Example #1
0
def nosplit(path: str, extensions: Optional[str] = None, no_spaces: bool = False, no_unicode: bool = False,
            no_com: bool = False, no_str: bool = False, full_strings: bool = False, max_str_length: int = sys.maxsize,
            output_path: Optional[str] = None, calc_vocab=False, suppress_caching=False) -> PreprocessedCorpus:
    """
    Split corpus at `path` into tokens leaving compound identifiers as they are.

    :param path: path to the corpus to be split.
    :param extensions: Limits the set of input files to the files with the specified extension(s).
    The format is the following: "ext1|ext2|...|extN" If not specififed, all the files are read.

    :param no_spaces: set to True to remove tabs and newlines.
    :param no_unicode: set to True to replace each word containing non-ascii characters to a special token,  e.g. <non-en>
    :param no_com: set to True to replace each comment with a special token, e.g. <comment>.
    :param no_str: set to True to replace each string literals with a special token, e.g <str_literal>.
    :param full_strings: do not split string literals even on whitespace characters. Does not have effect if `no_str` is set to `True`
    :param max_str_length: replace string literal with `""` if its length including quotes exceeds `max_str_length`.
    Does not have effect if `no_str` is set to `True`

    :return: `PreprocessedDataset` object which holds metadata of the preprocessed dataset

    Examples:
    ---------
    >>> prep_corpus = nosplit(os.path.join(test_data_dir, 'test-corpus'), 'js', output_path=tempfile.TemporaryDirectory().name, suppress_caching=True) # doctest: +ELLIPSIS
    Files scanned: 1...
    >>> prep_corpus.get_corpus_size()
    49294
    """
    prep_config= create_prep_config('nosplit', no_spaces=no_spaces, no_unicode=no_unicode, no_com=no_com, no_str=no_str,
                                    full_strings=full_strings, max_str_length=max_str_length)
    return preprocess_corpus(path, prep_config, extensions=extensions,
                             output_path=output_path, calc_vocab=calc_vocab, suppress_caching=suppress_caching)
Example #2
0
def chars(path: str, extensions: Optional[str] = None, no_spaces: bool = False, no_unicode: bool = False,
          no_com: bool = False, no_str: bool = False, max_str_length=sys.maxsize,
          output_path: Optional[str] = None, calc_vocab=False, suppress_caching=False) -> PreprocessedCorpus:
    """
    Split corpus at `path` into characters (With the exception of operators that consist of 2 character: such operators will remain as a single token).
    So that the information about original word boundaries is not lost, special tokens are inserted to denote original words beginnings and ends,
    e.g. myClass -> [<w>, m, y, C, l, a, s, s, </w>]

    :param path: path to the corpus to be split.
    :param extensions: Limits the set of input files to the files with the specified extension(s).
    The format is the following: "ext1|ext2|...|extN" If not specififed, all the files are read.

    :param no_spaces: set to True to remove tabs and newlines.
    :param no_unicode: set to True to replace each word containing non-ascii characters to a special token,  e.g. <non-en>
    :param no_com: set to True to replace each comment with a special token, e.g. <comment>.
    :param no_str: set to True to replace each string literals with a special token, e.g <str_literal>.
    :param max_str_length: replace string literal with `""` if its length including quotes exceeds `max_str_length`.
    Does not have effect if `no_str` is set to `True`

    :return: `PreprocessedDataset` object which holds metadata of the preprocessed dataset

    Examples:
    ---------
    >>> prep_corpus = chars(os.path.join(test_data_dir, 'test-corpus'), 'js', output_path=tempfile.TemporaryDirectory().name, suppress_caching=True) # doctest: +ELLIPSIS
    Files scanned: 1...
    >>> prep_corpus.get_corpus_size()
    97732
    """
    prep_config= create_prep_config('chars', no_spaces=no_spaces, no_unicode=no_unicode, no_com=no_com,
                                    no_str=no_str, max_str_length=max_str_length)
    return preprocess_corpus(path, prep_config, '0', extensions=extensions, output_path=output_path,
                             calc_vocab=calc_vocab, suppress_caching=suppress_caching)
Example #3
0
def basic(path: str,
          extensions: Optional[str] = None,
          split_numbers: bool = False,
          ronin=False,
          stem: bool = False,
          no_spaces: bool = False,
          no_unicode: bool = False,
          no_case: bool = False,
          no_com: bool = False,
          no_str: bool = False,
          max_str_length=sys.maxsize,
          output_path: Optional[str] = None,
          calc_vocab=False) -> PreprocessedCorpus:
    """
    Split corpus at `path` into tokens converting identifiers that follow CamelCase or snake_case into multiple subwords.
    So that the information about original word boundaries is not lost, special tokens are inserted to denote original words beginnings and ends,
    e.g. myClass -> [<w>, my, Class, </w>]

    :param path: path to the corpus to be split.
    :param extensions: Limits the set of input files to the files with the specified extension(s).
    The format is the following: "ext1|ext2|...|extN" If not specififed, all the files are read.

