Fix word name collision, add two new user-related features
continuous-integration/drone/push Build is passing Details

This commit changes the primary key of words to a serial number. That
way, two words with the same normalized value will not collide with
one another.

It also adds two new tables in the database:
- Users following languages
- Users learning words

The former can represent two stages of learning a word:
- Either the user is currently learning it
- Or they consider they know it and don’t need to work on it anymore

These two new tables now have their API query available through the
GraphQL API.

This commit also fixes the issue of word-related tables and types not
being dropped when resetting the database.
This commit is contained in:
Lucien Cartier-Tilet 2023-01-18 10:26:45 +01:00
parent b5dfdee453
commit c5f5e770e2
Signed by: phundrak
GPG Key ID: BD7789E705CB8DCA
10 changed files with 227 additions and 39 deletions

View File

@ -1,4 +1,5 @@
-- This file should undo anything in `up.sql`
DROP TABLE UserFollowLanguage;
DROP TABLE LangAndAgents;
DROP TABLE LangTranslatesTo;
DROP TABLE Languages;

View File

@ -51,3 +51,17 @@ CREATE TABLE LangAndAgents (
NOT NULL,
relationship AgentLanguageRelation NOT NULL
);
CREATE TABLE UserFollowLanguage (
id SERIAL PRIMARY KEY,
lang UUID
REFERENCES Languages(id)
ON UPDATE CASCADE
ON DELETE CASCADE
NOT NULL,
userid VARCHAR(31)
REFERENCES Users(id)
ON UPDATE CASCADE
ON DELETE CASCADE
NOT NULL
);

View File

@ -1 +1,7 @@
-- This file should undo anything in `up.sql`
-- This file should undo anything in `up.sql`
DROP TABLE WordRelation;
DROP TABLE WordLearning;
DROP TABLE Words;
DROP TYPE WordLearningStatus;
DROP TYPE WordRelationship;
DROP TYPE PartOfSpeech;

View File

@ -1,12 +1,14 @@
-- Your SQL goes here
CREATE TYPE PartOfSpeech as ENUM ('ADJ', 'ADP', 'ADV', 'AUX', 'CCONJ', 'DET', 'INTJ', 'NOUN', 'NUM', 'PART', 'PRON', 'PROPN', 'PUNCT', 'SCONJ', 'SYM', 'VERB', 'X');
CREATE TYPE WordRelationship as ENUM('def', 'related');
CREATE TYPE WordLearningStatus as ENUM('learning', 'learned');
CREATE TABLE Words (
norm VARCHAR(255) PRIMARY KEY, -- normalized word
id UUID DEFAULT uuid_generate_v4 () PRIMARY KEY,
norm VARCHAR(255) NOT NULL, -- normalized word, generally in latin alphabet
native VARCHAR(255),
lemma VARCHAR(255)
REFERENCES Words(norm)
lemma UUID
REFERENCES Words(id)
ON UPDATE CASCADE
ON DELETE SET NULL,
language UUID
@ -26,15 +28,30 @@ CREATE TABLE Words (
CREATE TABLE WordRelation (
id SERIAL PRIMARY KEY,
wordsource VARCHAR(255)
REFERENCES Words(norm)
wordsource UUID
REFERENCES Words(id)
ON UPDATE CASCADE
ON DELETE CASCADE
NOT NULL,
wordtarget VARCHAR(255)
REFERENCES Words(norm)
wordtarget UUID
REFERENCES Words(id)
ON UPDATE CASCADE
ON DELETE CASCADE
NOT NULL,
relationship WordRelationship NOT NULL
);
CREATE TABLE WordLearning (
id SERIAL PRIMARY KEY,
word UUID
REFERENCES Words(id)
ON UPDATE CASCADE
ON DELETE CASCADE
NOT NULL,
userid VARCHAR(31)
REFERENCES Users(id)
ON UPDATE CASCADE
ON DELETE CASCADE
NOT NULL,
status WordLearningStatus DEFAULT 'learning' NOT NULL
);

View File

@ -219,7 +219,7 @@ impl Database {
}
}
pub fn word_id(&self, id: &str) -> Result<Option<Word>, DatabaseError> {
pub fn word_id(&self, id: uuid::Uuid) -> Result<Option<Word>, DatabaseError> {
use self::schema::words::dsl;
match dsl::words.find(id).first::<Word>(&mut self.conn()?) {
Ok(val) => Ok(Some(val)),

