mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-11-09 22:48:54 +01:00
remove milli/src/update/new/extract/tokenize_document.rs
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@ -1,320 +0,0 @@
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use std::collections::HashMap;
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use charabia::{SeparatorKind, Token, TokenKind, Tokenizer};
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use serde_json::Value;
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use crate::update::new::KvReaderFieldId;
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use crate::{
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FieldId, GlobalFieldsIdsMap, InternalError, LocalizedAttributesRule, Result, MAX_WORD_LENGTH,
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};
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pub struct DocumentTokenizer<'a> {
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pub tokenizer: &'a Tokenizer<'a>,
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pub searchable_attributes: Option<&'a [&'a str]>,
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pub localized_attributes_rules: &'a [LocalizedAttributesRule],
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pub max_positions_per_attributes: u32,
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}
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impl<'a> DocumentTokenizer<'a> {
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pub fn tokenize_document(
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&self,
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obkv: &KvReaderFieldId,
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field_id_map: &mut GlobalFieldsIdsMap,
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token_fn: &mut impl FnMut(FieldId, u16, &str),
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) -> Result<()> {
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let mut field_position = HashMap::new();
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let mut field_name = String::new();
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for (field_id, field_bytes) in obkv {
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let Some(field_name) = field_id_map.name(field_id).map(|s| {
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field_name.clear();
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field_name.push_str(s);
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&field_name
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}) else {
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unreachable!("field id not found in field id map");
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};
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let mut tokenize_field = |name: &str, value: &Value| {
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let Some(field_id) = field_id_map.id_or_insert(name) else {
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/// TODO: better error
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panic!("it's over 9000");
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};
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let position =
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field_position.entry(field_id).and_modify(|counter| *counter += 8).or_insert(0);
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if *position as u32 >= self.max_positions_per_attributes {
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return;
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}
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match value {
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Value::Number(n) => {
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let token = n.to_string();
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if let Ok(position) = (*position).try_into() {
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token_fn(field_id, position, token.as_str());
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}
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}
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Value::String(text) => {
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// create an iterator of token with their positions.
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let locales = self
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.localized_attributes_rules
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.iter()
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.find(|rule| rule.match_str(field_name))
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.map(|rule| rule.locales());
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let tokens = process_tokens(
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*position,
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self.tokenizer.tokenize_with_allow_list(text.as_str(), locales),
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)
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.take_while(|(p, _)| (*p as u32) < self.max_positions_per_attributes);
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for (index, token) in tokens {
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// keep a word only if it is not empty and fit in a LMDB key.
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let token = token.lemma().trim();
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if !token.is_empty() && token.len() <= MAX_WORD_LENGTH {
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*position = index;
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if let Ok(position) = (*position).try_into() {
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token_fn(field_id, position, token);
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}
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}
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}
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}
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_ => (),
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}
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};
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// if the current field is searchable or contains a searchable attribute
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if self.searchable_attributes.map_or(true, |attributes| {
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attributes.iter().any(|name| perm_json_p::contained_in(name, &field_name))
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}) {
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// parse json.
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match serde_json::from_slice(field_bytes).map_err(InternalError::SerdeJson)? {
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Value::Object(object) => perm_json_p::seek_leaf_values_in_object(
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&object,
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self.searchable_attributes.as_deref(),
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&field_name,
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&mut tokenize_field,
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),
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Value::Array(array) => perm_json_p::seek_leaf_values_in_array(
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&array,
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self.searchable_attributes.as_deref(),
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&field_name,
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&mut tokenize_field,
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),
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value => tokenize_field(&field_name, &value),
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}
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}
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}
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Ok(())
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}
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}
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/// take an iterator on tokens and compute their relative position depending on separator kinds
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/// if it's an `Hard` separator we add an additional relative proximity of 8 between words,
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/// else we keep the standard proximity of 1 between words.
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fn process_tokens<'a>(
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start_offset: usize,
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tokens: impl Iterator<Item = Token<'a>>,
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) -> impl Iterator<Item = (usize, Token<'a>)> {
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tokens
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.skip_while(|token| token.is_separator())
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.scan((start_offset, None), |(offset, prev_kind), mut token| {
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match token.kind {
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TokenKind::Word | TokenKind::StopWord if !token.lemma().is_empty() => {
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*offset += match *prev_kind {
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Some(TokenKind::Separator(SeparatorKind::Hard)) => 8,
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Some(_) => 1,
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None => 0,
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};
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*prev_kind = Some(token.kind)
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}
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TokenKind::Separator(SeparatorKind::Hard) => {
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*prev_kind = Some(token.kind);
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}
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TokenKind::Separator(SeparatorKind::Soft)
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if *prev_kind != Some(TokenKind::Separator(SeparatorKind::Hard)) =>
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{
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*prev_kind = Some(token.kind);
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}
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_ => token.kind = TokenKind::Unknown,
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}
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Some((*offset, token))
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})
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.filter(|(_, t)| t.is_word())
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}
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/// TODO move in permissive json pointer
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mod perm_json_p {
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use serde_json::{Map, Value};
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const SPLIT_SYMBOL: char = '.';
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/// Returns `true` if the `selector` match the `key`.
