Metadata-Version: 2.1
Name: python-terrier
Version: 0.2.4
Summary: Terrier IR Python API
Home-page: https://github.com/A-Tsolov/Pyterrier
Author: A-Tsolov
Author-email: tsolov.aleksandar@gmail.com
License: UNKNOWN
Description: # Pyterrier
        
        ## Terrier Python API
        
        # Installation
        
        pip install python-terrier
        
        ### Windows
        
        ### Linux
        
        ### Colab notebooks
        
        # Indexing
        
        ### Indexing TREC formatted collections
        ```
        index_path = "/home/alex/Documents/index"
        path = "/home/alex/Downloads/books/doc-text.trec"
        index_path = createTRECIndex(index_path, path)
        ```
        
        ### Indexing text files
        
        ### Indexing a pandas dataframe
        
        Firstly, lets create an example dataframe
        
        ```
        df = pd.DataFrame({'docno':  ['1', '2', '3'],
                'url': ['url1', 'url2', 'url3'],
                 'text' : ['He ran out of money, so he had to stop playing',
                  'The waves were crashing on the shore; it was a',
                  'The body may perhaps compensates for the loss']
                })
        ```
        
        Then there are a number of options to index that dataframe:
        ```
        index = createDFIndex(index_path, df["text"])
        index = createDFIndex(index_path, df["text"], df["docno"])
        index = createDFIndex(index_path, df["text"], df["docno"], df["url"])
        index = createDFIndex(index_path, df["text"], df)
        index = createDFIndex(index_path, df["text"], docno=["1","2","3"])
        meta_fields={"docno":["1","2","3"],"url":["url1", "url2", "url3"]}
        index = createDFIndex(index_path, df["text"], **meta_fields)
        ```
        
        # Retrieval
        
        # Evaluation
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
