seq_id stringlengths 4 11 | text stringlengths 113 2.92M | repo_name stringlengths 4 125 ⌀ | sub_path stringlengths 3 214 | file_name stringlengths 3 160 | file_ext stringclasses 18
values | file_size_in_byte int64 113 2.92M | program_lang stringclasses 1
value | lang stringclasses 93
values | doc_type stringclasses 1
value | stars int64 0 179k ⌀ | dataset stringclasses 3
values | pt stringclasses 78
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
28984377057 | n = int(input())
start = 0 #지수 인덱스
end = int((2**63)**(0.5))+1
target = 0
while start <= end:
mid = (start+end)//2
if n > mid**2:
start = mid + 1
elif n <= mid**2:
target = mid
end = mid - 1
print(target) | youkyoungJung/solved_baekjoon | 백준/Silver/2417. 정수 제곱근/정수 제곱근.py | 정수 제곱근.py | py | 265 | python | en | code | 0 | github-code | 36 |
31002250811 | import numpy as np
def apply_poly(poly, x, y, z):
"""
Evaluates a 3-variables polynom of degree 3 on a triplet of numbers.
Args:
poly: list of the 20 coefficients of the 3-variate degree 3 polynom,
ordered following the RPC convention.
x, y, z: triplet of floats. They may be numpy arrays of same length.
Returns:
the value(s) of the polynom on the input point(s).
"""
out = 0
out += poly[0]
out += poly[1]*y + poly[2]*x + poly[3]*z
out += poly[4]*y*x + poly[5]*y*z +poly[6]*x*z
out += poly[7]*y*y + poly[8]*x*x + poly[9]*z*z
out += poly[10]*x*y*z
out += poly[11]*y*y*y
out += poly[12]*y*x*x + poly[13]*y*z*z + poly[14]*y*y*x
out += poly[15]*x*x*x
out += poly[16]*x*z*z + poly[17]*y*y*z + poly[18]*x*x*z
out += poly[19]*z*z*z
return out
def apply_rfm(num, den, x, y, z):
"""
Evaluates a Rational Function Model (rfm), on a triplet of numbers.
Args:
num: list of the 20 coefficients of the numerator
den: list of the 20 coefficients of the denominator
All these coefficients are ordered following the RPC convention.
x, y, z: triplet of floats. They may be numpy arrays of same length.
Returns:
the value(s) of the rfm on the input point(s).
"""
return apply_poly(num, x, y, z) / apply_poly(den, x, y, z)
class RPCModel(object):
def __init__(self, meta_dict):
rpc_dict = meta_dict['rpc']
# normalization constant
self.colOff = rpc_dict['colOff']
self.colScale = rpc_dict['colScale']
self.rowOff = rpc_dict['rowOff']
self.rowScale = rpc_dict['rowScale']
self.latOff = rpc_dict['latOff']
self.latScale = rpc_dict['latScale']
self.lonOff = rpc_dict['lonOff']
self.lonScale = rpc_dict['lonScale']
self.altOff = rpc_dict['altOff']
self.altScale = rpc_dict['altScale']
# polynomial coefficients
self.colNum = rpc_dict['colNum']
self.colDen = rpc_dict['colDen']
self.rowNum = rpc_dict['rowNum']
self.rowDen = rpc_dict['rowDen']
# img_width, img_height
self.width = meta_dict['width']
self.height = meta_dict['height']
def projection(self, lat, lon, alt):
cLon = (lon - self.lonOff) / self.lonScale
cLat = (lat - self.latOff) / self.latScale
cAlt = (alt - self.altOff) / self.altScale
cCol = apply_rfm(self.colNum, self.colDen, cLat, cLon, cAlt)
cRow = apply_rfm(self.rowNum, self.rowDen, cLat, cLon, cAlt)
col = cCol*self.colScale + self.colOff
row = cRow*self.rowScale + self.rowOff
return col, row
def to_string(self):
