def set_form(patient_id,search_text):
forward_args = request.args.to_dict(flat=False)
forward_args['_format'] = 'json'
forwarded_url = 'Patient' + '/' + patient_id
#api_url = '/neprivacy/%s?%s'% (forwarded_url, urlencode(forward_args, doseq=True))
api_url='/%s?%s'% (forwarded_url, urlencode(forward_args, doseq=True))
api_resp = api_call(api_url)
json_file = api_resp.json()
#json_file is the user info we get from the server
cross_loc = TextFilter(patient_id,search_text)
# First scan the observation data to locate specific observation result
cross_loc.get_observation_list()
#Then to locate the genetic info(i.e. Sequence Resource) in the data base
#cross_loc.observation_prune()
cross_loc.get_genetic_info()
print cross_loc.filtered_Observation
patient_info_form,patient_info_class,observed,sequence = init_setting(json_file,cross_loc.filtered_Observation, cross_loc.correlated_genetic)
#with the json file we now get from and class
if patient_info_form.validate_on_submit():
print observed
patient_private,ob_private,seq_private = pe.get_private_profile(patient_info_form,patient_info_class,observed,sequence,json_file)
# now we get the private profile
#print type(private_profile)
#if 'id' in private_profile:
# private_profile['resourceID'] = private_profile['id']
# del private_profile['id']
'''
resp = requests.put('%s/%s' %(PRIVACY_BASE,patient_private['resourceID']), data=json.dumps(patient_private), headers={'Content-Type': 'application/json'})
for ob in cross_loc.filtered_Observation:
ob_private['resourceID']=ob['id']
resp_ob = requests.put('%s/%s' %(PRIVACY_BASE,ob_private['resourceID']), data=json.dumps(ob_private), headers={'Content-Type': 'application/json'})
if resp_ob.status_code == 404:
return STATUS_ERROR
resp_ob = requests.put('%s/%s' %(PRIVACY_BASE,ob_private['resourceID']), data=json.dumps(ob_private), headers={'Content-Type': 'application/json'})
for seq in seq_private:
resp_seq = requests.put('%s/%s' %(PRIVACY_BASE,seq['resourceID']), data=json.dumps(seq), headers={'Content-Type': 'application/json'})
if resp_seq.status_code ==404:
return STATUS_ERROR
if resp.status_code == 404 :
return STATUS_ERROR
else:
'''
return json.dumps(ob_private,indent=4);
#return render_template('temp.html',result = {"Patient":resp.json(), "Observation": resp_ob.json(), "Sequence": resp_seq.json()})
#return redirect('/doctor')
return render_template('rebuild_set.html',form = patient_info_form,patient_info = patient_info_class,observation=observed,sequences= sequence)
class PWID(object):
"""
Finds passwords that are characters and digits, and are at least 8 characters long.
Basic regex also includes special characters except spaces.
"""
PW_MIN_LENGTH = 8
PW_MAX_LENGTH = 48
filter = None
fast = False
generic_pw_pattern = '(\w+\d+[\w\d\S]+)|(\d+\w+[\w\d\S]+)'
# generic_pw_pattern = '([\w\d\S\$]{0,32})'
def __init__(self, **kwargs):
self.fast = kwargs.get('fast', self.fast)
self.re_pattern = re.compile(self.generic_pw_pattern)
self.filter = TextFilter()
def identify_passwords(self, str_input):
matches = self.re_pattern.findall(str_input)
prepared_matches = []
for match in matches:
for item in match:
passed_filtering = self.filter.apply_filter(item)
valid_length = self.PW_MIN_LENGTH <= len(
item) <= self.PW_MAX_LENGTH
if item and valid_length and passed_filtering:
prepared_matches.append(item)
logging.info("Filter Score: {}".format(self.filter.aggregate_score))
score_length_ratio = float(
self.filter.aggregate_score) / len(str_input)
logging.info("Score-Length Ratio: {}".format(score_length_ratio))
self.filter.aggregate_score = 0
return prepared_matches
def test(patient_id):
cross_loc = TextFilter(patient_id,'Lung cancer')
# First scan the observation data to locate specific observation result
cross_loc.get_observation_list()
#Then to locate the genetic info(i.e. Sequence Resource) in the data base
cross_loc.observation_prune()
cross_loc.get_genetic_info()
bundle = {
'resourceType': 'searchset',
'entry': [],
'is_single_resource': False
}
for v in cross_loc.filtered_Observation:
bundle['entry'].append({'resource':v})
print cross_loc.seq_id
for v in cross_loc.correlated_genetic:
bundle['entry'].append({'resource':v})
def test(patient_id):
cross_loc = TextFilter(patient_id,'Lung cancer')
# First scan the observation data to locate specific observation result
cross_loc.get_observation_list()
#Then to locate the genetic info(i.e. Sequence Resource) in the data base
cross_loc.observation_prune()
cross_loc.get_genetic_info()
bundle = {
'resourceType': 'searchset',
'entry': [],
'is_single_resource': False
}
for v in cross_loc.filtered_Observation:
bundle['entry'].append({'resource':v})
print cross_loc.seq_id
for v in cross_loc.correlated_genetic:
bundle['entry'].append({'resource':v})
#print cross_loc.correlated_genetic
return json.dumps(bundle,indent =4 )
def __init__(self, **kwargs):
self.fast = kwargs.get('fast', self.fast)
self.re_pattern = re.compile(self.generic_pw_pattern)
self.filter = TextFilter()
def doctor():
form = set_query_form()
if form.validate_on_submit():
keys = tp.extend_option(form)
#get the keys the doctor selected
