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2024 11 10 Doc Driven Development Docdd

Deno KV (Dave)

I was thinking if we used Deno for the CLI and SSG, we could use the built-in Deno KV store to keep track of things like:

  • fingerprinting files with hashes (for change detection)
  • data file inventory (e.g., if the file disappears, prompt user whether it should be removed from namespace)
  • indexing mentions of NameIndividuals for cataloging purposes.

Deno KV ChatGPT

Using Deno KV for those purposes is a fantastic idea. It provides a lightweight, persistent way to manage the information you'll need to track, without introducing the overhead of setting up an external database. Let’s delve into how you could use Deno KV effectively for each of these use cases:

1. File Fingerprinting with Hashes for Change Detection

  • Goal: Detect changes in files by storing hashes in the KV store. When a file is updated or modified, its fingerprint should change.

  • How to Implement:

    • Initial Fingerprint Creation: When a data file is added or indexed, calculate a hash (e.g., using SHA256) and store it in the Deno KV store alongside the file path.

    • Change Detection: On subsequent runs, recalculate the hash of each file and compare it to the stored value in the KV. If the hash has changed, flag the file as modified.

    • Example in Deno:

      import { createHash } from "https://deno.land/std/hash/mod.ts";
import { openKv } from "https://deno.land/x/kv/mod.ts";

const kv = await openKv();

async function fingerprintFile(filePath: string) {
  const fileData = await Deno.readFile(filePath);
  const hash = createHash("sha256").update(fileData).toString();

  const kvKey = ["fileHash", filePath];
  const existingEntry = await kv.get(kvKey);

  if (existingEntry?.value !== hash) {
    // File has changed or is new
    console.log(`File changed or new: ${filePath}`);
    await kv.set(kvKey, hash);
  } else {
    // File is unchanged
    console.log(`File unchanged: ${filePath}`);
  }
}

// Example usage
await fingerprintFile("./data/sflow-ontology.ttl");

    • Workflow:

      • On each run, the CLI/SSG checks each data file, calculates its hash, and compares it to the stored hash.
      • If the hash is different, trigger any necessary rebuilds or updates.

2. Data File Inventory Management

  • Goal: Keep a live inventory of all data files and monitor changes, such as files being deleted or added. This inventory helps you ensure consistency between the data files and the generated namespace.

  • How to Implement:

    • Store Metadata: Track files along with their metadata, such as last modified date, fingerprint, and dataset references.

    • File Removal Detection: If a file goes missing, you can use the inventory to prompt the user about whether the NamedIndividual or any linked data should be removed or updated.

    • Example Inventory Management in Deno:

      async function updateInventory(filePath: string) {
  const kvKey = ["fileInventory", filePath];

  try {
    // Check if the file exists
    await Deno.stat(filePath);

    // File exists, update inventory
    const lastModified = (await Deno.stat(filePath)).mtime;
    await kv.set(kvKey, { exists: true, lastModified });

  } catch (e) {
    if (e instanceof Deno.errors.NotFound) {
      // File does not exist, prompt user for action
      const existingEntry = await kv.get(kvKey);
      if (existingEntry?.value?.exists) {
        console.log(`File ${filePath} is missing. Should it be removed from the namespace?`);
        // Here, you could prompt the user or automate removal actions
        await kv.set(kvKey, { exists: false });
      }
    }
  }
}

// Example usage
await updateInventory("./data/dave-richardson.jsonld");

    • Workflow:

      • On each scan, the script checks if files still exist and keeps the inventory up to date.
      • If a file is removed, the CLI could either prompt for manual intervention or automatically remove any related dataset references.

3. Indexing Mentions of NamedIndividuals for Cataloging

  • Goal: Track all occurrences and mentions of NamedIndividuals across different datasets and namespaces, facilitating cataloging and easy reference.

  • How to Implement:

    • Extract NamedIndividual Mentions: During the parsing of data files, extract any IRIs or mentions of NamedIndividuals.

    • Store Mentions in Deno KV: Store these mentions in the KV store, keyed by the NamedIndividual IRI. This makes it easy to query which datasets reference each NamedIndividual.

