Since DEVONthink is my primary knowledge-management and repository tool on the macOS desktop, I constantly work with mechanisms for efficiently getting data into and out of it. I previously wrote about using Hazel and DEVONthink together. This post extends those ideas about and looks into options for preprocessing documents in Hazel before importing into DEVONthink as a way of sidestepping some of the limitations of Smart Rules in the latter. I’m going to work from a particular use-case to illustrate some of the options.
Following up on my recent article on cleaning up Zettelkasten WikiLinks in DEVONthink, here’s another script to solve the problem of linking notes. Backing up to the problem. In the Zettelkasten (or archive) - Zettel (or notes) are stored as list of Markdown files. But what happens when I want to add a link to another note into one that I’m writing? Since DEVONthink recognizes WikiLinks, I can just start typing but then I have to remember the exact date so that I can pick the item out of the contextual list that DEVONthink offers as links.
Organizing and reorganizing knowledge is one my seemingly endless tasks. For years, I’ve used DEVONthink as my primary knowledge repository. Recently, though I began to lament the fact that while I seemed to be collecting and storing knowledge in a raw form in DEVONthink, that I wasn’t really processing and engaging with it intellectually.1 In other words, I found myself collecting content but not really synthesizing, personalizing and using it. While researching note-taking systems in the search for a better way to process and absord the information I had been collecting, I discovered the Zettelkasten method.
The AppleScript Safari API is apparently quite finicky and rejects Russian Cyrillic characters when loading URLs. For example, the following URL https://en.wiktionary.org/wiki/стоять#Russian throws an error in AppleScript. Instead, Safari requires URL’s of the form https://en.wiktionary.org/wiki/%D1%81%D1%82%D0%BE%D1%8F%D1%82%D1%8C#Russian whereas Chrome happily consumes whatever comes along. So, we just need to encode the URL thusly: use framework "Foundation" -- encode Cyrillic test as "%D0" type strings on urlEncode(input) tell current application's NSString to set rawUrl to stringWithString_(input) -- 4 is NSUTF8StringEncoding set theEncodedURL to rawUrl's stringByAddingPercentEscapesUsingEncoding:4 return theEncodedURL as Unicode text end urlEncode When researching Russian words for vocabulary study, I use the URL encoding handler to load the appropriate words into several reference sites in sequential Safari tabs.
This is an update to my previous post on automating iTunes on macOS to support chorus repetition practice. You can read the original post for the theory behind the idea; but in short, one way of developing prosody and quality pronunciation in a foreign language is to do mass repetitions in chorus with a recording of a native speaker. Because in macOS 10.15, iTunes is no more, I’ve updated the script to work with the new Music app.
macOS offers a variety of virtual keyboard layouts which are accessible through System Preferences > Keyboard > Input Sources. Because I spend about half of my time writing in Russian and half in English, rapid switching between keyboard layouts is important. Optionally in the Input Sources preference pane, you can choose to use the Caps lock key to toggle between sources. This almost always works well with the exception of Anki.
In Anki 2.1, it’s practically impossible to get plain text from the web into note fields. A solution (on macOS, at least)…
An AppleScript to create year and month groups in DEVONthink
Using AppleScript to automate chorus repetition practice
For the last two years, I’ve been working through a 10,000 word Russian vocabulary ordered by frequency. I have a goal of finishing the list before the end of 2019. This requires not only stubborn persistence but an efficient process of collecting the information that goes onto my Anki flash cards. My manual process has been to work from a Numbers spreadsheet. As I collect information about each word from several websites, I log it in this table.