async def fetch():
s = smmrpy.SMMRPY('8B1BD1A777') # Instantiate the SMMRPY instance.
article = await s.get_smmry(
'https://edition.cnn.com/2018/05/11/middleeast/iran-israel-syria-intl/index.html'
)
print(article.title) # Print the title of the found article.
a = article.content
my_list = a.split(".")
for sent in my_list:
analyzer.analyze(sent)
def compare(testname, olddir, curdir, config_file='perf.conf', output_dir="./result.txt"):
config = ConfigParser.ConfigParser()
config.read(config_file)
result_file_pattern = config.get(testname, "result_file_pattern")
def search_files(dir):
cmd = 'find %s|grep "%s.*/%s"' % (dir, testname, result_file_pattern)
print cmd
return commands.getoutput(cmd)
oldlist = search_files(olddir)
newlist = search_files(curdir)
if oldlist != "" or newlist != "":
analyzer.analyze(oldlist, newlist, output_dir)
def make_freq(file):
"""テキストファイルを読み込んで形態素解析結果を返す
戻り値 : 解析結果を格納した多重リスト
"""
print('テキストを読み込んでいます...')
with open(
file, # ファイル名を指定
'r', # 読み取り専用で開く
encoding='utf_8' # エンコード方式を指定
) as f:
text = f.read() # 全データをtextに格納
text = re.sub('\n', '', text) # 文末の改行文字を取り除く
word_dic = {} # 語を保持するリスト
# ①形態素解析の結果をリストとして取得
analyze_list = analyzer.analyze(text)
# ②多重リストの要素を2つのパラメーターに取り出す
for wd, part in analyze_list:
# keyword_check()関数の戻り値がTrueの場合
if (analyzer.keyword_check(part)):
if wd in word_dic: # 辞書に語と同じキーがあるか
word_dic[wd] += 1 # キーの値に1加算
else: # 該当するキーがなければ
word_dic[wd] = 1 # 単語をキーにして値を1にする
return (word_dic) # 頻度表としての辞書を返す
def getOutput():
global filename
# check if the filename is not empty
if filename:
# clear the treeview first before putting any data
removeAll(lexemeTable)
removeAll(symbolTable)
# process the file
data = analyzer.analyze(filename)
# display the data in the treeview (lexeme and symbol table)
printLexeme(data[0])
printSymbols(data[1])
# this will print the output of the LOLcode file
textOut = ""
for text in data[2]:
textOut += text
outputText.config(state=NORMAL)
outputText.delete(1.0, END)
outputText.insert(END, textOut)
outputText.config(state=DISABLED)
else:
messagebox.showwarning("Message Box", "No File Selected!")
def SelectClassHeat(self, evt):
self.Debug('SelectClassHeat')
if evt is None:
cls, heat = self.class_heat
else:
cls, heat = self.recs[evt.GetSelection()]
self.class_heat = cls, heat
self.Info('Selected class %s heat %s' % (cls, heat))
if self.editwin:
self.sizer.Remove(self.editwin)
self.editwin.Destroy()
#reload(analyzer)
res = analyzer.analyze(heat, self.record[cls][heat],
self.scoringsystem)
self.editwin = EditWin1(self.record[cls][heat][0],
self.record[cls][heat][1],
res,
self.topparent,
self,
self.debug + (not not self.debug),
zoom=self.zoom,
seltime=self.seltime)
self.sizer.Add(self.editwin, 1, wx.EXPAND)
self.sizer.Layout()
def test():
logging.info("test: begin ...")
# test flow order
flow = [
'T', 'A', 'T', 'G', 'T', 'C', 'B', 'A', 'G', 'T', 'G', 'C', 'A', 'T',
'G', 'T', 'C', 'A', 'T', 'G', 'T', 'C', 'A'
]
# test sequence
sequence = [
'T', 'C', 'A', 'G', 'G', 'G', 'C', 'A', 'G', 'C', 'G', 'C', 'A', 'A',
'A', 'A', 'G', 'G', 'G', 'A', 'A', 'G', 'A', 'T', 'A', 'C', 'C', 'A',
'A', 'G', 'G', 'A', 'G', 'G', 'C', 'A', 'T', 'G', 'G', 'C', 'C', 'T',
'T', 'T', 'G', 'T', 'C', 'A', 'A', 'G', 'G', 'G', 'C', 'C', 'C', 'C',
'C', 'C', 'T', 'C', 'T', 'C', 'T', 'G', 'A', 'G', 'C', 'T', 'C', 'T',
'C', 'A', 'T', 'C', 'A', 'C', 'T', 'T', 'T', 'C', 'C', 'T', 'C', 'C',
'C', 'C', 'C'
]
# test analysis
number_of_incorporation = analyzer.analyze(flow, sequence)
# test incorporation output
logging.info(number_of_incorporation)
# test output plotting
plotter.plot(flow, number_of_incorporation, "Test")
logging.info("test: complete ...")