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///
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/// ```text
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/// Example:
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/// `animaux` match `animaux`
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/// `animaux.chien` match `animaux`
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/// `animaux.chien` match `animaux`
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/// `animaux.chien.nom` match `animaux`
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/// `animaux.chien.nom` match `animaux.chien`
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/// -----------------------------------------
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/// `animaux` doesn't match `animaux.chien`
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/// `animaux.` doesn't match `animaux`
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/// `animaux.ch` doesn't match `animaux.chien`
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/// `animau` doesn't match `animaux`
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/// ```
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pub fn contained_in(selector: &str, key: &str) -> bool {
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selector.starts_with(key)
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&& selector[key.len()..].chars().next().map(|c| c == SPLIT_SYMBOL).unwrap_or(true)
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}
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pub fn seek_leaf_values<'a>(
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value: &Map<String, Value>,
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selectors: impl IntoIterator<Item = &'a str>,
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seeker: &mut impl FnMut(&str, &Value),
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) {
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let selectors: Vec<_> = selectors.into_iter().collect();
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seek_leaf_values_in_object(value, Some(&selectors), "", seeker);
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}
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pub fn seek_leaf_values_in_object(
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value: &Map<String, Value>,
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selectors: Option<&[&str]>,
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base_key: &str,
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seeker: &mut impl FnMut(&str, &Value),
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) {
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for (key, value) in value.iter() {
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let base_key = if base_key.is_empty() {
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key.to_string()
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} else {
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format!("{}{}{}", base_key, SPLIT_SYMBOL, key)
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};
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// here if the user only specified `doggo` we need to iterate in all the fields of `doggo`
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// so we check the contained_in on both side
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let should_continue = selectors.map_or(true, |selectors| {
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selectors.iter().any(|selector| {
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contained_in(selector, &base_key) || contained_in(&base_key, selector)
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})
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});
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if should_continue {
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match value {
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Value::Object(object) => {
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seek_leaf_values_in_object(object, selectors, &base_key, seeker)
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}
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Value::Array(array) => {
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seek_leaf_values_in_array(array, selectors, &base_key, seeker)
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}
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value => seeker(&base_key, value),
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}
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}
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}
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}
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pub fn seek_leaf_values_in_array(
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values: &[Value],
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selectors: Option<&[&str]>,
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base_key: &str,
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seeker: &mut impl FnMut(&str, &Value),
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) {
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for value in values {
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match value {
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Value::Object(object) => {
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seek_leaf_values_in_object(object, selectors, base_key, seeker)
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}
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Value::Array(array) => {
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seek_leaf_values_in_array(array, selectors, base_key, seeker)
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}
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value => seeker(base_key, value),
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}
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}
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}
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}
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#[cfg(test)]
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mod test {
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use charabia::TokenizerBuilder;
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use meili_snap::snapshot;
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use obkv::KvReader;
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use serde_json::json;
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use super::*;
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use crate::FieldsIdsMap;
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#[test]
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fn test_tokenize_document() {
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let mut fields_ids_map = FieldsIdsMap::new();
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let field_1 = json!({
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"name": "doggo",
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"age": 10,
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});
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let field_2 = json!({
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"catto": {
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"name": "pesti",
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"age": 23,
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}
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});
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let field_3 = json!(["doggo", "catto"]);
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let mut obkv = obkv::KvWriter::memory();
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let field_1_id = fields_ids_map.insert("doggo").unwrap();
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let field_1 = serde_json::to_string(&field_1).unwrap();
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obkv.insert(field_1_id, field_1.as_bytes()).unwrap();
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let field_2_id = fields_ids_map.insert("catto").unwrap();
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let field_2 = serde_json::to_string(&field_2).unwrap();
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obkv.insert(field_2_id, field_2.as_bytes()).unwrap();
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let field_3_id = fields_ids_map.insert("doggo.name").unwrap();
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let field_3 = serde_json::to_string(&field_3).unwrap();
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obkv.insert(field_3_id, field_3.as_bytes()).unwrap();
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let value = obkv.into_inner().unwrap();
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let obkv = KvReader::from_slice(value.as_slice());
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let mut tb = TokenizerBuilder::default();
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let document_tokenizer = DocumentTokenizer {
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tokenizer: &tb.build(),
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searchable_attributes: None,
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localized_attributes_rules: &[],
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max_positions_per_attributes: 1000,
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};
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let fields_ids_map_lock = std::sync::RwLock::new(fields_ids_map);
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let mut global_fields_ids_map = GlobalFieldsIdsMap::new(&fields_ids_map_lock);
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let mut words = std::collections::BTreeMap::new();
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document_tokenizer
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.tokenize_document(obkv, &mut global_fields_ids_map, &mut |fid, pos, word| {
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words.insert([fid, pos], word.to_string());
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})
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.unwrap();
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snapshot!(format!("{:#?}", words), @r###"
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{
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[
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2,
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0,
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]: "doggo",
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[
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2,
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8,
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]: "doggo",
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[
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2,
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16,
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]: "catto",
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[
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3,
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0,
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]: "10",
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[
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4,
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0,
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]: "pesti",
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[
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5,
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0,
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]: "23",
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}
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"###);
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}
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}
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