1. server.py

#!/usr/bin/env python3
#-*- coding:utf-8 -*-

import os
import json
import pickle

from flask import Flask,request,render_template,jsonify,make_response,url_for
from impala.dbapi import connect

#flask app
app = Flask(__name__)

@app.route("/api/v1.0/query",methods=[''GET'',''POST''])
def query():
    res = {}
    # if True:
    print(request.args)
    if request.method == ''GET'':
        res[''t''] = 123
    return jsonify(res)

def start_web_server():
    app.run(host=''0.0.0.0'',port=6666)

if __name__ == "__main__":
    start_web_server()

2. client端

import urllib
import urllib.request

url = ''http://127.0.0.1:6666/api/v1.0/query''
values = {''reg_begin_time'' : ''2016-11-01'',''reg_end_time'': ''2016-12-01'',''reg_type'' : ''android'' }


postdata = urllib.parse.urlencode(values)
print(postdata)
postdata = postdata.encode(''utf-8'')
print(postdata)

res = urllib.request.urlopen(url,postdata)

print(res)

         deleteall ''testtable'',''event_0''

5. 示例代码

#!/usr/bin/env python3
#! coding:utf-8 -*-


import happybase

#要先在hbase某个节点上开启thrift服务
#hbase thrift -p 9090 start
connection = happybase.Connection(''192.168.0.1'',autoconnect=False)
connection.open()

#print所有的表名
print(''All tables: '',connection.tables(),''\n'')

#操作testtable表
#这个操作是一个提前声明-我要用到这个表了-但不会提交给thrift server做操作
table = connection.table(b''testtable'')

#检索某一行
row = table.row(b''myrow-2'')
print(''a row:'',row,''\n'')

#right
print(row[b''colfam1:q1''])
print(row[b''colfam1:q2''])

#wrong
# print(row[''colfam1:q1''])
# print(row[''colfam1:q2''])

#显示所有列族
print(''所有列族'',table.families(),''\n'')

#输出两列
print(''print two rows:'')
rows = table.rows([b''myrow-1'',b''myrow-2''])
for key,data in rows:
    print(key,data)

#字典输出两列
print(''\n'',''print two dict rows'')
rows_as_dict = dict(table.rows([b''myrow-1'',b''myrow-2'']))
print(rows_as_dict)

#输入row的一个列族所有值
row = table.row(b''myrow-2'',columns=[b''colfam1''])
print(''\n'',''输出一个列族'',row)

#scan操作
print(''\n'',''do scan'')
for key,data in table.scan():
    print(key,data)

1 import sys
2 sys.path.append(''/projects/caffe-ssd/python'')
3 import caffe
4 net = caffe.NetSpec()

net.data ,net.label = caffe.layers.ImageData(
    name="InputData"
    source="train.txt",
    batch_size=32,
    new_width=48,
    new_height=48,
    ntop=2,
    is_color=True,
    shuffle=True,
    root_folder=''/'',
    transform_param=dict(crop_size=40,mirror=True))
print str(net.to_proto())

输出：
layer {
  name: "InputData"
  type: "ImageData"
  top: "data"
  top: "label"
  transform_param {
    mirror: true
    crop_size: 40
  }
  image_data_param {
    source: "train.txt"
    batch_size: 32
    shuffle: true
    new_height: 48
    new_width: 48
    is_color: true
    root_folder: "/"
  }
}

net.data, net.label = caffe.layers.Data(
    name="InputData",
    source="train_lmdb",
    backend = caffe.params.Data.LMDB,
    batch_size=32,
    ntop=2,
    include=dict(phase=caffe.TRAIN)
    transform_param=dict(
        crop_size=227,
        mean_value=[104, 117, 123],
        mirror=True
    )
)

输出：
layer {
  name: "InputData"
  type: "Data"
  top: "data"
  top: "label"
  transform_param {
    mirror: true
    crop_size: 227
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
  data_param {
    source: "train_lmdb"
    batch_size: 32
    backend: LMDB
  }
}

net.data, net.label = caffe.layers.HDF5Data(
            name="InputData",
            source=''./training_data_paths.txt'',
            batch_size=64,
            include=dict(phase=caffe.TRAIN),
            ntop=2
            )

输出：
layer {
  name: "InputData"
  type: "HDF5Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  hdf5_data_param {
    source: "./training_data_paths.txt"
    batch_size: 64
  }
}

另有：
image = L.HDF5Data( 
    hdf5_data_param={ ''source'': ''./training_data_paths.txt'', ''batch_size'': 64 },
     include={''phase'': caffe.TRAIN } 
)

解决方法

import pytz
import jsonpickle
import iso8601
from datetime import datetime

class Blah(object):

    def __init__(self,blah):
        self.datetime = datetime.Now(pytz.utc)
        self.blah = blah

    def to_json(self):
        return jsonpickle.encode(self)

    @classmethod
    def from_json(cls,json_str):
        return jsonpickle.decode(json_str)

class DatePickleISO8601(jsonpickle.handlers.DatetimeHandler):
    def flatten(self,obj,data):
        pickler = self.context
        if not pickler.unpicklable:
            return unicode(obj)
        cls,args = obj.__reduce__()
        flatten = pickler.flatten
        payload = obj.isoformat()
        args = [payload] + [flatten(i,reset=False) for i in args[1:]]
        data['__reduce__'] = (flatten(cls,reset=False),args)
        return data

    def restore(self,data):
        cls,args = data['__reduce__']
        unpickler = self.context
        restore = unpickler.restore
        cls = restore(cls,reset=False)
        value = iso8601.parse_date(args[0])
        return value

jsonpickle.handlers.registry.register(datetime,DatePickleISO8601)