为了处理来自旧CMS的旧URL,要将旧URL指向相应页面的硬HTML备份,我需要设置一个将/fixedname_[id]
重定向/重写为/fixedname_[id].html
的规则或者在遗留URL(没有.html)下加载实际的.html文件。
例如,将/druckfrisch_2016_15
重定向到/druckfrisch_2016_15.html
OR
在网址/druckfrisch_2016_15.html
/druckfrisch_2016_15
如果我使用RedirectMatch 301 /druckfrisch_(.*) /druckfrisch_$1\.html
它转到
/druckfrisch_2016_15.html.html.html.html.html.html.html.html.html.html.html.html.html.html.html.html.html.html.html.html.html
某种递归错误?目标地址也会一次又一次地被重写?我是否需要在查询的第一部分中排除包含.html
的任何网址?
我也试过这些没有运气:
RedirectMatch "/druckfrisch_(.*)" "/druckfrisch_$1\.html"
Redirect "^/druckfrisch_(.*)$" "/druckfrisch_$1\.html"
RewriteRule ^/druckfrisch_(.*)$ /druckfrisch_$1\.html
无论我添加什么新规则,都需要使用默认的Wordpress .htaccess配置:
RewriteEngine On
RewriteBase /
RewriteRule ^index\.php$ - [L]
RewriteCond %{REQUEST_FILENAME} !-f
RewriteCond %{REQUEST_FILENAME} !-d
RewriteRule . /index.php [L]
答案 0 :(得分:0)
我发现,如果我首先使用html
RewriteCond
RewriteRule
排除.
个文件,我就不需要将\.
视为RewriteEngine On
RewriteBase /
RewriteRule ^index\.php$ - [L]
RewriteCond %{REQUEST_URI} !\.(html)$
RewriteRule ^druckfrisch_(.+)$ /druckfrisch_$1.html [L,R]
RewriteCond %{REQUEST_FILENAME} !-f
RewriteCond %{REQUEST_FILENAME} !-d
RewriteRule . /index.php [L]
在规则的第二部分。
#!/usr/bin/python
# coding=utf-8
from scrapinghub import ScrapinghubClient
import unicodecsv as csv
import os
import logging
import pandas as pd
import datetime
import pickle
# Create and configure logger
LOG_FORMAT = "%(levelname)s %(asctime)s - %(message)s"
logging.basicConfig(level = logging.INFO,
format = LOG_FORMAT,
filemode = 'w')
logger = logging.getLogger()
logger.info("Starting downloading")
# Enter ScrapingHub
apikey = '........' # your API key as a string
client = ScrapinghubClient(apikey)
projectID = .......
project = client.get_project(projectID)
# # Give me a list of dictionaries with info (each for every spider i have)
spider_dicts_list = project.spiders.list()
for spider_dict in spider_dicts_list:
# # Extract from the list the id of my spider
spiderID = spider_dict["id"]
logger.info("Working with spider: " + spiderID)
# Get that spider and assign it to the object "spider"
spider = project.spiders.get(spiderID)
# Get a generator object for the jobs of that spider
jobs_summary = spider.jobs.iter()
# Generate all job keys using the generator object
job_keys = [j['key'] for j in jobs_summary]
for job_key in job_keys:
# Get the corresponding job from the key, as "job"
job = project.jobs.get(job_key)
# Check to see if the job was completed
if job.metadata.get(u'close_reason') == u'finished':
# Create an empty list that will store all items (dictionaries)
itemsDataFrame = pd.DataFrame()
for item_aggelia in job.items.iter():
# Save all items (dictionaries) to the DataFrame
itemsDataFrame = itemsDataFrame.append(item_aggelia, ignore_index=True)
job_key_name = job_key.split("/")[2]
# Export a pickle
# Check that the list is not empty
if not itemsDataFrame.empty:
for meta in job.metadata.iter():
if meta[0] == u"scrapystats":
timestamp = meta[1][u'finish_time']/1000.0
dt = datetime.datetime.fromtimestamp(timestamp)
filename = spiderID+" "+str(dt.year)+"-"+str(dt.month)+"-"+str(dt.day)+" "+str(dt.hour)+"_"+str(dt.minute)+"_"+str(dt.second)+" "+'Items.pickle'
directory = u"E:/Documents/OneDrive/4_Προγραμματισμός/Scrapy/Αγορά Ακινήτων/"+spiderID+u"/Αρχεία_pd.DataFrame"
os.chdir(directory)
with open(filename, 'w') as file:
pickle.dump(itemsDataFrame,file)
# Check for empty fields
colList = itemsDataFrame.columns.tolist()
for col in colList:
if itemsDataFrame[col].isnull().all():
logger.warning("Found Null Field, in job " + job_key_name +": " + col)
# Delete the job from ScrapingHub
logger.debug("Deleting job " + job_key_name)
job.delete()
else:
logger.info("Found a job that didn't finish properly. Job key: " + job_key+". close_reason:" + job.metadata.get(u'close_reason'))