    :param split_numbers: set to True to split numbers into digits
    :param ronin: Split words into subwords with Ronin algorithm: http://joss.theoj.org/papers/10.21105/joss.00653.
    Setting `ronin` to `True` implies `split_numbers`=`True`
    :param stem: set to True to do stemming with Porter stemmer.
    Setting `stem` to `True` implies `ronin`= `True`, and `split_numbers`=`True`

    :param no_spaces: set to True to remove tabs and newlines.
    :param no_case: set to True to lowercase identifiers and encode information about their case in a separate token,
    e.g. Identifier -> [<Cap>, identifier]; IDENTIFIER -> [<CAPS>, identifier]
    :param no_unicode: set to True to replace each word containing non-ascii characters to a special token,  e.g. <non-en>
    :param no_com: set to True to replace each comment with a special token, e.g. <comment>.
    :param no_str: set to True to replace each string literals with a special token, e.g <str_literal>.
    :param max_str_length: replace string literal with `""` if its length including quotes exceeds `max_str_length`.
    Does not have effect if `no_str` is set to `True`

    :return: `PreprocessedDataset` object which holds metadata of the preprocessed dataset
    """
    prep_config = create_prep_config('basic',
                                     no_spaces=no_spaces,
                                     no_unicode=no_unicode,
                                     no_case=no_case,
                                     no_com=no_com,
                                     no_str=no_str,
                                     max_str_length=max_str_length,
                                     split_numbers=split_numbers or stem
                                     or ronin,
                                     ronin=ronin or stem,
                                     stem=stem)
    return preprocess_corpus(path,
                             prep_config,
                             extensions=extensions,
                             output_path=output_path,
                             calc_vocab=calc_vocab)
Example #4
0
def bpe(path: str,
        bpe_codes_id: str,
        extensions: Optional[str] = None,
        no_spaces: bool = False,
        no_unicode: bool = False,
        no_com: bool = False,
        no_str: bool = False,
        max_str_length=sys.maxsize,
        output_path: Optional[str] = None,
        calc_vocab=False) -> PreprocessedCorpus:
    """
    Split corpus at `path` into tokens converting identifiers that follow CamelCase or snake_case into multiple subwords.
    On top of that Byte Pair Encoding (BPE) is applied with number of merges specified in `bpe_config`.
    So that the information about original word boundaries is not lost, special tokens are inserted to denote original words beginnings and ends,
    e.g. myClass -> [<w>, my, Class, </w>]

    :param path: path to the corpus to be split.
    :param bpe_codes_id: defines bpe codes to be used when applying bpe,
    predefined codes : 1k, 5k, 10k. Custom bpe codes can be learned by running `codeprep learn-bpe` command.
    :param extensions: Limits the set of input files to the files with the specified extension(s).
    The format is the following: "ext1|ext2|...|extN" If not specififed, all the files are read.


    :param no_spaces: set to True to remove tabs and newlines.
    :param no_case: set to True to lowercase identifiers and encode information about their case in a separate token,
    e.g. Identifier -> [<Cap>, identifier]; IDENTIFIER -> [<CAPS>, identifier]
    :param no_unicode: set to True to replace each word containing non-ascii characters to a special token,  e.g. <non-en>
    :param no_com: set to True to replace each comment with a special token, e.g. <comment>.
    :param no_str: set to True to replace each string literals with a special token, e.g <str_literal>.
    :param max_str_length: replace string literal with `""` if its length including quotes exceeds `max_str_length`.
    Does not have effect if `no_str` is set to `True`

    :return: `PreprocessedDataset` object which holds metadata of the preprocessed dataset
    """
    prep_config = create_prep_config('bpe',
                                     bpe_codes_id=bpe_codes_id,
                                     no_spaces=no_spaces,
                                     no_unicode=no_unicode,
                                     no_com=no_com,
                                     no_str=no_str,
                                     max_str_length=max_str_length)
    return preprocess_corpus(path,
                             prep_config,
                             bpe_codes_id,
                             extensions=extensions,
                             output_path=output_path,
                             calc_vocab=calc_vocab)
Example #5
0
def nosplit(text: str, extension: Optional[str] = None, no_spaces: bool = False, no_unicode: bool = False,
            no_com: bool = False, no_str: bool = False, full_strings: bool = False, max_str_length: int = sys.maxsize,
            return_metadata: bool = False, append_eof: bool = False) \
        -> Union[List[str], Tuple[List[str], PreprocessingMetadata]]:
    """
    Split `text` into tokens leaving compound identifiers as they are.

    :param text: text to be split.
    :param extension: extension which a file containing source code written in this programming language would have,
    e.g. 'java', 'py', 'js'.
    If specified, used to select a Pygments parser, otherwise Pygments will try to guess the language.

