本文整理汇总了Python中werkzeug.datastructures.MultiDict.get方法的典型用法代码示例。如果您正苦于以下问题:Python MultiDict.get方法的具体用法?Python MultiDict.get怎么用?Python MultiDict.get使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类werkzeug.datastructures.MultiDict
的用法示例。
在下文中一共展示了MultiDict.get方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: from_params
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def from_params(params: MultiDict, items: int) -> 'Page':
# page, page-size, limit (deprecated)
page = params.get('page', 1, int)
limit = params.get('limit', 0, int)
page_size = params.get('page-size', limit, int)
return Page(page, page_size, items)
示例2: treat
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def treat():
global final_html
global df,df_train,df_test,test_train_created,origin_df
firstkey = False
secondkey = False
if request.method == 'POST':
try:
Listkey1 = list(MultiDict(request.form).values())
Listkey2 = MultiDict(request.form)
for key1 in Listkey1:
if(key1 == "Replace nulls,NAs with zeros"):
firstkey = True
secondkey = False
elif(key1 == "Custom: Enter values to replace"):
secondkey = True
firstkey = False
if(secondkey):
replace_str = str(Listkey2.get('changeval'))
for key1 in Listkey1:
if(key1 <> "Replace nulls,NAs with zeros" and key1 <> replace_str and key1 <> "Custom: Enter values to replace"):
df[key1].fillna(replace_str)
elif(firstkey):
replace_str = str(Listkey2.get('changeval'))
for key1 in Listkey1:
if(key1 <> "Replace nulls,NAs with zeros" and key1 <> replace_str and key1 <> "Custom: Enter values to replace"):
df[key1].fillna(0)
temp_df = df[1:15]
final_html = template.s1 + "<br>Null values were replaced!!<br><br></div>" + temp_df.to_html()
return final_html
except:
final_html = template.s1 + """<br><font color="lightcoral"> Something went wrong. Please try again !! <font><br><br></div>""" + df[1:15].to_html()
return final_html
return 'helloo'
示例3: treat
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def treat():
global final_html
global df,origin_df
chi_key = list()
firstkey = False
secondkey = False
if request.method == 'POST':
Listkey1 = list(MultiDict(request.form).values())
Listkey2 = MultiDict(request.form)
df1 = df
for key1 in Listkey1:
if(key1 == "Replace nulls,NAs with zeros"):
firstkey = True
secondkey = False
elif(key1 == "Custom: Enter values to replace"):
secondkey = True
firstkey = False
if(secondkey):
replace_str = str(Listkey2.get('changeval'))
for key1 in Listkey1:
if(key1 <> "Replace nulls,NAs with zeros" and key1 <> replace_str and key1 <> "Custom: Enter values to replace"):
df[key1].fillna(replace_str)
elif(firstkey):
replace_str = str(Listkey2.get('changeval'))
for key1 in Listkey1:
if(key1 <> "Replace nulls,NAs with zeros" and key1 <> replace_str and key1 <> "Custom: Enter values to replace"):
df[key1].fillna(0)
temp_df = df[1:15]
final_html = template.s1 + "</div><br>Null values were removed<br><br>" + temp_df.to_html()
return final_html
return 'helloo'
示例4: register
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def register():
data = MultiDict(mapping=request.json)
inputs = RegistrationForm(data, csrf_enabled=False)
if not inputs.validate():
