mock-data-server 1.0.0

Spin up a fake REST API from JSON/CSV with zero code.

Data Server

Spin up a fake REST API from a JSON or CSV file with zero framework setup.

Data Server reads your file, exposes routes automatically, supports CRUD for list resources, and writes changes back to disk.

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Table of Contents

• Why Data Server
• Installation
• Quick Start
• How Routing Works
• Request and Response Behavior
• Query Parameters (filter, sort, paging)
• CLI Reference
• Data File Requirements
• Development
• Release and Publish (PyPI)
• License

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Why Data Server

• Generate an API from existing mock data in seconds.
• Test frontend flows without hand-writing backend endpoints.
• Simulate realistic behavior (pagination, sorting, filtering, latency).
• Keep data local and editable through HTTP requests.

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Installation

pip install data-server

You can run it either as a module or a CLI command:

python -m mock_data_server <file>
# or
data-server <file>

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Quick Start

1. Create a sample JSON file:

{
  "todos": [
    { "id": 1, "title": "Write docs", "done": false },
    { "id": 2, "title": "Ship feature", "done": false }
  ]
}

2. Start the server:

data-server ./todos.json --port 8000

3. Try requests:

curl http://127.0.0.1:8000/
curl http://127.0.0.1:8000/todos
curl http://127.0.0.1:8000/todos/1

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How Routing Works

• GET / returns discovered routes and supported methods.
• Each top-level list becomes a collection endpoint (for example, todos -> /todos).
• Collection endpoints support GET and POST.
• Item endpoints support GET, PUT, PATCH, and DELETE.

If you provide --url-path-prefix /api/v1, all routes are served under that prefix.

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Request and Response Behavior

• POST returns 201.
• DELETE returns 204 when successful.
• Other successful requests return 200.
• CORS header Access-Control-Allow-Origin: * is included.
• Errors are returned as JSON:

{
  "error": {
    "description": "...",
    "code": 400,
    "details": "..."
  }
}

You can add custom headers to every response with:

--additional-headers "X-Limit:20;X-Source:mock"

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Query Parameters (filter, sort, paging)

Collection GET requests support:

• Filtering: any extra query keys are treated as exact-match filters.
• Sorting: sort_by=<field> and order=asc|desc.
• Pagination:
  • page (starts at 0)
  • size (default comes from --page-size, default value is 10)

Example:

curl "http://127.0.0.1:8000/todos?done=false&sort_by=title&order=asc&page=0&size=5"

You can rename these query parameter names via CLI flags such as --page-param-name, --sort-param-name, --order-param-name, and --size-param-name.

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CLI Reference

Usage:

data-server <file> [options]

Required positional argument:

• file: Path to a .json or .csv file.

Server options:

• --host (default: 127.0.0.1)
• --port (default: 2000)
• --url-path-prefix
• --static-folder
• --static-url-prefix (default: static)
• --additional-headers
• --sleep-before-request (milliseconds)

Data/controller options:

• --id-name (default: id)
• --auto-generate-ids / --no-auto-generate-ids
• --use-timestamps / --no-use-timestamps
• --created-at-key-name (default: created_at)
• --updated-at-key-name (default: updated_at)
• --page-size (default: 10)
• --page-param-name (default: page)
• --sort-param-name (default: sort_by)
• --order-param-name (default: order)
• --size-param-name (default: size)

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Data File Requirements

JSON

• Must be valid JSON.
• Top-level object keys typically map to endpoint paths.
• List values are treated as resources that support CRUD.
• Changes are persisted back to the same file.

CSV

• The CSV filename (without extension) becomes the route name.
• Rows are exposed as a single collection.
• Values are read as strings.
• Changes are written back to the same CSV file.

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Development

# install with dev dependencies
pip install -e .[dev]

# format + lint
ruff format .
ruff check .

# type-check
mypy --strict mock_data_server

# run tests
coverage run -m unittest discover -v -s tests
coverage report -m

Main CI runs on push/PR to main.

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Release and Publish (PyPI)

Publishing is automated through GitHub Actions after a successful CI run on main.

1. Bump version in pyproject.toml.
2. Ensure repo secret PYPI_API_TOKEN is configured.
3. Merge to main.
4. CI passes, then the publish workflow uploads to PyPI.

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License

MIT