    :param no_spaces: set to True to remove tabs and newlines.
    :param no_unicode: set to True to replace each word containing non-ascii characters to a special token,  e.g. <non-en>
    :param no_com: set to True to replace each comment with a special token, e.g. <comment>.
    :param no_str: set to True to replace each string literals with a special token, e.g <str_literal>.
    :param full_strings: do not split string literals even on whitespace characters
    :param max_str_length: replace string literal with `""` if its length including quotes exceeds `max_str_length`.
    Does not have effect if `no_str` is set to `True`

    :param return_metadata: if set to True additionally pre-processing metadata is returned.
    :param append_eof: set to True for <EOF> token to be added to the end of the string

    :return: list of tokens `text` was split into. If `return_metadata` is set to True,
    the tuple is returned with the list of preprocessed tokens as the first element
    and pre-processing metadata as the second element
    (object of :class:`codeprep.model.metadata.Preprocessing.PreprocessingMetadata`)

    >>> input_text='''void test_WordUeberraschungPrinter() {
    ...     if (eps >= 0.345e+4) { // FIXME 10L
    ...         printWord("     ...     Überraschung 0x12");
    ...    }
    ... }'''

    >>> tokens, metadata = nosplit(input_text, "java", return_metadata=True, append_eof=True)
    >>> tokens
    ['void', 'test_WordUeberraschungPrinter', '(', ')', '{', '\\n', \
'\\t', 'if', '(', 'eps', '>', '=', '0.345e+4', ')', '{', '/', '/', 'FIXME', '10l', '\\n', '<EOL>', \
'\\t', '\\t', 'printWord', '(', '"', '.', '.', '.', 'Überraschung', '0x12', '"', ')', ';', '\\n', \
'}', '\\n', \
'}', '<EOF>']
    >>> sorted(metadata.nonprocessable_tokens)
    ['\\t', '\\n', '"', '(', ')', '.', '/', ';', '<EOF>', '=', '>', 'if', 'void', '{', '}']
    >>> metadata.word_boundaries
    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, \
21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39]
    >>> list(map(lambda x: x.__name__, metadata.token_types))
    ['KeyWord', 'SplitContainer', 'OpeningBracket', 'ClosingBracket', 'OpeningCurlyBracket', 'NewLine', \
'Tab', 'KeyWord', 'OpeningBracket', 'SplitContainer', 'Operator', 'Operator', 'Number', 'ClosingBracket', 'OpeningCurlyBracket', \
'OneLineComment', 'OneLineComment', 'OneLineComment', 'OneLineComment', 'OneLineComment', 'OneLineComment', \
'Tab', 'Tab', 'SplitContainer', 'OpeningBracket', 'StringLiteral', 'StringLiteral', 'StringLiteral', 'StringLiteral', \
'StringLiteral', 'StringLiteral', 'StringLiteral', 'ClosingBracket', 'Semicolon', 'NewLine', \
'ClosingCurlyBracket', 'NewLine', \
'ClosingCurlyBracket', 'SpecialToken']


    >>> nosplit('')
    []


    >>> nosplit(input_text, "java", no_spaces=True)
    ['void', 'test_WordUeberraschungPrinter', '(', ')', '{', \
'if', '(', 'eps', '>', '=', '0.345e+4', ')', '{', '/', '/', 'FIXME', '10l', \
'<EOL>', 'printWord', '(', '"', '.', '.', '.', 'Überraschung', '0x12', '"', ')', ';', \
'}', \
'}']

    >>> nosplit(input_text, "java", no_spaces=True, no_unicode=True)
    ['void', 'test_WordUeberraschungPrinter', '(', ')', '{', \
'if', '(', 'eps', '>', '=', '0.345e+4', ')', '{', '/', '/', 'FIXME', '10l', \
'<EOL>', 'printWord', '(', '"', '.', '.', '.', '<non-en>', '0x12', '"', ')', ';', \
'}', \
'}']

    >>> nosplit('"     ...     Überraschung 0x12"', "java", no_spaces=True, max_str_length=32)
    ['"', '.', '.', '.', 'Überraschung', '0x12', '"']

    >>> nosplit('"     ...     Überraschung 0x12"', "java", no_spaces=True, max_str_length=26, return_metadata=True)
    (['"', '"'], ({'"'}, [0, 2], ['StringLiteral']))

    >>> nosplit('"     ...     Überraschung 0x12"', "java", no_spaces=True, full_strings=True, max_str_length=31, \
return_metadata=True)
    (['""'], (set(), [0, 1], ['StringLiteral']))

    >>> nosplit('"     ...     Überraschung 0x12"', "java", full_strings=True, return_metadata=True)
    (['"\xa0\xa0\xa0\xa0\xa0...\xa0\xa0\xa0\xa0\xa0Überraschung\xa00x12"'], (set(), [0, 1], ['StringLiteral']))

