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|README||updated assumtions and TODO list|
Convert SplashID DB into keepassX (keepassx.org) and keePass (keepass.info) These python scripts can be used to migrate account database from SplashID software into either keePassX or keePass. They confusingly have identical names and share UI resemblance, but these are two differnt programs. keePassX is mostly used on Linux, while keePass dominates MS Windows, iOS and Android share. The scripts will take SplashID exported database (in native VID format) and convert it into keePassX or keePass XML files, that later can be imported to one of the program. ASSUMPTION: * keePassX <Last Access> and <Last Modified> time stamp filled with a date and time of conversion * SplashID <Description> and <Category> fields merge into keePassX <title> * SplashID <Type> is convert into keepass/X <subgroup> * All SplashID fields that do not match fixed keePassX ones, added to the keePassX <comments> * All SplashID fields that do not match fixed keePass ones, added to the keePass <notes> * SplashID Creation Date is expected in the following format <November 28, 2009> * Imported data saved in unicode utf-8 format * During SplashID VID file import, some correction is performed in case mismatch found it T and F fields TODO: * If SplashID has no username, check <comment> section for <account> data to substitute * Unicoded is implemented for keePass, push it to keePassX as well. ================= From SplashID website: You may also import and export SplashID records in CSV format. CSV stands for Comma Separated Values, and is a common file format readable by most spreadsheets, databases and word processors. If you wish to import a CSV file, the data must be in the following format: Type, Field 1, Field 2, Field 3, Field 4, Field 5, Field 6, Field 7, Field 8, Field 9, Date Modified, Notes, Category It is easy to create the above format in Excel by creating a spreadsheet with 13 columns (as designated above) with one record per row. Then save the splashid_export_f in CSV format. Note: When importing data, if the type field is blank the record will be placed in Unfiled. If there is a type name and it does not match an existing type a new type will be created.