def intraday_working_hour_only(stock_symbols, crypto_symbols, date):
start_time = "{} 09:30:00".format(date)
end_time = "{} 16:00:00".format(date)
df = load_data(start_time, end_time, crypto_symbols, stock_symbols, True)
analysis = analyze(df, start_time, end_time,
stock_symbols + crypto_symbols)
print(analysis)
def find_route(source, dest):
""" Find path from source to dest via Wikipedia links """
curr = "https://en.wikipedia.org/wiki/" + source
order = [source] # links traversed
print(curr)
while True:
unseen_links = []
# Grab all links in page
page_links = link_grab.get_links(curr)
for link in page_links:
# Ensures no cycles
if link not in SEEN:
# only store links that have not been visited
unseen_links.append(link)
# Ensures the program does not get stuck
if not unseen_links: # all links on page have been visited
if curr.lower() == source.lower(): # have tracked back to source
print("Impossible to get there") # no source to dest path
sys.exit()
if curr in order:
order.remove(curr)
curr = order[-1] # this link was a bad choice, move back
continue
best_links = analyzer.analyze(list(unseen_links), dest)
step = best_links[0]
SEEN.append(step)
order.append(step)
curr = "https://en.wikipedia.org/wiki/" + step
print(curr)
if step.lower() == dest.lower(): # destination reached
print(order)
break
def run_analyzer(self, timeout=TIMEOUT_DEFAULT):
import analyzer
analysis_results = to_unicode(analyzer.analyze(self.testee))
try:
self.result.update(json.loads(analysis_results))
except ValueError:
self.result["status"] = analysis_results
def analyze(request):
pwd = settings.BASE_DIR
JSON_FILE = pwd + '/don/don.json'
params = {
'error_file': pwd + '/don/static/don.error.txt',
'test:all': True,
'test:ping': False,
'test:ping_count': 1,
'test:ovs': True,
'test:report_file': pwd + '/don/static/don.report.html',
}
analyzer.analyze(JSON_FILE, params)
#output = analyzer.analyze(JSON_FILE, params)
#html = '<html><body>Output: %s</body></html>' % output
#return HttpResponse(html)
return HttpResponseRedirect('/static/don.report.html')
def analyze(request):
pwd = settings.BASE_DIR
JSON_FILE = pwd + "/don/don.json"
params = {
"error_file": pwd + "/don/static/don.error.txt",
"test:all": True,
"test:ping": False,
"test:ping_count": 1,
"test:ovs": True,
"test:report_file": pwd + "/don/static/don.report.html",
}
analyzer.analyze(JSON_FILE, params)
# output = analyzer.analyze(JSON_FILE, params)
# html = '<html><body>Output: %s</body></html>' % output
# return HttpResponse(html)
return HttpResponseRedirect("/static/don.report.html")
def compare(testname,
olddir,
curdir,
config_file='perf.conf',
output_dir="./result.txt"):
config = ConfigParser.ConfigParser()
config.read(config_file)
result_file_pattern = config.get(testname, "result_file_pattern")
def search_files(dir):
cmd = 'find %s|grep "%s.*/%s"' % (dir, testname, result_file_pattern)
print cmd
return commands.getoutput(cmd)
oldlist = search_files(olddir)
newlist = search_files(curdir)
if oldlist != "" or newlist != "":
analyzer.analyze(oldlist, newlist, output_dir)
def run_bot(r):
for mention in r.inbox.unread(limit=10):
if (mention.was_comment):
target = mention.parent().author
if (target.name != config.username):
countP = 0
countN = 0
ratio = 0
#summarize target comment history sentiment
for comment in r.redditor(
target.name).comments.new(limit=None):
sentiment = analyze(comment.body)
if (sentiment == 1):
countP += 1
elif (sentiment == -1):
countN += 1
if (countN + countP != 0):
ratio = countP / (countN + countP)
print('countP: ' + str(countP))
print('countN: ' + str(countN))
print('ratio: ' + str(ratio))
#Build comment reply
graph = "##👿 <"
for i in range(10):
if (ratio <= (i + 1) / 10 and ratio >= (i) / 10):
graph += " x "
else:
graph += " - "
graph += "> 😇 "
reply = "You have summoned the **Thought-Police-Bot** to investigate /u/" + target.name + "\n\n"
reply += graph + "\n\n"
if (ratio > 0.80):
reply += "/u/" + target.name + " passes the investigation with an impressively wholesome rating."
