Bug 1923364 - Add topic guides for app-services, r=nanj,markh DONTBUILD

Bug 1923364 - cleanup extensions, r=nanj

Bug 1923364 - Adding tabs to lint, r=nanj

Bug 1923364 - Ignore tabs linting, r=nanj

Bug 1923364 - Restructure and combine rust components, r=nanj

Bug 1923364 - Replace rst with MyST markdown, r=nanj

Bug 1923364 - PR review fixes, r=nanj

Differential Revision: https://phabricator.services.mozilla.com/D224949
This commit is contained in:
Bastian Gruber 2024-10-09 23:24:17 +00:00
parent 280ba92800
commit b7941358f4
10 changed files with 268 additions and 1 deletions

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@ -39,6 +39,7 @@ categories:
- accessible
- code-quality
- writing-rust-code
- rust-components
- tools/profiler
- performance
- storage

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@ -0,0 +1,10 @@
# Rust Components
This section is meant to make it easier to use and implement cross-platform components written in Rust.
```{toctree}
:titlesonly:
:maxdepth: 2
Topic Guides <topic-guides/index>
uniffi

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# Topic Guides
Here are the guides on various topics related to Rust components.
```{toctree}
:titlesonly:
:maxdepth: 1
:glob:
*

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---
myst:
enable_extensions: ["colon_fence"]
---
# Relevancy
The `relevancy` component tracks the user's interests locally, without sharing any data over the network. The component currently supports building an interest vector based on the URLs they visit.
## Setting up the store
To use the `RelevancyStore` in either Kotlin or Swift, you need to import the relevant classes and data types from the `MozillaAppServices` library.
:::{tab-set-code}
:sync-group: language
```kotlin
import mozilla.appservices.relevancy.RelevancyStore
import mozilla.appservices.relevancy.InterestVector
val store = RelevancyStore(dbPath)
```
```swift
import MozillaAppServices
let store = RelevancyStore(dbPath: "path/to/database")
```
:::
To work with the RelevancyStore, you need to create an instance using a database path where the users interest data will be stored:
:::{tab-set-code}
:sync-group: language
```kotlin
val store = RelevancyStore(dbPath)
```
```swift
let store = RelevancyStore(dbPath: "path/to/database")
```
:::
* `dbPath`: This is the path to the SQLite database where the relevancy data is stored. The initialization is non-blocking, and the database is opened lazily.
## Ingesting relevancy data
To build the user's interest vector, call the `ingest` function with a list of URLs ranked by frequency. This method downloads the interest data, classifies the user's top URLs, and builds the interest vector. This process may take time and should only be called from a worker thread.
### Example usage of `ingest`:
:::{tab-set-code}
:sync-group: language
```kotlin
val topUrlsByFrequency = listOf("https://example.com", "https://another-example.com")
val interestVector = store.ingest(topUrlsByFrequency)
```
```swift
let topUrlsByFrequency = ["https://example.com", "https://another-example.com"]
let interestVector = store.ingest(topUrlsByFrequency)
```
:::
* `topUrlsByFrequency`: A list of URLs ranked by how often and recently the user has visited them. This data is used to build the user's interest vector.
* The `ingest` function returns an `InterestVector`, which contains the user's interest levels for different tracked categories.