    >>> nosplit('"     ...     Überraschung 0x12"', "java", no_spaces=True, full_strings=True, max_str_length=500)
    ['"\xa0\xa0\xa0\xa0\xa0...\xa0\xa0\xa0\xa0\xa0Überraschung\xa00x12"']


    >>> tokens, metadata = nosplit(input_text, "java", no_spaces=True, no_com=True, no_str=True, return_metadata=True)
    >>> tokens
    ['void', 'test_WordUeberraschungPrinter', '(', ')', '{', \
'if', '(', 'eps', '>', '=', '0.345e+4', ')', '{', '<comment>', \
'printWord', '(', '<str-literal>', ')', ';', \
'}', \
'}']
    >>> sorted(metadata.nonprocessable_tokens)
    ['(', ')', ';', '=', '>', 'if', 'void', '{', '}']
    >>> metadata.word_boundaries
    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, \
21]
    >>> list(map(lambda x: x.__name__, metadata.token_types))
    ['KeyWord', 'SplitContainer', 'OpeningBracket', 'ClosingBracket', 'OpeningCurlyBracket', \
'KeyWord', 'OpeningBracket', 'SplitContainer', 'Operator', 'Operator', 'Number', 'ClosingBracket', 'OpeningCurlyBracket', 'OneLineComment', \
'SplitContainer', 'OpeningBracket', 'StringLiteral', 'ClosingBracket', 'Semicolon', \
'ClosingCurlyBracket', \
'ClosingCurlyBracket']


    >>> nosplit(input_text, "java", no_spaces=True, no_case=True)
    Traceback (most recent call last):
    ...
    TypeError: nosplit() got an unexpected keyword argument 'no_case'

    >>>
    """
    prep_config = create_prep_config('nosplit',
                                     no_spaces=no_spaces,
                                     no_unicode=no_unicode,
                                     no_com=no_com,
                                     no_str=no_str,
                                     full_strings=full_strings,
                                     max_str_length=max_str_length)
    return preprocess(text,
                      prep_config,
                      extension=extension,
                      return_metadata=return_metadata,
                      append_eof=append_eof)
Example #6
0
def bpe(
    text: str,
    bpe_codes_id: str,
    extension: Optional[str] = None,
    no_spaces: bool = False,
    no_unicode: bool = False,
    no_com: bool = False,
    no_str: bool = False,
    max_str_length=sys.maxsize,
    return_metadata: bool = False,
    force_reinit_bpe_data: bool = True,
    append_eof: bool = False
) -> Union[List[str], Tuple[List[str], PreprocessingMetadata]]:
    """
    Split `text` into tokens converting identifiers that follow CamelCase or snake_case into multiple subwords.
    On top of that Byte Pair Encoding (BPE) is applied with number of merges specified in `bpe_config`.
    So that the information about original word boundaries is not lost, special tokens are inserted to denote original
    words beginnings and ends,
    e.g. myClass -> [<w>, my, Class, </w>]

    :param text: text to be split.
    :param bpe_codes_id: defines bpe codes to be used when applying bpe,
    predefined codes : 1k, 5k, 10k. Custom bpe codes can be learned by running `codeprep learn-bpe` command.
    :param extension: extension which a file containing source code written in this programming language would have,
    e.g. 'java', 'py', 'js'.
    If specified, used to select a Pygments parser, otherwise Pygments will try to guess the language.

    :param no_spaces: set to True to remove tabs and newlines.
    :param no_case: set to True to lowercase identifiers and encode information about their case in a separate token,
    e.g. Identifier -> [<Cap>, identifier]; IDENTIFIER -> [<CAPS>, identifier]
    :param no_unicode: set to True to replace each word containing non-ascii characters to a special token,  e.g. <non-en>
    :param no_com: set to True to replace each comment with a special token, e.g. <comment>.
    :param no_str: set to True to replace each string literals with a special token, e.g <str_literal>.
    :param max_str_length: replace string literal with `""` if its length including quotes exceeds `max_str_length`.
    Does not have effect if `no_str` is set to `True`

    :param force_reinit_bpe_data: if set to True, bpe data (merges and bpe cache) is reloaded from the disk
    even if it has been loaded already (for example if this method has been called before). Defaults to True.
    Set this param to False if you want to call this method in a loop.
    Note: if you want to call this method multiple times with different bpe code ids, bpe data has to be reloaded,
    so you must not set this param to False!
    :param return_metadata: if set to True additionally pre-processing metadata is returned.
    :param append_eof: set to True for <EOF> token to be added to the end of the string

    :return: list of tokens `text` was split into. If `return_metadata` is set to True,
    the tuple is returned with the list of preprocessed tokens as the first element
    and pre-processing metadata as the second element
    (object of :class:`codeprep.model.metadata.Preprocessing.PreprocessingMetadata`)