    • Example Indexing Mentions in Deno:

      import { parse } from "https://deno.land/x/turtle/mod.ts"; // Hypothetical Turtle parser

async function indexNamedIndividuals(filePath: string) {
  const fileContent = await Deno.readTextFile(filePath);
  const parsedData = parse(fileContent); // Assuming the parse function returns structured triples

  for (const triple of parsedData) {
    if (triple.subject && triple.subject.startsWith("https://namespace/")) {
      // Assuming subject is a NamedIndividual IRI
      const kvKey = ["namedIndividualMentions", triple.subject];
      const currentMentions = (await kv.get(kvKey))?.value || [];
      currentMentions.push({ file: filePath, predicate: triple.predicate, object: triple.object });
      await kv.set(kvKey, currentMentions);
    }
  }
}

// Example usage
await indexNamedIndividuals("./data/sflow-ontology.ttl");

    • Workflow:

      • As you parse each file, extract the IRIs of NamedIndividuals and store references to where they are mentioned.
      • This allows you to catalog the relationships and easily generate cross-references, aiding in catalog generation and inter-linking data.

Benefits of Using Deno KV for These Tasks

  1. Simplicity and Integration:

    • Since Deno KV is built into Deno, there is no need for a separate database setup, simplifying dependencies and reducing complexity.
    • Native integration means faster performance and no cross-environment connection issues.

  2. Persistent Data Tracking:

    • Deno KV offers persistent storage, meaning the fingerprints, inventory, and indexes are stored between runs of the CLI or SSG.
    • You won’t need to recalculate everything from scratch each time, which significantly speeds up workflows.

  3. Efficient Change Detection:

    • Hashes stored in KV allow for quick detection of changes. Only files that have changed need to be processed during a rebuild.
    • This can drastically reduce processing time for large datasets.

  4. Query Capabilities:

    • You can leverage Deno KV queries to efficiently retrieve information, such as which datasets reference a given NamedIndividual or which files have changed since the last build.
    • This makes cataloging and other analysis tasks more straightforward.

Example Workflow Integration

  • During the CLI invocation:

    1. Hash all data files and compare to the stored hashes in KV to determine changes.
    2. Update the data inventory in KV, prompting the user if a file is removed.
    3. Index NamedIndividual mentions by parsing updated files and storing them in the KV.

  • During the SSG run:

    • The KV store is used to determine which files have changed and need rebuilding, ensuring that the generation process is both efficient and incremental.

Summary

By using Deno KV, you can efficiently track:

  • Hashes for change detection (fingerprinting).
  • A data inventory for consistency and management.
  • Mentions of NamedIndividuals for cataloging and cross-referencing purposes.

This approach keeps everything lean and integrated, avoiding the overhead of an external database, while providing the tracking, indexing, and management capabilities you need for a robust Semantic Flow setup. Let me know if you need help diving deeper into any part of this implementation!

documenting sflow-cli (dave, t.2024.11.11.09)

I want to try documentation-driven development, and use lume to generate the documentation for sflow-cli. So things get confusing, because I always want to use lume as part of the sflow-cli, i.e., as part of a SFNamespaceRepo whose folder structure we've discussed. Lume also has a script runner, so maybe it can be used instead of Cliffy as the basis for the sflow-cli. But I think it makes sense to start with a new sflow-cli repo that has a lume installation generating documentation into a docs folder. Assume the top-level folder will have a src folder for the eventual flow-cli source code. Should the markdown-based documentation source live in the src folder too? maybe as /src/documentation?

documenting sflow-cli (chatgpt)

Using documentation-driven development with Lume is a smart move, especially since Lume is well-suited for Deno environments, and it can help you maintain consistent, automatically generated documentation as you develop sflow-cli.