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---
myst:
enable_extensions: ["colon_fence"]
---
# Suggest
The API for the `SuggestStore` can be found in the [MozillaComponents Kotlin documentation](https://mozilla.github.io/application-services/kotlin/kotlin-components-docs/mozilla.appservices.suggest/-suggest-store/index.html).
```{note}
Make sure you initialize {doc}`viaduct` for this component.
```
```{warning}
The `SuggestStore` is synchronous, which means it needs to be wrapped in the asynchronous primitive of the target language you are using.
```
## Setting up the store
You need to import one or more of the following primitives to work with the `SuggestStore` (these come from the generated `suggest.kt` file, produced by `uniffi`):
:::{tab-set-code}
:sync-group: language
```kotlin
import mozilla.appservices.remotesettings.RemoteSettingsServer
import mozilla.appservices.suggest.SuggestApiException
import mozilla.appservices.suggest.SuggestIngestionConstraints
import mozilla.appservices.suggest.SuggestStore
import mozilla.appservices.suggest.SuggestStoreBuilder
import mozilla.appservices.suggest.Suggestion
import mozilla.appservices.suggest.SuggestionQuery
```
```swift
import MozillaAppServices
```
:::
Create a `SuggestStore` as a singleton. You do this via the `SuggestStoreBuilder`, which returns a `SuggestStore`. No I/O or network requests are performed during construction, which makes this safe to do at any point in the application startup:
:::{tab-set-code}
:sync-group: language
```kotlin
internal val store: SuggestStore = {
SuggestStoreBuilder()
.dataPath(context.getDatabasePath(DATABASE_NAME).absolutePath)
.remoteSettingsServer(remoteSettingsServer)
.build()
```
```swift
let store: SuggestStore = {
let storeBuilder = SuggestStoreBuilder()
storeBuilder.dataPath(context.getDatabasePath(DATABASE_NAME).absolutePath)
storeBuilder.remoteSettingsServer(remoteSettingsServer)
return storeBuilder.build()
}
```
:::
* You need to set the `dataPath`, which is the path (the SQLite location) where you store your suggestions.
* The `remoteSettingsServer` is only needed if you want to set the server to anything else but `prod`. If so, you pass a `RemoteSettingsServer` object.
## Ingesting suggestions
Ingesting suggestions happens in two different ways: On startup, and then, periodically, in the background.
* `SuggestIngestionConstraints` is used to control what gets ingested.
* Use the `providers` field to limit ingestion by provider type.
* Use the `providerConstraints` field to add additional constraints, currently this is only used for exposure suggestions.
### On Start Up
Ingest with `SuggestIngestionConstraints(emptyOnly=true)` shortly after each startup. This ensures we have something in the DB on the first run and also after upgrades where we often will clear the DB to start from scratch.
:::{tab-set-code}
:sync-group: language
```kotlin
store.value.ingest(SuggestIngestionConstraints(
emptyOnly = true,
providers = listOf(SuggestionProvider.AMP_MOBILE, SuggestionProvider.WIKIPEDIA, SuggestionProvider.WEATHER)
))
```
```swift
store.value.ingest(SuggestIngestionConstraints(
emptyOnly: true,
providers: [.AMP_MOBILE, .WIKIPEDIA, .WEATHER]
))
```
:::
### Periodically
Ingest with `SuggestIngestionConstraints(emptyOnly=false)` on a regular schedule (like once a day).
:::{tab-set-code}
:sync-group: language
```kotlin
store.value.ingest(SuggestIngestionConstraints(emptyOnly = false))
```
```swift
store.value.ingest(SuggestIngestionConstraints(emptyOnly: false))
```
:::
## Querying Suggestions
Call `SuggestStore::query` to fetch suggestions for the suggest bar. The `providers` parameter should be the same value that got passed to `ingest()`.
:::{tab-set-code}
:sync-group: language
```kotlin
store.value.query(
SuggestionQuery(
keyword = text,
providers = listOf(SuggestionProvider.AMP_MOBILE, SuggestionProvider.WIKIPEDIA, SuggestionProvider.WEATHER),
limit = MAX_NUM_OF_FIREFOX_SUGGESTIONS,
),
)
```
```swift
store.value.query(
SuggestionQuery(
keyword: text,
providers: [.AMP_MOBILE, .WIKIPEDIA, .WEATHER],
limit: MAX_NUM_OF_FIREFOX_SUGGESTIONS
)
)
```
:::
## Interrupt querying
Call `SuggestStore::Interrupt` with `InterruptKind::Read` to interrupt any in-progress queries when the user cancels a query and before running the next query.
:::{tab-set-code}
:sync-group: language
```kotlin
store.value.interrupt()
```
```swift
store.value.interrupt()
```
:::
## Shutdown the store
On shutdown, call `SuggestStore::Interrupt` with `InterruptKind::ReadWrite` to interrupt any in-progress ingestion and queries.
:::{tab-set-code}
:sync-group: language
```kotlin
store.value.interrupt()
```
```swift
store.value.interrupt()
```
:::

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# Viaduct
`Viaduct` initialization is required for all platforms and for multiple components. The [README](https://github.com/mozilla/application-services/blob/main/components/viaduct/README.md) explains the component in more detail.
There are 3 different options to use `viaduct`:
* Any `libxul` based can ignore initialization, since it's handled by `libxul`.
* Using the reqwest backend, which uses the `reqwest` library and a `reqwest`-managed thread.
* Implementing the C FFI like `libxul` does (https://searchfox.org/mozilla-central/source/toolkit/components/viaduct).

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@ -197,6 +197,8 @@ SPHINX_TREES["testing-rust-code"] = "docs/testing-rust-code"
SPHINX_TREES["writing-rust-code"] = "docs/writing-rust-code"
SPHINX_TREES["rust-components"] = "docs/rust-components"
SPHINX_TREES["bug-mgmt"] = "docs/bug-mgmt"
SPHINX_TREES["glossary"] = "docs/glossary"

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@ -9,6 +9,7 @@ pypi:myst-parser==2.0
pypi:sphinx-copybutton==0.5.2
pypi:sphinx-design==0.5.0
pypi:sphinx-js==3.2.2
pypi:sphinx-tabs==3.4.7
pypi:sphinx-markdown-tables==0.0.17
pypi:sphinx-rtd-theme==2.0.0
pypi:sphinxcontrib-mermaid==0.9.2

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@ -1,5 +1,5 @@
#
# This file is autogenerated by pip-compile with Python 3.11
# This file is autogenerated by pip-compile with Python 3.12
# by the following command:
#
# pip-compile --generate-hashes --output-file=tools/lint/rst/requirements.txt ./tools/lint/rst/requirements.in