forward_args = request.args.to_dict(flat=False)
forward_args['_format'] = 'json'
forwarded_url = 'Patient' + '/' + form.identifier.data
api_url = '/%s?%s'% (forwarded_url, urlencode(forward_args, doseq=True))
api_resp = api_call(api_url)
#print api_resp._content
raw_patient_file = json.dumps(api_resp.json())
resp = requests.get('%s/%s' %(PRIVACY_BASE,form.identifier.data), headers={'Content-Type': 'application/json'})
private_profile = json.loads(json.dumps(resp.json()))
try:
private_policy=[]
for k,v in private_profile['Resource'].items():
private_policy.append(v)
except:
private_policy=[{"Policy":"Nope","Policy_ResourceType":"NULL"}]
cross_loc = TextFilter(form.identifier.data, form.disease.data)
# First scan the observation data to locate specific observation result
cross_loc.get_observation_list()
#Then to locate the genetic info(i.e. Sequence Resource) in the data base
cross_loc.observation_prune()
cross_loc.get_genetic_info()
#print raw_patient_file
#print cross_loc.filtered_Observation
#print cross_loc.correlated_genetic
#print private_profile
#if resp.status_code == 404:
# return STATUS_ERROR
#json_data = pe.retrive_patient_info(keys,private_profile,raw_json_file);
#print cross_loc.filtered_Observation[0]
#private_policy = json.dumps(private_policy)
'''
try:
patient, observation, sequence = pe.retrive_patient_info(keys, private_policy, raw_patient_file, cross_loc.filtered_Observation[0] ,cross_loc.correlated_genetic)
except:
patient, observation, sequence = pe.retrive_patient_info(keys, private_policy, raw_patient_file, json.dumps({"message": "No result"}), cross_loc.correlated_genetic)
'''
#get the masked user info
#query_dict = json.loads(json_data)
#token needed, but now I don't konw how to get it
#user's id still in form.identifier.data
'''
return render_template('query_result.html',
token= 'Found',
json = json.dumps(query_dict,indent=4))
'''
#patient = json.loads(patient)
#print json.dumps(patient)
#print json.dumps(observation,indent= 4)
#print json.dumps(sequence,indent= 4)
print json.dumps(private_policy, indent= 4)
if(len(cross_loc.filtered_Observation)>0):
for observation in cross_loc.filtered_Observation:
resp = requests.get('%s/%s' %(PRIVACY_BASE,observation['id']), headers={'Content-Type': 'application/json'})
private_profile = json.loads(json.dumps(resp.json()))
print private_profile
try:
for k,v in private_profile['Resource'].items():
private_policy.append(v)
except:
pass
for seq in cross_loc.correlated_genetic:
resp = requests.get('%s/%s' %(PRIVACY_BASE,seq['id']), headers={'Content-Type': 'application/json'})
private_profile = json.loads(json.dumps(resp.json()))
try:
for k,v in private_profile['Resource'].items():
private_policy.append(v)
except:
pass
patient, observation,sequences = pe.display(keys, private_policy, raw_patient_file, cross_loc.filtered_Observation ,cross_loc.correlated_genetic)
else:
patient, observation,sequences = pe.display(keys, private_policy, raw_patient_file, [], cross_loc.correlated_genetic)
#patient,observation = pe.display(selected_keys, private_profile, raw_json_patient,raw_ob,raw_seq)
return render_template('rebuild_show.html',patient_info = patient,observation = observation,sequences = sequences)
#return redirect('/patient_test/%s' % (form.identifier.data))
return render_template('submit.html',
form=form)
class PWID(object):
"""
Finds passwords that are characters and digits, and are at least 8 characters long.
Basic regex also includes special characters except spaces.
"""
PW_MIN_LENGTH = 8
PW_MAX_LENGTH = 48
MAX_STR_LEN = 1024
filter = None
fast = False
ultra_verbose = True
MAX_VERBOSE_ANALYSIS = 512
generic_pw_pattern = '((?=[A-Za-z0-9\@\#\$\%\^\&\+\=\-\!]*?\d)(?=[A-Za-z0-9\@\#\$\%\^\&\+\=\-\!]*?[A-Z])(?=[A-Za-z0-9\@\#\$\%\^\&\+\=\-\!]*?[a-z])[A-Za-z0-9\@\#\$\%\^\&\+\=\-\!]{8,32})([ \n\|:]|$)'
def __init__(self, **kwargs):
self.fast = kwargs.get('fast', self.fast)
self.ultra_verbose = kwargs.get('ultra_verbose', self.ultra_verbose)
self.re_pattern = re.compile(self.generic_pw_pattern)
self.filter = TextFilter()
def identify_passwords(self, str_input):
self.filter.aggregate_score = 0
log.debug("Finding matches...")
matches = self.re_pattern.findall(str_input)
log.debug("Done")
prepared_matches = []
log.debug("Searching Total: %s possible matches..." % len(matches))
# for match in matches:
for item, tail in matches:
passed_filtering = self.filter.apply_filter(item)
valid_length = self.PW_MIN_LENGTH <= len(
item) <= self.PW_MAX_LENGTH
if item and valid_length and passed_filtering:
prepared_matches.append(item)
logging.info("Filter Score: {}".format(self.filter.aggregate_score))
score_length_ratio = float(
self.filter.aggregate_score) / len(str_input)
logging.info("Score-Length Ratio: {}".format(score_length_ratio))
# If ultra-verbose, apply filters to ENTIRE text if something that looks like a password is found
if self.ultra_verbose and len(prepared_matches) > 0:
log.info(
'Using ultra verbose filter on entire text. This will affect aggregate score...'
)
self.filter.apply_filter(str_input[:self.MAX_VERBOSE_ANALYSIS])
return prepared_matches, self.filter.aggregate_score
