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Platform for economics/financial time series analysis. Focus on creating a high productivity environment. Platform maintenance in Python, but other languages can use the database.

This package is currently for my use, but at the minimum, code snippets could be used as examples.

Key selling point is dynamic loading: loading a series is not just a database access, rather Python determines whether it needs to download from an external provider, or return what is stocked in the local database. Although not implemented, there will be rules to allow for a sensible update strategy.

The dynamic nature allows for user-calculated series to be updated on the fly.

Architecture is built around “databases” and “providers”; each type of database or provider is loaded as an extension. This allows new data sources to be easily plugged into the framework.