def run(): while True: for url in urls_to_crawl: print url proxy = False print '1 requests...' response = make_request(url, ip_list, browser_list, proxy) if not response: print 'fail...\n--------------------------------------' proxy = True t = 2 while not response: print '%d requests...' %t t += 1 response = make_request(url, ip_list, browser_list, proxy) print 'requests succeed...\n--------------------------------------' print 'parsing page...' item = spider.parse(response) print 'collecting into database...' pipelines.process_item(item) print 'finish this page\n--------------------------------------'
def storePageAndHeader ( url, webPage, headerInfo, itemName, itemType ):
"""
Adds reford for url, item, and urlToItem tables in database.
Writes webPage, header, and tokens to files.
"""
title, tokens = spider.parse( webPage, args.tokenizer )
lowerTokens = spider.lower( tokens )
stemTokens = spider.stem( lowerTokens, args.stemmer )
reStr = "content-type:(?P<ct>(.*))"
result = re.search( reStr, headerInfo, re.IGNORECASE )
if not title:
title = ""
urlId = db.insertCachedUrl( url, result.group( "ct" ), title )
itemId = db.insertItem( itemName, itemType )
u2iId = db.insertUrlToItem( urlId, itemId )
fileNum = makeFileName( urlId )
writeToFile( "data/raw/" + fileNum + ".html", webPage )
writeToFile( "data/header/" + fileNum + ".txt", headerInfo )
writeToFile( "data/clean/" + fileNum + ".txt", stemTokens, True )
print( urlId )
def restoreClean ( ):
"""
Opens every file in data/raw directory, parsing, lowercasing,
and stemming. Stores results in data/clean directory.
"""
for htmlFileName in os.listdir( 'data/raw' ):
with open( 'data/raw/' + htmlFileName ) as htmlFile:
webPage = htmlFile.read( )
title, tokens = spider.parse( webPage, args.tokenizer )
lowerTokens = spider.lower( tokens )
stemTokens = spider.stem( lowerTokens, args.stemmer )
cleanFileName = htmlFileName.strip( '.html' )
writeToFile( "data/clean/" + cleanFileName + ".txt", stemTokens, True )
print( int(cleanFileName) )
def mine(settings,results): """ Converts string settings to its corresponding file and uses the data in it to construct a list of IDs to parse Then, sicks spider.py on that list And appends the results to string results' corresponding file """ assert type(settings) is str and type(results) is str settings = getSettings(settings) if not settings['debug'] and not settings['missing']: idList = getIDs(settings) else: idList =[] if settings['debug']: idList.append(getErrors(results)) if settings['missing']: idList.append(getMissing(results)) urls = constructURLs(settings,idList) for url in urls: data = spider.parse(url) appendData(data,results)
purchasing_person_name = re.findall("金额(.*?)<", content_xml,
re.M)[0]
except:
try:
purchasing_person_name = re.findall(
"中标价(.*?)中标", content, re.M)[0]
except:
purchasing_person_name = ''
return purchasing_person_name.replace("：", "").replace(":", "").strip()
if __name__ == '__main__':
spider = MySpider()
spider.proxy_enable = False
spider.init_dedup()
spider.init_downloader()
# ------------ parse() ----------
# print "开始登录"
url = "http://www.fjggzyjy.cn/news/23439/"
resp = spider.download(url)
res = spider.parse(resp, url)
# ------------ parse_detail_page() ----------
# url = "http://www.bidcenter.com.cn/zbpage-4-%E6%B1%9F%E8%8B%8F-1.html"
# resp = spider.download(url)
res = spider.parse_detail_page(resp, url)
for item in res:
for k, v in item.iteritems():
print k, v
def get():
isbnvalue = request.args.get('isbn')
bookdict = parse(isbnvalue)
return jsonify({'isbn':bookdict})
def bin(align_param_file, ref_ang_file, pref_image_in, pref_image_out, pref_sel, pref_sel_all,thres):
# read in the alignment parameters and the reference angles
# 1st column is psi, 2nd is theta, and 3rd is phi
align = spider.parse(align_param_file)
#align,header = format.read_alignment(align_param_file, ndarray=True)
print("Reconstructing %d particles"%len(align))
#assert(header[0]=='id')
# read in reference angles
refang = spider.parse(ref_ang_file)
index = align[:, 0].astype(np.int)
#refang, header = format.read_alignment(ref_ang_file, ndarray=True)
#assert(header[0]=='id')
# from degree to radian from column 1
align[:,1:4] = np.deg2rad(align[:,1:4])
refang[:,1:4] = np.deg2rad(refang[:,1:4])
# read in pref of images
iter_single_images = ndimage_file.iter_images(pref_image_in, index)
# form unit directional vectors
rphi = mcol(refang[:,3])
rtheta = mcol(refang[:,2])
unit_v = get_unitv(rphi,rtheta)
# 2-array to track indeces of particles in the same angle bin
# Max number of particles in the same angle bin
MAX = 5000
index = np.zeros((refang.shape[0],MAX))
# array to track the number of particles in each bin
quant = np.zeros((refang.shape[0]))
# binning: loop through particles
for i, img in enumerate(iter_single_images):
# direction of one particle
phi = align[i,3]
theta = align[i,2]
uv = get_unitv(phi,theta)
# read in image
#print i
#img = ndimage_file.read_image(img)
if theta > math.pi:
img = get_mirror(img)
ndimage_file.write_image(pref_image_out, img, i)
# multiply with all ref ang and store the largest
ip = np.dot(unit_v,uv.T)
# store the largest in the right bin
bin = ip.argmax()
index[bin,quant[bin]] = align[i,0]
quant[bin] += 1
#print index
# adjust the psi angle
rpsi = refang[bin,1]
rtheta = refang[bin,2]
rphi = refang[bin,3]
psi = adjust_psi(rpsi,rtheta,rphi,theta,phi)
align[i,1] = psi
# loop through the bins and keep only those with more than 'thres' particles
S = [] # will hold the selected bin numbers
count = 0
for j in range(refang.shape[0]):
sz = len(np.nonzero(index[j,:])[0])
if sz > thres:
table = index[j,0:sz]
#print table
filename = pref_sel + '{:05d}'.format(j)
spider.write(filename,table)
S.append(j)
#print S
spider.write(pref_sel_all,S)