return transform(300, message="Invalid inputs")
else:
firstName = data.get('first_name')
lastName = data.get('last_name')
email = data.get('email')
password = data.get('password')
user = User(email, password, firstName, lastName)
auth = AuthToken()
user.tokens.append(auth)
try:
db.session.add(user)
# db.session.add(auth)
db.session.commit()
except IntegrityError as e:
return jsonify({"error": "email already taken"})
response = auth.__repr__()
response.update({
'user_id': user.id,
'first_name': user.first_name,
'last_name': user.last_name
})
return jsonify(response)
示例5: cond1
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def cond1():
global final_html
global df,df_train,df_test,test_train_created,origin_df
between_key = False
great_key = False
less_key = False
column_key = ""
new_column_key = ""
df['decision'] = False
if request.method == 'POST':
try:
Listkey1 = list(MultiDict(request.form).values())
Listkey2 = MultiDict(request.form)
Listkey3 = MultiDict(request.form).keys()
for key1 in Listkey3:
if(key1 <> "upper_val" and key1 <> "lower_val" and key1 <> "Submit" and key1 <> "func"):
column_key = str(key1)
print "Column key",column_key
for key1 in Listkey1:
if(key1 == "between"):
between_key = True
great_key = False
less_key = False
elif(key1 == "greater than"):
between_key = False
great_key = True
less_key = False
elif(key1 == "less than"):
between_key = False
great_key = False
less_key = True
if(between_key):
upper_val = float(Listkey2.get('upper_val'))
lower_val = float(Listkey2.get('lower_val'))
new_column_key = "Dummy_"+ column_key + "_between_" + str(lower_val) + "_and_" + str(upper_val)
df['decision'] = Series((df[column_key] > lower_val) & (df[column_key] < upper_val))
elif(great_key):
upper_val = float(Listkey2.get('upper_val'))
new_column_key = "Dummy_"+ column_key + "_great_than_" + str(upper_val)
df['decision'] = Series(df[column_key] > upper_val)
elif(less_key):
upper_val = float(Listkey2.get('upper_val'))
new_column_key = "Dummy_"+ column_key + "_less_than_" + str(upper_val)
df['decision'] = Series(df[column_key] < upper_val)
df[new_column_key] = 0
df[new_column_key][df['decision']] = 1
df = df.drop('decision',1)
#print 'COL names',df.columns.values
temp_df = df[1:15]
final_html = template.s1 + "<br>New Dummy variables created based on condition <br><br></div>" + temp_df.to_html()
return final_html
except ValueError:
final_html = template.s1 + """<br><font color="lightcoral"> Please enter valid value </font><br><br></div>""" + df[1:15].to_html()
return final_html
except KeyError:
final_html = template.s1 + """<br><font color="lightcoral"> Please enter valid value </font><br><br></div>""" + df[1:15].to_html()
return final_html
return 'helloo'
示例6: documents_query
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def documents_query(args, fields=None, facets=True, newer_than=None):
"""Parse a user query string, compose and execute a query."""
if not isinstance(args, MultiDict):
args = MultiDict(args)
text = args.get('q', '').strip()
q = text_query(text)
q = authz_filter(q)
if newer_than is not None:
q = add_filter(q, {
"range": {
"created_at": {
"gt": newer_than
}
}
})
