Date: 2025 07-July 03

Clayton 0:

there has been a key change: src/{projectname}/projectmanager.py has been changed to src/workpace_manager.py

the name of the tool is now mulch, as in pipx install mulch

mulch is currently incomplete (due to a session limit with ChatGPT, the intent got confused and now I am sorting out problems caused by that confusion)

there is a distincation between workspace_manager (a product generated by mulch) and workspace_factory (the portion of the mulch code that generates new workspaces and initilized new projects which include root/src/{projectname}/workspace_manager and root/workspaces/default and root/workspaces/{new}, etc)

a key problem is that my scaffold.json works to generate empty files but does not fill them

also, i need to generate the root/src/{projectname}/workspace_manager.py files, possibly based on jinja 2 templating

my thought is that mulch init will run phase one, to merely establish things which are constant, like the root/workspaces/ folder and the root/src folder, and also to generate an example default root/scaffold.json file

the scaffold.json file can then be edited to specify what the default workspace will be like and this will also be reflected in the successfuly templated root/src/{projectname}/workspace_manager.py file,

clearer than mud? ask clarifying questions, one at a time

ChatGPT 0:

Crystalizing beautifully. Let me confirm what I think you’re saying before we proceed:

❓ First Clarification Question:
When you say that scaffold.json currently "works to generate empty files but does not fill them," do you mean that:

• mulch is creating the correct file paths,

• but not writing templated content into those files?

Or do you mean that:

• it’s not even resolving the Jinja2 template with values from scaffold.json?

(Just want to pin down whether it’s a templating issue or a file-writing issue.)

Clayton 1:

the first one

the code base does not currently support filling files

it is not using jinja2 yet

this is a function from the current (incomplete) version of mulch/src/mulch/workspace_factory.py

def load_scaffold(self) -> dict: 
        scaffold_path = Path(__file__).parent / self.DEFAULT_SCAFFOLD_FILENAME
        
        #fallback_scaffold = {
        #    "folders": ["workspaces", "logs", "configs"],
        #    "files": ["README.md", "default-workspace.toml"]
        #}
        
        fallback_scaffold = {
            "": ["config", "data", "imports", "exports", "scripts", "secrets", "queries"],
            "exports": ["aggregate"],
            "config": ["default-workspace.toml"],
            "secrets": ["secrets.yaml", "secrets-example.yaml"],
            "queries": ["default-queries.toml"]
        }
        
        if not scaffold_path.exists():
            # File missing, log warning and return fallback
            print(f"Warning: Missing scaffold file: {scaffold_path}, using fallback scaffold.")
            return fallback_scaffold
            
        #with open(scaffold_path, "r") as f:
        #    return json.load(f)
            
        try:
            with open(scaffold_path, "r") as f:
                content = f.read().strip()
                if not content:
                    print(f"Warning: Scaffold file {scaffold_path} is empty, using fallback scaffold.")
                    return fallback_scaffold
                return json.loads(content)
        except json.JSONDecodeError as e:
            print(f"Warning: Scaffold file {scaffold_path} contains invalid JSON ({e}), using fallback scaffold.")
            return fallback_scaffold

this is the current state of mulch/src/mulch/cli.py (which is wrong)

import typer
from pathlib import Path
from mulch.workspace_factory import WorkspaceFactory

HELP_TEXT = "Workspace Manager CLI for scaffolding project workspaces."

app = typer.Typer(help=HELP_TEXT, no_args_is_help=True)

@app.callback()
def main():
    f"""
    {HELP_TEXT}
    """
    pass
@app.command()
def init(
    target_dir: Path = typer.Argument(
        Path.cwd(),
        help="Target project root. Defaults to current directory."
    ),
    name: str = typer.Option("default", "--name", "-n", help="Name of the workspace to create."),
    set_default: bool = typer.Option(True, "--set-default/--no-set-default", help="Write default-workspace.toml")
):
    """
    Initialize a new workspace inside the given target directory.
    """
    target_dir = target_dir.resolve()
    wm = WorkspaceFactory(base_path=target_dir, workspace_name=name)
    wm.check_and_create_dirs_from_scaffold()

    if set_default:
        wm.create_default_workspace_toml(target_dir / "workspaces", name)

    typer.echo(f"Workspace '{name}' initialized at {wm.workspace_dir}")


if __name__ == "__main__":
    app()

ChatGPT 1:

Perfect. That clears it up. Here's the situation as I understand it, broken down surgically:

✅ What is working:

• You have a CLI command (mulch init) that:

  • Creates a target workspace folder structure (via WorkspaceFactory.check_and_create_dirs_from_scaffold()).