    >>> input_text='''void test_WordUeberraschungPrinter() {
    ...     if (eps >= 0.345e+4) { // FIXME 10L
    ...         printWord("     ...     Überraschung 0x12");
    ...    }
    ... }'''

    >>> tokens, metadata = bpe(input_text, '10k', "java", no_spaces=True, return_metadata=True, append_eof=True)
    >>> tokens
    ['void</t>', 'test_', 'Word', 'U', 'eb', 'err', 'as', 'ch', 'un', 'g', 'Print', 'er</t>', \
'(</t>', ')</t>', '{</t>', \
'if</t>', '(</t>', 'e', 'ps</t>', '></t>', '=</t>', '0.', '34', '5', 'e+', '4</t>', ')</t>', \
'{</t>', '/</t>', '/</t>', 'FIX', 'M', 'E</t>', '10', 'l</t>', '<EOL></t>', \
'print', 'Word</t>', '(</t>', '"\\xa0\\xa0\\xa0', '\\xa0\\xa0', '..', '.', '\\xa0\\xa0', '\\xa0\\xa0', \
'\\xa0', 'Ü', 'b', 'err', 'as', 'ch', 'un', 'g', '\\xa0', '0x', '12', '"</t>', ')</t>', ';</t>', \
'}</t>', \
'}</t>', '<EOF></t>']

    >>> sorted(metadata.nonprocessable_tokens)
    ['(', ')', '/', ';', '<EOF>', '=', '>', 'if', 'void', '{', '}']

    >>> metadata.word_boundaries
    [0, 1, 12, 13, 14, 15, 16, 17, 19, 20, 21, 26, 27, 28, 29, 30, 33, 35, 36, 38, 39, 57, 58, 59, 60, 61, 62]

    >>> list(map(lambda x: x.__name__, metadata.token_types))
    ['KeyWord', 'SplitContainer', 'OpeningBracket', 'ClosingBracket', 'OpeningCurlyBracket', \
'KeyWord', 'OpeningBracket', 'SplitContainer', 'Operator', 'Operator', 'Number', 'ClosingBracket', 'OpeningCurlyBracket', 'OneLineComment', 'OneLineComment', 'OneLineComment', 'OneLineComment', 'OneLineComment', \
'SplitContainer', 'OpeningBracket', 'StringLiteral', 'ClosingBracket', 'Semicolon', \
'ClosingCurlyBracket', \
'ClosingCurlyBracket', 'SpecialToken']

    >>> tokens, metadata = bpe(input_text, '1k', "java", no_spaces=True, max_str_length=14, return_metadata=True)
    >>> tokens
    ['void</t>', 'test', '_', 'Wor', 'd', 'U', 'eb', 'err', 'as', 'ch', 'un', 'g', 'P', 'r', 'int', 'er</t>', \
'(</t>', ')</t>', '{</t>', \
'if</t>', '(</t>', 'e', 'p', 's</t>', '></t>', '=</t>', '0.', '3', '4', '5', 'e', '+', '4</t>', ')</t>', \
'{</t>', '/</t>', '/</t>', 'FI', 'X', 'M', 'E</t>', '1', '0', 'l</t>', '<EOL></t>', \
'print', 'Wor', 'd</t>', '(</t>', '"', '"</t>', ')</t>', ';</t>', \
'}</t>', \
'}</t>']
    >>> metadata.word_boundaries
    [0, 1, 16, 17, 18, 19, 20, 21, 24, 25, 26, 33, 34, 35, 36, 37, 41, 44, 45, 48, 49, 51, 52, 53, 54, 55]


    >>> bpe(input_text, '5k', "java", no_spaces=True)
    ['void</t>', 'test', '_', 'Wor', 'd', 'U', 'eb', 'err', 'as', 'ch', 'un', 'g', 'Print', 'er</t>', \
'(</t>', ')</t>', '{</t>', \
'if</t>', '(</t>', 'e', 'ps</t>', '></t>', '=</t>', '0.', '34', '5', 'e+', '4</t>', ')</t>', \
'{</t>', '/</t>', '/</t>', 'FI', 'X', 'M', 'E</t>', '10', 'l</t>', '<EOL></t>', \
'print', 'Wor', 'd</t>', '(</t>', '"\\xa0', '\\xa0\\xa0', '\\xa0\\xa0', '.', '.', '.', '\\xa0\\xa0', '\\xa0\\xa0', \
'\\xa0', 'Ü', 'b', 'err', 'as', 'ch', 'un', 'g', '\\xa0', '0x', '12', '"</t>', ')</t>', ';</t>', \
'}</t>', \
'}</t>']

