Bump to 0.2.0
- Add Unweighted mode to command line - Download nltk data if needed.
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@ -4,4 +4,4 @@
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# This is free software, see the included LICENSE for terms and conditions.
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#
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version = '0.1.2'
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version = '0.2.0'
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@ -61,17 +61,18 @@ def parse_arguments() -> argparse.Namespace:
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chain_sub = subparsers.add_parser('chain', help="Output from a chainer")
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chain_sub.add_argument('input', help="The chain file to load", type=pathlib.Path)
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chain_sub.add_argument('-u', '--unweighted', help="Don't weight token selection by statistical frequency.", action='store_true')
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chain_sub.add_argument('-c', '--count', help="Number of chain outputs to output", type=int, default=10)
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chain_sub.add_argument('-m', '--maxlen', help="Maximum length in tokens of output (0 is unlimited)", type=int, default=0)
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return parser.parse_args()
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def print_chainer_output(chainer: Chain, random_state: Random):
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def print_chainer_output(chainer: Chain, random_state: Random, weighted: bool = False):
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if chainer.analyzer_class in JOINERS:
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print(JOINERS[cast(str, chainer.analyzer_class)](chainer.walk(random_state, True)))
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print(JOINERS[cast(str, chainer.analyzer_class)](chainer.walk(random_state, weighted)))
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else:
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print(chainer.walk(random_state, True))
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print(chainer.walk(random_state, weighted))
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def command_analyze(args: argparse.Namespace) -> int:
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@ -145,7 +146,7 @@ def command_chain(args: argparse.Namespace) -> int:
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args.count = 1
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for _ in range(0, args.count):
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print_chainer_output(chainer, r)
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print_chainer_output(chainer, r, not args.unweighted)
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return 0
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@ -9,6 +9,12 @@ import nltk
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from .abstract import AbstractAnalyzer
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try:
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nltk.sent_tokenize("foo bar")
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except LookupError:
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nltk.download('punkt')
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class English(AbstractAnalyzer):
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def __init__(self, order, filters=None):
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if filters is None:
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@ -1,3 +0,0 @@
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[build-system]
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requires = ["setuptools", "wheel"]
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build-backend = "setuptools.build_meta"
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