pipoket

# Copyright (c) 2009-2010 Denis Bilenko. See LICENSE for details.
"""UDP/SSL server"""
import sys
import errno
import traceback
from gevent import socket
from gevent import core
from gevent.baseserver import BaseServer

sehugg

#!/usr/bin/env python
from __future__ import print_function
from keras.models import Sequential
from keras.layers import TimeDistributed
from keras.layers.core import Dense, Activation, Dropout, RepeatVector, TimeDistributedDense
from keras.layers.recurrent import LSTM
from keras.utils.data_utils import get_file
import numpy as np
import random,string
import sys

plugnburn

XT.js

Let's close the ultra-small library cycle with some awesome array-based templating. 323 bytes minified.

How to obtain

Just download the minified version here or include it into your code:

mtesseracted

'''
matplotlib must be developer release for voxel support
  install instructions:
https://matplotlib.org/devdocs/users/installing.html
'''

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.animation as manimation

nicksam112

#Evolution Strategies with Keras
#Based off of: https://blog.openai.com/evolution-strategies/
#Implementation by: Nicholas Samoray

#README
#Meant to be run on a single machine
#APPLY_BIAS is currently not working, keep to False
#Solves Cartpole as-is in about 50 episodes
#Solves BipedalWalker-v2 in about 1000

jgomezdans

#!/usr/bin/env python
"""
Some Hessian codes
"""
import numpy as np
from scipy.optimize import approx_fprime


def hessian ( x0, epsilon=1.e-5, linear_approx=False, *args ):
    """

gingerBill

////////////////////////////////////////////////////////////////
//
// Defer statement
//     - Akin to D's SCOPE_EXIT or similar to Go's defer but scope-based
//
////////////////////////////////////////////////////////////////
#if defined(__cplusplus)
extern "C++" {
	// NOTE(bill): Stupid fucking templates
	template <typename T> struct gbRemove_Reference       { typedef T Type; };

gregvish

from socket import socket, SO_REUSEADDR, SOL_SOCKET
from asyncio import Task, coroutine, get_event_loop

class Peer(object):
    def __init__(self, server, sock, name):
        self.loop = server.loop
        self.name = name
        self._sock = sock
        self._server = server
        Task(self._peer_handler())

mangecoeur

Easy parallel python with concurrent.futures

As of version 3.3, python includes the very promising concurrent.futures module, with elegant context managers for running tasks concurrently. Thanks to the simple and consistent interface you can use both threads and processes with minimal effort.

For most CPU bound tasks - anything that is heavy number crunching - you want your program to use all the CPUs in your PC. The simplest way to get a CPU bound task to run in parallel is to use the ProcessPoolExecutor, which will create enough sub-processes to keep all your CPUs busy.

We use the context manager thusly:

with concurrent.futures.ProcessPoolExecutor() as executor:

typehorror

Flask-SQLAlchemy Caching

The following gist is an extract of the article Flask-SQLAlchemy Caching. It allows automated simple cache query and invalidation of cache relations through event among other features.

Usage

retrieve one object

# pulling one User object

user = User.query.get(1)