acarl005

DROP TABLE IF EXISTS matrices;
CREATE TABLE matrices (
  matrix_id int NOT NULL, -- unique identifier for each matrix
  i int NOT NULL,         -- row number
  j int NOT NULL,         -- column number
  val decimal NOT NULL,   -- the value in this cell
  PRIMARY KEY (matrix_id, i, j)
);

-- insert sparse representation of

acarl005

import trio # async task synchronization library
import asks # async version of `requests`
from inspect import iscoroutinefunction
import requests

async def concurrent_map(inputs, task, conc_limit=1000):
    """
    Like `map` except it is async. It runs an async function for each item in an iterable, and returns an array of the outputs in the correct order
    args:
        inputs - iterable of items which are passed to the async function