  • Accepts a --name to define the workspace directory name.

  • Creates a default TOML file pointing to that workspace.

• scaffold.json defines the nested folder and file structure.

• You fall back to a hardcoded dict if scaffold.json is missing or invalid.

🚫 What is not working yet:

• Files listed in scaffold.json are created empty, with no content.

• You’re not using Jinja2 (or any templating engine) to generate the contents of files like workspace_manager.py.

• workspace_manager.py is not generated at all yet.

• scaffold.json is not used to inject any content into files.

🧭 Next Logical Step

You need to:

1. Add support for file templating (e.g., using Jinja2).

2. Define one or more template files (workspace_manager.py.j2, etc.)

3. Inject values from scaffold.json into those templates.

4. Write the rendered content to the proper location (src/<workspace_name>/workspace_manager.py)

❓My Next Clarifying Question:

Do you want to treat scaffold.json as:

• a layout spec only (just folders + filenames, maybe a few config values),
  or

• a data context for template rendering (values like workspace_name, dir names, defaults)
  that gets passed into Jinja templates?

Clarifying this will help determine:

• Whether you use scaffold.json to just define what gets made,

• Or whether you load it as a context into Jinja when rendering the workspace_manager.py file.

Clayton 2:

Well, let's talk about which existing tools I might use to accomplish my goal, or to wrap mulch around

cookiecutter is a good candidate

is cookiecutter able to create variable numbers of folders based on the stub? or is it stuck with a particular format and all that changes is the names?

in comparison, tell me about jinja2 and what i can do with it and how it works

ChatGPT 2:

Excellent topic. Understanding the boundaries between Cookiecutter, Jinja2, and your own logic (e.g., mulch) will help you choose the right tool for the right layer. Let’s break them down clearly:

🧁 Cookiecutter: Full Project Scaffolder

✅ What Cookiecutter is:

• A wrapper around Jinja2 that scaffolds entire directory structures and files.

• It uses a folder-based template project, and a cookiecutter.json (or .yaml) to ask questions or accept values to fill into Jinja templates.

• It supports templating of file contents, filenames, folder names, etc.

✅ What it can do:

• Create multiple folders/files, conditionally, using Jinja2 logic (e.g., loops, conditionals).

• Create dynamic paths and nested folders, as long as the logic is handled inside the template.

• Run post-hooks (Python scripts or shell) after generation.

• Be used programmatically (cookiecutter(...)) or via CLI (cookiecutter ./template).

🚫 What it can’t do easily:

• Take a complex config like your scaffold.json and dynamically interpret an arbitrary number of folders/files unless you pre-bake that logic into the template structure.

• React to runtime logic in Python unless you build that into post-generation hooks.

Verdict: Cookiecutter is great for "create a new repo with a pre-defined structure and templated code"
But it’s not meant to be an engine that ingests a config file and generates N folders/files based on that.

🧩 Jinja2: Templating Engine Only

✅ What Jinja2 is:

• A Python string rendering engine, used to convert a template (.j2 file) into a real file by injecting a context dictionary.

• The logic behind Cookiecutter (and Flask templates, Ansible, etc.)

✅ What it can do:

• Render text files, including .py, .json, .toml, etc.

• Run logic in templates: if/else, for-loops, filters (capitalize, lower, etc.)

• Dynamically generate code with injected values.

Example:

# workspace_manager.py.j2
class WorkspaceManager:
    WORKSPACE_NAME = "{{ workspace_name }}"
    {% for folder in folders %}
    {{ folder.upper() }}_DIR = Path("{{ folder }}")
    {% endfor %}

With context:

context = {
  "workspace_name": "eds_to_rjn",
  "folders": ["config", "exports", "queries"]
}

The output is a fully rendered Python file.

Verdict: Jinja2 is perfect for dynamically generating files like workspace_manager.py from a structured config like scaffold.json.

🛠️ So What Should Mulch Do?

Given your structure and goals:

• Use Jinja2 directly to:

  • Load scaffold.json as a dict

  • Use it as the context

  • Render workspace_manager.py into src/<name>/workspace_manager.py

• You can still offer optional Cookiecutter-style scaffolding for full projects (e.g., creating README.md, pyproject.toml, etc.), but that should be a plugin or alternate path, not your core.

🧠 Decision Summary

✅ Ready for Action?

If you agree with this model, the next logical step is:

Integrate Jinja2 into mulch so that workspace_manager.py.j2 can be rendered using scaffold.json.