Folder Structure for sflow-cli Repository

Since you're going for documentation-driven development, it makes sense to have the documentation tightly integrated with the source code, but you still want clarity and ease of use when navigating your project. Here's a suggestion on how to structure your new sflow-cli repository to balance documentation, source code, and site generation:

sflow-cli/
│
├── docs/                        # Lume-generated documentation (static output)
│
├── src/                         # Source code for sflow-cli
│   ├── cli/                     # CLI source code files
│   └── documentation/           # Markdown files for CLI documentation
│
├── lume.config.js               # Lume configuration file
│
├── _includes/                   # Template files for Lume (e.g., layout.html)
│
├── assets/                      # Static assets for Lume-generated documentation (CSS, JS)
│
├── _site/                       # Optional folder to preview built site locally if needed
│
└── README.md                    # Project overview and setup instructions

Where Should the Documentation Live?

  • Placing the Markdown-based documentation in /src/documentation keeps the documentation close to the source code it describes.
  • This helps ensure that any changes to the code can easily be matched with corresponding updates to the documentation, since both will be in the same logical section of the repository (src).
  • It also supports a single source of truth approach: as you develop, the documentation is directly tied to the source code, reducing the risk of forgetting to update it when things change.

Advantages of Placing Documentation in /src/documentation:

  1. Documentation-Driven Development: By putting the documentation alongside the source code, developers are reminded to update docs as they change the codebase. This naturally leads to a documentation-first workflow.
  2. Ease of Navigation: When developers are in the /src directory, they can easily locate documentation, making it faster to understand the current state of the implementation or update docs.
  3. Centralized Changes: Version control systems like Git will track changes in both the code and docs together, making it easier to see how a feature implementation relates to the corresponding documentation.

Using Lume to Generate Documentation

  • Source Folder (src/documentation): You can tell Lume to look for your Markdown files in this folder.
  • Destination Folder (docs/): The generated site will be output to the docs/ folder, which you can also use as a GitHub Pages target for publishing your sflow-cli documentation.

Here's how you can configure Lume to accomplish this:

  1. Configure Lume to Use /src/documentation as Input:

    • You will need to adjust the lume.config.js file to use /src/documentation as the source.

    • Example lume.config.js:

      import lume from "https://deno.land/x/lume/mod.ts";

const site = lume({
  src: "./src/documentation",  // Source folder for documentation
  dest: "./docs",              // Output folder for generated site
});

// Add any custom configurations or plugins you need
export default site;

  2. Structure of /src/documentation:

    • You can use a structure within documentation that logically follows the different parts of your sflow-cli:
    src/
└── documentation/
    ├── index.md              # Main documentation page
    ├── getting-started.md    # Guide for setup and installation
    ├── commands.md           # Detailed breakdown of all sflow-cli commands
    ├── architecture.md       # Explain the internal design of sflow-cli
    └── examples.md           # Provide usage examples

  3. Generate Documentation Using Lume:

    • Run Lume from your repository’s root directory:
    lume build
    • This will generate the static documentation pages based on the Markdown content inside /src/documentation, outputting them to the docs/ folder.
    • If you’re hosting the generated site using GitHub Pages, the docs/ folder is automatically recognized as the root for serving static files.

Use Lume Script Runner Instead of Cliffy

Another interesting point you made is about using Lume’s script runner as the basis for sflow-cli. This can be a great approach if you want to minimize dependencies and leverage the scripting capabilities built into Lume.

  • How Lume’s Script Runner Works: Lume allows you to define custom scripts that can be run during the build process or at other points in the project lifecycle. These scripts can be integrated into the CLI to handle various tasks like:

    • Updating or transforming RDF data.
    • Building new versions of dataset series or NamedIndividuals.
    • Automating site generation.

  • Replacing Cliffy with Lume Scripts:

    • Instead of relying on Cliffy for command interaction, you could write scripts in Lume that handle command-like actions.

