我试图使用python下载kaggle dataset。但是，我使用request方法遇到问题，下载的输出.csv文件是损坏的html文件。
import requests
# The direct link to the Kaggle data set
data_url = 'https://www.kaggle.com/crawford/gene-expression/downloads/actual.csv'
# The local path where the data set is saved.
local_filename = "actsual.csv"
# Kaggle Username and Password
kaggle_info = {'UserName': "myUsername", 'Password': "myPassword"}
# Attempts to download the CSV file. Gets rejected because we are not logged in.
r = requests.get(data_url)
# Login to Kaggle and retrieve the data.
r = requests.post(r.url, data = kaggle_info)
# Writes the data to a local file one chunk at a time.
f = open(local_filename, 'wb')
for chunk in r.iter_content(chunk_size = 512 * 1024): # Reads 512KB at a time into memory
if chunk: # filter out keep-alive new chunks
f.write(chunk)
f.close()
输出文件
<!DOCTYPE html>
<html>
<head>
<title>Gene expression dataset (Golub et al.) | Kaggle</title>
<meta charset="utf-8" />
<meta name="robots" content="index, follow"/>
<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, minimum-scale=1.0"> <meta name="theme-color" content="#008ABC" />
<link rel="dns-prefetch" href="https://www.google-analytics.com" /><link rel="dns-prefetch" href="https://stats.g.doubleclick.net" /><link rel="dns-prefetch" href="https://js.intercomcdn.com" /><link rel="preload" href="https://az416426.vo.msecnd.net/scripts/a/ai.0.js" as=script /><link rel="dns-prefetch" href="https://kaggle2.blob.core.windows.net" />
<link href="/content/v/d420a040e581/kaggle/favicon.ico" rel="shortcut icon" type="image/x-icon" />
<link rel="manifest" href="/static/json/manifest.json">
<link href="//fonts.googleapis.com/css?family=Open+Sans:400,300,300italic,400italic,600,600italic,700,700italic" rel='stylesheet' type='text/css'>
<link rel="stylesheet" type="text/css" href="/static/assets/vendor.css?v=72f4ef2ebe4f"/>
<link rel="stylesheet" type="text/css" href="/static/assets/app.css?v=d997fa977b65"/>
<script>
(function () {
var originalError = window.onerror;
window.onerror = function (message, url, lineNumber, columnNumber, error) {
var handled = originalError && originalError(message, url, lineNumber, columnNumber, error);
var blockedByCors = message && message.toLowerCase().indexOf("script error") >= 0;
return handled || blockedByCors;
};
})();
</script>
<script>
var appInsights=window.appInsights||function(config){
function i(config){t[config]=function(){var i=arguments;t.queue.push(function(){t[config].apply(t,i)})}}var t={config:config},u=document,e=window,o="script",s="AuthenticatedUserContext",h="start",c="stop",l="Track",a=l+"Event",v=l+"Page",y=u.createElement(o),r,f;y.src=config.url||"https://az416426.vo.msecnd.net/scripts/a/ai.0.js";u.getElementsByTagName(o)[0].parentNode.appendChild(y);try{t.cookie=u.cookie}catch(p){}for(t.queue=[],t.version="1.0",r=["Event","Exception","Metric","PageView","Trace","Dependency"];r.length;)i("track"+r.pop());return i("set"+s),i("clear"+s),i(h+a),i(c+a),i(h+v),i(c+v),i("flush"),config.disableExceptionTracking||(r="onerror",i("_"+r),f=e[r],e[r]=function(config,i,u,e,o){var s=f&&f(config,i,u,e,o);return s!==!0&&t["_"+r](config,i,u,e,o),s}),t
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答案 0 :(得分：5)
基本上，如果您要使用Kaggle python API（@ minh-triet提供的解决方案是针对命令行而非的python），则必须执行以下：
import kaggle
kaggle.api.authenticate()
kaggle.api.dataset_download_files('The_name_of_the_dataset', path='the_path_you_want_to_download_the_files_to', unzip=True)
我希望这会有所帮助。
答案 1 :(得分：4)
我建议您查看Kaggle API而不是使用自己的代码。根据最新版本，下载数据集的示例命令是
kaggle datasets download -d zillow/zecon
答案 2 :(得分：0)
kaggle api密钥和usersame在kaggle个人资料页面和数据集中可用 下载链接可在kaggle上的数据集详细信息页面上找到
#Set the enviroment variables
import os
os.environ['KAGGLE_USERNAME'] = "xxxx"
os.environ['KAGGLE_KEY'] = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
