release/1.0.0: Add subcommand show to list the supportes estimators…

…, languages and templates in a compact table

setup.py

@@ -60,6 +60,7 @@ def main():
  'scikit-learn>=0.17,<=0.22a0',
  'Jinja2>=2.10.1',
  'loguru>=0.3.2',
+ 'tabulate>=0.8.6',
  'joblib',
  ],
  extras_require={

sklearn_porter/Estimator.py

@@ -2,22 +2,24 @@
 
 import urllib.request
 from abc import ABCMeta
-from json import loads, JSONDecodeError
+from collections import OrderedDict
+from functools import partial
+from json import JSONDecodeError, loads
 from multiprocessing import Pool, cpu_count
 from os import environ, remove
 from pathlib import Path
+from shutil import which
 from subprocess import STDOUT, CalledProcessError, check_output
 from sys import platform, stdout, version_info
-from shutil import which
 from tempfile import mktemp
 from textwrap import dedent
 from time import sleep
 from typing import Callable, Dict, List, Optional, Tuple, Union
-from functools import partial
 
 # Additional installed modules:
 import numpy as np
 from loguru import logger as L
+from tabulate import tabulate
 
 # scikit-learn
 from sklearn import __version__ as sklearn_version
@@ -26,8 +28,8 @@
 from sklearn.metrics import accuracy_score
 
 # sklearn-porter
-from sklearn_porter import enums as enum
 from sklearn_porter import decorators as decorator
+from sklearn_porter import enums as enum
 from sklearn_porter import exceptions as exception
 from sklearn_porter import meta
 from sklearn_porter.utils import options
@@ -969,6 +971,59 @@ def _system_call(cmd: str, executable='/bin/bash'):
  return [out.get('predict')]
 
 
+def show(language: Optional[Union[str, enum.Language]] = None):
+ """
+ Show the supported estimators, programming languages
+ and templates in a compact table.
+
+ Parameters
+ ----------
+ language : Language
+ The requested programming language.
+
+ Returns
+ -------
+ Show the table.
+ """
+ languages = enum.LANGUAGES
+ if language:
+ language = enum.Language.convert(language)
+ languages = {language.value.KEY: language.value}
+ headers = ['Estimator'] + [l.LABEL for l in languages.values()]
+ clazzes = Estimator.classifiers() + Estimator.regressors()
+ clazzes = {_get_qualname(c()): c() for c in clazzes}
+ clazzes = OrderedDict(sorted(clazzes.items()))
+ table = []
+ templates = dict(attached='ᴀ', combined='ᴄ', exported='ᴇ')
+ for name, est in clazzes.items():
+ tr = [name]
+ for lang in languages.keys():
+ td = []
+ for tpl in templates.keys():
+ if can(
+ estimator=est,
+ language=lang,
+ template=tpl,
+ method='predict_proba'
+ ):
+ out = '✓{}ᴾ'.format(templates.get(tpl))
+ elif can(estimator=est, language=lang, template=tpl):
+ out = '✓{} '.format(templates.get(tpl))
+ else:
+ out = '···'
+ td.append(out)
+ td = ' | '.join(td)
+ tr.append(td)
+ table.append(tr)
+ return tabulate(
+ table,
+ headers=headers,
+ tablefmt='presto',
+ disable_numparse=True,
+ colalign=['left'] + ['center'] * len(languages)
+ )
+
+
 def can(
  estimator: Union[BaseEstimator, ABCMeta],
  language: Optional[Union[str, enum.Language]] = None,

sklearn_porter/__init__.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 
-from sklearn_porter.Estimator import Estimator, make, port, save, test
+from sklearn_porter.Estimator import Estimator, make, port, save, show, test
 from sklearn_porter import meta
 from sklearn_porter.utils import options
 

sklearn_porter/cli/command/show.py

@@ -6,8 +6,9 @@
 from typing import Dict
 
 # sklearn-porter
-from sklearn_porter import Estimator, options
+from sklearn_porter import options, show
 from sklearn_porter.cli.common import arg_debug, arg_help
+from sklearn_porter.language import LANGUAGES
 
 
 def config(sub_parser: _SubParsersAction):
@@ -28,22 +29,21 @@ def config(sub_parser: _SubParsersAction):
  )
  for group in parser._action_groups:
  group.title = str(group.title).capitalize()
-
+ parser.add_argument(
+ '-l',
+ '--language',
+ type=str,
+ required=False,
+ choices=LANGUAGES.keys(),
+ help='The name of the programming language.'
+ )
  for fn in (arg_debug, arg_help):
  fn(parser)
 
  parser.set_defaults(func=main)
 
 
-def _get_qualname(obj: object):
- return obj.__class__.__module__ + '.' + obj.__class__.__qualname__
-
-
 def main(args: Dict):
  if args.get('debug'):
  options['logging.level'] = DEBUG
-
- estimators = Estimator.classifiers() + Estimator.regressors()
-
- for e in estimators:
- print(e.__name__)
+ print(show(args.get('language')))

tests/EstimatorTest.py

@@ -401,10 +401,11 @@ def test_regressions_of_classifiers(
 
 @pytest.mark.parametrize(
  'args', [
- ['show'], ['port', str(SERIALIZED_MODEL), '--skip-warnings'],
+ ['show'], ['show', '-l', 'java'], ['show', '-l', 'js'],
+ ['port', str(SERIALIZED_MODEL), '--skip-warnings'],
  ['save', str(SERIALIZED_MODEL), '--skip-warnings']
  ],
- ids=['show', 'port', 'save']
+ ids=['show', 'show_java', 'show_js', 'port', 'save']
 )
 def test_cli_subcommand(args: List):
  parsed = parse_args(args)