    >>> bpe('', '1k')
    []
    """
    prep_config = create_prep_config('bpe',
                                     bpe_codes_id=bpe_codes_id,
                                     no_spaces=no_spaces,
                                     no_unicode=no_unicode,
                                     no_com=no_com,
                                     no_str=no_str,
                                     max_str_length=max_str_length)
    return preprocess(text,
                      prep_config,
                      bpe_codes_id,
                      extension=extension,
                      return_metadata=return_metadata,
                      force_reinit_bpe_data=force_reinit_bpe_data,
                      append_eof=append_eof)
Example #7
0
def basic(
    text: str,
    extension: Optional[str] = None,
    split_numbers: bool = False,
    ronin: bool = False,
    stem: bool = False,
    no_spaces: bool = False,
    no_unicode: bool = False,
    no_case: bool = False,
    no_com: bool = False,
    no_str: bool = False,
    max_str_length: int = sys.maxsize,
    return_metadata: bool = False,
    append_eof: bool = False
) -> Union[List[str], Tuple[List[str], PreprocessingMetadata]]:
    """
    Split `text` into tokens converting identifiers that follow CamelCase or snake_case into multiple subwords.
    So that the information about original word boundaries is not lost, special tokens are inserted to denote original
    words beginnings and ends, e.g. myClass -> [<w>, my, Class, </w>]

    :param text: text to be split.
    :param extension: extension which a file containing source code written in this programming language would have,
    e.g. 'java', 'py', 'js'.
    If specified, used to select a Pygments parser, otherwise Pygments will try to guess the language.

    :param split_numbers: set to True to split numbers into digits
    :param ronin: Split words into subwords with Ronin algorithm: http://joss.theoj.org/papers/10.21105/joss.00653.
    :param stem: set to True to do stemming with Porter stemmer. Setting this param to True, sets `spit_numbers` to True

    :param no_spaces: set to True to remove tabs and newlines.
    :param no_case: set to True to lowercase identifiers and encode information about their case in a separate token,
    e.g. Identifier -> [<Cap>, identifier]; IDENTIFIER -> [<CAPS>, identifier]
    :param no_unicode: set to True to replace each word containing non-ascii characters to a special token,  e.g. <non-en>
    :param no_com: set to True to replace each comment with a special token, e.g. <comment>.
    :param no_str: set to True to replace each string literals with a special token, e.g <str_literal>.
    :param max_str_length: replace string literal with `""` if its length including quotes exceeds `max_str_length`.
    Does not have effect if `no_str` is set to `True`

    :param return_metadata: if set to True additionally pre-processing metadata is returned.
    :param append_eof: set to True for <EOF> token to be added to the end of the string

    :return: list of tokens `text` was split into. If `return_metadata` is set to True,
    the tuple is returned with the list of preprocessed tokens as the first element
    and pre-processing metadata as the second element (object of :class:`codeprep.model.metadata.Preprocessing.PreprocessingMetadata`)


    >>> input_text='''void test_WordUeberraschungPrinter() {
    ...     if (eps >= 0.345e+4) { // FIXME 10L
    ...         printWord("     ...     Überraschung 0x12");
    ...    }
    ... }'''

    >>> tokens, metadata = basic(input_text, "java", no_spaces=True, return_metadata=True, append_eof=True)
    >>> tokens
    ['void', '<w>', 'test', '_', 'Word', 'Ueberraschung', 'Printer', '</w>', '(', ')', '{', \
'if', '(', 'eps', '>', '=', '0.345e+4', ')', '{', '/', '/', 'FIXME', '10l', '<EOL>', \
'<w>', 'print', 'Word', '</w>', '(', '"', '.', '.', '.', 'Überraschung', '0x12', '"', ')', ';', \
'}', \
'}', '<EOF>']

    >>> sorted(metadata.nonprocessable_tokens)
    ['"', '(', ')', '.', '/', ';', '<EOF>', '=', '>', 'if', 'void', '{', '}']

    >>> metadata.word_boundaries
    [0, 1, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 28, 29, 30, 31, 32, 33, 34, 35, 36, \
37, 38, 39, 40, 41]

    >>> list(map(lambda x: x.__name__, metadata.token_types))
    ['KeyWord', 'SplitContainer', 'OpeningBracket', 'ClosingBracket', 'OpeningCurlyBracket', \
'KeyWord', 'OpeningBracket', 'SplitContainer', 'Operator', 'Operator', 'Number', 'ClosingBracket', 'OpeningCurlyBracket', 'OneLineComment', 'OneLineComment', 'OneLineComment', 'OneLineComment', 'OneLineComment', \
'SplitContainer', 'OpeningBracket', 'StringLiteral', 'StringLiteral', 'StringLiteral', 'StringLiteral', 'StringLiteral', 'StringLiteral', 'StringLiteral', 'ClosingBracket', 'Semicolon', \
'ClosingCurlyBracket', \
'ClosingCurlyBracket', 'SpecialToken']