I can help you set up:

• A templates/ folder

• A first workspace_manager.py.j2

• A render_template() function inside WorkspaceFactory or a new TemplateRenderer class

Ready to proceed? Or want to add your own thoughts first?

Clayton 3:

is scaffold.json really a good approach for the kind of templating I want to do?

let me break down what i want to accomplish, by showing a working example

as a reminder, here is an example of a current projectmanager.py file, which will soon be known as a "workspace_manager.py" file

PS C:\Users\george.bennett\OneDrive - City of Memphis\Documents\dev\mulch> cat ..\pipeline\src\pipeline\projectmanager.py

import os

import toml

import logging

from pathlib import Path

'''

Goal:

Implement default-project.toml variable: use-most-recently-edited-project-directory

'''

# Configure logging (adjust level as needed)

logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s")

class ProjectManager:

# It has been chosen to not make the ProjectManager a singleton if there is to be batch processing.

PROJECTS_DIR_NAME = 'projects'

QUERIES_DIR_NAME = 'queries'

IMPORTS_DIR_NAME = 'imports'

EXPORTS_DIR_NAME = 'exports'

SCRIPTS_DIR_NAME = 'scripts'

CONFIGS_DIR_NAME ='secrets'

SECRETS_YAML_FILE_NAME ='secrets.yaml'

SECRETS_EXAMPLE_YAML_FILE_NAME ='secrets-example.yaml'

DEFAULT_PROJECT_TOML_FILE_NAME = 'default-project.toml'

TIMESTAMPS_JSON_FILE_NAME = 'timestamps_success.json'

ROOT_DIR = Path(__file__).resolve().parents[2] # root directory

# This climbs out of /src/pipeline/ to find the root.

# parents[0] → The directory that contains the (this) Python file.

# parents[1] → The parent of that directory.

# parents[2] → The grandparent directory (which should be the root), if root_pipeline\src\pipeline\

# This organization anticipates PyPi packaging.

def __init__(self, project_name):

self.project_name = project_name

self.projects_dir = self.get_projects_dir()

self.project_dir = self.get_project_dir()

self.exports_dir = self.get_exports_dir()

self.imports_dir = self.get_imports_dir()

self.queries_dir = self.get_queries_dir()

self.configs_dir = self.get_configs_dir()

self.scripts_dir = self.get_scripts_dir()

self.aggregate_dir = self.get_aggregate_dir()

self.check_and_create_dirs(list_dirs =

[self.project_dir,

self.exports_dir,

self.imports_dir,

self.configs_dir,

self.scripts_dir,

self.aggregate_dir])

def get_projects_dir(self):

return self.ROOT_DIR / self.PROJECTS_DIR_NAME

def get_project_dir(self):

return self.get_projects_dir() / self.project_name

def get_exports_dir(self):

return self.project_dir / self.EXPORTS_DIR_NAME

def get_exports_file_path(self, filename):

# Return the full path to the export file

return self.exports_dir / filename

def get_aggregate_dir(self):

# This is for five-minute aggregation data to be stored between hourly bulk passes

# This should become defunct once the tabular trend data request is functional

return self.exports_dir / 'aggregate'

def get_imports_dir(self):

return self.project_dir / self.IMPORTS_DIR_NAME

def get_imports_file_path(self, filename):

# Return the full path to the export file

return self.imports_dir / filename

def get_configs_dir(self):

return self.project_dir / self.CONFIGS_DIR_NAME

def get_configs_secrets_file_path(self):

# Return the full path to the config file

file_path = self.configs_dir / self.SECRETS_YAML_FILE_NAME

if not file_path.exists():

logging.warning(f"Configuration file {self.SECRETS_YAML_FILE_NAME} not found in:\n{self.configs_dir}.\nHint: Copy and edit the {self.SECRETS_YAML_FILE_NAME}.")

print("\n")

choice = str(input(f"Auto-copy {self.SECRETS_EXAMPLE_YAML_FILE_NAME} [Y] or sys.exit() [n] ? "))

if choice.lower().startswith("y"):

file_path = self.get_configs_secrets_file_path_or_copy()

else:

# edge case, expected once per machine, or less, if the user knows to set up a secrets.yaml file.

import sys

sys.exit()

return file_path

def get_configs_secrets_file_path_or_copy(self):