string = ''
tmp = [str(x) for x in self.colNum]
string += ' '.join(tmp) + '\n'
tmp = [str(x) for x in self.colDen]
string += ' '.join(tmp) + '\n'
tmp = [str(x) for x in self.rowNum]
string += ' '.join(tmp) + '\n'
tmp = [str(x) for x in self.rowDen]
string += ' '.join(tmp) + '\n'
string += '{} {} {} {} {} {} {} {} {} {}\n'.format(self.latOff, self.latScale, self.lonOff, self.lonScale, self.altOff, self.altScale,
self.colOff, self.colScale, self.rowOff, self.rowScale)
return string
##################################################################################################
# local approximation of the rpc model with an affine model
##################################################################################################
def generate_grid(x_points, y_points, z_points):
x_point_cnt = x_points.size
y_point_cnt = y_points.size
z_point_cnt = z_points.size
point_cnt = x_point_cnt * y_point_cnt * z_point_cnt
xx, yy = np.meshgrid(x_points, y_points, indexing='ij')
xx = np.reshape(xx, (-1, 1))
yy = np.reshape(yy, (-1, 1))
xx = np.tile(xx, (z_point_cnt, 1))
yy = np.tile(yy, (z_point_cnt, 1))
zz = np.zeros((point_cnt, 1))
for j in range(z_point_cnt):
idx1 = j * x_point_cnt * y_point_cnt
idx2 = (j + 1) * x_point_cnt * y_point_cnt
zz[idx1:idx2, 0] = z_points[j]
return xx, yy, zz
def solve_affine(xx, yy, zz, col, row, valid_mask=None):
diff_size = np.array([yy.size - xx.size, zz.size - xx.size, col.size - xx.size, row.size - xx.size])
assert (np.all(diff_size == 0))
if valid_mask is not None:
xx = xx[valid_mask].reshape((-1, 1))
yy = yy[valid_mask].reshape((-1, 1))
zz = zz[valid_mask].reshape((-1, 1))
row = row[valid_mask].reshape((-1, 1))
col = col[valid_mask].reshape((-1, 1))
# construct a least square problem
point_cnt = xx.size
all_ones = np.ones((point_cnt, 1))
all_zeros = np.zeros((point_cnt, 4))
# construct the least square problem
A1 = np.hstack((xx, yy, zz, all_ones, all_zeros))
A2 = np.hstack((all_zeros, xx, yy, zz, all_ones))
A = np.vstack((A1, A2))
b = np.vstack((col, row))
res = np.linalg.lstsq(A, b, rcond=-1)
P = res[0].reshape((2, 4))
return P
def affine_approx(rpc_model, bbx):
lat_min, lat_max, lon_min, lon_max, alt_min, alt_max = bbx
xy_axis_grid_points = 100
z_axis_grid_points = 20
lat_points = np.linspace(lat_min, lat_max, xy_axis_grid_points)
lon_points = np.linspace(lon_min, lon_max, xy_axis_grid_points)
alt_points = np.linspace(alt_min, alt_max, z_axis_grid_points)
lat_points, lon_points, alt_points = generate_grid(lat_points, lon_points, alt_points)
col, row = rpc_model.projection(lat_points, lon_points, alt_points)
valid_mask = np.logical_and.reduce((col>=0, row>=0, col<rpc_model.width, row<rpc_model.height))
P = solve_affine(lat_points, lon_points, alt_points, col, row, valid_mask)
return P
if __name__ == '__main__':
pass
| Kai-46/rpc_triangulation_solver | rpc_model.py | rpc_model.py | py | 5,918 | python | en | code | 14 | github-code | 36 |
9288624612 | # Given a string S, you need to remove all the duplicates. That means, the output string should contain each character only once. The respective order of characters should remain same, as in the input string.
