The Public Utility Data Liberation Project provides analysis-ready energy system data to climate advocates, researchers, policymakers, and journalists.
We now have a python module which downloads the original data and keeps it organized in the datastore directory. We need to go through the code and update everything that accesses the datastore to use that module, rather than using hard-coded paths. This will allow us to encapsulate the data access so that we can change it, and access it in a more standardized way going forward. This should also allow us to get rid of some of the values which are hard-coded in the settings module, on a data source by data source basis, and instead construct those paths based on the source, form, and year (and later for CEMS, month and state) of data being accessed.
We now have a python module which downloads the original data and keeps it organized in the datastore directory. We need to go through the code and update everything that accesses the datastore to use that module, rather than using hard-coded paths. This will allow us to encapsulate the data access so that we can change it, and access it in a more standardized way going forward. This should also allow us to get rid of some of the values which are hard-coded in the settings module, on a data source by data source basis, and instead construct those paths based on the source, form, and year (and later for CEMS, month and state) of data being accessed.