# Return the full path to the config file or create it from the fallback copy if it exists

file_path = self.configs_dir / self.SECRETS_YAML_FILE_NAME

fallback_file_path = self.configs_dir / self.SECRETS_EXAMPLE_YAML_FILE_NAME

if not file_path.exists() and fallback_file_path.exists():

import shutil

shutil.copy(fallback_file_path, file_path)

print(f"{self.SECRETS_YAML_FILE_NAME} not found, copied from {self.SECRETS_YAML_FILE_NAME}")

elif not file_path.exists() and not fallback_file_path.exists():

raise FileNotFoundError(f"Configuration file {self.SECRETS_YAML_FILE_NAME} nor {self.SECRETS_EXAMPLE_YAML_FILE_NAME} not found in directory '{self.configs_dir}'.")

return file_path

def get_scripts_dir(self):

return self.project_dir / self.SCRIPTS_DIR_NAME

def get_scripts_file_path(self, filename):

# Return the full path to the config file

return self.get_scripts_dir() / filename

def get_queries_dir(self):

return self.project_dir / self.QUERIES_DIR_NAME

def get_queries_file_path(self,filename): #

# Return the full path to the config file

filepath = self.get_queries_dir() / filename

if not filepath.exists():

raise FileNotFoundError(f"Query filepath={filepath} not found. \nPossible reason: You are in the wrong project directory.")

return filepath

def get_timestamp_success_file_path(self):

# Return the full path to the timestamp file

return self.get_queries_dir() / self.TIMESTAMPS_JSON_FILE_NAME

def check_and_create_dirs(self, list_dirs):

for dir_path in list_dirs:

if not dir_path.exists():

dir_path.mkdir(parents=True, exist_ok=True)

@classmethod

def identify_default_project(cls):

"""

Class method that reads default-project.toml to identify the default-project.

"""

projects_dir = cls.ROOT_DIR / cls.PROJECTS_DIR_NAME

logging.info(f"projects_dir = {projects_dir}\n")

default_toml_path = projects_dir / cls.DEFAULT_PROJECT_TOML_FILE_NAME

if not default_toml_path.exists():

raise FileNotFoundError(f"Missing {cls.DEFAULT_PROJECT_TOML_FILE_NAME} in {projects_dir}")

with open(default_toml_path, 'r') as f:

data = toml.load(f)

logging.debug(f"data = {data}")

try:

return data['default-project']['project'] # This dictates the proper formatting of the TOML file.

except KeyError as e:

raise KeyError(f"Missing key in {cls.DEFAULT_PROJECT_TOML_FILE_NAME}: {e}")

def get_default_query_file_paths_list(self):

default_query_path = self.get_queries_dir()/ 'default-queries.toml'

with open(default_query_path, 'r') as f:

query_config = toml.load(f)

filenames = query_config['default-query']['files']

if not isinstance(filenames, list):

raise ValueError("Expected a list under ['default-query']['files'] in default-queries.toml")

paths = [self.get_queries_file_path(fname) for fname in filenames]

for path in paths:

if not os.path.exists(path):

raise FileNotFoundError(f"Query file not found: {path}")

return paths

def establish_default_project():

project_name = ProjectManager.identify_default_project()

logging.info(f"project_name = {project_name}")

project_manager = ProjectManager(project_name)

logging.info(f"project_manager.get_project_dir() = {project_manager.get_project_dir()}")

return

def demo_establish_default_project():

establish_default_project()

if __name__ == "__main__":

import sys

cmd = sys.argv[1] if len(sys.argv) > 1 else "default"

if cmd == "demo-default":

demo_establish_default_project()

else:

print("Usage options: \n"

"poetry run python -m pipeline.api.eds demo-default \n")

PS C:\Users\george.bennett\OneDrive - City of Memphis\Documents\dev\mulch>

and, here are the workspaces (currently erroneously called projects) from the onging pipeline use cases.

PS C:\Users\george.bennett\OneDrive - City of Memphis\Documents\dev\pipeline> tree projects

Folder PATH listing for volume Windows

Volume serial number is AE7E-28A1

C:\USERS\GEORGE.BENNETT\ONEDRIVE - CITY OF MEMPHIS\DOCUMENTS\DEV\PIPELINE\PROJECTS

├───eds_to_rjn

│ ├───code

│ │ └───__pycache__

│ ├───exports

│ │ └───aggregate

│ ├───history

│ ├───imports

│ ├───queries

│ ├───scripts

│ │ └───__pycache__

│ ├───secrets

│ └───__pycache__

└───eds_to_termux

PS C:\Users\george.bennett\OneDrive - City of Memphis\Documents\dev\pipeline>

Note that eds_to_termux is empty. If we succeed, we could use mulch to set up that workspace directory to have the necessary file structure reflected in the workspace_manager.py file (currently projectmanager.py, pasted above).

note the relationship between the eds_to_rjn directory contents and the patterns in the projectmanager.json file. I need a way to drive those patterns, possibly using scaffold.json, stubs, jinja2, or something else.

also note that projectmanager.py already has a check_and_create_dirs() function, though it does not build the files such as secrets.yaml or secrets-example.yaml. these example files could be baked in and copied into the mulch cli tool

ChatGPT 3:

Great breakdown—this is exactly the level of specificity that lets you engineer the right system.