# Input format:
# The first and only line of input contains a string, that denotes the value of S.
# Output format :
# The first and only line of output contains the updated string, as described in the task.
# Constraints :
# 0 <= Length of S <= 10^8
# Time Limit: 1 sec
# Sample Input 1 :
# ababacd
# Sample Output 1 :
# abcd
# Sample Input 2 :
# abcde
# Sample Output 2 :
# abcde
def removeDublicate(s):
d=dict()
s1=""
for i in s:
if d.get(i,0)==0:
s1+=i
d[i]=d.get(i,0)+1
return s1
if __name__=='__main__':
s=input()
print(removeDublicate(s))
| sam-072/data-structure | hash map/remove dublicate.py | remove dublicate.py | py | 818 | python | en | code | 1 | github-code | 36 |
38841107343 | import re
import random
from django.shortcuts import render
from django.views.decorators.csrf import csrf_exempt
import razorpay
from django.db.models import Q
from operator import itemgetter
from django.core.paginator import Paginator
import datetime
from property_management_system.settings import razorpay_api_key, razorpay_api_secret_key
from django.contrib.auth.decorators import login_required
from django.shortcuts import redirect, render
from django.contrib import messages
from django.contrib.auth.models import User
from django.conf import settings
from django.db.models import Sum, Func, Count
from django.contrib.auth import login, logout, authenticate
from pms.send_mail import send_customise_mail
from django.db import models
from pms.models import Blogs, Contact, Property, PropertyContacts, PropertyImages, PropertyMembership, UserProfile
months_mapping = {
1: "January",
2: "February",
3: "March",
4: "April",
5: "May",
6: "June",
7: "July",
8: "August",
9: "September",
10: "October",
11: "November",
12: "December",
}
def index(request):
try:
property_list = list(Property.objects.filter(
is_listed=True).order_by('-membership_purchased'))
if len(property_list) > 6:
random_properties = random.sample(property_list, 6)
else:
random_properties = (Property.objects.filter(
is_listed=True).order_by('-membership_purchased'))
except Exception as e:
print(e)
try:
agents_list = list(UserProfile.objects.filter(
user_type="Agent").order_by('-created_at'))
if len(agents_list) > 3:
random_agents = random.sample(agents_list, 3)
else:
random_agents = UserProfile.objects.filter(
user_type="Agent").order_by('-created_at')
except Exception as e:
print(e)
all_properties = Property.objects.filter(is_listed=True)
blogs = Blogs.objects.all().order_by('-created_at')
index_page_blogs = None
if len(blogs) > 6:
index_page_blogs = blogs[:6]
else:
index_page_blogs = blogs
context = {
'random_properties': random_properties,
'all_properties': all_properties,
'random_agents': random_agents,
'index_page_blogs': index_page_blogs,
}
return render(request, 'ui_templates/index.html', context)
def error_404_view(request, exception):
return render(request, 'ui_templates/404.html')
def about(request):
registered_users = UserProfile.objects.filter(user_type='').count()
agents = UserProfile.objects.filter(user_type='').count()
total_properties = Property.objects.all().count()
context = {
'registered_users': registered_users,
'agents': agents,
'total_properties': total_properties
}
return render(request, 'ui_templates/about.html', context)
def all_properties(request):
filtered_properties = Property.objects.filter(
is_listed=True).order_by('-membership_purchased')
if request.method == 'GET':
search_filter = request.GET.get('searching_filters')
sorting_properties = request.GET.get('sort')
property_size = request.GET.get('property_size')
nearbuy_location = request.GET.get('nearbuy_location')
if search_filter:
filtered_properties = Property.objects.filter(
Q(city__icontains=search_filter) |
Q(state__icontains=search_filter) |
Q(address__icontains=search_filter) |
Q(type__icontains=search_filter) |
Q(zip_code__icontains=search_filter) |
Q(furnishing__icontains=search_filter) |
Q(availability__icontains=search_filter) |
Q(ownership__icontains=search_filter) |
Q(expected_price__icontains=search_filter) |
Q(details__icontains=search_filter)
).order_by('-membership_purchased')
if sorting_properties and sorting_properties == 'lth':
filtered_properties = filtered_properties.order_by(
'expected_price')
if sorting_properties and sorting_properties == 'htl':
filtered_properties = filtered_properties.order_by(
'-expected_price')
if property_size:
filtered_properties = filtered_properties.filter(
area__gte=property_size)
if nearbuy_location:
filtered_properties = filtered_properties.filter(
Q(city__icontains=nearbuy_location) |
Q(state__icontains=nearbuy_location) |
Q(address__icontains=nearbuy_location))
paginator = Paginator(filtered_properties, 9)
page_number = request.GET.get('page')
page_obj = paginator.get_page(page_number)
context = {
'active_properties': filtered_properties,
'page_obj': page_obj,
}
return render(request, 'ui_templates/properties.html', context)
else:
active_properties = Property.objects.filter(
is_listed=True).order_by('-membership_purchased')
paginator = Paginator(active_properties, 9)
page_number = request.GET.get('page')
page_obj = paginator.get_page(page_number)
context = {
'active_properties': active_properties,
'page_obj': page_obj,
}
return render(request, 'ui_templates/properties.html', context)
def property_details(request, id):
property = Property.objects.get(id=id)
property_images = PropertyImages.objects.filter(property=property)
amenities = []
if property.amenities:
amenities = [amenity.strip()
for amenity in property.amenities.split(',')]
context = {
'property': property,
'amenities': amenities,
'property_images': property_images,
}
return render(request, 'ui_templates/property_detail.html', context)
def blog(request):
recent_blogs = Blogs.objects.all().order_by('-created_at')
paginator = Paginator(recent_blogs, 8)
page_number = request.GET.get('page')
page_obj = paginator.get_page(page_number)
context = {
'recent_blogs': recent_blogs,
'page_obj': page_obj,
}
return render(request, 'ui_templates/blog.html', context)
def blog_description(request, id):
requested_blog = Blogs.objects.filter(id=id)
context = {'requested_blog': requested_blog}
return render(request, 'ui_templates/blog_description.html', context)
@login_required(login_url='login')
def add_new_blog(request):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
if request.method == 'POST':
blog_image = None
title = request.POST.get('title')
body = request.POST.get('body')
try:
blog_image = request.FILES.get('blog_image')
except Exception as e:
print(e)
if blog_image:
create_new_blog = Blogs(
blog_title=title, blog_body=body, blog_image=blog_image,
uploaded_by=user)
create_new_blog.save()
messages.add_message(request, messages.WARNING,
"New Blog Created Successfully.")
else:
messages.add_message(request, messages.WARNING,
"Blog Image is Required")
return render(request, 'dashboard_templates/blog/add_new_blog.html')
@login_required(login_url='login')
def view_blogs_list(request):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
all_blogs = Blogs.objects.all()
context = {'all_blogs': all_blogs}
return render(request, 'dashboard_templates/blog/blogs_view.html', context)
@login_required(login_url='login')
def update_blog(request, id):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
requested_blog = Blogs.objects.filter(id=id)
if request.method == 'POST':
blog_update = Blogs.objects.filter(id=id).first()
updated_title = request.POST.get('title')
updated_body = request.POST.get('body')
blog_update.blog_title = updated_title
blog_update.blog_body = updated_body
try:
updated_blog_image = request.FILES['blog_image']
blog_update.blog_image = updated_blog_image
except Exception as e:
print(e)
blog_update.save()
messages.add_message(request, messages.WARNING,
"Blog Updated Successfully.")
context = {
'requested_blog': requested_blog
}
return render(request, 'dashboard_templates/blog/update_blog.html', context)
@login_required(login_url='login')
def delete_blog(request, id):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
requested_blog = Blogs.objects.filter(id=id)
requested_blog.delete()
return redirect('blog_list')
def auth_login(request):
if request.user.is_authenticated:
messages.add_message(request, messages.WARNING,
"You already logged in.")
return redirect('index')
else:
if request.method == 'POST':
email = request.POST.get('email')
password = request.POST.get('password')
user = authenticate(username=email, password=password)
if user:
login(request, user)
messages.add_message(
request, messages.WARNING, f"Welcome, {request.user.first_name} {request.user.last_name} you logged in successfully.")
return redirect('index')
else:
messages.add_message(
request, messages.WARNING, "Sorry, check again your email or password.")
return render(request, 'ui_templates/login_page.html')
@login_required(login_url='login')
def user_logout(request):
logout(request)
messages.add_message(request, messages.SUCCESS,
"Success, You Logged Out Successfully.")
