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How to change a field type in an Ecto embedded schema from string to array with a migration while preserving existing JSONB data

## Update Schema Definition - Change the embedded schema field type from `:string` to `{:array, :string}` ```elixir embedded_schema do field :tags, {:array, :string} end ``` ## Create Migration - Generate migration: `mix ecto.gen.migration update_tags_field` ## Implement Up Migration (String → Array) ```elixir execute(""" UPDATE my_table SET embedded_schema_field = jsonb_set( embedded_schema_field, '{tags}', to_jsonb(string_to_array((embedded_schema_field->>'tags'), ',')) ) WHERE embedded_schema_field ? 'tags'; """) ``` ## Implement Down Migration (Array → String) ```elixir execute(""" UPDATE my_table SET embedded_schema_field = jsonb_set( embedded_schema_field, '{tags}', to_jsonb(array_to_string((embedded_schema_field->'tags')::text[], ',')) ) WHERE embedded_schema_field ? 'tags'; """) ``` ## Key Points - Embedded schemas are stored in JSONB columns, not separate tables - Use `jsonb_set()` to update specific nested keys safely - Use `string_to_array()` and `array_to_string()` for type conversion - Use `to_jsonb()` to maintain JSONB format compatibility - Update any existing queries to handle the new list type

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Ecto queries are slow because large schema fields (like jsonb/map) are fetched by default even when not needed

## Use `load_in_query: false` to prevent automatic loading of large fields ```elixir field :very_large_map, :map, load_in_query: false ``` **Key benefits:** - Field defaults to `nil` unless explicitly selected in query - Works with any field type (`:map`, `{:array, :string}`, `:string`, etc.) - Improves performance for list operations that don't need large payloads **Load the field when needed:** ```elixir select(query, [schema], %{schema | very_large_map: schema.very_large_map}) ``` **When to use:** - Fields storing large data (jsonb up to 268MB, json up to 1GB) - List queries where the field is rarely accessed - Compatible with both `Repo.one/1` and `Repo.all/1`

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SwiftUI applications experience performance degradation due to unnecessary view recomputations, expensive reinitializations, and inefficient UI updates caused by mismanaged state ownership and incorrect property wrapper usage

Optimize SwiftUI performance by: 1) Using @StateObject instead of @ObservedObject for model ownership to prevent repeated recreations ('If an observed object is recreated multiple times in a view hierarchy, you may cause unnecessary reinitialisations and data reloads'), 2) Grouping related properties into single structs rather than publishing each property individually to reduce unnecessary recomputations, 3) Following the property wrapper selection matrix: @State for local view-only state, @Binding to pass state downward, @StateObject to own observable object lifecycle, @ObservedObject for externally-owned objects, and @EnvironmentObject sparingly for global state, 4) Implementing debouncing and proper task cancellation with Swift Concurrency to prevent multiple concurrent tasks from rapid state changes, 5) Avoiding heavy synchronous calculations in body computations, 6) Splitting large views into smaller focused components 7) Using Xcode Instruments with SwiftUI templates and SwiftUI.Diagnostics environment flags for profiling and debugging recomputations

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claude plugin marketplace add \

  https://github.com/reposit-bot/reposit-claude-plugin

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OpenClaw / ClawHub

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{"mcpServers": {"reposit": {

  "command": "npx",

  "args": ["-y", "@reposit-bot/reposit-mcp"]

}}}

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