HTMX requests, create a server-side script (e.g., in Python or another language of your choice) to serve the data dynamically.

**Example Python Flask Endpoint (app.py):**

```python
from flask import Flask, jsonify
import json

app = Flask(__name__)

@app.route('/clients/client1-data')
def client1_data():
    with open('data/clients/client1.json') as f:
        data = json.load(f)
    return jsonify(data['ads_data'])

if __name__ == '__main__':
    app.run(debug=True)
```

#### 9. Run the Hugo Server

```sh
hugo server -D
```

Visit `http://localhost:1313` to see your site in action.

### Summary

**Tech Stack:**
- **Hugo**: For building and deploying your static site.
- **Markdown**: For writing content and reports.
- **Bootstrap**: For responsive design and consistent styling.
- **Chart.js**: For creating interactive data visualizations.
- **HTMX**: For enhancing interactivity with minimal JavaScript.
- **Python/Flask**: For server-side data processing and handling HTMX requests.

**Implementation:**
- Set up Hugo and configure your project structure.
- Create data files and content files for each client.
- Use Bootstrap for styling and Chart.js for visualizations.
- Enhance interactivity with HTMX for dynamic data loading.
- Use Python/Flask for server-side data handling.

This approach ensures you have a robust, scalable, and interactive solution for SMMA data reporting, leveraging your data analysis skills while keeping the setup and maintenance straightforward. If you have further questions or need more detailed guidance, feel free to ask!

---

Here's a detailed approach to creating a data visualization project using Hugo, Bootstrap, and Chart.js, broken down into specific steps and components:

### 1. **Project Setup**
   - **Install Hugo**: Make sure Hugo is installed on your machine. Follow the installation guide from the [official Hugo site](https://gohugo.io/getting-started/installing/).
   - **Create a New Hugo Site**: Run `hugo new site <site-name>` to generate a new Hugo site.
     ```sh
     hugo new site smma-telemetry
     cd smma-telemetry
     ```
   - **Choose a Theme**: Select a Hugo theme that supports Bootstrap, or integrate Bootstrap manually. For this example, we'll use the "Hugo Bootstrap" theme.
     ```sh
     git init
     git submodule add https://github.com/razonyang/hugo-theme-bootstrap themes/hugo-theme-bootstrap
     ```

### 2. **Organize Content Structure**
   - **Create Sections**: Define sections in your Hugo site for different reports. Each section can represent a different data report.
     - Example: `content/reports/`
     ```sh
     mkdir -p content/reports
     ```
   - **Markdown Files**: Create Markdown files for each report in the corresponding section.
     - Example: `content/reports/report1.md`
     ```sh
     hugo new reports/report1.md
     ```

### 3. **Layout and Templates**
   - **Base Template**: Create a base template in `layouts/_default/baseof.html` to include the common HTML structure, including Bootstrap CSS and JS.
     **layouts/_default/baseof.html:**
     ```html
     <!DOCTYPE html>
     <html lang="en">
     <head>
         <meta charset="UTF-8">
         <meta name="viewport" content="width=device-width, initial-scale=1.0">
         <title>{{ .Title }}</title>
         <meta name="description" content="{{ .Description }}">
         <link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css">
         <link rel="stylesheet" href="{{ "css/styles.css" | relURL }}">
     </head>
     <body>
         <nav class="navbar navbar-expand-lg navbar-light bg-light">
             <a class="navbar-brand" href="{{ "/" | relURL }}">{{ .Site.Title }}</a>
             <button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation">
                 <span class="navbar-toggler-icon"></span>
             </button>
             <div class="collapse navbar-collapse" id="navbarNav">
                 <ul class="navbar-nav">
                     <li class="nav-item">
                         <a class="nav-link" href="{{ "/" | relURL }}">Home</a>
                     </li>
                     <li class="nav-item">
                         <a class="nav-link" href="{{ "/reports/" | relURL }}">Reports</a>
                     </li>
                 </ul>
             </div>
         </nav>
         <main class="container mt-4">
             {{ block "main" . }}{{ end }}
         </main>
         <footer class="footer bg-light text-center py-3">
             <p>&copy; {{ now.Format "2006" }} {{ .Site.Title }}</p>
         </footer>
         <script src="https://code.jquery.com/jquery-3.5.1.slim.min.js"></script>
         <script src="https://cdn.jsdelivr.net/npm/@popperjs/core@2.9.2/dist/umd/popper.min.js"></script>
         <script src="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/js/bootstrap.min.js"></script>
         <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
         <script src="{{ "js/scripts.js" | relURL }}"></script>
     </body>
     </html>
     ```

