def main():
print("Enter search query")
query = raw_input()
q = link_extractor.main(query)
print "HTML data extracted"
summary.main(query)
def main():
parse.main()
wait_enter()
search.main()
wait_enter()
test.main()
wait_enter()
summary.main()
def summary_para(inputfile):
name, ext = inputfile.split(".");
summaryfile = name+"_summary.txt"
if os.path.exists(summaryfile):
os.remove(summaryfile)
try:
fi = open(inputfile, 'r',encoding="utf8")
contents = fi.read()
except Exception as e:
fi = open(inputfile, 'r')
contents = fi.read()
for para in paragraphs(contents):
try:
summary.main(summaryfile, para)
except Exception as e:
pass
fi.close()
def summary_para(inputfile):
#uses summary class to find generate filename_summary.txt(summary of the pdf/word )
name, ext = inputfile.split(".")
summaryfile = name + "_summary.txt"
if os.path.exists(summaryfile):
os.remove(summaryfile)
try:
fi = open(inputfile, 'r', encoding="utf8")
contents = fi.read()
except Exception as e:
fi = open(inputfile, 'r')
contents = fi.read()
for para in paragraphs(contents):
try:
summary.main(summaryfile, para)
except Exception as e:
pass
fi.close()
def main(argv):
"""
同じディレクトリのhtmlファイルをすべて変換
"""
outDir = 'result/'
inpFiles = '*.htm'
# ドロップファイルした時のカレントディレクトリがwindows/system32などになっているので、
# スクリプトのあるディレクトリに移動しておく
os.chdir(os.path.abspath(os.path.dirname(__file__)))
if len(argv)==0:
iafiles = glob.glob(inpFiles)
else:
iafiles = argv
print " Found %d files" % (len(iafiles))
ifiles = []
for j in iafiles:
ifiles.append(os.path.basename(j))
if len(ifiles)<=0:
print "No file(s) : " + inpFiles
raw_input()
sys.exit(0)
pfiles = []
for fname in ifiles:
f = str('"'+str(fname)+'"')
pfiles.append(convMT4TestReportHTML2.do_conv(f,outDir))
#------------------------------------------------------
import summary
print 'OutputDirectory: ' + str(outDir)
summary.main([outDir])
#print "\n*** pfiles ***\n"
#print pfiles
import analyzeReport
for f in pfiles:
print f
analyzeReport.main(["-o",outDir,"-i",f[1],f[0]+".htm"])
def run(sc, sql_context, isHive):
mat.main(sc, sql_context, isHive=True)
summary.main(sc, sql_context, isHive=True)
import runexp
import testexp
import summary
memo = "multi_phase/sumo/pipeline"
runexp.main(memo)
print("****************************** runexp ends (generate, train, test)!! ******************************")
summary.main(memo)
print("****************************** summary_detail ends ******************************")
def run(sc, sql_context, isHive):
mat.main(sc, sql_context, isHive = True)
summary.main(sc, sql_context, isHive = True)
import pareTo import trendChart import summary p, month = pareTo.main() trd = trendChart.main(p, month) summary.main(trd, month)
def _close_db():
_conn.commit()
_conn.close()
summary.main()
index = 0
r = randint(0, len(current[index]) - 1)
#print(r)
#print(current[index][r])
ans = input()
pos, neg = sentiment2.predict(ans)
#print("\nPositive: "+pos+"\nnegative: "+neg)
answers.append(ans)
stage.append(ans)
if (pos > neg):
r2 = randint(0, len(current[index + 1]) - 1)
print(current[index + 1][r2])
ans2 = input()
answers.append(ans2)
stage.append(ans2)
else:
r3 = randint(0, len(current[index + 2]) - 1)
print(current[index + 2][r3])
ans3 = input()
answers.append(ans3)
stage.append(ans3)
stage = ' '.join(stage)
pos, neg = sentiment2.predict(stage)
#print("\nPositive: "+pos+"\nnegative: "+neg)
answers = '\n'.join(answers)
summary.main(answers)