View File

@ -13,7 +13,7 @@ use super::users::User;
use std::convert::Into;
use schema::{langandagents, langtranslatesto, languages};
use schema::{langandagents, langtranslatesto, languages, userfollowlanguage};
#[derive(
diesel_derive_enum::DbEnum, Debug, Clone, PartialEq, Eq, GraphQLEnum,
@ -209,7 +209,7 @@ impl Language {
"Failed to retrieve owner {} of language {}: {e:?}",
self.owner, self.name
),
"Database reading error",
"Database error",
)
})?),
Err(e) => Err(DatabaseError::new(
@ -235,6 +235,42 @@ impl Language {
self.relationship(&context.db, AgentLanguageRelation::Publisher)
.map_err(Into::into)
}
#[graphql(description = "People following the language")]
fn followers(&self, context: &Context) -> FieldResult<Vec<User>> {
use schema::userfollowlanguage::dsl;
match &mut context.db.conn() {
Ok(conn) => {
Ok(dsl::userfollowlanguage
.filter(dsl::lang.eq(self.id))
.load::<UserFollowLanguage>(conn)
.map_err(|e| {
DatabaseError::new(format!("Failed to retrieve language followers for language {}: {e:?}", self.id),
"Database error")
})?
.into_iter()
.filter_map(|follow| {
use schema::users::dsl;
match dsl::users
.find(follow.userid.clone())
.first::<User>(conn) {
Ok(user) => Some(user),
Err(e) => {
info!("Failed to retrieve user {} from database: {e:?}", follow.userid);
None
}
}
})
.collect::<Vec<User>>()
)
}
Err(e) => Err(DatabaseError::new(
format!("Failed to connect to the database: {e:?}"),
"Database connection failure",
)
.into()),
}
}
}
#[derive(Queryable, Insertable, Debug, Clone, PartialEq, Eq)]
@ -253,3 +289,11 @@ pub struct LangTranslatesTo {
langfrom: Uuid,
langto: Uuid,
}
#[derive(Queryable, Insertable, Debug, Clone, PartialEq, Eq)]
#[diesel(table_name = userfollowlanguage)]
pub struct UserFollowLanguage {
id: i32,
lang: Uuid,
userid: String,
}

View File

@ -1,7 +1,12 @@
use super::super::schema::{userfollows, users};
use super::{
super::schema,
words::{Word, WordLearning, WordLearningStatus},
};
use diesel::prelude::*;
use juniper::FieldResult;
use tracing::debug;
use tracing::{debug, info};
use schema::{userfollows, users};
use crate::{db::DatabaseError, graphql::Context};
@ -33,8 +38,8 @@ impl User {
)
})?;
Ok(userfollows::dsl::userfollows
.filter(userfollows::dsl::follower.eq(self.id.clone()))
.load::<UserFollow>(conn)
.filter(userfollows::dsl::follower.eq(self.id.clone()))
.load::<UserFollow>(conn)
.map_err(|e| {
DatabaseError::new(
format!(
@ -62,6 +67,53 @@ impl User {
})
.collect::<Vec<User>>())
}
#[graphql(
description = "What words the user is learning or has learned",
arguments(status(
description = "Display either words being learned or words learned"
))
)]
pub fn words_learning(
&self,
context: &Context,
status: WordLearningStatus,
) -> FieldResult<Vec<Word>> {
use schema::wordlearning::dsl;
let conn = &mut context.db.conn().map_err(|e| {
DatabaseError::new(
format!("Failed to connect to database: {e:?}"),
"Database connection error",
)
})?;
Ok(dsl::wordlearning
.filter(dsl::userid.eq(self.id.clone()))
.filter(dsl::status.eq(status))
.load::<WordLearning>(conn)
.map_err(|e| {
DatabaseError::new(
format!(
"Failed to retrieve user follows from database: {e:?}"
),
"Database reading error",
)
})?
.iter()
.filter_map(|lang_learn| {
use schema::words::dsl;
match dsl::words.find(lang_learn.word).first::<Word>(conn) {
Ok(word) => Some(word),
Err(e) => {
info!(
"Failed to retrieve word {} from database: {e:?}",
lang_learn.word
);
None
}
}
})
.collect::<Vec<Word>>())
}
}
#[derive(Queryable, Insertable, Debug, Clone, PartialEq, Eq)]