    • Example: Add a script to Lume that can initialize a new NamedIndividual:

      import lume from "https://deno.land/x/lume/mod.ts";

const site = lume({
  src: "./src/documentation",
  dest: "./docs",
});

// Example Lume script to add a new NamedIndividual
site.script("initNamedIndividual", async (args) => {
  const [name] = args;

  if (!name) {
    console.log("Please provide a NamedIndividual name.");
    return;
  }

  // Example operation: create a new Markdown file for the NamedIndividual documentation
  await Deno.writeTextFile(`./src/documentation/${name}.md`, `# ${name}\n\nInitial documentation.`);
  console.log(`NamedIndividual ${name} initialized with a new documentation file.`);
});

export default site;

    • Usage:

      lume run initNamedIndividual MyNewIndividual

Summary

  1. Folder Structure:

    • Use /src/documentation for storing Markdown-based documentation close to the source code.
    • Use /docs as the output folder where Lume will generate the static documentation site.

  2. Configuration:

    • Use Lume to point to /src/documentation as the source folder and /docs as the output.
    • Define your templates in _includes or any custom directory to maintain consistent formatting.

  3. Lume for CLI Tasks:

    • You can potentially replace Cliffy by leveraging Lume’s script runner to handle interactive command tasks.
    • Define custom scripts in Lume to manage aspects of sflow-cli, such as dataset handling, template generation, and site builds.

This approach will give you a documentation-driven development cycle where Lume not only generates the documentation for sflow-cli but also potentially becomes the basis for executing CLI commands and automation tasks. Let me know if you need more guidance on setting up specific Lume scripts or integrating other tools!

lume in subfolder

Using Lume in a subfolder within your project can make sense in some contexts, but there are pros and cons depending on how you organize your workflow and your objectives for sflow-cli. Let me elaborate on whether this is a good approach and suggest some potential paths.

Considerations for Placing Lume in a Subfolder

If you’re thinking about having Lume inside a subfolder, such as /ssg, let’s discuss the implications:

1. Folder Structure with Lume in a Subfolder

sflow-cli/
│
├── src/                       # Source code for sflow-cli
│   ├── cli/                   # CLI source code files
│   └── documentation/         # Markdown files for CLI documentation
│
├── ssg/                       # Lume installation and related SSG configuration
│   ├── lume.config.js         # Lume configuration for the static site
│   ├── _includes/             # Templates for generating documentation pages
│   ├── assets/                # Static assets (e.g., CSS, JavaScript)
│   └── scripts/               # Custom Lume scripts for sflow-cli tasks
│
├── docs/                      # Lume-generated documentation (static output)
│
└── README.md                  # Project overview and setup instructions

Benefits of Having Lume in a Subfolder

  1. Clear Separation of Concerns:

    • By putting Lume in a subfolder like /ssg, you are isolating everything related to static site generation from the core logic and documentation of sflow-cli. This makes it easier for contributors to understand where each part belongs.
    • It creates a clear distinction between the source content, the documentation logic, and the generated static output. This organization can help when onboarding new developers or contributors, as each part of the project is compartmentalized.

  2. Modular Design:

    • Keeping Lume in a subfolder, along with all its related configurations and assets, makes it modular. If you want to swap out Lume for another SSG or change the build process in the future, it becomes much simpler since all Lume-related files are contained within a dedicated subfolder.

  3. Centralized SSG Configurations:

    • All SSG-specific configurations (e.g., templates, assets, plugins) are in one place. If you have Lume inside a dedicated folder, you can manage updates, templates, and other configurations without affecting the main source code or documentation content.

  4. Less Noise in the Root Directory:

    • The root folder of your project remains cleaner. This reduces clutter, making it easier to manage project-level configurations and understand the overall structure.

Challenges of Placing Lume in a Subfolder

  1. Path Complexity:

    • You may need to manage additional paths when it comes to input/output for Lume. For instance, Lume’s source files (src) might reside outside of the /ssg folder (in /src/documentation), and its output should be to /docs. This can add some complexity to the lume.config.js where you’ll need to explicitly configure paths for both source and destination.

    • Example lume.config.js:

      import lume from "https://deno.land/x/lume/mod.ts";

const site = lume({
  src: "../src/documentation",  // Source folder for Markdown files
  dest: "../docs",              // Destination for static HTML files
});

// Configure custom settings, add plugins, etc.
export default site;

  2. Integration with CLI:

    • Since you want sflow-cli to also manage static site generation, having Lume in a separate subfolder could mean additional commands and navigation between folders during your workflow.
    • For example, you’d need to run commands from the /ssg folder, or provide relative paths to target the proper configuration.

