add newline at end of file

.clang-format

@@ -26,4 +26,4 @@ BraceWrapping:
   SplitEmptyNamespace: false
 AllowAllConstructorInitializersOnNextLine: true
 ConstructorInitializerAllOnOneLineOrOnePerLine: true
-AllowShortCaseLabelsOnASingleLine: true
+AllowShortCaseLabelsOnASingleLine: true

.coveragerc

@@ -5,4 +5,4 @@ omit =
     src/cpp_common.pxd
 
 [precision]
-show_missing = true
+show_missing = true

.gitignore

@@ -26,4 +26,3 @@ bench_results/
 
 # Cython generated files
 *.cxx
-

CITATION.bib

@@ -7,4 +7,4 @@
   version      = {v1.8.0},
   doi          = {10.5281/zenodo.5584996},
   url          = {https://doi.org/10.5281/zenodo.5584996}
-}
+}

LICENSE

@@ -18,4 +18,4 @@ MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
 NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
 LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
 OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
-WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

bench/benchmark_fuzz.py

@@ -87,4 +87,4 @@ df = pandas.DataFrame(data={
     "max(partial_token_sort_ratio, partial_token_set_ratio)": time_partial_token_ratio_simple,
 })
 
-df.to_csv(f"results/partial_token_ratio.csv", sep=',',index=False)
+df.to_csv(f"results/partial_token_ratio.csv", sep=',',index=False)

docs/Contributing/index.rst

@@ -50,4 +50,3 @@ Submitting an issue
 Before you submit an issue, please search the issue tracker, maybe an issue for
 your problem already exists and the discussion might inform you of workarounds
 readily available.
-

docs/Usage/distance/Hamming.rst

@@ -19,4 +19,3 @@ similarity
 normalized_similarity
 ~~~~~~~~~~~~~~~~~~~~~
 .. autofunction:: rapidfuzz.distance.Hamming.normalized_similarity
-

docs/Usage/distance/Indel.rst

@@ -74,4 +74,4 @@ The following implementation is used with a worst-case performance of ``O([N/64]
   a blockwise implementation of the Hyyrös' lcs algorithm is used, which calculates
   the Levenshtein distance in parallel (64 characters at a time).
   The algorithm is described by :cite:t:`2004:hyrroe`. The time complexity of this
-  algorithm is ``O([N/64]M)``.
+  algorithm is ``O([N/64]M)``.

docs/Usage/distance/Levenshtein.rst

@@ -112,4 +112,3 @@ Generic
 The implementation for other weights is based on Wagner-Fischer.
 It has a performance of ``O(N * M)`` and has a memory usage of ``O(N)``.
 Further details can be found in :cite:t:`1974:WagFisch`.
-

docs/Usage/index.rst

@@ -9,4 +9,3 @@ Usage
    fuzz
    string_metric
    utils
-

docs/Usage/string_metric.rst

@@ -23,4 +23,4 @@ jaro_similarity
 
 jaro_winkler_similarity
 -----------------------
-.. autofunction:: rapidfuzz.string_metric.jaro_winkler_similarity
+.. autofunction:: rapidfuzz.string_metric.jaro_winkler_similarity

docs/changelog_link.rst

@@ -1,2 +1,2 @@
 
-.. mdinclude:: ../CHANGELOG.md
+.. mdinclude:: ../CHANGELOG.md

docs/conf.py

@@ -60,4 +60,4 @@ html_static_path = ['_static']
 
 napoleon_google_docstring = False
 
-# -- Extension configuration -------------------------------------------------
+# -- Extension configuration -------------------------------------------------

docs/index.rst

@@ -15,4 +15,4 @@ RapidFuzz
    changelog_link
    License
    References
-   GitHub Repository <https://github.com/maxbachmann/RapidFuzz>
+   GitHub Repository <https://github.com/maxbachmann/RapidFuzz>

docs/refs.bib

@@ -43,6 +43,3 @@
     title = {Bit-Parallel LCS-length Computation Revisited},
     journal = {Proc. 15th Australasian Workshop on Combinatorial Algorithms (AWOCA 2004)}
 }
-
-
-

docs/requirements.txt

@@ -3,4 +3,4 @@ Sphinx
 furo
 numpy
 sphinxcontrib-bibtex
-m2r2
+m2r2

src/rapidfuzz/_utils.pyi

@@ -4,4 +4,4 @@
 default_distance_attribute : dict
 default_similarity_attribute : dict
 default_normalized_distance_attribute : dict
-default_normalized_similarity_attribute : dict
+default_normalized_similarity_attribute : dict

src/rapidfuzz/cpp_common.hpp

@@ -703,4 +703,4 @@ static inline PyObject* editops_apply(const rapidfuzz::Editops& ops, const RF_St
         auto proc_str = rapidfuzz::editops_apply<uint32_t>(ops, s1, s2);
         return PyUnicode_FromKindAndData(PyUnicode_4BYTE_KIND, proc_str.data(), (Py_ssize_t)proc_str.size());
     });
-}
+}

src/rapidfuzz/distance/_initialize_cpp.pxd

@@ -16,4 +16,4 @@ cdef class ScoreAlignment:
     cdef public Py_ssize_t src_start
     cdef public Py_ssize_t src_end
     cdef public Py_ssize_t dest_start
-    cdef public Py_ssize_t dest_end
+    cdef public Py_ssize_t dest_end

src/rapidfuzz/distance/metrics.hpp

@@ -618,4 +618,4 @@ static inline bool JaroWinklerNormalizedSimilarityInit(RF_ScorerFunc* self, cons
 {
     double prefix_weight = *static_cast<double*>(kwargs->context);
     return normalized_similarity_init<rapidfuzz::CachedJaroWinkler, double>(self, str_count, str, prefix_weight);
-}
+}

src/rapidfuzz/simd/avx2/edit_based_avx2.cpp

@@ -3,4 +3,4 @@
 namespace Avx2
 {
 #include "../edit_based_simd.impl"
-}
+}

src/rapidfuzz/simd/avx2/edit_based_avx2.hpp

@@ -5,4 +5,4 @@
 namespace Avx2
 {
 #include "../edit_based_simd.incl"
-}
+}

src/rapidfuzz/simd/sse2/edit_based_sse2.cpp

@@ -3,4 +3,4 @@
 namespace Sse2
 {
 #include "../edit_based_simd.impl"
-}
+}

src/rapidfuzz/simd/sse2/edit_based_sse2.hpp

@@ -5,4 +5,4 @@
 namespace Sse2
 {
 #include "../edit_based_simd.incl"
-}
+}

src/rapidfuzz/unicodetype_db.h

@@ -6265,4 +6265,3 @@ int _PyUnicode_IsLinebreak(const uint32_t ch)
     }
     return 0;
 }
-

tests/test_hypothesis.py

@@ -616,4 +616,4 @@ def test_jaro_winkler_block(s1, s2):
 @settings(max_examples=50, deadline=1000)
 def test_jaro_winkler_random(s1, s2):
     print(s1, s2)
-    assert isclose(jaro_winkler_similarity(s1, s2), jarowinkler_similarity(s1, s2))
+    assert isclose(jaro_winkler_similarity(s1, s2), jarowinkler_similarity(s1, s2))