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Pierre Carbonnelle committed be6b505

add description to README.txt

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+pyDatalog adds the logic programming paradigm to python's toolbox, in a pythonic way.  
+You can now run logic queries on databases or python objects, and use logic clauses to define python classes.
+
+Datalog is a truly declarative subset of prolog that is best at
+
+* managing large sets of related information (e.g. in data integration or the semantic web).  
+* simulating intelligent behavior (e.g. in games), 
+* performing recursive algorithms (e.g. in network protocol, code and graph analysis)
+* solving discrete constraint problems. 
+
+In particular, pyDatalog can be used for object-relational mapping: 
+
+* it can perform multi-database queries (from memory datastore,  relational databases, and noSQL database with appropriate connectors)
+* it is more expressive than SQL, with a cleaner syntax; 
+* it facilitates re-use of SQL code snippet (e.g. for frequent joins or formula); 
+* it offloads the database server by performing joins on the application tier. 
+
+Datalog excels at accelerated development : Datalog programs are often shorter than their python equivalent, 
+and Datalog statements can be specified in any order, as simply as formula in a spreadsheet.
+
 See pyDatalog's home page : https://bitbucket.org/pcarbonn/pydatalog/wiki/Home
 * managing large sets of related information (e.g. in data integration or the semantic web).  
 * simulating intelligent behavior (e.g. in games), 
 * performing recursive algorithms (e.g. in network protocol, code and graph analysis)
-* at solving discrete constraint problems. 
+* solving discrete constraint problems. 
 
 In particular, pyDatalog can be used for object-relational mapping: