Metadata-Version: 2.1
Name: grub
Version: 0.0.8
Summary: A ridiculously simple search engine
Home-page: https://github.com/thorwhalen/grub
Author: Thor Whalen
License: mit
Description: 
        # grub
        A ridiculously simple search engine
        
        
        # Example: Search code
        
        
        ```python
        from grub import SearchStore
        ```
        
        
        ```python
        import sklearn  # instead of talking any file, let's search the files of sklearn itself!
        
        path_format = os.path.dirname(sklearn.__file__) + '{}.py'
        search = SearchStore(path_format)
        ```
        
        Let's search for ANN. That stands for Artificial Neural Networks. Did you know? Well search figures it out, pretty early, that I was talking about neural networks.
        
        
        ```python
        search('ANN')  
        ```
        
        
        
        
            array(['sklearn/tree/_export.py', 'sklearn/linear_model/_least_angle.py',
                   'sklearn/feature_selection/_base.py',
                   'sklearn/feature_selection/tests/test_variance_threshold.py',
                   'sklearn/neural_network/tests/test_stochastic_optimizers.py',
                   'sklearn/neural_network/__init__.py',
                   'sklearn/neural_network/_stochastic_optimizers.py',
                   'sklearn/neural_network/_multilayer_perceptron.py',
                   'sklearn/neural_network/rbm.py',
                   'sklearn/neural_network/tests/test_rbm.py'], dtype='<U75')
        
        Let's search for something more complicated. Like a sentence. 
        The results show promise promises: It's about calibration, but related are robustness, feature selection and validation...
        
        ```python
        search('how to calibrate the estimates of my classifier')  
        ```
        
        
        
        
            array(['sklearn/covariance/_robust_covariance.py',
                   'sklearn/svm/_classes.py',
                   'sklearn/covariance/_elliptic_envelope.py',
                   'sklearn/neighbors/_lof.py', 'sklearn/ensemble/_iforest.py',
                   'sklearn/feature_selection/_rfe.py', 'sklearn/calibration.py',
                   'sklearn/model_selection/_validation.py',
                   'sklearn/ensemble/_forest.py', 'sklearn/ensemble/_gb.py'],
                  dtype='<U75')
        
Platform: any
Description-Content-Type: text/markdown
