slideflow-presentations 0.0.4

Automated Google Slides presentation builder with charts and data replacements.

🚀 SlideFlow

  ____  _ _     _       __ _                
 / ___|| (_) __| | ___ / _| | _____      __ 
 \___ \| | |/ _` |/ _ \ |_| |/ _ \ \ /\ / / 
  ___) | | | (_| |  __/  _| | (_) \ V  V /  
 |____/|_|_|\__,_|\___|_| |_|\___/ \_/\_/   

         Generate
     Beautiful slides.
       Direct from your data.

SlideFlow is a Python-based tool for generating beautiful, data-driven presentations directly from your data sources.

Key Features • How It Works • Installation • Getting Started • CLI Usage • Configuration • Customization • Contributing

---

✨ Why SlideFlow?

SlideFlow was built to solve a simple problem: automating the tedious process of creating data-heavy presentations. If you find yourself repeatedly copying and pasting charts and metrics into slide decks, SlideFlow is for you.

• 🎨 Beautiful, Consistent Visuals: Leverage the power of Plotly for stunning, replicable charts. Use YAML templates to create a library of reusable chart designs.
• 📊 Connect Directly to Your Data: Pull data from CSV files, JSON, Databricks, or even your dbt models. No more manual data exports.
• ⚡ Automate Your Reporting: Stop the manual work. Reduce errors and save time. Your presentations are always up-to-date with your latest data.
• 🚀 Scale Instantly: Need to create a presentation for every customer, region, or product? Generate hundreds of personalized presentations at once from a single template.

---

🔑 Key Features

• Declarative YAML Configuration: Define your entire presentation in a simple, human/agent readable YAML file.
• Multiple Data Source Connectors:
  • csv: For local CSV files.
  • json: For local JSON files.
  • databricks: For running SQL queries directly against Databricks.
  • databricks_dbt: For using your existing dbt models as data sources.
• Dynamic Content Replacements:
  • Text: Replace simple placeholders like {{TOTAL_REVENUE}} with dynamic values.
  • Tables: Populate entire tables in your slides from a DataFrame.
  • AI-Generated Text: Use OpenAI or Gemini to generate summaries, insights, or any other text, right from your data.
• Powerful Charting Engine:
  • Plotly Graph Objects: Create any chart you can imagine with the full power of Plotly.
  • YAML Chart Templates: Use packaged built-ins or define reusable local templates.
  • Custom Python Functions: For when you need complete control over your chart generation logic.
• Extensible and Customizable:
  • Use Function Registries to extend SlideFlow with your own Python functions for data transformations, formatting, and more.
• Powerful CLI:
  • slideflow build: Generate one or many presentations.
  • slideflow validate: Validate your configuration before you build.
  • slideflow templates: Inspect available template names and parameter contracts.
  • Generate multiple presentations from a single template using a CSV parameter file.

---

🔧 How It Works

SlideFlow works in three simple steps:

1. Define: You create a YAML file that defines your presentation. This includes the Google Slides template to use, the data sources to connect to, and the content for each slide (text, charts, etc.).
2. Connect & Transform: SlideFlow connects to your specified data sources, fetches the data, and applies any transformations you've defined.
3. Build: SlideFlow creates a new presentation, populates it with your data and charts, and saves it to your Google Drive.

---

🛠 Installation

pip install slideflow-presentations

---

🧑‍💻 Getting Started

To create your first presentation, you'll need:

1. A Google Slides Template: Create a Google Slides presentation with the layout and branding you want. Note the ID of each slide you want to populate.

2. Your Data: Have your data ready in a CSV file, or have your Databricks credentials configured.

3. A YAML Configuration File: This is where you'll define your presentation. See the Configuration section for more details.

4. Google Cloud Credentials: You'll need a Google Cloud service account with access to the Google Slides and Google Drive APIs. Provide your credentials in one of the following ways:

   • Set the credentials field in your config.yml to the path of your JSON credentials file.
   • Set the credentials field in your config.yml to the JSON content of your credentials file as a string.
   • Set the GOOGLE_SLIDEFLOW_CREDENTIALS environment variable to the path of your JSON credentials file or the content of the file itself.

Once you have these, you can run the build command:

slideflow build your_config.yml

---

⚙️ CLI Usage

SlideFlow comes with a simple CLI.

build

The build command generates your presentation(s).

slideflow build [CONFIG_FILE] [OPTIONS]

Arguments:

• CONFIG_FILE: Path to your YAML configuration file.

Options:

• --registry, -r: Path to a Python file containing a function_registry. You can use this option multiple times.
• --params-path, -f: Path to a CSV file containing parameters for generating multiple presentations.
• --dry-run: Validate the configuration without building the presentation.

validate

The validate command checks your configuration for errors.

slideflow validate [CONFIG_FILE] [OPTIONS]

Arguments:

• CONFIG_FILE: Path to your YAML configuration file.

Options:

• --registry, -r: Path to a Python file containing a function_registry.

---

📝 Configuration

Your config.yml file is the heart of your SlideFlow project. Here's a high-level overview of its structure:

presentation:
  name: "My Awesome Presentation"
  slides:
    - id: "slide_one_id"
      title: "Title Slide"
      replacements:
        # ... text, table, and AI replacements
      charts:
        # ... chart definitions

provider:
  type: "google_slides"
  config:
    credentials: "/path/to/your/credentials.json"
    template_id: "your_google_slides_template_id"

template_paths:
  - "./templates"

For more detailed information on the configuration options, please see the documentation.

---

🎨 Customization

SlideFlow is designed to be extensible. You can use your own Python functions for:

• Data Transformations: Clean, reshape, or aggregate your data before it's used in charts or replacements.
• Custom Formatting: Format numbers, dates, and other values exactly as you need them.
• Custom Charts: Create unique chart types that are specific to your needs.

To use your own functions, create a registry.py file with a function_registry dictionary:

# registry.py

def format_as_usd(value):
    return f"${value:,.2f}"

function_registry = {
    "format_as_usd": format_as_usd,
}

You can then reference format_as_usd in your YAML configuration.

---

📜 License

MIT License © Joe Broadhead