  3. Build Workflow Complexity:

    • If you integrate Lume’s script runner into sflow-cli, then having Lume in a subfolder means you’ll need to call those scripts explicitly by navigating to the /ssg folder or adjusting the relative path in your commands.
    • This could potentially increase the complexity of your build workflow, especially if multiple people are working on the project and paths need to be managed consistently.

Alternative Approach: Keeping Lume in the Root Folder

If placing Lume in a subfolder seems like it might add unnecessary complexity, another option is to keep Lume at the root level:

  • By keeping the Lume configuration (lume.config.js) and related folders in the root directory, you make Lume more accessible.
  • This setup allows you to easily run Lume commands without navigating deep into the folder structure.
  • The configuration would have simpler paths since the source (/src/documentation) and the output (/docs) are all at the same level.

Example Folder Structure Without Lume in a Subfolder:

sflow-cli/
│
├── src/                      # Source code for sflow-cli
│   ├── cli/                  # CLI source code files
│   └── documentation/        # Markdown files for CLI documentation
│
├── docs/                     # Lume-generated documentation (static output)
│
├── _includes/                # Templates for Lume (e.g., layout.html)
├── assets/                   # Static assets for Lume-generated documentation (CSS, JS)
├── lume.config.js            # Lume configuration file
└── README.md                 # Project overview and setup instructions

Summary of Pros and Cons

Lume in a Subfolder (e.g., /ssg)

Pros:

  • Clear Separation of site generation logic.
  • Modular and Replaceable.
  • Easier to manage SSG configurations without affecting core code.

Cons:

  • Path Complexity when specifying source/destination paths.
  • Slightly more complex build process, especially if integrating Lume’s script runner.
  • Requires additional navigation between folders when running commands.

Lume at the Root Level

Pros:

  • Simpler paths for input and output, making configuration easier.
  • More accessible when running commands or working with documentation-driven development.
  • Direct integration with sflow-cli without needing explicit subfolder references.

Cons:

  • Less modular, as all configuration and SSG logic are mixed in the top level.
  • Less separation of concerns, which could make it harder to isolate SSG-related issues from core project concerns.

Recommendation

If your priority is keeping things modular and well-separated, then putting Lume in a subfolder (/ssg) is a solid choice. It keeps the overall repository clean and makes Lume easy to replace or refactor independently of the main project. You just need to ensure that the path management in lume.config.js is clearly documented to avoid confusion for team members.

However, if you want simplicity and less friction during development, especially since you’re incorporating documentation-driven workflows with Lume, keeping it in the root is a more straightforward option. It will keep commands simple and make onboarding new contributors easier.

Ultimately, it depends on whether the benefits of modularity outweigh the added complexity of navigating between folders and managing paths. If you are leaning towards modularity and scalability, the subfolder approach (/ssg) will serve you well. Let me know if you want to dive deeper into configuring either setup!

Deno KV (Dave)
Deno KV ChatGPT
1. File Fingerprinting with Hashes for Change Detection
2. Data File Inventory Management
3. Indexing Mentions of NamedIndividuals for Cataloging
Benefits of Using Deno KV for These Tasks
Example Workflow Integration
Summary
documenting sflow-cli (dave, t.2024.11.11.09)
documenting sflow-cli (chatgpt)
Folder Structure for sflow-cli Repository
Where Should the Documentation Live?
Advantages of Placing Documentation in /src/documentation:
Using Lume to Generate Documentation
Use Lume Script Runner Instead of Cliffy
Summary
lume in subfolder
Considerations for Placing Lume in a Subfolder
1. Folder Structure with Lume in a Subfolder
Benefits of Having Lume in a Subfolder
Challenges of Placing Lume in a Subfolder
Alternative Approach: Keeping Lume in the Root Folder
Summary of Pros and Cons
Lume in a Subfolder (e.g., /ssg)
Lume at the Root Level
Recommendation