elif (ratio > 0.6):
reply += "/u/" + target.name + " passes the investigation respectably."
elif (ratio > 0.45):
reply += "/u/" + target.name + " passes the investigation... but just barely."
elif (ratio > 0.2):
reply += "/u/" + target.name + " has failed the investigation!"
else:
reply += "/u/" + target.name + " has failed the investigation with a highly toxic rating!"
try:
mention.reply(reply)
except Exception:
print("Error replying - PRAWException")
else:
print("Skipped")
mention.mark_read()
time.sleep(5)
def analyze(request):
# pwd = settings.BASE_DIR
pwd = settings.ROOT_PATH
JSON_FILE = pwd + '/don/ovs/don.json'
params = {
'error_file': pwd + '/don/templates/don/don.error.txt',
'test:all': True,
'test:ping': False,
'test:ping_count': 1,
'test:ovs': True,
'test:report_file': pwd + '/don/templates/don/don.report.html',
}
print "params ====> ", params
analyzer.analyze(JSON_FILE, params)
# output = analyzer.analyze(JSON_FILE, params)
# html = '<html><body>Output: %s</body></html>' % output
# return HttpResponse(html)
# return HttpResponseRedirect('/static/don.report.html')
return render(request, "don/ovs/analyze.html")
def runScrapper(source, e, queue): # Button press function
if source in source_functions:
print("Started ", source, " Extraction")
fileToAnalyze = source_functions[source]()
print("Finished extraction")
e.set() # Done extraction
time.sleep(0.4) # To ensure progress bar shows done
e.clear() # reset flag
print("Calling Analyzer on file ", fileToAnalyze)
output_file = analyzer.analyze(fileToAnalyze)
time.sleep(0.2)
e.set() # Done analysis
queue.put(output_file)
print("Done Analysis")
else:
# Custom Headline
output_file = analyzer.analyze(source) # Analyze custom headline file
e.set() # Done analysis
queue.put(output_file)
def classify_tweet(c, tweet):
cities, transportations = analyze(tweet['text'])
if len(cities) > 0 or len(transportations) > 0:
update(c, tweet['id'], {
'cities': cities,
'transportations': map(serialize_transport, transportations),
'confirmedAsOffer': True
})
print ('Updated a tweet.')
else:
print ('Ignored the update')
def post(self):
actual_text = request.json['actual_text']
optimal_text = request.json['optimal_text']
sentiment_analysis, targetting_analysis = analyze(
actual_text, optimal_text)
print(sentiment_analysis)
print(targetting_analysis)
return {
'sentiment_analysis': str(sentiment_analysis),
'targetting_analysis': str(targetting_analysis),
}
def featuresScreenTimerFired(data):
# if cannot complete analysis, direct user to load screen
if data.analysisInProgress:
try:
data.results = a.analyze(data.filename, data.features)
data.analysisInProgress = False
data.mode = "analyzeScreen"
except Exception as e:
print(e)
data.analysisInProgress = False
data.mode = "loadDataScreen"
def analyze(request):
# pwd = settings.BASE_DIR
pwd = settings.ROOT_PATH
JSON_FILE = pwd + '/don/ovs/don.json'
params = {
'error_file' : pwd + '/don/templates/don/don.error.txt',
'test:all' : True,
'test:ping' : False,
'test:ping_count' : 1,
'test:ovs' : True,
'test:report_file' : pwd + '/don/templates/don/don.report.html',
}
print "params ====> ",params
analyzer.analyze(JSON_FILE, params)
#output = analyzer.analyze(JSON_FILE, params)
#html = '<html><body>Output: %s</body></html>' % output
#return HttpResponse(html)
# return HttpResponseRedirect('/static/don.report.html')
return render(request,"don/ovs/analyze.html")
def upload_file():
if request.method == 'POST':
f = request.files['the_file']
destination = os.path.join(app.config['UPLOAD'], f.filename)
f.save(os.path.join(app.config['UPLOAD'], f.filename))
# Add analyze code
output = a.analyze(destination)
print(output)
return output
def schemeLoad(self, cont, env, args):
"""Special primitive: implements LOAD."""
