》》

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())

Views.py

 # 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())

haha.py

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