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"""

    导出数据
    ~~~~~~~~~~~~~

    反序列化数据列，支持字符，数组，字典等复杂结构，

    TODO:

        - 数据类型标注: string,bool,int,float

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const mapper = function() {
  const value = {
    country: this.country,
    province: this.province,
    city: this.city,
    region: this.region,
    wifi: this.wifi,
    app_version: this.app_version,
    os_version: this.os_version,
    os: this.os,

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import string
import random


def id_generator(size=64, chars=string.ascii_uppercase + string.digits):
    return ''.join(random.choice(chars) for _ in range(size))

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from django.dispatch import Signal

# 注册
user_created = Signal(providing_args=['user', 'app_id'])
# 更新
user_updated = Signal(providing_args=['user', 'app_id'])
# 登录
user_logged = Signal(providing_args=['user', 'ip', 'app_id'])
# 登出
user_logout = Signal(providing_args=['user', 'ip', 'app_id'])

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from django.db import models
from django.contrib.auth.models import User
from django.db.models.signals import post_save

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import unicodecsv
from django.http import HttpResponse

def export_as_csv_action(description="Export selected objects as CSV file",
                         fields=None, exclude=None, header=True):
    """
    This function returns an export csv action
    'fields' and 'exclude' work like in django ModelForm
    'header' is whether or not to output the column names as the first row
    """

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# using libfaac on Mac OS X 10.6.8
# -vn : not copying video
# -acodec : specify codec used in flv file
# -ac : channels. 1 is for mono, 2 is for stereo
# -ab : specify bitrate for output file (note that rate is not kbps but bps)
# -ar : sampling frequency (Hz)
# -threads: number of threads for encoding
# "-strict experimental" is necessary to use libfaac

ffmpeg -y -i xxxxxxxxxxx.flv -vn -acodec aac -ac 2 -ab 128000 -ar 44100 -threads 4 -strict experimental xxxxx.m4a

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class Success(object):
    def __init__(self, value):
        self.value = value

class Error(object):
    def __init__(self, value):
        self.value = value

class wrapper(object):
    def __init__(self, result):

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class Heap(object):
    def __init__(self, test_func):
        self._data = []
        self._pos = 0
        self.test_func = test_func

    def size(self):
        return self._pos

    def add(self, val):

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# TODO: this program too slow, got be some nice solution. :(
# some graph related knownledge

def f(node, x):
    return node[0] * x + node[1]

paths = {}

def cache(fn):
    def _(u, v, *args, **kwargs):