    >>> tokens, metadata = basic(input_text, "java", no_spaces=True, no_case=True, return_metadata=True)
    >>> tokens
    ['void', '<w>', 'test', '_', '<Cap>', 'word', '<Cap>', 'ueberraschung', '<Cap>', 'printer', '</w>', '(', ')', '{', \
'if', '(', 'eps', '>', '=', '0.345e+4', ')', '{', '/', '/', '<CAPS>', 'fixme', '10l', '<EOL>', \
'<w>', 'print', '<Cap>', 'word', '</w>', '(', '"', '.', '.', '.', '<Cap>', 'überraschung', '0x12', '"', ')', ';', \
'}', \
'}']
    >>> sorted(metadata.nonprocessable_tokens)
    ['"', '(', ')', '.', '/', ';', '=', '>', 'if', 'void', '{', '}']

    >>> metadata.word_boundaries
    [0, 1, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 28, 33, 34, 35, 36, 37, 38, 40, 41, 42, \
43, 44, 45, 46]

    >>> list(map(lambda x: x.__name__, metadata.token_types))
    ['KeyWord', 'SplitContainer', 'OpeningBracket', 'ClosingBracket', 'OpeningCurlyBracket', \
'KeyWord', 'OpeningBracket', 'SplitContainer', 'Operator', 'Operator', 'Number', 'ClosingBracket', 'OpeningCurlyBracket', 'OneLineComment', 'OneLineComment', 'OneLineComment', 'OneLineComment', 'OneLineComment', \
'SplitContainer', 'OpeningBracket', 'StringLiteral', 'StringLiteral', 'StringLiteral', 'StringLiteral', 'StringLiteral', 'StringLiteral', 'StringLiteral', 'ClosingBracket', 'Semicolon', \
'ClosingCurlyBracket', \
'ClosingCurlyBracket']

    >>> basic(input_text, "java", no_spaces=True, no_case=True, no_com=True, no_str=True)
    ['void', '<w>', 'test', '_', '<Cap>', 'word', '<Cap>', 'ueberraschung', '<Cap>', 'printer', '</w>', '(', ')', '{', \
'if', '(', 'eps', '>', '=', '0.345e+4', ')', '{', '<comment>', \
'<w>', 'print', '<Cap>', 'word', '</w>', '(', '<str-literal>', ')', ';', \
'}', \
'}']

    >>> basic('"     Überraschung 0x12"', "java", no_spaces=True, no_unicode=True, no_case=True, return_metadata=True)
    (['"', '<non-en>', '0x12', '"'], ({'"'}, [0, 1, 2, 3, 4], \
['StringLiteral', 'StringLiteral', 'StringLiteral', 'StringLiteral']))

    >>> basic('')
    []

    >>> basic("movingVehiclesspeed = 0.345e+4", "java", split_numbers=True, return_metadata=True)
    (['<w>', 'moving', 'Vehiclesspeed', '</w>', '=', '<w>', '0', '.', '3', '4', '5', 'e', '+', '4', '</w>'], \
({'='}, [0, 4, 5, 15], ['SplitContainer', 'Operator', 'Number']))

    >>> basic("movingVehiclesspeed = 0.345e+4", "java", ronin=True, return_metadata=True)
    (['<w>', 'moving', 'Vehicles', 'speed', '</w>', '=', '<w>', '0', '.', '3', '4', '5', 'e', '+', '4', '</w>'], \
({'='}, [0, 5, 6, 16], ['SplitContainer', 'Operator', 'Number']))

    >>> basic("movingVehiclesspeed = 0.345e+4", "java", stem=True, return_metadata=True)
    (['<w>', 'move', 'Vehicl', 'speed', '</w>', '=', '<w>', '0', '.', '3', '4', '5', 'e', '+', '4', '</w>'], \
({'='}, [0, 5, 6, 16], ['SplitContainer', 'Operator', 'Number']))

    """
    prep_config = create_prep_config('basic',
                                     no_spaces=no_spaces,
                                     no_unicode=no_unicode,
                                     no_case=no_case,
                                     no_com=no_com,
                                     no_str=no_str,
                                     max_str_length=max_str_length,
                                     split_numbers=split_numbers or ronin
                                     or stem,
                                     ronin=ronin or stem,
                                     stem=stem)
    return preprocess(text,
                      prep_config,
                      extension=extension,
                      return_metadata=return_metadata,
                      append_eof=append_eof)
Example #8
0
def chars(
    text: str,
    extension: Optional[str] = None,
    no_spaces: bool = False,
    no_unicode: bool = False,
    no_com: bool = False,
    no_str: bool = False,
    max_str_length=sys.maxsize,
    return_metadata: bool = False,
    append_eof: bool = False
) -> Union[List[str], Tuple[List[str], PreprocessingMetadata]]:
    """
    Split `text` into characters (With the exception of operators that consist of 2 character:
    such operators will remain as a single token). So that the information about original word boundaries is not lost,
    special tokens are inserted to denote original words beginnings and ends,
    e.g. myClass -> [<w>, m, y, C, l, a, s, s, </w>]


    :param text: text to be split.
    :param extension: extension which a file containing source code written in this programming language would have,
    e.g. 'java', 'py', 'js'.
    If specified, used to select a Pygments parser, otherwise Pygments will try to guess the language.