# Sorting -- should this be passed into search directly, instead of
# these aliases?
sort_mode = args.get('sort', '').strip().lower()
if text or sort_mode == 'score':
sort = ['_score']
elif sort_mode == 'newest':
sort = [{'dates': 'desc'}, {'created_at': 'desc'}, '_score']
elif sort_mode == 'oldest':
sort = [{'dates': 'asc'}, {'created_at': 'asc'}, '_score']
else:
sort = [{'updated_at': 'desc'}, {'created_at': 'desc'}, '_score']
# Extract filters, given in the form: &filter:foo_field=bla_value
filters = []
for key in args.keys():
for value in args.getlist(key):
if not key.startswith('filter:'):
continue
_, field = key.split(':', 1)
filters.append((field, value))
for entity in args.getlist('entity'):
filters.append(('entities.uuid', entity))
aggs = {}
if facets:
aggs = aggregate(q, args, filters)
aggs = facet_source(q, aggs, filters)
q = entity_collections(q, aggs, args, filters)
return {
'sort': sort,
'query': filter_query(q, filters),
'aggregations': aggs,
'_source': fields or DEFAULT_FIELDS
}
示例7: bin2
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def bin2():
global final_html
global df,origin_df
unique_count = 0
chi_key = list()
firstkey = ""
bin_val_fail = False
if request.method == 'POST':
Listkey1 = list(MultiDict(request.form).values())
Listkey2 = MultiDict(request.form)
bin_val = int(Listkey2.get('changeval'))
for key1 in Listkey1:
if(key1 <> "Bin the Columns" and key1 <> str(bin_val)):
k3 = set(df[key1])
unique_count = sum(1 for num in k3)
if(unique_count <= bin_val):
bin_val_fail = True
break
temp_bin_col = pd.qcut(df[key1],bin_val)
temp_col_name = key1 + "_bin"
df[temp_col_name] = Series(temp_bin_col.labels)
temp_df = df[1:15]
if(bin_val_fail):
final_html = template.s1 + "</div><br><br> Bin count is more than the number of categories in columns <br> " + temp_df.to_html()
else:
final_html = template.s1 + "</div><br>" + temp_df.to_html()
return final_html
return 'helloo'
示例8: peek_query
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def peek_query(args):
if not isinstance(args, MultiDict):
args = MultiDict(args)
text = args.get('q', '').strip()
q = text_query(text)
filters = parse_filters(args)
for entity in args.getlist('entity'):
filters.append(('entities.id', entity))
q = filter_query(q, filters, [])
q = add_filter(q, {
'not': {
'terms': {
'collection_id': authz.collections(authz.READ)
}
}
})
q = {
'query': q,
'size': 0,
'aggregations': {
'collections': {
'terms': {'field': 'collection_id', 'size': 30}
}
},
'_source': False
}
# import json
# print json.dumps(q, indent=2)
result = get_es().search(index=get_es_index(), body=q,
doc_type=TYPE_DOCUMENT)
aggs = result.get('aggregations', {}).get('collections', {})
buckets = aggs.get('buckets', [])
q = Collection.all_by_ids([b['key'] for b in buckets])
q = q.filter(Collection.creator_id != None) # noqa
objs = {o.id: o for o in q.all()}
roles = {}
for bucket in buckets:
collection = objs.get(bucket.get('key'))
if collection is None or collection.private:
continue
if collection.creator_id in roles:
roles[collection.creator_id]['total'] += bucket.get('doc_count')
else:
roles[collection.creator_id] = {
'name': collection.creator.name,
'email': collection.creator.email,
'total': bucket.get('doc_count')
}
roles = sorted(roles.values(), key=lambda r: r['total'], reverse=True)
roles = [format_total(r) for r in roles]
total = result.get('hits', {}).get('total')
return format_total({
'roles': roles,
'active': total > 0,
'total': total
})
示例9: tree2
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def tree2():
global final_html
global df,origin_df
chi_key = list()
firstkey = ""
init_style_string = """<p style="position: absolute; font-size: 12px; top: <top>px; width: <width>px; height: <height>px; left:<left>px; text-align: center;">tree_text_here</p>"""
if request.method == 'POST':
Listkey1 = list(MultiDict(request.form).values())
Listkey2 = MultiDict(request.form)