🧠 Is scaffold.json a good choice for driving templating?

✅ Yes, with minor expansion, it can work really well.

Right now your scaffold.json behaves like a folder map, which is perfect for check_and_create_dirs(). But if you want to drive generation of workspace_manager.py, you’ll need to expand its role from just a filesystem map into a templating context object.

✨ What You Need It to Do:

You want scaffold.json to:

1. Define the folder names (as it already does).

2. Define the filenames to generate inside those folders.

3. Act as a source of config for injecting constants into workspace_manager.py:

   • Dir names → class attributes

   • Default file names → method logic (e.g. SECRETS_YAML_FILE_NAME = "secrets.yaml")

🧱 Suggested scaffold.json Format

Here’s a version that supports both your current behavior and can power Jinja2:

{
  "workspace_name": "eds_to_termux",
  "directories": {
    "": ["config", "data", "imports", "exports", "scripts", "secrets", "queries"],
    "exports": ["aggregate"]
  },
  "files": {
    "config": ["default-workspace.toml"],
    "secrets": ["secrets.yaml", "secrets-example.yaml"],
    "queries": ["default-queries.toml"]
  },
  "constants": {
    "DEFAULT_PROJECT_TOML_FILE_NAME": "default-project.toml",
    "TIMESTAMPS_JSON_FILE_NAME": "timestamps_success.json"
  }
}

Then you can pass this entire dictionary to Jinja2 as the context:

template.render(**scaffold_data)

And in workspace_manager.py.j2:

class WorkspaceManager:
    {% for const, val in constants.items() %}
    {{ const }} = "{{ val }}"
    {% endfor %}

    {% for folder in directories[""] %}
    {{ folder.upper() }}_DIR_NAME = "{{ folder }}"
    {% endfor %}

You can even use it to drive check_and_create_dirs() logic inside the class.

🧩 Relationship to Current Structure

• The structure of eds_to_rjn/ clearly maps to the directories field.

• The files (secrets.yaml, etc.) are declared in files, and mulch can copy those from a built-in /templates/examples/ directory using shutil.copy(...).

✅ So, yes — scaffold.json is a good tool

...as long as you treat it like structured input for both:

• directory scaffolding (phase 1), and

• Jinja2 templating (phase 2)

And once the file includes both layout and value declarations, workspace_manager.py.j2 becomes incredibly flexible.

Would you like help writing the first version of that .j2 template file, or the function to render and write it?

Clayton 4:

i presume that your scaffold.json file looks nice, though i dont think it should include "workspace_name": "eds_to_termux",, because this scaffold file in root will be used to drive the creation of all new workspaces

the workspacemanager.py file only needs to be generated once, but each new workspace in workspaces/ needs to use the necessary file structre

with this in mind, maybe the mulch tool should be used to just generate the workspace_manager.py file, and then in turn that code can be used to generate new workspaces based on its own baked in structure

also, this all presumes that I will want different scaffolds each time, but it is possible / likely I will want to reuse the same scaffold for most of my projects and perform necessary tweaks manually. Maybe we should stick with cookiecutter for now, and set up a good scaffold git repo

ChatGPT 4:

That’s a wise move. Your clarification reveals two core realities:

✅ Refined Architecture Insight

🌱 1. scaffold.json lives at the root, and defines a reusable default scaffold for all future workspaces

• It does not belong to any one workspace (eds_to_termux, eds_to_rjn, etc.).

• So yes—remove "workspace_name" from the JSON.

🏗️ 2. workspace_manager.py is a once-per-repo product, not per-workspace

• It is generated once into src/<project_name>/workspace_manager.py.

• Its baked-in constants and directory logic will then manage new workspaces (under workspaces/) at runtime.

• The CLI (mulch init) doesn't create the workspaces directly—it uses the WorkspaceManager class to do that. This decouples the tooling from the logic.

🌀 3. Most of your projects will share a common scaffold (for now)

• So it makes sense to start by versioning a canonical scaffold in a Git repo.

• Then you can wrap that in Cookiecutter, or simply copy it in mulch phase 1.

• If your scaffold evolves, you can still modify the workspace_manager.py template and re-roll it later.