    :param no_spaces: set to True to remove tabs and newlines.
    :param no_case: set to True to lowercase identifiers and encode information about their case in a separate token,
    e.g. Identifier -> [<Cap>, identifier]; IDENTIFIER -> [<CAPS>, identifier]
    :param no_unicode: set to True to replace each word containing non-ascii characters to a special token,
    e.g. <non-en>
    :param no_com: set to True to replace each comment with a special token, e.g. <comment>.
    :param no_str: set to True to replace each string literals with a special token, e.g <str_literal>.
    :param max_str_length: replace string literal with `""` if its length including quotes exceeds `max_str_length`.
    Does not have effect if `no_str` is set to `True`

    :param return_metadata: if set to True additionally pre-processing metadata is returned.
    :param append_eof: set to True for <EOF> token to be added to the end of the string

    :return: list of tokens `text` was split into. If `return_metadata` is set to True,
    the tuple is returned with the list of preprocessed tokens as the first element
    and pre-processing metadata as the second element
    (object of :class:`codeprep.model.metadata.Preprocessing.PreprocessingMetadata`)

    >>> input_text='''void test_WordUeberraschungPrinter() {
    ...     if (eps >= 0.345e+4) { // FIXME 10L
    ...         printWord("     ...     Überraschung 0x12");
    ...    }
    ... }'''

    >>> tokens, metadata = chars(input_text, "java", no_spaces=True, return_metadata=True, append_eof=True)
    >>> tokens
    ['void</t>', 't', 'e', 's', 't', '_', 'W', 'o', 'r', 'd', 'U', 'e', 'b', 'e', 'r', 'r', 'a', 's', 'c', 'h', \
'u', 'n', 'g', 'P', 'r', 'i', 'n', 't', 'e', 'r', '</t>', '(</t>', ')</t>', '{</t>', \
'if</t>', '(</t>', 'e', 'p', 's', '</t>', '></t>', '=</t>', '0', '.', '3', '4', '5', 'e', '+', '4', '</t>', ')</t>', \
'{</t>', '/</t>', '/</t>', 'F', 'I', 'X', 'M', 'E', '</t>', '1', '0', 'l', '</t>', '<EOL></t>', \
'p', 'r', 'i', 'n', 't', 'W', 'o', 'r', 'd', '</t>', '(</t>', '"', \
'\\xa0', '\\xa0', '\\xa0', '\\xa0', '\\xa0', '.', '.', '.', \
'\\xa0', '\\xa0', '\\xa0', '\\xa0', '\\xa0', 'Ü', 'b', 'e', 'r', 'r', 'a', 's', 'c', 'h', 'u', 'n', 'g', \
'\\xa0', '0', 'x', '1', '2', '"', '</t>', ')</t>', ';</t>', \
'}</t>', \
'}</t>', '<EOF></t>']
    >>> sorted(metadata.nonprocessable_tokens)
    ['(', ')', '/', ';', '<EOF>', '=', '>', 'if', 'void', '{', '}']
    >>> metadata.word_boundaries
    [0, 1, 31, 32, 33, 34, 35, 36, 40, 41, 42, 51, 52, 53, 54, 55, 61, 65, 66, 76, 77, 110, 111, 112, 113, 114, 115]
    >>> list(map(lambda x: x.__name__, metadata.token_types))
    ['KeyWord', 'SplitContainer', 'OpeningBracket', 'ClosingBracket', 'OpeningCurlyBracket', \
'KeyWord', 'OpeningBracket', 'SplitContainer', 'Operator', 'Operator', 'Number', 'ClosingBracket', 'OpeningCurlyBracket', \
'OneLineComment', 'OneLineComment', 'OneLineComment', 'OneLineComment', 'OneLineComment', \
'SplitContainer', 'OpeningBracket', 'StringLiteral', 'ClosingBracket', 'Semicolon', \
'ClosingCurlyBracket', \
'ClosingCurlyBracket', 'SpecialToken']


    >>> chars('')
    []
    """
    prep_config = create_prep_config('chars',
                                     no_spaces=no_spaces,
                                     no_unicode=no_unicode,
                                     no_com=no_com,
                                     no_str=no_str,
                                     max_str_length=max_str_length)
    return preprocess(text,
                      prep_config,
                      '0',
                      extension=extension,
                      return_metadata=return_metadata,
                      append_eof=append_eof)