DV_tree = Listkey2.get('DV')
df1 = df
for key1 in Listkey1:
if(key1 <> "Build Tree" and key1 <> DV_tree):
chi_key.append(key1)
df1 = df.loc[:,chi_key]
df2 = df1.values
temp_count = 0
Y = df[DV_tree]
clf = tree.DecisionTreeClassifier()
clf = clf.fit(df2,Y.values)
dot_data = StringIO()
tree.export_graphviz(clf, out_file=dot_data)
k = dot_data.getvalue()
k1 = k.split(";")
left_px = 600
width_px = 150
top_px = 50
height_px = 309
s = build_tree_html(k,init_style_string,left_px,width_px,top_px,height_px)
temp_df = df[0:15]
t = """</div><div style="float:right;"><br> Decision Tree result <br>"""
final_html = template.s1 + t + k + "</div><br><br><br>" + temp_df.to_html()
return final_html
return 'helloo'
示例10: linreg2
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def linreg2():
global final_html
global df,origin_df
lin_reg_key = list()
firstkey = ""
if request.method == 'POST':
Listkey1 = list(MultiDict(request.form).values())
Listkey2 = MultiDict(request.form)
DV_lin_reg = Listkey2.get('DV')
df1 = df
for key1 in Listkey1:
if(key1 <> "Build Linear Regression Model" and key1 <> DV_lin_reg):
lin_reg_key.append(key1)
df1 = df.loc[:,lin_reg_key]
df2 = df1.values
temp_count = 0
Y = df[DV_lin_reg]
linreg = linear_model.LinearRegression()
fit1 = linreg.fit(df2,Y.values)
s = fit1.coef_
temp_df = df[0:15]
t = """</div><div style="float:right;"><br> Linear Regression Result <br>"""
final_html = template.s1 + t + s + "</div><br><br><br>" + temp_df.to_html()
return final_html
return 'helloo'
示例11: test1
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def test1():
global final_html
global df,df_train,df_test,test_train_created,origin_df
unique_count = 0
err_key=0
if request.method == 'POST':
try:
Listkey1 = list(MultiDict(request.form).values())
Listkey2 = MultiDict(request.form)
test_per = int(Listkey2.get('test_percent'))
temp_df = df[1:15]
if(float(test_per) < 0 or float(test_per) > 100):
err_key = 1
if(err_key==0):
prop_test = float(test_per)/float(100)
msk = np.random.rand(len(df)) < prop_test
df_train = df[~msk]
df_test = df[msk]
print "Length of Train",len(df_train)
print "Length of Test",len(df_test)
test_train_created = True
final_html = template.s1 + "</div><br><br> Test and Train datasets created <br> " + temp_df.to_html()
elif(err_key==1):
final_html = template.s1 + """<br><br> <font color="red"> Please enter a valid percentage value </font> <br></div> """ + temp_df.to_html()
return final_html
except ValueError:
final_html = template.s1 + """<br><br><font color="lightcoral"> Error. Please enter proper value to create Test and Train dataset. </font><br> </div>""" + df[1:15].to_html()
return 'helloo'
示例12: tree3
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def tree3():
global final_html
global df,df_train,df_test,test_train_created,origin_df
chi_key = list()
init_style_string = template.style_string
if request.method == 'POST':
Listkey1 = list(MultiDict(request.form).values())
Listkey2 = MultiDict(request.form)
DV_tree = Listkey2.get('DV')
df1 = df
for key1 in Listkey1:
if(key1 <> "Build Tree" and key1 <> DV_tree):
chi_key.append(key1)
df1 = df.loc[:,chi_key]
df2 = df1.values
Y = df[DV_tree]
clf = tree.DecisionTreeClassifier()
clf = clf.fit(df2,Y.values)
dot_data = StringIO()
tree.export_graphviz(clf, out_file=dot_data)
k = dot_data.getvalue()
left_px = 600
width_px = 150
top_px = 50
height_px = 309
s = build_tree_html(k,init_style_string,left_px,width_px,top_px,height_px)
temp_df = df[0:15]
t = """</div><div style="width:600px; height:700px; position: absolute; top: 20px; left:500px;"><br> Decision Tree result <br>"""
final_html = template.s1 + t + k + "<br><br></div>" + temp_df.to_html()
return final_html
return 'helloo'
示例13: entities_query
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def entities_query(args, fields=None, facets=True):
"""Parse a user query string, compose and execute a query."""