✅ So, your revised system could look like this:

Phase 1: Use mulch to bootstrap a repo

• Output:

  • workspaces/ directory

  • src/<project_name>/workspace_manager.py (from Jinja2 template)

  • scaffold.json (copied or symlinked from repo)

Phase 2: At runtime, use WorkspaceManager to:

• Generate folders under workspaces/<name> according to its built-in rules

• Optionally copy over stub files (e.g. secrets.yaml, etc.)

✅ What's Next

Here’s what I recommend:

1. ✅ Keep scaffold.json simple and universal
   You already have the right structure for it:

   {
     "": ["config", "data", "imports", "exports", "scripts", "secrets", "queries"],
     "exports": ["aggregate"],
     "config": ["default-workspace.toml"],
     "secrets": ["secrets.yaml", "secrets-example.yaml"],
     "queries": ["default-queries.toml"]
   }
   

2. ✅ Create a workspace_manager.py.j2 template
   It will embed the above structure as attributes/methods.

3. ✅ Write a render_template() function inside mulch
   Use jinja2 to render the file using scaffold.json.

4. ✅ Create a scaffold-template Git repo
   Let it contain:

   • scaffold.json

   • workspace_manager.py.j2

   • Optional stub files like secrets-example.yaml

5. ✅ Later, you can decide to wrap this repo with Cookiecutter if desired.
   This will allow command-line generation of whole repo templates, but for now, a mulch init command that copies and renders files is enough.

Would you like me to help generate a starter workspace_manager.py.j2 file now, based on your real implementation and the scaffold data structure?

Clayton 5:

leveraging a github repo will make it easier to fill / copy important workspace files like secrets-example.yaml, default-workspace.toml (aka default-project.toml), default-query.toml, etc, right?

down the line (take this with a grain of salt) it might be reasonable to:

1. Use github / jinja2 / cookiecutter / mulch to standup new code directories, using the most feature rich possible version

2. edit the scaffold file and/or interact with a CLI to remove unecesary components

3. submit these changes so that unnecessary compnents are removed (like if the package does not need queries or secrets, for example)

Let me clarify that files like secrets-example.yaml, default-workspace.toml, default-queries.toml are meant to control values for each workspace. each piece of python software that leverages a version workspace_manager can have multiple workspaces, each with different values in these files. while these files might be used as a standard across pieces of software I write, they by no means need to maintain the same internal values.

ChatGPT 5:

Yes—you're thinking clearly, and you're laying the groundwork for a robust and flexible system. Let’s break this down and clarify where GitHub, Jinja2, Cookiecutter, and your own tooling (mulch) can be leveraged effectively.

✅ Why GitHub Is a Smart Move

Using a GitHub-based template repo gives you:

• ✅ Version control over template files (like secrets-example.yaml, default-workspace.toml, etc.)

• ✅ A canonical source for updates or changes to standard scaffolds

• ✅ A way to clone or include those templates directly during mulch init or cookiecutter invocation

You can organize it like:

workspace-template/
├── scaffold.json
├── templates/
│   ├── workspace_manager.py.j2
│   └── stub_files/
│       ├── secrets-example.yaml
│       ├── default-workspace.toml
│       └── default-queries.toml

🧩 Clarifying Template Use and Runtime Behavior

You’re absolutely right to draw a line between:

Each of your Python projects uses the same logic (workspace_manager.py) to parse and handle these per-workspace files—but the values inside them will vary per workspace. That means the stub values are just starting points.

🔁 Future Workflow Vision (and it’s realistic)

Here’s your "maybe down the line" workflow—refined into a clear lifecycle:

Phase 1: Initialize using richest default template

• mulch init --name myproject

• Pulls scaffold and templates from GitHub (or local cache)

• Outputs:

  • src/myproject/workspace_manager.py

  • scaffold.json

  • workspaces/default/ with stub files

Phase 2: Tweak scaffold file or edit project manually

• Remove "queries" from scaffold if not needed

• Optionally run a CLI wizard:

  mulch customize
  # [x] Keep 'secrets'
  # [ ] Remove 'queries'
  # [x] Keep 'exports'
  

Phase 3: Re-render

• Mulch regenerates or trims workspace_manager.py

• Deletes removed dirs/files (optional interactive confirmation)

Phase 4: Lock in the new form

• Git commit the final setup

🟡 Where You're Headed

You're designing mulch as a hybrid tool:

• It wraps lower-level tools like Jinja2 and Cookiecutter

• It also adds lifecycle management of workspaces based on runtime logic (workspace_manager.py)

• It avoids tight coupling with Cookiecutter templates—you can use them, but don’t depend on them exclusively

✅ Summary: You’re on the Right Track

• Yes, GitHub-based scaffolds make filling/stubbing workspace files easier and cleaner.