symbolicFilename = str(args[0])
try:
f = open(symbolicFilename)
try:
text = "(begin \n%s\n 'ok)" % f.read()
finally:
f.close()
expandedExp = self.get_expander().expand(parser.parse(text))
analyzedExp = analyzer.analyze(expandedExp)
return analyzer.texec(analyzedExp, env, cont)
except IOError, e:
raise error.SchemeError, "LOAD error -- %s" % str(e)
def runScrapper(source, e, queue):
if source in source_functions:
print("Started ", source, " Extraction")
fileToAnalyze = source_functions[source]()
print("Finished extraction")
# Set sync flag to done
e.set()
# To ensure progress bar shows done
time.sleep(0.4)
# Reset sync done flag before calling analyzer
e.clear()
print("Calling Analyzer on file ", fileToAnalyze)
output_file = analyzer.analyze(fileToAnalyze)
# Done analysis, set flag
e.set()
# Store the file name where the analyzer stored it's scores
queue.put(output_file)
print("Done Analysis")
else:
# Custom Headline
output_file = analyzer.analyze(source)
e.set() # Done analysis
queue.put(output_file)
def schemeLoad(self, cont, env, args):
"""Special primitive: implements LOAD."""
symbolicFilename = str(args[0])
try:
f = open(symbolicFilename)
try:
text = "(begin \n%s\n 'ok)" % f.read()
finally:
f.close()
expandedExp = self.get_expander().expand(parser.parse(text))
analyzedExp = analyzer.analyze(expandedExp)
return analyzer.texec(analyzedExp, env, cont)
except IOError, e:
raise error.SchemeError, "LOAD error -- %s" % str(e)
def analyze_result(self, version, spectra_list, fault_list, formula):
# print('spectra len to analyze : %s' % len(spectra_list))
spectra_list.sort(reverse=True)
# print_spectra(version.cal_result_dir(formula), spectra_list)
# analyzer.count_fault_rank(fault_list, spectra_list)
self.ranker(fault_list, spectra_list, version)
fault_result_list = [fault_now.to_dict() for fault_now in fault_list]
# analyze_judgements = ['EXAM']
result_dict = {'project': version.name(), 'no': int(version.no())}
to_exclude = version.return_spectra_exclude() if self.exclude_blank else []
for analyze_judgement in self.analyze_judgements:
result_dict[analyze_judgement] = analyzer.analyze(
analyze_judgement, spectra_list, fault_list, to_exclude)
# print('finish analyze')
return fault_result_list, result_dict
def main():
logging.info("main: begin ...")
# reading the sequence from the fasta file
sequence = fastareader.read_sequence()
# reading the flow order
flow_order_map = h5reader.read_flow_order()
# for each flow order do the following
for flow_order in flow_order_map:
logging.info("For flow order: " + flow_order)
# getting the list against the key
flow = flow_order_map.get(flow_order)
# passing in the flow and the sequence to get the number on incorporation for the current flow order
number_of_incorporation = analyzer.analyze(flow, sequence)
# plot the output with the current flow order
plotter.plot(flow, number_of_incorporation, flow_order)
logging.info("main: complete ...")
