| |
| |
| |
| |
| """ |
| Command line for PyThaiNLP's tokenizers. |
| """ |
|
|
| import argparse |
|
|
| from pythainlp import cli |
| from pythainlp.tokenize import ( |
| DEFAULT_SENT_TOKENIZE_ENGINE, |
| DEFAULT_SUBWORD_TOKENIZE_ENGINE, |
| DEFAULT_WORD_TOKENIZE_ENGINE, |
| sent_tokenize, |
| subword_tokenize, |
| word_tokenize, |
| ) |
| from pythainlp.tools import safe_print |
|
|
| DEFAULT_SENT_TOKEN_SEPARATOR = "@@" |
| DEFAULT_SUBWORD_TOKEN_SEPARATOR = "/" |
| DEFAULT_SYLLABLE_TOKEN_SEPARATOR = "~" |
| DEFAULT_WORD_TOKEN_SEPARATOR = "|" |
|
|
|
|
| class SubAppBase: |
| def __init__(self, name, argv): |
| parser = argparse.ArgumentParser(**cli.make_usage("tokenize " + name)) |
| parser.add_argument( |
| "text", |
| type=str, |
| nargs="?", |
| help="input text", |
| ) |
| parser.add_argument( |
| "-s", |
| "--sep", |
| dest="separator", |
| type=str, |
| help=f"default: {self.separator}", |
| default=self.separator, |
| ) |
| parser.add_argument( |
| "-a", |
| "--algo", |
| dest="algorithm", |
| type=str, |
| help=f"default: {self.algorithm}", |
| default=self.algorithm, |
| ) |
| parser.add_argument( |
| "-w", |
| "--keep-whitespace", |
| dest="keep_whitespace", |
| action="store_true", |
| ) |
| parser.add_argument( |
| "-nw", |
| "--no-whitespace", |
| dest="keep_whitespace", |
| action="store_false", |
| ) |
| parser.set_defaults(keep_whitespace=True) |
|
|
| args = parser.parse_args(argv) |
| self.args = args |
|
|
| cli.exit_if_empty(args.text, parser) |
| result = self.run( |
| args.text, |
| engine=args.algorithm, |
| keep_whitespace=args.keep_whitespace, |
| ) |
| safe_print(args.separator.join(result) + args.separator) |
|
|
|
|
| class WordTokenizationApp(SubAppBase): |
| def __init__(self, *args, **kwargs): |
| self.keep_whitespace = True |
| self.algorithm = DEFAULT_WORD_TOKENIZE_ENGINE |
| self.separator = DEFAULT_WORD_TOKEN_SEPARATOR |
| self.run = word_tokenize |
| super().__init__(*args, **kwargs) |
|
|
|
|
| class SentenceTokenizationApp(SubAppBase): |
| def __init__(self, *args, **kwargs): |
| self.keep_whitespace = True |
| self.algorithm = DEFAULT_SENT_TOKENIZE_ENGINE |
| self.separator = DEFAULT_SENT_TOKEN_SEPARATOR |
| self.run = sent_tokenize |
| super().__init__(*args, **kwargs) |
|
|
|
|
| class SubwordTokenizationApp(SubAppBase): |
| def __init__(self, *args, **kwargs): |
| self.keep_whitespace = True |
| self.algorithm = DEFAULT_SUBWORD_TOKENIZE_ENGINE |
| self.separator = DEFAULT_SUBWORD_TOKEN_SEPARATOR |
| self.run = subword_tokenize |
| super().__init__(*args, **kwargs) |
|
|
|
|
| class App: |
| def __init__(self, argv): |
| parser = argparse.ArgumentParser( |
| prog="tokenize", |
| description="Break a text into small units (tokens).", |
| usage=( |
| 'thainlp tokenize <token_type> [options] "<text>"\n\n' |
| "token_type:\n\n" |
| "subword subword (may not be a linguistic unit)\n" |
| "syllable syllable\n" |
| "word word\n" |
| "sent sentence\n\n" |
| "options:\n\n" |
| "--sep or -s <separator> specify custom separator\n" |
| " (default is a space)\n" |
| "--algo or -a <algorithm> tokenization algorithm\n" |
| " (see API doc for more info)\n" |
| "--keep-whitespace or -w keep whitespaces in output\n" |
| " (default)\n\n" |
| "<separator> and <text> should be inside double quotes.\n\n" |
| "Example:\n\n" |
| 'thainlp tokenize word -s "|" "ใต้แสงนีออนเปลี่ยวเหงา"\n\n' |
| "--" |
| ), |
| ) |
| parser.add_argument( |
| "token_type", |
| type=str, |
| help="[subword|word|sent]", |
| ) |
|
|
| args = parser.parse_args(argv[2:3]) |
| cli.exit_if_empty(args.token_type, parser) |
| token_type = str.lower(args.token_type) |
|
|
| argv = argv[3:] |
| if token_type.startswith("w"): |
| WordTokenizationApp("word", argv) |
| elif token_type.startswith("su"): |
| SubwordTokenizationApp("subword", argv) |
| elif token_type.startswith("se"): |
| SentenceTokenizationApp("sent", argv) |
| else: |
| safe_print(f"Token type not available: {token_type}") |
|
|