View File

@ -5,8 +5,9 @@ use crate::{
};
use diesel::prelude::*;
use juniper::{FieldResult, GraphQLEnum};
use schema::{wordrelation, words};
use schema::{wordrelation, words, wordlearning};
use tracing::info;
use uuid::Uuid;
use std::convert::Into;
@ -19,6 +20,13 @@ pub enum WordRelationship {
Related,
}
#[derive(diesel_derive_enum::DbEnum, Debug, Clone, PartialEq, Eq, juniper::GraphQLEnum)]
#[DieselTypePath = "crate::db::schema::sql_types::Wordlearningstatus"]
pub enum WordLearningStatus {
Learning,
Learned
}
#[derive(
diesel_derive_enum::DbEnum, Debug, Clone, PartialEq, Eq, GraphQLEnum,
)]
@ -48,9 +56,10 @@ pub enum PartOfSpeech {
#[derive(Queryable, Insertable, Debug, Clone, PartialEq, Eq)]
pub struct Word {
id: Uuid,
norm: String,
native: Option<String>,
lemma: Option<String>,
lemma: Option<Uuid>,
language: uuid::Uuid,
partofspeech: PartOfSpeech,
audio: Option<String>,
@ -71,7 +80,7 @@ impl Word {
use schema::wordrelation::dsl;
match &mut db.conn() {
Ok(conn) => Ok(dsl::wordrelation
.filter(dsl::wordsource.eq(self.norm.clone()))
.filter(dsl::wordsource.eq(self.id))
.filter(dsl::relationship.eq(relationship))
.load::<WordRelation>(conn)
.map_err(|e| {
@ -81,9 +90,9 @@ impl Word {
)
})?
.into_iter()
.flat_map(|w| {
.flat_map(|word| {
use schema::words::dsl;
dsl::words.find(w.wordtarget).first::<Word>(conn)
dsl::words.find(word.wordtarget).first::<Word>(conn)
})
.collect::<Vec<Word>>()),
Err(e) => Err(DatabaseError::new(
@ -109,20 +118,18 @@ impl Word {
#[graphql(description = "Base form of the current word")]
fn lemma(&self, context: &Context) -> Option<Word> {
use schema::words::dsl;
match self.lemma.clone() {
match self.lemma {
Some(lemma) => match &mut context.db.conn() {
Ok(conn) => {
match dsl::words.find(lemma.clone()).first::<Word>(conn) {
Ok(word) => Some(word),
Err(e) => {
info!(
"Failed to retrieve lemma {} of word {}: {:?}",
lemma, self.norm, e
);
None
}
Ok(conn) => match dsl::words.find(lemma).first::<Word>(conn) {
Ok(word) => Some(word),
Err(e) => {
info!(
"Failed to retrieve lemma {} of word {}: {:?}",
lemma, self.norm, e
);
None
}
}
},
Err(e) => {
info!("Could not connect to the database: {:?}", e);
None
@ -211,7 +218,16 @@ impl Word {
#[diesel(table_name = wordrelation)]
pub struct WordRelation {
id: i32,
wordsource: String,
wordtarget: String,
wordsource: Uuid,
wordtarget: Uuid,
relationship: WordRelationship,
}
#[derive(Queryable, Insertable, Debug, Clone, PartialEq, Eq)]
#[diesel(table_name = wordlearning)]
pub struct WordLearning {
pub id: i32,
pub word: Uuid,
pub userid: String,
pub status: WordLearningStatus
}

View File

@ -17,6 +17,10 @@ pub mod sql_types {
#[diesel(postgres_type(name = "release"))]
pub struct Release;
#[derive(diesel::sql_types::SqlType)]
#[diesel(postgres_type(name = "wordlearningstatus"))]
pub struct Wordlearningstatus;
#[derive(diesel::sql_types::SqlType)]
#[diesel(postgres_type(name = "wordrelationship"))]
pub struct Wordrelationship;
@ -63,6 +67,14 @@ diesel::table! {
}
}
diesel::table! {
userfollowlanguage (id) {
id -> Int4,
lang -> Uuid,
userid -> Varchar,
}
}
diesel::table! {
userfollows (id) {
id -> Int4,
@ -78,14 +90,26 @@ diesel::table! {
}
}
diesel::table! {
use diesel::sql_types::*;
use super::sql_types::Wordlearningstatus;
wordlearning (id) {
id -> Int4,
word -> Uuid,
userid -> Varchar,
status -> Wordlearningstatus,
}
}
diesel::table! {
use diesel::sql_types::*;
use super::sql_types::Wordrelationship;
wordrelation (id) {
id -> Int4,
wordsource -> Varchar,
wordtarget -> Varchar,
wordsource -> Uuid,
wordtarget -> Uuid,
relationship -> Wordrelationship,
}
}
@ -94,10 +118,11 @@ diesel::table! {
use diesel::sql_types::*;
use super::sql_types::Partofspeech;
words (norm) {
words (id) {
id -> Uuid,
norm -> Varchar,
native -> Nullable<Varchar>,
lemma -> Nullable<Varchar>,
lemma -> Nullable<Uuid>,
language -> Uuid,
partofspeech -> Partofspeech,
audio -> Nullable<Varchar>,
@ -113,14 +138,20 @@ diesel::table! {
diesel::joinable!(langandagents -> languages (language));
diesel::joinable!(langandagents -> users (agent));
diesel::joinable!(languages -> users (owner));
diesel::joinable!(userfollowlanguage -> languages (lang));
diesel::joinable!(userfollowlanguage -> users (userid));
diesel::joinable!(wordlearning -> users (userid));
diesel::joinable!(wordlearning -> words (word));
diesel::joinable!(words -> languages (language));
diesel::allow_tables_to_appear_in_same_query!(
langandagents,
langtranslatesto,
languages,
userfollowlanguage,
userfollows,
users,
wordlearning,
wordrelation,
words,
);

View File

@ -96,7 +96,14 @@ impl Query {
arguments(id(description = "Unique identifier of a word"))
)]
fn word(context: &Context, id: String) -> FieldResult<Option<Word>> {
context.db.word_id(id.as_str()).map_err(Into::into)
match Uuid::from_str(&id) {
Ok(uuid) => context.db.word_id(uuid).map_err(Into::into),
Err(e) => Err(DatabaseError::new(
format!("Failed to convert {id} to a UUID: {e:?}"),
"Conversion Error",
)
.into()),
}
}
#[graphql(