archan 3.0.0

Description:

archan 3.0.0

Archan





Analysis of your architecture strength based on DSM data.
A Python module that analyzes your architecture strength
based on Design Structure Matrix (DSM) data.
Archan is a Python module that analyzes the strength of your
project architecture according to some criteria described in
"The Protection of Information in Computer Systems", written by
Jerome H. Saltzer and Michael D. Schroeder.
Features

Usable directly on the command-line.
Support for plugins. See for example the Provider plugin in dependenpy.
You can also take a look at django-meerkat, a Django app using Archan.
Configurable through command-line or configuration file (YAML format).
Read DSM data on standard input.

Installation
With pip:
pip install archan

With pipx:
python3.8 -m pip install --user pipx
pipx install archan

Usage
Archan defines three main classes: Analyzer, Provider and Checker.
A provider is an object that will produce data and return it in the form of
a DSM (Design Structure Matrix). The checker is an object that
will analyze this DSM according to some criteria, and return a status code
saying if the criteria are verified or not. An analyzer is just a combination
of providers and checkers to run a analysis test suite.
On the command-line
Examples:
$ archan -h
usage: archan [-c FILE] [-h] [-i FILE] [-l] [--no-color] [--no-config] [-v]

Analysis of your architecture strength based on DSM data

optional arguments:
-c FILE, --config FILE Configuration file to use.
-h, --help Show this help message and exit.
-i FILE, --input FILE Input file containing CSV data.
-l, --list-plugins Show the available plugins. Default: false.
--no-color Do not use colors. Default: false.
--no-config Do not load configuration from file. Default: false.
-v, --version Show the current version of the program and exit.

# See a list of all supported Archan plugins
archan --list-plugins

# Archan can locate the configuration file automatically (See the Configuration section)
archan
# or a specific configuration can be specified
archan --config my_config.yml

# Archan can load DSM data in CSV format such as the output from dependenpy (install separately)
dependenpy pytest --format=csv --output pytest_dsm.csv

# Read CSV data from file (No configuration)
archan --no-config --input pytest_dsm.csv
# or read CSV data from STDIN
dependenpy pytest --format=csv | archan --no-config

Configuration
Archan applies the following methods to find the configuration file folder:

read the contents of the file .configconfig in the current directory
to get the path to the configuration directory,
use config folder in the current directory if it exists,
use the current directory.

It then searches for a configuration file named:

archan.yml
archan.yaml
.archan.yml
.archan.yaml

Format of the configuration file is as follow:
analyzers: [list of strings and/or dict]
- identifier: [optional string]
name: [string]
description: [string]
providers: [string or list]
- provider.Name: [as string or dict]
provider_arguments: as key value pairs
checkers: [string or list]
- checker.Name: [as string or dict]
checker_arguments: as key value pairs

It means you can write:
analyzers:
# a first analyzer with one provider and several checker
- name: My first analyzer
description: Optional description
providers: just.UseThisProvider
checkers:
- and.ThisChecker
- and.ThisOtherChecker:
which: has
some: arguments
# a second analyzer with several providers and one checker
- name: My second analyzer
providers:
- use.ThisProvider
checkers: and.ThisChecker
# a third analyzer, using its name directly
- some.Analyzer

Every checker support an ignore argument, set to True or False (default).
If set to True, the check will not make the test suit fail.
You can reuse the same providers and checkers in different analyzers, they
will be instantiated as different objects and won't interfere between each other.
As an example, see Archan's own configuration file.
To get the list of available plugins in your current environment,
run archan --list-plugins or archan -l.
Writing a plugin
Plugin discovery
You can write three types of plugins: analyzers, providers and checkers.
Your plugin does not need to be in an installable package. All it needs to
be summoned is to be available in your current Python path. However, if you want
it to be automatically discovered by Archan, you will have to make it installable,
through pip or simply python setup.py install command or equivalent.
If you decide to write a Python package for your plugin, I recommend you
to name it archan-your-plugin for consistency. If you plan to make it live
along other code in an already existing package, just leave the name as it is.
To make your plugin discoverable by Archan, use the archan entry point
in your setup.py:
from setuptools import setup

setup(
...,
'entry_points': {
'archan': [
'mypackage.MyPlugin = mypackage.mymodule:MyPlugin',
]
}

If you build your package with Poetry, use this instead:
[tool.poetry.plugins.archan]
"mypackage.MyPlugin" = "mkdocstrings.plugin:MkdocstringsPlugin"

The name of the entry point should by convention be composed of the name of
your package in lower case, a dot, and the name of the Python class, though
you can name it whatever you want. Remember that this name will be the one
used in the configuration file.
Also a good thing is to make the plugin importable thanks to its name only:
import mypackage.MyPlugin

But again, this is just a convention.
Plugin class
You can write three types of plugins: analyzers, providers and checkers.
For each of them, you have to inherit from its corresponding class:
from archan import Analyzer, Provider, Checker

class MyAnalyzer(Analyzer): ...
class MyProvider(Provider): ...
class MyChecker(Checker): ...

A provider or checker plugin must have the following class attributes:

identifier: the identifier of the plugin. It must be the same name as in
your entry points, so that displaying its help tells how to summon it.
name: the verbose name of the plugin.
description: a description to explain what it does.
(optional) arguments: a tuple/list of Argument instances. This one is only
used to display some help for the plugin. An argument is composed of a name,
a type, a description and a default value.

from archan import Provider, Argument

class MyProvider(Provider):
identifier = 'mypackage.MyProvider'
name = 'This is my Provider'
description = """
Don't hesitate to use multi-line strings as the lines will be de-indented,
concatenated again and wrapped to match the console width.

Blank lines will be kept though, so the above line will not be removed.
"""

arguments = (
Argument('my_arg', int, 'This argument is useful.', 42),
# don't forget the ending comma if you have just one ^ argument
)

Additionally, a checker plugin should have the hint class attribute (string).
The hint describe what you should do if the check fails.
For now, the analyzers plugins just have the providers and checkers
class attributes.
Plugin methods
A provider must implement the get_dsm(self, **kwargs) method. This method
must return an instance of DSM. A DSM is composed of a two-dimensions
array, the matrix, a list of strings, the keys or names for each line/column
of the matrix, and optionally the categories for each key (a list of same size).
from archan import DSM, Provider

class MyProvider(Provider):
name = 'mypackage.MyProvider'

def get_dsm(self, my_arg=42, **kwargs):
# this is where you compute your stuff
matrix_data = [...]
entities = [...]
categories = [...] or None
# and return a DSM instance
return DSM(matrix_data, entities, categories)

A checker must implement the check(self, dsm, **kwargs) method.
from archan import DSM, Checker

class MyChecker(Checker):
name = 'mypackage.MyChecker'

def check(self, dsm, **kwargs):
# this is where you check your stuff
# with dsm.data, dsm.entities, dsm.categories, dsm.size (rows, columns)
...
# and return True, False, or a constant from Checker: PASSED or FAILED
# with an optional message
return Checker.FAILED, 'too much issues in module XXX'

Logging messages
Each plugin instance has a logger attribute available. Use it to log
messages with self.logger.debug, info, warning, error or
critical.
Available plugins
Here is the list of plugins available in other packages.
See other plugins published to PyPi by searching for
"archan-"
Providers

dependenpy.InternalDependencies: Provide matrix data about internal
dependencies in a set of packages. Install it with pip install dependenpy.