- Elasticsearch – Analyzers and Text Analysis
Almost every “why does my search return nothing?” is one bug: the analyzer that ran when the document was indexed and the analyzer that ran on the query disagreed, so the terms never matched. What an analyzer is made of, the _analyze API that shows you the tokens instead of making you guess, building a custom one, and the two classic traps — keyword fields are not analysed at all, and changing an analyzer does nothing to documents already indexed.
- HTML Introduction
HTML is the standard markup language for creating Web pages. It is the most widely used language on the web. A markup language uses sets of markup tags to characterize text elements within a document, which gives instructions to the web browsers on how the document should appear. Originally, HTML…
- Testing
Resources https://flask.palletsprojects.com/en/1.1.x/testing/
- Postgres – Schema Migrations Without Downtime
The DDL that takes a lock long enough to be an outage, and the version of the same change that does not. Adding a column with a default, adding NOT NULL in two steps with a validated CHECK, CREATE INDEX CONCURRENTLY and the invalid index it can leave behind, renaming a column across two deploys, and lock_timeout — the one setting that turns a migration from an outage into a retry.
- Elasticsearch – The Field Types That Matter
Not a catalogue. The eight or so types a real project actually needs and the decisions behind them: text versus keyword and why that one distinction causes most beginner confusion, scaled_float for money, date and what it accepts, boolean, geo_point, and object versus nested — including the array-flattening behaviour that makes nested necessary and is invisible until it returns a wrong result.