Test-Run Trigger (on branch: free)

.github/workflows/test.yml

@@ -21,8 +21,10 @@ jobs:
       with:
         python-version: ${{ matrix.python-version }}
 
-    - name: Install package
-      run: pip install .
+    - name: Install dev-package
+      run: |
+        python -m pip install --upgrade pip
+        pip install -v -e .
 
     - name: Run tests
       run: python -m unittest

CHANGELOG.md

@@ -7,6 +7,23 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [0.4.1?] - 2021-06-11
+
+### Added
+
+* Added new keyword argument **`tfidf_matrix_dtype`** (the datatype for the tf-idf values of the matrix components). Allowed values are `numpy.float32` and `numpy.float64` (used by the required external package `sparse_dot_topn` version 0.3.1).  Default is `numpy.float32`.  (Note: `numpy.float32` often leads to faster processing and a smaller memory footprint albeit less numerical precision than `numpy.float64`.)
+
+### Changed
+
+* Changed dependency on `sparse_dot_topn` from version 0.2.9 to 0.3.1
+* Changed the default datatype for cosine similarities from numpy.float64 to numpy.float32 to boost computational performance at the expense of numerical precision.
+* Changed the default value of the keyword argument `max_n_matches` from 20 to the number of strings in `duplicates` (or `master`, if `duplicates` is not given). 
+* Changed warning issued when the condition \[`include_zeroes=True` and `min_similarity` ≤ 0 and `max_n_matches` is not sufficiently high to capture all nonzero-similarity-matches\] is met to an exception. 
+
+### Removed
+
+* Removed the keyword argument `suppress_warning`
+
 ## [0.4.0] - 2021-04-11
 
 ### Added

README.md

@@ -134,16 +134,16 @@ All functions are built using a class **`StringGrouper`**. This class can be use
    All keyword arguments not mentioned in the function definitions above are used to update the default settings. The following optional arguments can be used:
 
    * **`ngram_size`**: The amount of characters in each n-gram. Default is `3`.
+   * **`tfidf_matrix_dtype`**: The datatype for the tf-idf values of the matrix components. Allowed values are `numpy.float32` and `numpy.float64`.  Default is `numpy.float32`.  (Note: `numpy.float32` often leads to faster processing and a smaller memory footprint albeit less numerical precision than `numpy.float64`.)
    * **`regex`**: The regex string used to clean-up the input string. Default is `"[,-./]|\s"`.
-   * **`max_n_matches`**: The maximum number of matches allowed per string in `master`. Default is `20`.
+   * **`max_n_matches`**: The maximum number of matches allowed per string in `master`. Default is the number of strings in `duplicates` (or `master`, if `duplicates` is not given).
    * **`min_similarity`**: The minimum cosine similarity for two strings to be considered a match.
     Defaults to `0.8`
    * **`number_of_processes`**: The number of processes used by the cosine similarity calculation. Defaults to
     `number of cores on a machine - 1.`
    * **`ignore_index`**: Determines whether indexes are ignored or not.  If `False` (the default), index-columns will appear in the output, otherwise not.  (See [tutorials/ignore_index_and_replace_na.md](https://github.com/Bergvca/string_grouper/blob/master/tutorials/ignore_index_and_replace_na.md) for a demonstration.)
    * **`replace_na`**: For function `match_most_similar`, determines whether `NaN` values in index-columns are replaced or not by index-labels from `duplicates`. Defaults to `False`.  (See [tutorials/ignore_index_and_replace_na.md](https://github.com/Bergvca/string_grouper/blob/master/tutorials/ignore_index_and_replace_na.md) for a demonstration.)
-   * **`include_zeroes`**: When `min_similarity` ≤ 0, determines whether zero-similarity matches appear in the output.  Defaults to `True`.  (See [tutorials/zero_similarity.md](https://github.com/Bergvca/string_grouper/blob/master/tutorials/zero_similarity.md) for a demonstration.)  **Warning:** Make sure the kwarg `max_n_matches` is sufficiently high to capture ***all*** nonzero-similarity-matches, otherwise some zero-similarity-matches returned will be false.
-   * **`suppress_warning`**: when `min_similarity` ≤ 0 and `include_zeroes`  is `True`, determines whether or not to suppress the message warning that `max_n_matches` may be too small.  Defaults to `False`.
+   * **`include_zeroes`**: When `min_similarity` ≤ 0, determines whether zero-similarity matches appear in the output.  Defaults to `True`.  (See [tutorials/zero_similarity.md](https://github.com/Bergvca/string_grouper/blob/master/tutorials/zero_similarity.md).)  **Note:** If `include_zeroes` is `True` and the kwarg `max_n_matches` is set then it must be sufficiently high to capture ***all*** nonzero-similarity-matches, otherwise an error is raised and `string_grouper` suggests an alternative value for `max_n_matches`.  To allow `string_grouper` to automatically use the appropriate value for `max_n_matches` then do not set this kwarg at all.
    * **`group_rep`**: For function `group_similar_strings`, determines how group-representatives are chosen.  Allowed values are `'centroid'` (the default) and `'first'`.  See [tutorials/group_representatives.md](https://github.com/Bergvca/string_grouper/blob/master/tutorials/group_representatives.md) for an explanation.
 
 ## Examples

setup.py

@@ -25,6 +25,6 @@
                       , 'scipy'
                       , 'scikit-learn'
                       , 'numpy'
-                      , 'sparse_dot_topn>=0.2.6'
+                      , 'sparse_dot_topn>=0.3.1'
                       ]
 )