• Each workspace gets a copy of stub files whose internal values are workspace-specific.

• The master templating logic lives in workspace_manager.py.j2, powered by scaffold.json.

• Cookiecutter can be part of this, but mulch remains your glue for long-term customization.

Would you like a draft repo structure or workspace_manager.py.j2 next?

Clayton 6:

I think you might be off track

I think you might be conflating the organization of the mulch tool with the organization of my python projects.

i dont think my python projects need a templates folder, but you can convince me otherwise

ChatGPT 6:

You’re right to pause here. Let’s reset with a hard boundary between:

• 🔧 mulch (the CLI tool you’re building)

• 🧠 Your Python projects (which are managed using a workspace_manager.py and a workspaces/ folder)

You're not off track—your instinct is correct.

🔧 mulch: a tool

This lives on its own. You install it via pipx install mulch, and it:

• Bootstraps a repo (sets up workspace_manager.py, scaffold.json, workspaces/)

• Optionally copies over stub files

• Optionally uses Jinja2 templates to render content

📁 Structure of mulch (itself, as a tool):

mulch/
├── src/
│   └── mulch/
│       ├── cli.py
│       ├── workspace_factory.py
│       ├── templates/                  <--- yes, this makes sense here
│       │   ├── workspace_manager.py.j2
│       │   └── stub_files/
│       │       ├── secrets-example.yaml
│       │       └── default-workspace.toml
│       └── ...
├── scaffold.json                       <--- optional fallback default

👉 The templates/ folder belongs to mulch, not to your downstream Python projects.

🧠 Your Python Projects: No templates folder needed

When mulch init is run inside a user’s repo, it might generate:

myproject/
├── workspaces/
│   └── default/
│       ├── config/
│       │   └── default-workspace.toml
│       ├── secrets/
│       │   ├── secrets-example.yaml
│       │   └── secrets.yaml   (optional copy)
│       ├── queries/
│       │   └── default-queries.toml
│       └── ...
├── src/
│   └── myproject/
│       └── workspace_manager.py       <-- rendered from jinja2 template
├── scaffold.json                      <-- defines what gets generated

🔁 But the downstream Python project does not include a templates/ folder. All rendering and templating happens inside the mulch engine.

✅ Your Intuition Is Correct

• The templates/ folder belongs to mulch, not to your actual projects.

• Your projects only contain the result of template rendering.

• The user shouldn’t even need to know how it was rendered unless they’re modifying mulch itself.

TL;DR

You don’t need templates/ in your Python projects.
Only mulch (as a CLI tool) needs them.

Would you like a clean mulch/templates/workspace_manager.py.j2 file next? Or an overview of how mulch renders it based on scaffold.json?

Clayton 7:

okay, good review. Your prjoect structure is close, but there is a mistake. default-workspace.toml is meant to live inside the workspaces/ directory, so that on start up is can point to which workspace to use

like this

myproject/
├── workspaces/
│ └── default-workspace.toml
│ └── default/
│ ├── config/
│ │
│ ├── secrets/
│ │ ├── secrets-example.yaml
│ │ └── secrets.yaml (optional copy)
│ ├── queries/
│ │ └── default-queries.toml
│ └──
├── src/
│ └── myproject/
│ └── workspace_manager.py <-- rendered from jinja2 template
├── scaffold.json <-- defines what gets generated

and the content of default-workspace.toml is

[default-workspace]
workspace = "eds_to_rjn"
use-most-recently-edited-workspace-directory = false

ChatGPT 7:

Crystal clear now — thanks for that correction. Here's the updated and accurate structure of a downstream Python project that uses mulch to manage workspaces:

✅ Corrected Project Structure

myproject/
├── workspaces/
│   ├── default-workspace.toml         <-- points to active workspace
│   └── eds_to_rjn/                    <-- one actual workspace
│       ├── config/
│       │   └── ...
│       ├── secrets/
│       │   ├── secrets-example.yaml
│       │   └── secrets.yaml
│       ├── queries/
│       │   └── default-queries.toml
│       ├── exports/
│       │   └── aggregate/
│       ├── imports/
│       ├── scripts/
│       └── ...
├── src/
│   └── myproject/
│       └── workspace_manager.py       <-- rendered once from Jinja2 template
├── scaffold.json                      <-- editable to define workspace layout

📌 default-workspace.toml Example

[default-workspace]
workspace = "eds_to_rjn"
use-most-recently-edited-workspace-directory = false

This lives in workspaces/ (not inside any workspace), so the workspace_manager.py logic can reliably locate it and use it to decide which workspace folder (like eds_to_rjn/) to activate at runtime.

