//! This module provides the functionality to scrape and gathers all the results from the upstream //! search engines and then removes duplicate results. use std::{collections::HashMap, time::Duration}; use error_stack::Report; use rand::Rng; use tokio::task::JoinHandle; use super::{ aggregation_models::{EngineErrorInfo, RawSearchResult, SearchResult, SearchResults}, user_agent::random_user_agent, }; use crate::engines::{ duckduckgo, engine_models::{EngineError, SearchEngine}, searx, }; /// Aliases for long type annotations type FutureVec = Vec, Report>>>; /// The function aggregates the scraped results from the user-selected upstream search engines. /// These engines can be chosen either from the user interface (UI) or from the configuration file. /// The code handles this process by matching the selected search engines and adding them to a vector. /// This vector is then used to create an asynchronous task vector using `tokio::spawn`, which returns /// a future. This future is awaited in another loop. Once the results are collected, they are filtered /// to remove any errors and ensure only proper results are included. If an error is encountered, it is /// sent to the UI along with the name of the engine and the type of error. This information is finally /// placed in the returned `SearchResults` struct. /// /// Additionally, the function eliminates duplicate results. If two results are identified as coming from /// multiple engines, their names are combined to indicate that the results were fetched from these upstream /// engines. After this, all the data in the `HashMap` is removed and placed into a struct that contains all /// the aggregated results in a vector. Furthermore, the query used is also added to the struct. This step is /// necessary to ensure that the search bar in the search remains populated even when searched from the query URL. /// /// Overall, this function serves to aggregate scraped results from user-selected search engines, handling errors, /// removing duplicates, and organizing the data for display in the UI. /// /// # Example: /// /// If you search from the url like `https://127.0.0.1/search?q=huston` then the search bar should /// contain the word huston and not remain empty. /// /// # Arguments /// /// * `query` - Accepts a string to query with the above upstream search engines. /// * `page` - Accepts an u32 page number. /// * `random_delay` - Accepts a boolean value to add a random delay before making the request. /// * `debug` - Accepts a boolean value to enable or disable debug mode option. /// * `upstream_search_engines` - Accepts a vector of search engine names which was selected by the /// user through the UI or the config file. /// /// # Error /// /// Returns an error a reqwest and scraping selector errors if any error occurs in the results /// function in either `searx` or `duckduckgo` or both otherwise returns a `SearchResults struct` /// containing appropriate values. pub async fn aggregate( query: String, page: u32, random_delay: bool, debug: bool, upstream_search_engines: Vec, ) -> Result> { let user_agent: String = random_user_agent(); let mut result_map: HashMap = HashMap::new(); // Add a random delay before making the request. if random_delay || !debug { let mut rng = rand::thread_rng(); let delay_secs = rng.gen_range(1..10); std::thread::sleep(Duration::from_secs(delay_secs)); } // fetch results from upstream search engines simultaneously/concurrently. let search_engines: Vec> = upstream_search_engines .iter() .map(|engine| match engine.to_lowercase().as_str() { "duckduckgo" => Box::new(duckduckgo::DuckDuckGo) as Box, "searx" => Box::new(searx::Searx) as Box, &_ => panic!("Config Error: Incorrect config file option provided"), }) .collect(); let task_capacity: usize = search_engines.len(); let tasks: FutureVec = search_engines .into_iter() .map(|search_engine| { let query: String = query.clone(); let user_agent: String = user_agent.clone(); tokio::spawn( async move { search_engine.results(query, page, user_agent.clone()).await }, ) }) .collect(); let mut outputs = Vec::with_capacity(task_capacity); for task in tasks { if let Ok(result) = task.await { outputs.push(result) } } let mut engine_errors_info: Vec = Vec::new(); let mut initial: bool = true; let mut counter: usize = 0; outputs.iter().for_each(|results| { if initial { match results { Ok(result) => { result_map.extend(result.clone()); counter += 1; initial = false } Err(error_type) => { engine_errors_info.push(EngineErrorInfo::new( error_type.downcast_ref::().unwrap(), upstream_search_engines[counter].clone(), )); counter += 1 } } } else { match results { Ok(result) => { result.clone().into_iter().for_each(|(key, value)| { result_map .entry(key) .and_modify(|result| { result.add_engines(value.clone().engine()); }) .or_insert_with(|| -> RawSearchResult { RawSearchResult::new( value.title.clone(), value.visiting_url.clone(), value.description.clone(), value.engine.clone(), ) }); }); counter += 1 } Err(error_type) => { engine_errors_info.push(EngineErrorInfo::new( error_type.downcast_ref::().unwrap(), upstream_search_engines[counter].clone(), )); counter += 1 } } } }); Ok(SearchResults::new( result_map .into_iter() .map(|(key, value)| { SearchResult::new( value.title, value.visiting_url, key, value.description, value.engine, ) }) .collect(), query.to_string(), engine_errors_info, )) }