Learnings

<p>Handling Concurrency Without Locks </p>

<p>How To Use ThreadPoolExecutor in Python 3: </p>

<p>Discussion on the various ways to wait for results in asyncio: </p>

<p>Latency in Asynchronous Python: </p>

<p>Good introduction to Python concurrency with concurrent.futures module: #generic-workflows-for-running-tasks-concurrently</p>

<p>When using psycopg2's ThreadedConnectionPool, an additional sempahore is needed to avoid "connection pool exhausted" errors: </p>

<p>Easy distributed computing with Python: Word count example with Dask.distributed futures </p>

<p>How to scale Python multiprocessing to a cluster with one line of code: </p>

<p>When should we call multiprocessing.Pool.join? </p>

<p>Must read article on common Celery issues: </p>

<p>Python multiprocessing: understanding logic behind <code>chunksize</code>: </p>

<p>Small Python library that makes it easy to exploit race conditions in web apps with Requests </p>

<p>Python vs Copy on Write: </p>

<p>PostgreSQL Concurrency with MVCC: </p>

<p>Has the Python GIL been slain? Sub-interpreters: a middle ground solution - </p>

<p>This blog post explains two approaches for dealing with concurrent access in Django models, a pessimistic and an optimistic one </p>