def detect(data, channel):
try:
response = {
'id': data['id'],
'status': 'processing',
'result': {},
'fullname': data['fullname'],
}
channel.basic_publish(exchange='',
routing_key='detection-response',
body=json.dumps(response))
print(data)
file_params = analyzer.analyze(data['fullname'])
params_array = np.array(file_params, dtype=np.float32).reshape(1, -1)
transformed_params = sc.transform(params_array)
# prediction = classifier.predict(transformed_params)
probs = classifier.predict_proba(transformed_params)
best_n = np.argsort(probs, axis=1)
print(probs)
print(best_n)
response = {
'id': data['id'],
'status': 'finished',
'result': {
"probs": probs[0].tolist(),
},
'fullname': data['fullname'],
}
channel.basic_publish(exchange='',
routing_key='detection-response',
body=json.dumps(response))
except:
response = {
'id': data['id'],
'status': 'failed',
'result': {},
'fullname': data['fullname'],
}
channel.basic_publish(exchange='',
routing_key='detection-response',
body=json.dumps(response))
def analyze_code(pythonfile):
# transform to cfg
cfg, g = transform.transformToCFG('./uploads/' + pythonfile)
start_time = time.time()
# analyze broken authentication
vulnerabilities, count_node = analyzer.analyze(cfg, g,
'./uploads/' + pythonfile)
end_time = time.time()
# analyze time in second
exec_time = end_time - start_time
# visualize output
visualize.createImage(g, pythonfile)
return vulnerabilities, exec_time * 1000, count_node
def runScrapperDate(source, e, queue, year, month, day):
name_functions = {
"guardian": guardianScrapperDate,
"new-york-times": nyTimesScrapperDate,
"times-of-india": toiScrapperDate
}
if source in name_functions:
print("Started ", source, " Extraction")
fileToAnalyze = name_functions[source](str(year), str(month), str(day))
print("Calling Analyzer on file ", fileToAnalyze)
output_file = analyzer.analyze(fileToAnalyze)
e.set()
queue.put(output_file)
print("Done Analysis")
else:
e.set()
pass
def analyzerhtml(tmpfilename, htmlfilename, execpath, reqspath, aaffiles):
if not len(aaffiles) > 0:
print "empty AAF file list, no action taken"
return
(files, removedFiles) = analyzer.analyze(tmpfilename, execpath, aaffiles,
reqspath)
files = ['File Set'] + files
# Run the analyzer to generate a detailed requirement listing
reqsDetailCmdArgs = [
execpath, "-report", "-detail", "-type", "all", "-reqs", reqspath
]
reqsDetailPipe = subprocess.Popen(reqsDetailCmdArgs,
stdout=subprocess.PIPE,
stderr=None)
# Run the analyzer to generate a list of requirements that are covered
# by test implementations.
reqsCovCmdArgs = [execpath, "-report", "-testcoverage", "-reqs", reqspath]
reqsCovPipe = subprocess.Popen(reqsCovCmdArgs,
stdout=subprocess.PIPE,
stderr=None)
# Parse the detailed requirement listing and the coverage listing.
requirements = parse.parse_requirements(reqsDetailPipe.stdout,
reqsCovPipe.stdout)
parse.parse_file_coverage(tmpfilename, requirements)
for i in range(0, len(files)):
if sys.platform == 'win32' or sys.platform == 'cygwin':
files[i] = files[i].split('\\')[-1]
else:
files[i] = files[i].split('/')[-1]
# Parse the test result data to generate the result table and output
# the table in html
testResults = parse.get_result_data(files, requirements)
parse.write_html(htmlfilename, testResults, requirements, removedFiles)
print "succesfully wrote html file:", htmlfilename
def report(repo_url):
repo = create_repository(repo_url)
if repo is None:
flash('Given repository does not exists or could not be accessed')
return redirect(url_for('index'))
if is_cached(repo):
results = mongo.db.repositories.find_one({'url': repo.url})
else:
path = clone(repo)
results = analyze(path)
repo.save_analysis_results(results)
cache(repo)
clear(path)
results = repo.to_document()
return render_template('report/results.html', report=results)
def main():
p = argparse.ArgumentParser()
p.add_argument('rootdir', metavar='rootdir', nargs='?', default='.', help='the directory to scan (optional: default is the current directory)')
args = p.parse_args()
root = os.path.abspath(args.rootdir)
sanity.ensure(root)
files = scanner.scan(root)
defs = list(parser.parse(root, files))
fix_methods = False
if fix_methods:
results = analyzer.analyze(root, files, defs)
fixer.fix_method_declarations(root, defs, results)
else:
a2 = analyzer.analyze2(root, files, defs)
fixer.fix2(root, defs, files, a2)
def dialogue(self, input):
"""
マルコフ連鎖によって生成された文章群から
ユーザーの発言に含まれる名詞を含むものを抽出して応答メッセージとして返す。
Parameters:
input(str) :ユーザーによって入力された文字列。
Returns:
str: 応答メッセージ。
"""
# インプット文字列を形態素解析
parts = analyzer.analyze(input)
m = [] #
# 解析結果の形態素と品詞に対して反復処理
for word, part in parts:
# インプット文字列に名詞があればそれを含むマルコフ連鎖文を検索
if analyzer.keyword_check(part):
#print('afetr_check_word===',word)
# マルコフ連鎖で生成した文章を1つずつ処理
for element in self.sentences:
# 形態素の文字列がマルコフ連鎖の文章に含まれているか検索する
# 最後を'.*?'にすると「花」のように検索文字列だけにもマッチ
#
# + '.*'として検索文字列だけにマッチしないようにする
#
find = '.*?' + word + '.*'
# マルコフ連鎖文にマッチさせる
tmp = re.findall(find, element)
if tmp:
# マッチする文章があればリストmに追加
m.append(tmp)
# findall()はリストを返してくるので多重リストをフラットにする
m = list(chain.from_iterable(m))
if m:
# インプット文字列の名詞にマッチしたマルコフ連鎖文からランダムに選択
return random.choice(m)
else:
# マッチするマルコフ連鎖文がない場合
return random.choice(self.sentences)
def SelectClassHeat(self,evt):
self.Debug('SelectClassHeat')
if evt is None:
cls, heat = self.class_heat
else:
cls, heat = self.recs[evt.GetSelection()]
self.class_heat = cls, heat
self.Info('Selected class %s heat %s'%(cls,heat))
if self.editwin:
self.sizer.Remove(self.editwin)
self.editwin.Destroy()
#reload(analyzer)
res = analyzer.analyze(heat,self.record[cls][heat],self.scoringsystem)
self.editwin = EditWin1(self.record[cls][heat][0],self.record[cls][heat][1],
res,
self.topparent,self,self.debug+(not not self.debug),
zoom = self.zoom, seltime=self.seltime)
self.sizer.Add(self.editwin,1,wx.EXPAND)
self.sizer.Layout()
def main(self, analyzer):
offset = 6
isFinished = False
isNewTime = True
self.getOptions()
tools = ["iperf", "scp"]
if not os.path.exists(self.uriTime):
print('WARN! Create a timeRead file!')
sys.exit(0)
timeRead = self.readTimeRead(self.uriTime)
timeR = timeRead.split(",")
timeRNew = timeRead
while (not isFinished):
fileLines, isFinished = self.readLog(self.uriLog)
for i in range(len(fileLines) - 1, 0, -1):
#print(line)
result = analyzer.analyze(fileLines[i], tools)
if result[0]:
if self.check(result, timeR, offset):
isFinished = True
break
if isNewTime:
timestampNew = self.splitStr(result[1], ' ', offset)
timeRNew = result[2] + "," + timestampNew
isNewTime = False
print self.combi(result[1], result[2])
self.excuteShell(self.combi(result[1], result[2]))
self.closeFile()
print(timeRNew)
with open(self.uriTime, 'w') as timeReadFile:
timeReadFile.write(timeRNew)
def main(self, analyzer):
offset = 6
isFinished = False
isNewTime = True
self.getOptions()
tools = ["iperf", "scp"]
if not os.path.exists(self.uriTime):
print('WARN! Create a timeRead file!')
sys.exit(0)
timeRead = self.readTimeRead(self.uriTime)
timeR = timeRead.split(",")
timeRNew = timeRead
while(not isFinished):
fileLines, isFinished = self.readLog(self.uriLog)
for i in range (len(fileLines) - 1, 0, -1):
#print(line)
result = analyzer.analyze(fileLines[i], tools)
if result[0]:
if self.check(result, timeR, offset):
isFinished = True
break
if isNewTime:
timestampNew = self.splitStr(result[1], ' ', offset)
timeRNew = result[2] + "," + timestampNew
isNewTime = False
print self.combi(result[1], result[2])
self.excuteShell(self.combi(result[1], result[2]))
self.closeFile()
print(timeRNew)
with open(self.uriTime, 'w') as timeReadFile:
timeReadFile.write(timeRNew)
def analyzerhtml(tmpfilename, htmlfilename, execpath, reqspath, aaffiles):
if not len(aaffiles) > 0:
print "empty AAF file list, no action taken"
return
(files, removedFiles) = analyzer.analyze(tmpfilename, execpath, aaffiles, reqspath)
files = ["File Set"] + files
# Run the analyzer to generate a detailed requirement listing
reqsDetailCmdArgs = [execpath, "-report", "-detail", "-type", "all", "-reqs", reqspath]
reqsDetailPipe = subprocess.Popen(reqsDetailCmdArgs, stdout=subprocess.PIPE, stderr=None)
# Run the analyzer to generate a list of requirements that are covered
# by test implementations.
reqsCovCmdArgs = [execpath, "-report", "-testcoverage", "-reqs", reqspath]
reqsCovPipe = subprocess.Popen(reqsCovCmdArgs, stdout=subprocess.PIPE, stderr=None)
