Skip to main content

A minimal, unopinionated file processing engine intended for static website generation.

Project description

PyPI - Project Version PyPI - Python Version GitHub - Project License GitHub - Code Size codecov

Anchovy

Anchovy is a minimal, unopinionated file-processing framework equipped with a complete static website generation toolkit.

  • Minimal: Anchovy’s core is around a thousand lines of code and has no mandatory dependencies. Plus, Anchovy can be used for real projects with just a few pip-installable extras, even if you want to preprocess CSS.

  • Unopinionated: Anchovy offers a set of components which can be easily configured to your site’s exact requirements, without tediously ripping out or overriding entrenched behaviors. Anchovy does not assume you are building a blog or that you wish to design your templates in a specific way. You can even build things that aren’t websites! Plus, Anchovy operates on files, so it’s simple to integrate tools like imagemagick, dart-sass, or less.js if you need them.

  • Complete: Anchovy comes with a dependency auditing system, allowing you to grab any component you want without installing anything but Anchovy and find out what you will need to run your build. Choose from a wealth of Steps, Anchovy’s modular file processors, for everything from rendering Jinja templates and minifying CSS to unpacking archives and thumbnailing images. Plus, add a few extra parameters or lines of configuration to get automatic intelligent minimum builds based on input checksums, and get a reproducible run artifact to boot— even if you want to fetch HTTP resources or write your own Steps. Iterate quickly by launching a lightweight development-grade web server once the build is complete.

Installation

Anchovy has no essential prerequisites and can be installed with pip install anchovy to get just the framework and a few built-in components, but for typical usage pip install anchovy[base] is recommended. This will pull in support for Jinja2 templating, markdown, minification, and Anchovy’s CSS preprocessor. A full list of available extras may be found in the pyproject.toml file.

Alternatively, Anchovy may be installed directly from source with pip install git+https://github.com/pydsigner/anchovy or the corresponding pip install git+https://github.com/pydsigner/anchovy#egg=anchovy[base].

Command Line Usage

Anchovy operates on config files written in Python, or even modules directly.

  • python -m anchovy -h
  • anchovy -m mypackage.anchovyconf -o ../release/
  • python -m anchovy mysite/anchovy_site.py -h

If -h is supplied with a module or config file, help will be displayed for the pipeline configuration. If it is supplied without a module or config file, help will be displayed for anchovy's own run-time options, such as --audit-steps and --serve, as well as how to specify a module/config file.

Show Me

Run anchovy examples/code_index.py -s -p 8080, then open a browser to localhost:8080 (or click the link in the console). This example offers the most extensive demonstration of Anchovy’s functionality as of version 1.0.

What’s the Baseline?

Here’s minimal example performing about what the staticjinja markdown example offers:

from pathlib import Path

from anchovy import (
    DirectCopyStep,
    InputBuildSettings,
    JinjaMarkdownStep,
    OutputDirPathCalc,
    REMatcher,
    Rule,
)


# Optional, and can be overridden with CLI arguments.
SETTINGS = InputBuildSettings(
    input_dir=Path('site'),
    working_dir=Path('working'),
    output_dir=Path('build'),
    custody_cache=Path('build-cache.json'),
)
RULES = [
    # Ignore dotfiles found in either the input_dir or the working dir.
    Rule(
        (
            REMatcher(r'(.*/)*\..*', parent_dir='input_dir')
            | REMatcher(r'(.*/)*\..*', parent_dir='working_dir')
        ),
        None
    ),
    # Render markdown files, then stop processing them.
    Rule(
        REMatcher(r'.*\.md'),
        [OutputDirPathCalc('.html'), None],
        JinjaMarkdownStep()
    ),
    # Copy everything else in static/ directories through.
    Rule(
        REMatcher(r'(.*/)*static/.*', parent_dir='input_dir'),
        OutputDirPathCalc(),
        DirectCopyStep()
    ),
]

This example is very simple, but it’s legitimately enough to start with for a small website, and offers an advantage over other minimal frameworks by putting additional batteries within an arm’s reach. If we stored the configuration in config.py and added a raw site like this:

site/
    static/
        styles.css
        toolbar.js
    base.jinja.html
    index.md
    about.md
    contact.md

python -m anchovy config.py would produce output like this:

output/
    static/
        styles.css
        toolbar.js
    index.html
    about.html
    contact.html

This example can be found in runnable form as examples/basic_site.py in the source distribution. Available command line arguments can be seen by passing -h: python -m anchovy examples/basic_site.py -h.

Programmatic Usage

Anchovy is very usable from the command line, but projects desiring to customize behavior, for example by running tasks before or after pipeline execution, may utilize anchovy.cli.run_from_rules():

import time
from pathlib import Path

from anchovy.cli import run_from_rules
from anchovy.core import Context

from my_site.config import SETTINGS, RULES


class MyContext(Context):
    def find_inputs(path: Path):
        # Only process files modified in the last hour.
        hour_ago = time.time() - 3600
        for candidate in super().find_inputs(path):
            if candidate.stat().st_mtime > hour_ago:
                yield candidate


def main():
    print('Pretending to run pre-pipeline tasks...')
    run_from_rules(SETTINGS, RULES, context_cls=MyContext)
    print('Pretending to run post-pipeline tasks...')


if __name__ == '__main__':
    main()

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

anchovy-1.1.0.tar.gz (3.2 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

anchovy-1.1.0-py3-none-any.whl (40.0 kB view details)

Uploaded Python 3

File details

Details for the file anchovy-1.1.0.tar.gz.

File metadata

  • Download URL: anchovy-1.1.0.tar.gz
  • Upload date:
  • Size: 3.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for anchovy-1.1.0.tar.gz
Algorithm Hash digest
SHA256 bf3a0949a288e3f78d11065baea4c020442fb787bbe64bda8c99a2b2cac84605
MD5 46e33731dbe6d91d29a7bab9117e0e7e
BLAKE2b-256 376e8f90cbaa5d627ffd2edcafa61a8e245650b3ed649de27f5811b60b5a7153

See more details on using hashes here.

File details

Details for the file anchovy-1.1.0-py3-none-any.whl.

File metadata

  • Download URL: anchovy-1.1.0-py3-none-any.whl
  • Upload date:
  • Size: 40.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for anchovy-1.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 64aeba3bcc89aaf42f3d2ed4c0902fb5d4d123fb1c13ff7837e3b4ef7e6b8631
MD5 adf9984e21490491a25a5436be12a417
BLAKE2b-256 2515237ed1aa7f280f3d96a00f74c66b04cb2b06d28efa78f78a4d1f6d8d7695

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page