A minimal, unopinionated file processing engine intended for static website generation.
Project description
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
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
. The --
is
required because anchovy
itself also accepts the flag.
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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file anchovy-1.0.1.tar.gz
.
File metadata
- Download URL: anchovy-1.0.1.tar.gz
- Upload date:
- Size: 3.2 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.9.20
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9fc09af66b7c5e8130c83e47348f657d4ae269347c788bc485d26242a0d64d77 |
|
MD5 | 360de8a9cd46354ff6293e31c67c3f5c |
|
BLAKE2b-256 | 5c54dd214b646cd421ec8bf1e4384838acb8f66dbd70a30cb35961a0453647e0 |
File details
Details for the file anchovy-1.0.1-py3-none-any.whl
.
File metadata
- Download URL: anchovy-1.0.1-py3-none-any.whl
- Upload date:
- Size: 37.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.9.20
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2f76560db57cb3d2e06a82b7f1c4905441f89747f85ac2e95fce38d471818fa7 |
|
MD5 | 6af1df80f4085f57409766eb24c9e8f8 |
|
BLAKE2b-256 | 9e845186b113528ec75a4c9bc7f4d7f650f4f89418ceb8bec16d3d1ade67891d |