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String Functions

Functions for string manipulation, text processing, and string analysis.

Usage

String functions are available under the func.string namespace to avoid name collisions with other functions:

from datachain.func import string

# Use string functions with the string namespace
dc.mutate(
    str_len=string.length("text_column"),
    parts=string.split("text_column", ","),
    cleaned=string.replace("text_column", "old", "new"),
    regex_cleaned=string.regexp_replace("text_column", r"\d+", "X"),
    distance=string.byte_hamming_distance("col1", "col2")
)

string

byte_hamming_distance 

byte_hamming_distance(*args: ColT) -> Func

Computes the Hamming distance between two strings.

The Hamming distance is the number of positions at which the corresponding characters are different. This function returns the dissimilarity between the strings, where 0 indicates identical strings and values closer to the length of the strings indicate higher dissimilarity.

Parameters:

  • args (str | Column | Func | literal, default: () ) –

    Two strings to compute the Hamming distance between. If a string is provided, it is assumed to be the name of the column. If a Column is provided, it is assumed to be a column in the dataset. If a Func is provided, it is assumed to be a function returning a string. If a literal is provided, it is assumed to be a string literal.

Returns:

  • Func ( Func ) –

    A Func object that represents the Hamming distance function.

Example 
dc.mutate(
    hd1=func.byte_hamming_distance("file.phash", literal("hello")),
    hd2=func.byte_hamming_distance(dc.C("file.phash"), "hello"),
    hd3=func.byte_hamming_distance(
        dc.func.literal("hi"),
        dc.func.literal("hello"),
    ),
)
Notes
  • The result column will always be of type int.
Source code in datachain/func/string.py 
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def byte_hamming_distance(*args: ColT) -> Func:
    """
    Computes the Hamming distance between two strings.

    The Hamming distance is the number of positions at which the corresponding
    characters are different. This function returns the dissimilarity between
    the strings, where 0 indicates identical strings and values closer to the length
    of the strings indicate higher dissimilarity.

    Args:
        args (str | Column | Func | literal): Two strings to compute
            the Hamming distance between.
            If a string is provided, it is assumed to be the name of the column.
            If a Column is provided, it is assumed to be a column in the dataset.
            If a Func is provided, it is assumed to be a function returning a string.
            If a literal is provided, it is assumed to be a string literal.

    Returns:
        Func: A `Func` object that represents the Hamming distance function.

    Example:
        ```py
        dc.mutate(
            hd1=func.byte_hamming_distance("file.phash", literal("hello")),
            hd2=func.byte_hamming_distance(dc.C("file.phash"), "hello"),
            hd3=func.byte_hamming_distance(
                dc.func.literal("hi"),
                dc.func.literal("hello"),
            ),
        )
        ```

    Notes:
        - The result column will always be of type int.
    """
    cols, func_args = [], []
    for arg in args:
        if get_origin(arg) is literal:
            func_args.append(arg)
        else:
            cols.append(arg)

    if len(cols) + len(func_args) != 2:
        raise ValueError("byte_hamming_distance() requires exactly two arguments")

    return Func(
        "byte_hamming_distance",
        inner=string.byte_hamming_distance,
        cols=cols,
        args=func_args,
        result_type=int,
    )

length 

length(col: ColT) -> Func

Returns the length of the string.

Parameters:

  • col (str | Column | Func | literal) –

    String to compute the length of. If a string is provided, it is assumed to be the name of the column. If a Column is provided, it is assumed to be a column in the dataset. If a Func is provided, it is assumed to be a function returning a string. If a literal is provided, it is assumed to be a string literal.

Returns:

  • Func ( Func ) –

    A Func object that represents the string length function.

Example 
dc.mutate(
    len1=func.string.length("file.path"),
    len2=func.string.length(dc.C("file.path")),
    len3=func.string.length(dc.func.literal("Random string")),
)
Notes
  • The result column will always be of type int.
Source code in datachain/func/string.py 
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def length(col: ColT) -> Func:
    """
    Returns the length of the string.

    Args:
        col (str | Column | Func | literal): String to compute the length of.
            If a string is provided, it is assumed to be the name of the column.
            If a Column is provided, it is assumed to be a column in the dataset.
            If a Func is provided, it is assumed to be a function returning a string.
            If a literal is provided, it is assumed to be a string literal.

    Returns:
        Func: A `Func` object that represents the string length function.

    Example:
        ```py
        dc.mutate(
            len1=func.string.length("file.path"),
            len2=func.string.length(dc.C("file.path")),
            len3=func.string.length(dc.func.literal("Random string")),
        )
        ```

    Notes:
        - The result column will always be of type int.
    """
    return Func("length", inner=string.length, cols=[col], result_type=int)

regexp_replace 

regexp_replace(
    col: ColT, regex: str, replacement: str
) -> Func

Replaces substring that match a regular expression.

Parameters:

  • col (str | Column | Func | literal) –

    Column to perform replacement on. If a string is provided, it is assumed to be the name of the column. If a Column is provided, it is assumed to be a column in the dataset. If a Func is provided, it is assumed to be a function returning a string. If a literal is provided, it is assumed to be a string literal.

  • regex (str) –

    Regular expression pattern to replace.

  • replacement (str) –

    Replacement string.

Returns:

  • Func ( Func ) –

    A Func object that represents the regexp_replace function.

Example 
dc.mutate(
    s1=func.string.regexp_replace("signal.name", r"\d+", "X"),
    s2=func.string.regexp_replace(dc.C("signal.name"), r"\d+", "X"),
    s3=func.string.regexp_replace(
        dc.func.literal("Random string"),
        r"\s+",
        "_",
    ),
)
Notes
  • The result column will always be of type string.
Source code in datachain/func/string.py 
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def regexp_replace(col: ColT, regex: str, replacement: str) -> Func:
    r"""
    Replaces substring that match a regular expression.

