| from __future__ import unicode_literals | |
| from django.db import models | |
| from django.db.models.fields.related_descriptors import ForwardManyToOneDescriptor # noqa | |
| class RelationNotLoaded(Exception): | |
| pass |
| """ Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
| import numpy as np | |
| import cPickle as pickle | |
| import gym | |
| # hyperparameters | |
| H = 200 # number of hidden layer neurons | |
| batch_size = 10 # every how many episodes to do a param update? | |
| learning_rate = 1e-4 | |
| gamma = 0.99 # discount factor for reward |
Load testing is a good way to understand your website or web app behaviour under high traffic.
Here is how to use siege, a simple CLI tool.
Note: Use siege only on sites you own as its traffic could be interpreted as a DDOS attack.
Using 100 concurrent requests and up to 3 seconds between requests:
| # post_loc.txt contains the json you want to post | |
| # -p means to POST it | |
| # -H adds an Auth header (could be Basic or Token) | |
| # -T sets the Content-Type | |
| # -c is concurrent clients | |
| # -n is the number of requests to run in the test | |
| ab -p post_loc.txt -T application/json -H 'Authorization: Token abcd1234' -c 10 -n 2000 http://example.com/api/v1/locations/ |
| """ | |
| This module adds Redis Sentinel transport support to Celery. | |
| Current version of celery doesn't support Redis sentinel client, which is must have for automatic failover. | |
| To use it:: | |
| import register_celery_alias | |
| register_celery_alias("redis-sentinel") | |
| celery = Celery(..., broker="redis-sentinel://...", backend="redis-sentinel://...") |
For this configuration you can use web server you like, i decided, because i work mostly with it to use nginx.
Generally, properly configured nginx can handle up to 400K to 500K requests per second (clustered), most what i saw is 50K to 80K (non-clustered) requests per second and 30% CPU load, course, this was 2 x Intel Xeon with HyperThreading enabled, but it can work without problem on slower machines.
You must understand that this config is used in testing environment and not in production so you will need to find a way to implement most of those features best possible for your servers.
| # get into the master branch | |
| git checkout master | |
| # create a new branch for the changes and check it out | |
| git checkout -b dev_branch | |
| # stash the changes until we revert master | |
| git stash | |
| # go back to master |
| """ | |
| Celery tasks that batch a job with many tasks into smaller work sets. | |
| The problem I'm attempting to solve is one where a job comprised of many | |
| tasks (say 100) will snub out a job comprised of only a few tasks (say 5). It | |
| appears as though by default celery will queue up the second job's 5 tasks | |
| behind the first job's 100 and it will have to wait until the first job's | |
| completion before it even begins. |