return redirect('index')
@login_required(login_url='login')
def profile(request):
requested_user = request.user
user_profile = UserProfile.objects.get(user=requested_user)
context = {
'profile_details': user_profile
}
return render(request, 'dashboard_templates/profile/user_profile.html', context)
def contact_us(request):
if request.method == 'POST':
name = request.POST.get('name')
email = request.POST.get('email')
contact_no = request.POST.get('contact_no')
subject = request.POST.get('subject')
message = request.POST.get('message')
if name and email and contact_no and subject and message:
new_contact = Contact(name=name, email=email, contact_no=contact_no,
subject=subject, message=message)
new_contact.save()
messages.add_message(
request, messages.SUCCESS, "Thanks for Contacting us. We will contact you shortly.")
return redirect('index')
else:
messages.add_message(request, messages.WARNING,
"Please fill all the required details.")
return render(request, 'ui_templates/contact.html')
return render(request, 'ui_templates/contact.html')
def auth_register(request):
password_validation = False
if request.method == 'POST':
profile_image = None
fname = request.POST.get('fname')
lname = request.POST.get('lname')
email = request.POST.get('email')
contact = request.POST.get('contact')
password = request.POST.get('password')
user_type = request.POST.get('user_type')
try:
profile_image = request.FILES.get('profile_image')
except Exception as e:
print(e)
user_exists = User.objects.filter(username=email)
# Minimum six characters, Maximum 20 Characters, at least one Uppercase and Lowecase letter and one number:
password_regex = (
"(?=.*[a-z])(?=.*[A-Z])(?=.*\d)(?=.*[@$!%*#?&])[A-Za-z\d@$!#%*?&]{6,20}$")
password_regex_compile = re.compile(password_regex)
if (re.search(password_regex_compile, password)):
password_validation = True
if password_validation:
if profile_image:
if not user_exists:
if user_type == "Agent":
new_user = User.objects.create_user(
first_name=fname, last_name=lname, username=email, email=email, password=password, is_active=True, is_staff=True)
new_user.save()
subject = "Dream Homes: Registration Successfully"
body = (
"Hi "+fname+". Thanks for Registering with Dream Homes as a " + user_type+".")
send_customise_mail(
subject=subject,
body=body,
email_id=email)
else:
new_user = User.objects.create_user(
first_name=fname, last_name=lname, username=email, email=email, password=password, is_active=True)
new_user.save()
subject = "Dream Homes: Registration Successfully"
body = (
"Hi "+fname+". Thanks for Registering with Dream Homes as a " + user_type+".")
send_customise_mail(
subject=subject,
body=body,
email_id=email)
user_profile = UserProfile(
contact=contact, user=new_user, user_type=user_type, user_image=profile_image)
user_profile.save()
messages.add_message(
request, messages.SUCCESS, "Thanks for Registering with us.Please Login")
return redirect('login')
else:
messages.add_message(
request, messages.WARNING, "You Already have an Account. Please Login")
else:
messages.add_message(
request, messages.SUCCESS, "Profile Image is Required")
else:
messages.add_message(
request, messages.WARNING, "Please Create Strong Password as mentioned criteria.")
return render(request, 'ui_templates/register_page.html')
class Month(Func):
function = 'EXTRACT'
template = "%(function)s(MONTH from %(expressions)s)"
output_field = models.IntegerField()
@login_required(login_url='login')
def dashboard(request):
logged_in_user = request.user
if logged_in_user.is_superuser:
total_membership_amount = PropertyMembership.objects.aggregate(
Sum('property_membership_amount'))['property_membership_amount__sum']
total_membership_taken = PropertyMembership.objects.all().count()
approved_properties = Property.objects.filter(
approved=True).count()
pending_properties = Property.objects.filter(
approved=False).count()
listed_properties = Property.objects.filter(
is_listed=True).count()
unlisted_properties = Property.objects.filter(
is_listed=False).count()
# In case of admin all responses
current_time = datetime.datetime.now()
response_summary = (PropertyContacts.objects.filter(created_at__year=current_time.year)
.annotate(response_by_month=Month('created_at'))
.values('response_by_month')
.annotate(total=Count('id')))
response_data = []
for data in response_summary:
response_data.append(
{
"month": months_mapping.get(data.get('response_by_month')),
