lihuanshuai

"""
Simple demo of a scatter plot.
"""
import numpy as np
import matplotlib.pyplot as plt


N = 50
x = np.random.rand(N)
y = np.random.rand(N)

lihuanshuai

# for js analyzer
sudo npm install -g ternjs
# in project root
touch .tern-project

# for gtags
sudo apt-get install global
wget https://raw.githubusercontent.com/Schnouki/dotfiles/master/globalrc -O ~/.globalrc

# for cscope

lihuanshuai

def compose(*functions):
    return functools.reduce(lambda f, g: lambda x: f(g(x)), functions, lambda x: x)

lihuanshuai

__attribute__ ((noreturn)) static void
usage(int code)
{

        fprintf(stderr,
                "Usage: %s [-behuwxMACHPWY] [-c vcpus] [-F <pidfile>] [-g <gdb port>] [-l <lpc>]\n"
		"       %*s [-m mem] [-p vcpu:hostcpu] [-s <pci>] [-U uuid] -f <fw>\n"
		"       -A: create ACPI tables\n"
		"       -c: # cpus (default 1)\n"
		"       -C: include guest memory in core file\n"

lihuanshuai

# monkey-patch
import gevent.monkey
gevent.monkey.patch_all()

import gevent.pool
import gevent.queue

import sys
import re
import requests

lihuanshuai

import random
user_agents = ['1', '2', '3']


class RandomHeader(dict):

    def __getitem__(self, key):
        if key == 'User-Agent':
            return random.choice(user_agents)
        return super(RandomHeader, self).__getitem__(key)

lihuanshuai

def gen_reduced_dict(iterable, key=None, reverse=False):
    key = (lambda x: x) if key is None else key
    d = {}
    for k, v in iterable:
        if k not in d:
            d[k] = v
        pv = d[k]
        cmp_ = (lambda x, y: x > y) if reverse else (lambda x, y: x < y)
        if cmp_(key(v), key(pv)):
            d[k] = v

lihuanshuai

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lihuanshuai

import tables as tb
from numpy import array
from scipy import sparse


def store_sparse_mat(path, name, m, separator='__'):
    if (m.__class__ not in [sparse.csr.csr_matrix, sparse.csc.csc_matrix]):
        raise TypeError("This code only works for csr/csc matrices")
    with tb.openFile(path, 'a') as f:
        for par in ('data', 'indices', 'indptr', 'shape'):

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