Thanks to great tools written by other people, and succinct and readable documentation for the sqlite3 module, within hours I was looking at images from my filesystem, chosen by their digiKam tags, within a fresh local TiddlyWiki.
For this kind of code, reading data and outputting to text files, we don’t really need the flexibility and interactivity of Jupyter or a more conventional IDE, but I’d argue it’s more convenient. If there’s a library for Python to manipulate SQLite databases (which of course there is), then I can play with this in Jupyter Notebook. Then I had an epiphany, because Peter Teuben, in one super-simple Python script, opened his digiKam database and extracted information from it, just like that. I’m sure that would have worked too, but the bit about rewriting tens of thousands of files on my drive was not attractive. I actually thought about getting digiKam to overwrite all my JPEG files to incorporate their metadata, and then using ExifTool to read them. When I initially thought about trying to build a photo album using tags and other metadata that I’d curated in digiKam, the digikam4.db file had such a force field around it that I didn’t really think about extracting data from it. A script by Peter Teuben for accessing digiKam SQLite DB in Python (GitHub).
#Janetter sqlite mac#
digiKam downloads for Linux, Windows, and Mac ().
#Janetter sqlite software#
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