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This post is a followup to an older dicsussion [on recordmanaging]( I am writing this to share with colleagues, so it may be a bit fluffy and not straight to the point. I apologize to all the experts. Good programs always start by managing data in a flexible and robust manner. Python has great builtin container datatypes (lists, tuples, dictionaries), but often, we need to go beyond these and create flexible data handlers which are custom-fitted to our analysis. To this end, the programmer really does become an architect, and a myriad of possible approaches are applicable. This is a …

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This code was inspired after several discussions on the forum, and I'm especially indebted to PyTony for all of his help with these aspects. The motivation behind this code is quite simple. I wanted a robust, light and general way of storing CSV data that could be used over and over again and had to have the following properties: The user sets fields and defaults values, and then field typecasting was automatically employed. The data is stored in a regular, lightweight type (In this case a mutable namedtuple) The data is managed by a custom dictionary object. The MutableNamedTuple class …

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The End.