Python aiosqlite - async SQLITE

Install the aiosqlite package: aiosqlite is an async version of sqlite3 that works with Python's asyncio library. You can install it using pip:

 Import the necessary libraries: You need to import aiosqlite and asyncio for this task.

Create an async function to execute your query: This function will connect to a SQLite database, execute a query, and return the results. It uses the aiosqlite.connect() method to establish a connection to the database and the execute() method to run the SQL query.

Create tasks for each database: For each database you want to search, create a task using asyncio.create_task(). Each of these tasks will run the query_db function concurrently.

Execute the tasks: Use asyncio.gather() to run all the tasks concurrently and wait for all of them to finish. The results will be returned as a list of lists, with each sublist containing the results from one database.

Iterate through the results: You can now iterate through the results to process the data from each database.

import asyncio
import aiosqlite

async def query_db(database, query):
    async with aiosqlite.connect(database) as db:
        async with db.execute(query) as cursor:
            return await cursor.fetchall()

async def main():
    databases = ["database1.db", "database2.db", "database3.db"]
    query = "SELECT * FROM some_table"
    tasks = [asyncio.create_task(query_db(database, query)) for database in databases]

    results = await asyncio.gather(*tasks)

    for db_results in results:
        for row in db_results:
            # Process row
            pass

asyncio.run(main())
 

# This code will initiate connections to each of the specified databases concurrently and execute the same query on each. The results from each database are collected into a list of lists, which can then be processed as needed.Note: It's important to remember that although asyncio allows for concurrent execution of tasks, SQLite databases are stored on disk and therefore I/O bound. The actual speedup from using asyncio will depend on the speed of your disk and how large the databases are

Yes, you can search for different queries in each database using a similar method. You just need to adjust the query_db function to take both a database and a query parameter. You can then pass a different query for each database when creating the tasks. Here's how you can do it:

1. Modify the query_db function: The query_db function now takes two parameters: database and query. It will execute the query on the specified database.

 Create tasks for each database with different queries: For each database-query pair, create a task using asyncio.create_task(). Each of these tasks will run the query_db function concurrently.

 Execute the tasks: Use asyncio.gather() to run all the tasks concurrently and wait for all of them to finish. The results will be returned as a list of lists, with each sublist containing the results from one database.

Iterate through the results: You can now iterate through the results to process the data from each database.

import asyncio
import aiosqlite

async def query_db(database, query):
    async with aiosqlite.connect(database) as db:
        async with db.execute(query) as cursor:
            return await cursor.fetchall()

async def main():
    db_query_pairs = [("database1.db", "SELECT * FROM table1"),
                      ("database2.db", "SELECT * FROM table2"),
                      ("database3.db", "SELECT * FROM table3")]
    tasks = [asyncio.create_task(query_db(database, query)) for database, query in db_query_pairs]

    results = await asyncio.gather(*tasks)

    for db_results in results:
        for row in db_results:
            # Process row
            pass

asyncio.run(main())

# This code will initiate connections to each of the specified databases concurrently and execute a different query on each. The results from each database are collected into a list of lists, which can then be processed as needed

 Can I pass multiple queries for the same database using this method?

import asyncio
import aiosqlite

async def query_db(database, queries):
async with aiosqlite.connect(database) as db:
results = []
for query in queries:
async with db.execute(query) as cursor:
results.append(await cursor.fetchall())
return results

async def main():
database = "database.db"
query_sets = [["SELECT * FROM table1", "SELECT * FROM table2"],
["SELECT * FROM table3", "SELECT * FROM table4"]]
tasks = [asyncio.create_task(query_db(database, queries)) for queries in query_sets]

results = await asyncio.gather(*tasks)

for query_set_results in results:
for query_results in query_set_results:
for row in query_results:
# Process row
pass

asyncio.run(main())

This code will initiate a connection to the specified database concurrently for each set of queries and execute each query on the same connection. The results from each query are collected into a list of lists, which can then be processed as needed.

Note: Always be careful when executing multiple queries, especially if they modify the database. Make sure your queries are executed in the correct order and handle any errors that may occur