"""

Tests for the pure string and utility helpers in _plotly_utils.utils.

These functions have no external dependencies and back the "did you mean"

suggestions and path-parsing used in validator error messages. The expected

values below were taken from the function docstrings and confirmed against the

actual output.

"""

import pytest

from _plotly_utils.utils import (

chomp_empty_strings,

display_string_positions,

find_closest_string,

is_skipped_key,

levenshtein,

split_multichar,

split_string_positions,

_natural_sort_strings,

)

@pytest.mark.parametrize(

"s1,s2,expected",

[

("kitten", "sitting", 3),

("", "abc", 3),

("abc", "", 3),

("abc", "abc", 0),

("flaw", "lawn", 2),

],

)

def test_levenshtein_distance(s1, s2, expected):

assert levenshtein(s1, s2) == expected

def test_levenshtein_is_symmetric():

assert levenshtein("kitten", "sitting") == levenshtein("sitting", "kitten")

def test_find_closest_string_exact_match():

assert find_closest_string("range", ["rang", "range", "orange"]) == "range"

def test_find_closest_string_picks_nearest():

assert find_closest_string("colour", ["color", "colored", "scale"]) == "color"

def test_find_closest_string_ties_break_lexicographically():

# "ac" and "ad" are both distance 1 from "ab"; the lexicographically

# smaller one wins regardless of input order.

assert find_closest_string("ab", ["ad", "ac", "xy"]) == "ac"

def test_split_multichar_splits_on_every_char():

ss = ["a.string[0].with_separators"]

assert split_multichar(ss, list(".[]_")) == [

"a",

"string",

"0",

"",

"with",

"separators",

]

def test_split_multichar_no_chars_returns_input():

assert split_multichar(["abc"], []) == ["abc"]

def test_split_string_positions():

ss = split_multichar(["a.string[0].with_separators"], list(".[]_"))

assert split_string_positions(ss) == [0, 2, 9, 11, 12, 17]

def test_display_string_positions_single_index():

p = [0, 2, 9, 11, 12, 17]

assert display_string_positions(p, 4) == " ^"

def test_display_string_positions_offset_length_char_no_trim():

p = [0, 2, 9, 11, 12, 17]

assert (

display_string_positions(p, 4, offset=1, length=3, char="~", trim=False)

== " ~~~ "

)

def test_display_string_positions_all_indices():

p = [0, 2, 9, 11, 12, 17]

assert display_string_positions(p) == "^ ^ ^ ^^ ^"

@pytest.mark.parametrize(

"strings,expected",

[

([], []),

([""], [""]),

(["", ""], ["_"]),

(["", "", "", ""], ["___"]),

(["hey", "", "why", "", "", "whoa", "", ""], ["hey_", "why__", "whoa__"]),

(["", "hi", "", "I'm", "bob", "", ""], ["_", "hi_", "I'm", "bob__"]),

(["hi", "i'm", "a", "good", "string"], ["hi", "i'm", "a", "good", "string"]),

],

)

def test_chomp_empty_strings(strings, expected):

assert chomp_empty_strings(strings, "_") == expected

def test_chomp_empty_strings_reverse():

strings = ["", "hi", "", "I'm", "bob", "", ""]

assert chomp_empty_strings(strings, "_", reverse=True) == [

"_hi",

"_I'm",

"bob",

"__",

]

@pytest.mark.parametrize("key", ["geojson", "layer", "layers", "range"])

def test_is_skipped_key_true(key):

assert is_skipped_key(key) is True

@pytest.mark.parametrize("key", ["x", "y", "geo", "Range", ""])

def test_is_skipped_key_false(key):

assert is_skipped_key(key) is False

def test_natural_sort_strings_orders_numbers_naturally():

assert _natural_sort_strings(["x10", "x2", "x1"]) == ["x1", "x2", "x10"]

def test_natural_sort_strings_reverse():

assert _natural_sort_strings(["x10", "x2", "x1"], reverse=True) == [

"x10",

"x2",

"x1",

]