from django.shortcuts import render

# Create your views here.

from hdfs.client import Client

from django.views import View

from hdfs.client import Client

import os

#

# # 关于python操作hdfs的API可以查看官网:

# # https://hdfscli.readthedocs.io/en/latest/api.html

#

# # 读取hdfs文件内容,将每行存入数组返回

# def read_hdfs_file(client, filename):

#     lines = []

#     with client.read(filename, encoding='utf-8', delimiter='\n') as reader:

#         for line in reader:

#             # pass

#             # print line.strip()

#             lines.append(line.strip())

#     return lines

#

#

# # 创建目录

# def mkdirs(client, hdfs_path):

#     client.makedirs(hdfs_path)

#

#

# # 删除hdfs文件

# def delete_hdfs_file(client, hdfs_path):

#     client.delete(hdfs_path)

#

#

# # 上传文件到hdfs

def put_to_hdfs(client, local_path, hdfs_path):

    client.upload(hdfs_path, local_path, cleanup=True)

#

# # 从hdfs获取文件到本地

# def get_from_hdfs(client, hdfs_path, local_path):

#     download(hdfs_path, local_path, overwrite=False)

#

#

# # 追加数据到hdfs文件

# def append_to_hdfs(client, hdfs_path, data):

#     client.write(hdfs_path, data, overwrite=False, append=True)

#

#

# # 覆盖数据写到hdfs文件

def write_to_hdfs(client, hdfs_path, data):

    client.write(hdfs_path, data, overwrite=True, append=False)

#

# # 移动或者修改文件

def move_or_rename(client, hdfs_src_path, hdfs_dst_path):

    client.rename(hdfs_src_path, hdfs_dst_path)

#

#

# # 返回目录下的文件

# def list(client, hdfs_path):

#     return client.list(hdfs_path, status=False)

#

#

# # root:连接的跟目录

# client = Client("http://192.168.88.129:50070",

#                 root="/", timeout=5 * 1000, session=False)

# # put_to_hdfs(client,'a.csv','/user/root/a.csv')

# # append_to_hdfs(client,'/b.txt','111111111111111'+'\n')

# # write_to_hdfs(client,'/b.txt','222222222222'+'\n')

# # move_or_rename(client,'/b.txt', '/user/b.txt')

# mkdirs(client, '/input1/python1')

# print(list(client,'/input'))

# read_hdfs_file(client,'/')

# client.list("/")

def mkdirs(client, hdfs_path):

    client.makedirs(hdfs_path)

def get_IS_File(client,hdfs_paht):

    return client.status(hdfs_paht)['type'] == 'FILE'

from hadoop_hdfs.settings import UPLOAD_ROOT

import os

def put_to_hdfs(client, local_path, hdfs_path):

        client.upload(hdfs_path, local_path, cleanup=True)

client = Client("http://192.168.88.129:50070",

                root="/", timeout=5 * 1000, session=False)

class Index(View):

    def get(self,request):

        return render(request,"index.html")

    def post(self,request):

        def uploadfile(img):

            f = open(os.path.join(UPLOAD_ROOT, '', img.name), 'wb')

            for chunk in img.chunks():

                f.write(chunk)

            f.close()

        def read_hdfs_file(client, filename):

            lines = []

            with client.read(filename, encoding='utf-8', delimiter='\n') as reader:

                for line in reader:

                    # pass

                    # print line.strip()

                    lines.append(line.strip())

            return lines

        file = request.FILES.get("file")

        uploadfile(file)

        all_file = client.list("/")

        for i in all_file:

            file_true =get_IS_File(client,"/{}".format(i)),i

            print(file_true)

            # if file_true == "True":

            return render(request,"index.html",locals())

            # else:

            #     pass

            #     # data = {"file_true":file_true}

            #     return render(request,"index.html",locals())

            # else:

            #     pass

        # get_IS_File(all_file,"/")

        # lujin = "/upload/"+file.name

        mkdirs(client,file.name)

        # move_or_rename(client,file.name, '/c.txt')

        # put_to_hdfs(client, "C:/Users/Lenovo/Desktop/hadoop_hdfs/upload/"+file.name, '/')

        # write_to_hdfs(client,"upload"+file.name,'222222222222'+'\n')

        return render(request,"index.html",locals())

 # 导入必要模块

import pandas as pd

from sqlalchemy import create_engine

from  matplotlib import pylab as plt

from django.views import View

from django.shortcuts import render

import os

from hadoop_hdfs.settings import UPLOAD_ROOT

from web.models import *

def uploadfile(img):

 f = open(os.path.join(UPLOAD_ROOT, '', img.name), 'wb')

 for chunk in img.chunks():

     f.write(chunk)

 f.close()

class Upload(View):

    def get(self,request):

        # show = Image.objects.all()

        return render(request,"haha.html",locals())

    def post(self,request):

        imgs = request.FILES.get('img')

        uploadfile(imgs)

        all = Image(img="/upload/"+imgs.name)

        all.save()

        return render(request,"haha.html")

    # def post(self,request):

    #     # 初始化数据库连接，使用pymysql模块

    #     # MySQL的用户：root, 密码:147369, 端口：3306,数据库：mydb

    #     engine = create_engine('mysql+pymysql://root:@127.0.0.1/dj')

    #

    #     # 查询语句，选出employee表中的所有数据

    #     sql = '''select * from haha;'''

    #

    #     # read_sql_query的两个参数: sql语句， 数据库连接

    #     df = pd.read_sql_query(sql, engine)

    #

    #     # 输出employee表的查询结果

    #     print(df)

    #

    #     # 新建pandas中的DataFrame, 只有id,num两列

    #     # df = pd.DataFrame({'id':[1,2],'name': ['111','222'],'image_url':['http://111','http://222']})

    #     # df = pd.DataFrame({"id":df['sentiment'],"text":df['text'],})

    #     df.groupby(by='sentiment').count()['text'].plot.pie(autopct="%0.4f%%", subplots=True)

    #     plt.savefig("../upload/1.jpg")

    #     plt.show()

    #     # 将新建的DataFrame储存为MySQL中的数据表，不储存index列

    #     # df.to_sql(name='lallala', con=engine, index=False)

    #

    #     print('Read from and write to Mysql table successfully!')

    #     return render(request,"haha.html",locals())

class Uploads(View):

    def get(self,request):

        show = Image.objects.all()

        return render(request,"haha.html",locals())