Added add_keywords_from_file_dict function

.coveragerc

@@ -1,2 +1,4 @@
 [run]
-omit = test/*
+omit = 
+    test/*
+    setup.py

README.rst

@@ -67,6 +67,24 @@ Case Sensitive example
     >>> keywords_found
     >>> # ['Bay Area']
 
+Span of keywords extracted
+    >>> from flashtext import KeywordProcessor
+    >>> keyword_processor = KeywordProcessor()
+    >>> keyword_processor.add_keyword('Big Apple', 'New York')
+    >>> keyword_processor.add_keyword('Bay Area')
+    >>> keywords_found = keyword_processor.extract_keywords('I love big Apple and Bay Area.', span_info=True)
+    >>> keywords_found
+    >>> # [('New York', 7, 16), ('Bay Area', 21, 29)]
+
+Get Extra information with keywords extracted
+    >>> from flashtext import KeywordProcessor
+    >>> kp = KeywordProcessor()
+    >>> kp.add_keyword('Taj Mahal', ('Monument', 'Taj Mahal'))
+    >>> kp.add_keyword('Delhi', ('Location', 'Delhi'))
+    >>> kp.extract_keywords('Taj Mahal is in Delhi.')
+    >>> # [('Monument', 'Taj Mahal'), ('Location', 'Delhi')]
+    >>> # NOTE: replace_keywords feature won't work with this.
+
 No clean name for Keywords
     >>> from flashtext import KeywordProcessor
     >>> keyword_processor = KeywordProcessor()
@@ -134,9 +152,9 @@ Get all keywords in dictionary
     >>> from flashtext import KeywordProcessor
     >>> keyword_processor = KeywordProcessor()
     >>> keyword_processor.add_keyword('j2ee', 'Java')
-    >>> keyword_processor.add_keyword('onGoing', 'rendom')
+    >>> keyword_processor.add_keyword('colour', 'color')
     >>> keyword_processor.get_all_keywords()
-    >>> # output: {'j2ee': 'Java', 'ongoing': 'rendom'}
+    >>> # output: {'colour': 'color', 'j2ee': 'Java'}
 
 For detecting Word Boundary currently any character other than this `\\w` `[A-Za-z0-9_]` is considered a word boundary.
 
@@ -199,11 +217,27 @@ The idea for this library came from the following `StackOverflow question
 <https://stackoverflow.com/questions/44178449/regex-replace-is-taking-time-for-millions-of-documents-how-to-make-it-faster>`_.
 
 
-References
+Citation
 ----------
 
 The original paper published on `FlashText algorithm <https://arxiv.org/abs/1711.00046>`_.
 
+::
+
+    @ARTICLE{2017arXiv171100046S,
+       author = {{Singh}, V.},
+        title = "{Replace or Retrieve Keywords In Documents at Scale}",
+      journal = {ArXiv e-prints},
+    archivePrefix = "arXiv",
+       eprint = {1711.00046},
+     primaryClass = "cs.DS",
+     keywords = {Computer Science - Data Structures and Algorithms},
+         year = 2017,
+        month = oct,
+       adsurl = {http://adsabs.harvard.edu/abs/2017arXiv171100046S},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+    }
+
 The article published on `Medium freeCodeCamp <https://medium.freecodecamp.org/regex-was-taking-5-days-flashtext-does-it-in-15-minutes-55f04411025f>`_.
 
 

docs/index.rst

@@ -64,6 +64,24 @@ Case Sensitive example
     >>> keywords_found
     >>> # ['Bay Area']
 
+Span of keywords extracted
+    >>> from flashtext import KeywordProcessor
+    >>> keyword_processor = KeywordProcessor()
+    >>> keyword_processor.add_keyword('Big Apple', 'New York')
+    >>> keyword_processor.add_keyword('Bay Area')
+    >>> keywords_found = keyword_processor.extract_keywords('I love big Apple and Bay Area.', span_info=True)
+    >>> keywords_found
+    >>> # [('New York', 7, 16), ('Bay Area', 21, 29)]
+
+Get Extra information with keywords extracted
+    >>> from flashtext import KeywordProcessor
+    >>> kp = KeywordProcessor()
+    >>> kp.add_keyword('Taj Mahal', ('Monument', 'Taj Mahal'))
+    >>> kp.add_keyword('Delhi', ('Location', 'Delhi'))
+    >>> kp.extract_keywords('Taj Mahal is in Delhi.')
+    >>> # [('Monument', 'Taj Mahal'), ('Location', 'Delhi')]
+    >>> # NOTE: replace_keywords feature won't work with this.
+
 No clean name for Keywords
     >>> from flashtext import KeywordProcessor
     >>> keyword_processor = KeywordProcessor()
@@ -131,9 +149,9 @@ Get all keywords in dictionary
     >>> from flashtext import KeywordProcessor
     >>> keyword_processor = KeywordProcessor()
     >>> keyword_processor.add_keyword('j2ee', 'Java')
-    >>> keyword_processor.add_keyword('onGoing', 'rendom')
+    >>> keyword_processor.add_keyword('colour', 'color')
     >>> keyword_processor.get_all_keywords()
-    >>> # output: {'j2ee': 'Java', 'ongoing': 'rendom'}
+    >>> # output: {'colour': 'color', 'j2ee': 'Java'}
 
 For detecting Word Boundary currently any character other than this `\\w` `[A-Za-z0-9_]` is considered a word boundary.
 
@@ -207,11 +225,27 @@ The idea for this library came from the following `StackOverflow question
 <https://stackoverflow.com/questions/44178449/regex-replace-is-taking-time-for-millions-of-documents-how-to-make-it-faster>`_.
 
 
-References
+Citation
 ----------
 
 The original paper published on `FlashText algorithm <https://arxiv.org/abs/1711.00046>`_.
 
+::
+
+    @ARTICLE{2017arXiv171100046S,
+       author = {{Singh}, V.},
+        title = "{Replace or Retrieve Keywords In Documents at Scale}",
+      journal = {ArXiv e-prints},
+    archivePrefix = "arXiv",
+       eprint = {1711.00046},
+     primaryClass = "cs.DS",
+     keywords = {Computer Science - Data Structures and Algorithms},
+         year = 2017,
+        month = oct,
+       adsurl = {http://adsabs.harvard.edu/abs/2017arXiv171100046S},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+    }
+
 The article published on `Medium freeCodeCamp <https://medium.freecodecamp.org/regex-was-taking-5-days-flashtext-does-it-in-15-minutes-55f04411025f>`_.