# Parse the detailed requirement listing and the coverage listing.
requirements = parse.parse_requirements(reqsDetailPipe.stdout, reqsCovPipe.stdout)
parse.parse_file_coverage(tmpfilename, requirements)
for i in range(0, len(files)):
if sys.platform == "win32" or sys.platform == "cygwin":
files[i] = files[i].split("\\")[-1]
else:
files[i] = files[i].split("/")[-1]
# Parse the test result data to generate the result table and output
# the table in html
testResults = parse.get_result_data(files, requirements)
parse.write_html(htmlfilename, testResults, requirements, removedFiles)
print "succesfully wrote html file:", htmlfilename
def schemeEval(self, cont, env, args):
expandedExp = self.get_expander().expand(args[0])
analyzedExp = analyzer.analyze(expandedExp)
return analyzer.texec(analyzedExp, env, cont)
def handle(filename):
sdpdata = sdpdatafile.SdpDataFile(filename)
log = simplelogger.SimpleLogReader(sdpdata.logfilename)
logw = simplelogger.SimpleLogWriter('sub', sdpdata.logfilename)
status = log.getstatus()
if status == 'concluded':
inlineprint('all done.')
elif status is None or status == 'tosubmit':
inlineprint('submitting...')
submit(sdpdata)
handle(filename)
elif status == 'failed':
if args.force:
inlineprint('failed; forced resubmission...')
submit(sdpdata)
handle(filename)
else:
inlineprint('failed.')
elif status == 'submitted' or status == 'running':
inlineprint('submitted.')
if args.reallyrunning:
inlineprint('checking...')
submissionid = log.lastbonusexprwith(expr='submissionid')
if world.isreallyrunning(submissionid):
inlineprint('is really running.')
else:
inlineprint('is NOT really running:')
logw.setstatus('failed')
handle(filename)
if args.pause:
inlineprint('waiting for completion...')
submissionid = log.lastbonusexprwith(expr='submissionid')
world.waitforcompletion(submissionid)
inlineprint('completed.')
handle(filename)
elif status == 'finished':
tr = log.lastbonusexprwith(expr='terminateReason')
primopt = log.lastbonusexprwith(expr='primalObjective')
if tr == 'maxRuntime exceeded' or \
tr == 'maxIterations exceeded':
inlineprint('ran out of time.')
if args.maxsubmissions and \
log.numlineswith(expr='status', bonusexpr='submitted') >= \
args.maxsubmissions:
inlineprint('too many submissions to resubmit.')
logw.write('too many submissions.')
logw.setstatus('failed')
handle(filename)
else:
inlineprint('resubmitting... ')
submit(sdpdata)
handle(filename)
else: # i.e. terminateReason is not timed out
try:
newfilename = analyzer.analyze(sdpdata, tr, primopt)
except ValueError:
logw.write('analyzer failed with ValueError')
logw.setstatus('failed')
inlineprint('could not analyze the result.')
handle(filename)
else:
logw.setstatus('concluded')
if newfilename is None:
inlineprint('done.')
elif newfilename == filename:
inlineprint('resubmitting according to analyzer...')
logw.setstatus('tosubmit')
handle(filename)
else:
print('replaced -->')
inlineprint(os.path.basename(newfilename) + ' :')
logw.write('replaced with', newfilename)
handle(newfilename)
else:
# How did you get here?
print('Unknown status for ' + filename + '!')
import downloader
import analyzer
import time
prefix = r'http://www.lingdiankanshu.com/html/0/175/'
url = r'75298.html'
n = 1
while True:
now = time.time()
soup = downloader.download(prefix + url)
if soup == None:
print('Finished or Error')
break
url = analyzer.analyze(soup)
print('Chapter',n,'finished in',time.time()-now,'seconds')
if url == None:
print('No found next!')