!kaggle competitions download -c dogs-vs-cats-redux-kernels-edition
答案 3 :(得分：0)
完整版本的示例 Download_Kaggle_Dataset_To_Colab 并在 Windows 下开始为我工作
#Step1
#Input:
from google.colab import files
files.upload() #this will prompt you to upload the kaggle.json. Download from Kaggle>Kaggle API-file.json. Save to PC to PC folder and choose it here
#Output Sample:
#kaggle.json
#kaggle.json(application/json) - 69 bytes, last modified: 29.06.2021 - 100% done
#Saving kaggle.json to kaggle.json
#{'kaggle.json':
#b'{"username":"sergeysukhov7","key":"23d4d4abdf3bee8ba88e653cec******"}'}
#Step2
#Input:
!pip install -q kaggle
!mkdir -p ~/.kaggle
!cp kaggle.json ~/.kaggle/
!ls ~/.kaggle
!chmod 600 /root/.kaggle/kaggle.json # set permission
#Output:
#kaggle.json
#Step3
#Input:
#Set the enviroment variables
import os
os.environ['KAGGLE_USERNAME'] = "sergeysukhov7" #manually input My_Kaggle User_Name
os.environ['KAGGLE_KEY'] = "23d4d4abdf3bee8ba88e653cec5*****" #manually input My_Kaggle Key
#Step4
#!kaggle datasets download -d zillow/zecon #download dataset to default folder content/zecon.zip if I want
#find kaggle dataset link (for example) https://www.kaggle.com/willkoehrsen/home-credit-default-risk-feature-tools and choose part_of_the_link - willkoehrsen/home-credit-default-risk-feature-tools
#set link_from Kaggle willkoehrsen/home-credit-default-risk-feature-tools
#set Colab folder download_to /content/gdrive/My Drive/kaggle/credit/home-credit-default-risk-feature-tools.zip
!kaggle datasets download -d willkoehrsen/home-credit-default-risk-feature-tools -p /content/gdrive/My\ Drive/kaggle/credit
#Output
#Downloading home-credit-default-risk-feature-tools.zip to /content/gdrive/My Drive/kaggle/credit
#100% 3.63G/3.63G [01:31<00:00, 27.6MB/s]
#100% 3.63G/3.63G [01:31<00:00, 42.7MB/s]
答案 4 :(得分：-1)
为了让下一个人更轻松，我将很棒的 answer from CaitLAN Jenner与一些代码结合在一起，这些代码将原始csv信息放入了一个Pandas DataFrame，假设row 0具有列名。我用它从Kaggle下载了Pima Diabetes数据集，并且运行良好。
我敢肯定有更多优雅的方法可以做到这一点，但是它在我所教的课程中效果很好，很容易解释，并且可以让您轻松地进行分析。
import pandas as pd
import requests
import csv
payload = {
'__RequestVerificationToken': '',
'username': 'username',
'password': 'password',
'rememberme': 'false'
}
loginURL = 'https://www.kaggle.com/account/login'
dataURL = "https://www.kaggle.com/uciml/pima-indians-diabetes-database/downloads/diabetes.csv"
with requests.Session() as c:
response = c.get(loginURL).text
AFToken = response[response.index('antiForgeryToken')+19:response.index('isAnonymous: ')-12]
#print("AntiForgeryToken={}".format(AFToken))
payload['__RequestVerificationToken']=AFToken
c.post(loginURL + "?isModal=true&returnUrl=/", data=payload)
download = c.get(dataURL)
decoded_content = download.content.decode('utf-8')
cr = csv.reader(decoded_content.splitlines(), delimiter=',')
my_list = list(cr)
#for row in my_list:
# print(row)
df = pd.DataFrame(my_list)
header = df.iloc[0]
df = df[1:]
diab = df.set_axis(header, axis='columns', inplace=False)
# to make sure it worked, uncomment this next line:
# diab
`
答案 5 :(得分：-2)
任何事情之前：
pip install kaggle
对于数据集：
import os
os.environ['KAGGLE_USERNAME'] = "uname" # username from the json file
os.environ['KAGGLE_KEY'] = "kaggle_key" # key from the json file
!kaggle datasets download -d zynicide/wine-reviews
比赛：
import os
os.environ['KAGGLE_USERNAME'] = "uname" # username from the json file
os.environ['KAGGLE_KEY'] = "kaggle_key" # key from the json file
!kaggle competitions download -c dogs-vs-cats-redux-kernels-edition
前一段时间，我提供了另一个similar answer。
答案 6 :(得分：-3)
参考https://github.com/Kaggle/kaggle-api
步骤_1， 尝试Insatling Kaggle
pip install kaggle # Windows
pip install --user kaggle # **Mac/Linux**.
第2步，
更新您的凭据，以便kaggle可以根据从Kaggle生成的令牌在.kaggle/kaggel_json上进行身份验证。
参考：https://medium.com/@ankushchoubey/how-to-download-dataset-from-kaggle-7f700d7f9198
第3步
现在已kaggle competitions download ..
运行~/.local/bin/kaggle competitions download ..
避免找不到命令Kaggle