   - **Single Report Template**: Create a single report layout in `layouts/reports/single.html` to define how each report page will be rendered.
     **layouts/reports/single.html:**
     ```html
     {{ define "main" }}
     <article class="report">
         <header>
             <h1>{{ .Title }}</h1>
             <time datetime="{{ .Date }}">{{ .Date }}</time>
         </header>
         <section>
             {{ .Content }}
         </section>
     </article>
     {{ end }}
     ```

### 4. **Static Files**
   - **CSS and JS**: Add custom CSS and JS files in the `static/` directory for additional styling and scripting if needed.
     ```sh
     mkdir -p static/css
     mkdir -p static/js
     ```

   - **Custom CSS**: Create a custom CSS file for additional styles.
     **static/css/styles.css:**
     ```css
     body {
         font-family: Arial, sans-serif;
         line-height: 1.6;
         margin: 0;
         padding: 0;
         background: #f4f4f4;
     }

     .report {
         max-width: 800px;
         margin: 50px auto;
         padding: 20px;
         background: white;
         border-radius: 10px;
         box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
     }

     .report header {
         margin-bottom: 20px;
     }
     ```

   - **Custom JS**: Create a custom JS file for additional scripts.
     **static/js/scripts.js:**
     ```js
     document.addEventListener('DOMContentLoaded', function () {
         console.log('Custom JS Loaded');
     });
     ```

### 5. **Integrate Chart.js**
   - **Chart.js Configuration**: In your report Markdown files, include configuration details for the charts. You can use shortcodes or partials for better organization.

   - **Shortcode Example**: Create a shortcode for Chart.js in `layouts/shortcodes/chart.html`.
     **layouts/shortcodes/chart.html:**
     ```html
     <canvas id="{{ .Get "id" }}" width="400" height="200"></canvas>
     <script>
       var ctx = document.getElementById('{{ .Get "id" }}').getContext('2d');
       var myChart = new Chart(ctx, {
         type: '{{ .Get "type" }}',
         data: {
           labels: {{ .Get "labels" }},
           datasets: [{
             label: '{{ .Get "label" }}',
             data: {{ .Get "data" }},
             backgroundColor: {{ .Get "backgroundColor" }},
             borderColor: {{ .Get "borderColor" }},
             borderWidth: 1
           }]
         },
         options: {
           scales: {
             y: {
               beginAtZero: true
             }
           }
         }
       });
     </script>
     ```

   - **Usage in Markdown**: Use the shortcode in your report Markdown files.
     **content/reports/report1.md:**
     ```markdown
     ---
     title: "Report 1"
     date: 2024-05-23
     ---

     # Report 1 Data Visualization

     {{< chart id="myChart" type="bar" labels='["Red", "Blue", "Yellow", "Green", "Purple", "Orange"]' data='[12, 19, 3, 5, 2, 3]' label="Votes" backgroundColor='["rgba(255, 99, 132, 0.2)", "rgba(54, 162, 235, 0.2)", "rgba(255, 206, 86, 0.2)", "rgba(75, 192, 192, 0.2)", "rgba(153, 102, 255, 0.2)", "rgba(255, 159, 64, 0.2)"]' borderColor='["rgba(255, 99, 132, 1)", "rgba(54, 162, 235, 1)", "rgba(255, 206, 86, 1)", "rgba(75, 192, 192, 1)", "rgba(153, 102, 255, 1)", "rgba(255, 159, 64, 1)"]' >}}
     ```

### 6. **Build and Deploy**
   - **Local Development**: Use `hugo server` to serve your site locally and see the changes in real-time.
     ```sh
     hugo server -D
     ```

   - **Deployment**: Once satisfied, deploy your site to a hosting platform of your choice (e.g., GitHub Pages, Netlify).
     ```sh
     hugo --minify
     ```

### **Deliverables Checklist**
1. **Hugo Site**: A fully functional Hugo site with Bootstrap integration.
2. **Content Structure**: Organized content structure with separate sections for different reports.
3. **Templates**: Base template and report-specific templates configured.
4. **Static Assets**: Custom CSS and JS files for additional styling and scripting.
5. **Chart Integration**: Shortcodes or partials for integrating Chart.js into Markdown files.
6. **Reports**: Sample reports with various types of charts (bar, line, pie, etc.).
7. **Deployment**: The site deployed and accessible online.

By following these steps, you can efficiently create a data visualization site using Hugo, Bootstrap

, and Chart.js. This structured approach will help you manage the project components and achieve a clear deliverable. If you have any questions or need further assistance, feel free to ask!