if not isinstance(args, MultiDict):
args = MultiDict(args)
text = args.get('q', '').strip()
if text is None or not len(text):
q = match_all()
else:
q = {
"query_string": {
"query": text,
"fields": ['name^15', 'name_latin^5',
'terms^12', 'terms_latin^3',
'summary^10', 'summary_latin^7',
'description^5', 'description_latin^3'],
"default_operator": "AND",
"use_dis_max": True
}
}
q = authz_filter(q)
filters = parse_filters(args)
aggs = {'scoped': {'global': {}, 'aggs': {}}}
if facets:
facets = args.getlist('facet')
if 'collections' in facets:
aggs = facet_collections(q, aggs, filters)
facets.remove('collections')
aggs = aggregate(q, aggs, facets)
sort_mode = args.get('sort', '').strip().lower()
default_sort = 'score' if len(text) else 'doc_count'
sort_mode = sort_mode or default_sort
if sort_mode == 'doc_count':
sort = [{'doc_count': 'desc'}, '_score']
elif sort_mode == 'alphabet':
sort = [{'name': 'asc'}, '_score']
elif sort_mode == 'score':
sort = ['_score']
return {
'sort': sort,
'query': filter_query(q, filters, OR_FIELDS),
'aggregations': aggs,
'_source': fields or DEFAULT_FIELDS
}
示例14: documents_query
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def documents_query(args, fields=None, facets=True):
"""Parse a user query string, compose and execute a query."""
if not isinstance(args, MultiDict):
args = MultiDict(args)
text = args.get('q', '').strip()
q = text_query(text)
q = authz_filter(q)
# Sorting -- should this be passed into search directly, instead of
# these aliases?
sort_mode = args.get('sort', '').strip().lower()
if text or sort_mode == 'score':
sort = ['_score']
elif sort_mode == 'newest':
sort = [{'dates': 'desc'}, {'created_at': 'desc'}, '_score']
elif sort_mode == 'oldest':
sort = [{'dates': 'asc'}, {'created_at': 'asc'}, '_score']
else:
sort = [{'updated_at': 'desc'}, {'created_at': 'desc'}, '_score']
filters = parse_filters(args)
for entity in args.getlist('entity'):
filters.append(('entities.id', entity))
aggs = {'scoped': {'global': {}, 'aggs': {}}}
if facets:
facets = args.getlist('facet')
if 'collections' in facets:
aggs = facet_collections(q, aggs, filters)
facets.remove('collections')
if 'entities' in facets:
aggs = facet_entities(aggs, args)
facets.remove('entities')
aggs = aggregate(q, aggs, facets)
signals.document_query_process.send(q=q, args=args)
return {
'sort': sort,
'query': filter_query(q, filters, OR_FIELDS),
'aggregations': aggs,
'_source': fields or DEFAULT_FIELDS
}
示例15: query
# 需要导入模块: from werkzeug.datastructures import MultiDict [as 别名]
# 或者: from werkzeug.datastructures.MultiDict import get [as 别名]
def query(args):
""" Parse a user query string, compose and execute a query. """
if not isinstance(args, MultiDict):
args = MultiDict(args)
q = text_query(args.get('q', ''))
q = authz_filter(q)
# Extract filters, given in the form: &filter:foo_field=bla_value
filters = []
for key in args.keys():
for value in args.getlist(key):
if not key.startswith('filter:'):
continue
_, field = key.split(':', 1)
filters.append((field, value))
facets = args.getlist('facet')
aggs = aggregate(q, facets, filters)
sort = ['_score']
if args.get('sort') == 'linkcount':
sort.insert(0, {'$linkcount': 'desc'})
q = {
'sort': sort,
'query': filter_query(q, filters),
'aggregations': aggs,
'_source': DEFAULT_FIELDS
}
if args.get('hl'):
q["highlight"] = {
"pre_tags": ["<em>"],
"post_tags": ["</em>"],
"fields": {
"$text": {}
}
}
q = paginate(q, args.get('limit'), args.get('offset'))
return execute_query(args, q, facets)