    Args:
        col (str | Column | Func | literal): Column to perform replacement on.
            If a string is provided, it is assumed to be the name of the column.
            If a Column is provided, it is assumed to be a column in the dataset.
            If a Func is provided, it is assumed to be a function returning a string.
            If a literal is provided, it is assumed to be a string literal.
        regex (str): Regular expression pattern to replace.
        replacement (str): Replacement string.

    Returns:
        Func: A `Func` object that represents the regexp_replace function.

    Example:
        ```py
        dc.mutate(
            s1=func.string.regexp_replace("signal.name", r"\d+", "X"),
            s2=func.string.regexp_replace(dc.C("signal.name"), r"\d+", "X"),
            s3=func.string.regexp_replace(
                dc.func.literal("Random string"),
                r"\s+",
                "_",
            ),
        )
        ```

    Notes:
        - The result column will always be of type string.
    """

    def inner(arg):
        return string.regexp_replace(arg, regex, replacement)

    if get_origin(col) is literal:
        cols = None
        args = [col]
    else:
        cols = [col]
        args = None

    return Func("regexp_replace", inner=inner, cols=cols, args=args, result_type=str)

replace 

replace(col: ColT, pattern: str, replacement: str) -> Func

Replaces substring with another string.

Parameters:

  • col (str | Column | Func | literal) –

    Column to perform replacement on. If a string is provided, it is assumed to be the name of the column. If a Column is provided, it is assumed to be a column in the dataset. If a Func is provided, it is assumed to be a function returning a string. If a literal is provided, it is assumed to be a string literal.

  • pattern (str) –

    Pattern to replace.

  • replacement (str) –

    Replacement string.

Returns:

  • Func ( Func ) –

    A Func object that represents the replace function.

Example 
dc.mutate(
    s1=func.string.replace("signal.name", "pattern", "replacement"),
    s2=func.string.replace(dc.C("signal.name"), "pattern", "replacement"),
    s3=func.string.replace(dc.func.literal("Random string"), "Random", "New"),
)
Notes
  • The result column will always be of type string.
Source code in datachain/func/string.py 
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def replace(col: ColT, pattern: str, replacement: str) -> Func:
    """
    Replaces substring with another string.

    Args:
        col (str | Column | Func | literal): Column to perform replacement on.
            If a string is provided, it is assumed to be the name of the column.
            If a Column is provided, it is assumed to be a column in the dataset.
            If a Func is provided, it is assumed to be a function returning a string.
            If a literal is provided, it is assumed to be a string literal.
        pattern (str): Pattern to replace.
        replacement (str): Replacement string.

    Returns:
        Func: A `Func` object that represents the replace function.

    Example:
        ```py
        dc.mutate(
            s1=func.string.replace("signal.name", "pattern", "replacement"),
            s2=func.string.replace(dc.C("signal.name"), "pattern", "replacement"),
            s3=func.string.replace(dc.func.literal("Random string"), "Random", "New"),
        )
        ```

    Notes:
        - The result column will always be of type string.
    """

    def inner(arg):
        return string.replace(arg, pattern, replacement)

    if get_origin(col) is literal:
        cols = None
        args = [col]
    else:
        cols = [col]
        args = None

    return Func("replace", inner=inner, cols=cols, args=args, result_type=str)

split 

split(
    col: ColT, sep: str, limit: Optional[int] = None
) -> Func

Takes a column and split character and returns an array of the parts.

Parameters:

  • col (str | Column | Func | literal) –

    Column to split. If a string is provided, it is assumed to be the name of the column. If a Column is provided, it is assumed to be a column in the dataset. If a Func is provided, it is assumed to be a function returning a string. If a literal is provided, it is assumed to be a string literal.

  • sep (str) –

    Separator to split the string.

  • limit (int, default: None ) –

    Maximum number of splits to perform.

Returns:

  • Func ( Func ) –

    A Func object that represents the split function.

Example 
dc.mutate(
    path_parts=func.string.split("file.path", "/"),
    signal_values=func.string.split(dc.C("signal.value"), ","),
    str_words=func.string.split(dc.func.literal("Random string"), " "),
)
Notes
  • The result column will always be of type array of strings.
Source code in datachain/func/string.py 
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def split(col: ColT, sep: str, limit: Optional[int] = None) -> Func:
    """
    Takes a column and split character and returns an array of the parts.

    Args:
        col (str | Column | Func | literal): Column to split.
            If a string is provided, it is assumed to be the name of the column.
            If a Column is provided, it is assumed to be a column in the dataset.
            If a Func is provided, it is assumed to be a function returning a string.
            If a literal is provided, it is assumed to be a string literal.
        sep (str): Separator to split the string.
        limit (int, optional): Maximum number of splits to perform.

    Returns:
        Func: A `Func` object that represents the split function.

    Example:
        ```py
        dc.mutate(
            path_parts=func.string.split("file.path", "/"),
            signal_values=func.string.split(dc.C("signal.value"), ","),
            str_words=func.string.split(dc.func.literal("Random string"), " "),
        )
        ```

    Notes:
        - The result column will always be of type array of strings.
    """

    def inner(arg):
        if limit is not None:
            return string.split(arg, sep, limit)
        return string.split(arg, sep)

    if get_origin(col) is literal:
        cols = None
        args = [col]
    else:
        cols = [col]
        args = None

    return Func("split", inner=inner, cols=cols, args=args, result_type=list[str])