break
n = n + 1
#! /usr/bin/python
# -*- coding: utf-8 -*-
import sys, getopt, analyzer
# Usage:
# python runanalyzer.py coverage_file_to_create AAFAnalyzer_executable \
# file1.aaf file2.aaf file3.aaf ... AAFRequirements.xml
#
# where,
# coverage_file_to_create is the coverage file to generate
# AAFAnalyzer_executable is the location of the AAFAnalyzer executable
# AAFRequirements.xml is the location of the AAFRequirements.xml document
# file{1,2,3,...}.aaf are the .aaf files to be processed
analyzer.analyze( sys.argv[1], sys.argv[2], sys.argv[4:-1], sys.argv[3] )
def get_pretty_path_list(self):
return analyzer.analyze(self).get_pretty_path_list()
def get_pretty_path(self):
if settings.VERBOSE > 2:
print 'File.get_pretty_path()'
print 'Path from analyzer: %s' % analyzer.analyze(self).get_pretty_path()
return analyzer.analyze(self).get_pretty_path()
doObject = True
if len(args) != 2:
usage(stream=stderr)
return 1
name, filename, = args
import parser
import analyzer
import log
import codegen
log.setStreams(stdout=stdout, stderr=stderr)
parseTree = parser.parse(filename, debug=doDebug)
parseTree.name = name
analyzer.analyze(parseTree)
if doClient:
print >> stderr, 'Generating client ...'
codegen.genClient(parseTree, outdir=dirClient)
if doDBus:
codegen.genClientDBus(parseTree, outdir=dirClient)
if doTests:
codegen.genTests(parseTree, outdir=dirClient)
if doShell:
codegen.genShell(parseTree, outdir=dirClient)
if doObject:
codegen.genObject(parseTree, outdir=dirClient)
if doServer:
print >> stderr, 'Generating server ...'
codegen.genServer(parseTree, outdir=dirServer)
if doDBus:
def do_task_fetch_material(username, force_top):
user = CurryUser.get_by_key_name(username)
force_top = bool(int(force_top))
if not user:
logging.error("no such user '%s'" % username)
return 'bad'
tweet_list = api.GetUserTimeline(screen_name=username, count=config.FETCH_COUNT)
tweet = None
material_list = None
success = False
if force_top:
tweet_list = tweet_list[0:1]
else:
shuffle(tweet_list)
#
# select material
#
for tweet in tweet_list:
# check history
if not force_top and is_duplicated(tweet):
continue
text = tweet.GetText().encode('utf-8')
material_list = analyze(
text,
count=config.TWEET_MATERIAL_MAX
)
if len(material_list) > 0:
# found material
success = True
break
if success:
# record to history
# TODO: trim history chronically
History(
key_name=str(tweet.id),
timestamp=datetime.now()
).put()
else:
logging.info("material not found for user '%s'" % username)
return 'bad'
#
# select receivers
#
link_list = (UserLink
.all()
.filter('sender = ', user)
.order('timestamp')
.fetch(limit=config.RECEIVER_MAX)
)
for link in link_list:
# randomize material per receiver
shuffle(material_list)
count = 1 + int(random() * len(material_list))
receive_material = material_list[:count]
taskqueue.add(
queue_name='post-queue',
url='/task/post_material/%s/%s' % (username, link.receiver.key().name()),
params={'material': receive_material}
)
link.timestamp=datetime.now()
logging.debug("sending from user '%s' to '%s' with material '%s'" %
(username, link.receiver.key().name(), repr(receive_material)))
# update timestamp
db.put(link_list)
# send to karei_bot if no receivers
if len(link_list) == 0:
shuffle(material_list)
count = 1 + int(random() * len(material_list))
receive_material = material_list[:count]
taskqueue.add(
queue_name='post-queue',
url='/task/post_material/%s/%s' % (username, config.MY_NAME),
params={'material': receive_material}
)
logging.debug("sending from user '%s' to '%s' with material '%s'" %
(username, config.MY_NAME, repr(receive_material)))
return 'ok'
url = "https://www.nytimes.com/2017/09/29/us/politics/tom-price-trump-hhs.html"
outputFile = "summarized.txt"
freqFile = "wordFreq.txt"
#settings
PERCENT_SUMMARIZED = 15
LENGTH_ADJUSTMENT_FACTOR = 10
OPTIMAL_SENTENCE_LENGTH = 20
SENTENCE_LOCATION_FACTOR = 2
WORD_IN_TITLE_FACTOR = 20
#run
extract = client.Extract({"url": url})
parse(extract.get('article').encode('ascii', 'xmlcharrefreplace'), "temp.txt")
parse(
extract.get('title').encode('ascii', 'xmlcharrefreplace'), "titleTemp.txt")
analyze(url, "temp.txt", "titleTemp.txt", outputFile, freqFile,
PERCENT_SUMMARIZED, LENGTH_ADJUSTMENT_FACTOR, OPTIMAL_SENTENCE_LENGTH,
SENTENCE_LOCATION_FACTOR, WORD_IN_TITLE_FACTOR)
def get_analyzer(self):
return analyzer.analyze(self)
