semvec/pypi-packages huggingface dataset:
datasette-copy-to-memory 0.2
Copy database files into an in-memory database on startup
License: Apache License, Version 2.0
Requires Python: >=3.7

# datasette-copy-to-memory

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Copy database files into an in-memory database on startup

This plugin is **highly experimental**. It currently exists to support Datasette performance research, and is not designed for actual production usage.

## Installation

Install this plugin in the same environment as Datasette.

    datasette install datasette-copy-to-memory

## Usage

On startup, Datasette will create an in-memory named database for each attached database. This database will have the same name but with `_memory` at the end.

So running this:

    datasette fixtures.db

Will serve two databases: the original at `/fixtures` and the in-memory copy at `/fixtures_memory`.

## Demo

A demo is running on [latest-with-plugins.datasette.io](https://latest-with-plugins.datasette.io/) - the [/fixtures_memory](https://latest-with-plugins.datasette.io/fixtures_memory) table there is provided by this plugin.

## Configuration

By default every attached database file will be loaded into a `_memory` copy.

You can use plugin configuration to specify just a subset of the database. For example, to create `github_memory` but not `fixtures_memory` you would use the following `metadata.yml` file:

```yaml
plugins:
  datasette-copy-to-memory:
    databases:
    - github
```
Then start Datasette like this:

    datasette github.db fixtures.db -m metadata.yml

If you don't want to have a `fixtures` and `fixtures_memory` database, you can use `replace: true` to have the plugin replace the file-backed database with the new in-memory one, reusing the same database name:

```yaml
plugins:
  datasette-copy-to-memory:
    replace: true
```
Then:

    datasette github.db fixtures.db -m metadata.yml

This will result in both `/github` and `/fixtures` but no `/github_memory` or `/fixtures_memory`.

## Development

To set up this plugin locally, first checkout the code. Then create a new virtual environment:

    cd datasette-copy-to-memory
    python3 -m venv venv
    source venv/bin/activate

Now install the dependencies and test dependencies:

    pip install -e '.[test]'

To run the tests:

    pytest