🧠 Summary of Roles

Would you like me to now help:

1. Generate the workspace_manager.py.j2 Jinja template?

2. Build logic in mulch to fill files using Jinja and scaffold.json?

3. Create a separate GitHub repo for your default scaffold structure?

Or something else?

Clayton 8:

PS C:\Users\george.bennett\OneDrive - City of Memphis\Documents\dev\new> poetry run python
Python 3.11.9 (tags/v3.11.9:de54cf5, Apr  2 2024, 10:12:12) [MSC v.1938 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import mulch
>>> dir(mulch)
['__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__spec__']
>>> mulch.__dict__
{'__name__': 'mulch', '__doc__': None, '__package__': 'mulch', '__loader__': <_frozen_importlib_external.NamespaceLoader object at 0x000002A15FB1F850>, '__spec__': ModuleSpec(name='mulch', loader=<_frozen_importlib_external.NamespaceLoader object at 0x000002A15FB1F850>, submodule_search_locations=_NamespacePath(['C:\\Users\\george.bennett\\AppData\\Local\\pypoetry\\Cache\\virtualenvs\\new-PTuB56Zx-py3.11\\Lib\\site-packages\\mulch'])), '__file__': None, '__path__': _NamespacePath(['C:\\Users\\george.bennett\\AppData\\Local\\pypoetry\\Cache\\virtualenvs\\new-PTuB56Zx-py3.11\\Lib\\site-packages\\mulch'])}
>>> mulch()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'module' object is not callable
>>> mulch
<module 'mulch' (<_frozen_importlib_external.NamespaceLoader object at 0x000002A15FB1F850>)>
>>>

i think i want to use a loaded scaffold.json dictionary on an input.

how can i expose it when using the mulch library?

Chat GPT 8:

Great question. Since you're trying to use the mulch library programmatically (e.g., import mulch and call something like mulch.load_scaffold()), you need to:

✅ 1. Expose the Function in __init__.py

In your mulch/__init__.py, you can expose specific utilities from deeper modules. For example:

# mulch/__init__.py

from .workspace_factory import WorkspaceFactory, load_scaffold

__all__ = ["WorkspaceFactory", "load_scaffold"]

✅ 2. Define the Scaffold Loader as a Callable

Make sure load_scaffold() is a function you can call directly. If it’s currently a method on a class, and you want it as a standalone tool, refactor like this:

# mulch/workspace_factory.py

import json
from pathlib import Path

DEFAULT_SCAFFOLD_FILENAME = "scaffold.json"

def load_scaffold(scaffold_path: Path | None = None) -> dict:
    fallback_scaffold = {
        "": ["config", "data", "imports", "exports", "scripts", "secrets", "queries"],
        "exports": ["aggregate"],
        "config": ["default-workspace.toml"],
        "secrets": ["secrets.yaml", "secrets-example.yaml"],
        "queries": ["default-queries.toml"]
    }

    if scaffold_path is None:
        scaffold_path = Path(__file__).parent / DEFAULT_SCAFFOLD_FILENAME

    if not scaffold_path.exists():
        print(f"Warning: Missing scaffold file: {scaffold_path}, using fallback scaffold.")
        return fallback_scaffold

    try:
        content = scaffold_path.read_text().strip()
        if not content:
            print(f"Warning: Scaffold file {scaffold_path} is empty, using fallback scaffold.")
            return fallback_scaffold
        return json.loads(content)
    except json.JSONDecodeError as e:
        print(f"Warning: Scaffold file {scaffold_path} contains invalid JSON ({e}), using fallback scaffold.")
        return fallback_scaffold

✅ 3. Use it Like This

Now from Python:

>>> import mulch
>>> scaffold = mulch.load_scaffold()
>>> scaffold['secrets']
['secrets.yaml', 'secrets-example.yaml']

Or with a custom file:

>>> from pathlib import Path
>>> mulch.load_scaffold(Path("my/custom_scaffold.json"))

Bonus: If You Want a CLI Hook

Add a command like this to mulch/cli.py:

@app.command()
def show_scaffold(path: Optional[Path] = None):
    """Print the scaffold structure."""
    from .workspace_factory import load_scaffold
    scaffold = load_scaffold(path)
    typer.echo(json.dumps(scaffold, indent=2))

Then run:

poetry run mulch show-scaffold

Would you like help turning the load_scaffold() data into a file generator next?

Clayton 9:

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