"total_responses": int(data.get('total'))
}
)
for month in months_mapping.keys():
result = [i for i in response_data if i['month'] == month]
if not result:
response_data.append(
{"month": months_mapping.get(month), "total_responses": 0})
sorted_response_data = sorted(response_data, key=lambda d: datetime.datetime.strptime(d['month'], "%B")
)
context = {
'approved_properties': approved_properties,
'listed_properties': listed_properties,
'unlisted_properties': unlisted_properties,
'pending_properties': pending_properties,
'total_membership_amount': total_membership_amount,
'total_membership_taken': total_membership_taken,
'response_data': sorted_response_data,
'current_year': current_time.year,
}
else:
approved_properties = Property.objects.filter(
uploaded_by=logged_in_user, approved=True).count()
pending_properties = Property.objects.filter(
uploaded_by=logged_in_user, approved=False).count()
listed_properties = Property.objects.filter(
uploaded_by=logged_in_user, is_listed=True).count()
unlisted_properties = Property.objects.filter(
uploaded_by=logged_in_user, is_listed=True).count()
properties_uploaded_by_user = Property.objects.filter(
uploaded_by=logged_in_user)
current_time = datetime.datetime.now()
response_summary = (PropertyContacts.objects.filter(property_id__in=properties_uploaded_by_user, created_at__year=current_time.year)
.annotate(response_by_month=Month('created_at'))
.values('response_by_month')
.annotate(total=Count('id')))
response_data = []
for data in response_summary:
response_data.append(
{
"month": months_mapping.get(data.get('response_by_month')),
"total_responses": int(data.get('total'))
}
)
for month in months_mapping.keys():
result = [i for i in response_data if i['month'] == month]
if not result:
response_data.append(
{"month": months_mapping.get(month), "total_responses": 0})
sorted_response_data = sorted(response_data, key=lambda d: datetime.datetime.strptime(d['month'], "%B")
)
context = {
'approved_properties': approved_properties,
'listed_properties': listed_properties,
'unlisted_properties': unlisted_properties,
'pending_properties': pending_properties,
'response_data': sorted_response_data,
'current_year': current_time.year,
}
return render(request, 'dashboard_templates/dashboard.html', context)
@login_required(login_url='login')
def add_new_property(request):
user = request.user
last_property_id = Property.objects.all().order_by('id').last()
if not last_property_id:
prop_id = 'WHPR' + '000001'
else:
last_prop_id = last_property_id.property_id
prop_no_int = int(last_prop_id[4:10])
new_property_id = prop_no_int + 1
prop_id = 'WHPR' + str(new_property_id).zfill(6)
if request.method == 'POST':
property_sr = request.POST.get('property_sr')
property_type = request.POST.get('property_type')
property_address = request.POST.get('property_address')
property_city = request.POST.get('property_city')
property_state = request.POST.get('property_state')
no_bedrooms = request.POST.get('no_bedrooms')
no_bathrooms = request.POST.get('no_bathrooms')
no_balconies = request.POST.get('no_balconies')
area_details = request.POST.get('area_details')
furnishing_type = request.POST.get('furnishing_type')
open_parking = request.POST.get('open_parking')
covered_parking = request.POST.get('covered_parking')
availability_status = request.POST.get('availability_status')
property_age = request.POST.get('property_age')
property_ownership = request.POST.get('property_ownership')
expected_price = request.POST.get('expected_price')
price_sq_ft = request.POST.get('price_sq_ft')
property_unique_details = request.POST.get('property_unique_details')
zip_code = request.POST.get('zip_code')
amenities = request.POST.get('amenities')
create_new_property = Property(
property_id=prop_id,
sell_rent=property_sr,
type=property_type,
address=property_address,
city=property_city,
state=property_state,
zip_code=zip_code,
bedrooms=no_bedrooms,
bathrooms=no_bathrooms,
balconies=no_balconies,
area=area_details,
furnishing=furnishing_type,
open_parking=open_parking,
covered_parking=covered_parking,
availability=availability_status,
age=property_age,
ownership=property_ownership,
expected_price=expected_price,
area_price=price_sq_ft,
details=property_unique_details,
approved=False,
uploaded_by=request.user,
amenities=amenities
)
create_new_property.save()
try:
property_images = request.FILES.getlist('property_images')
for img in property_images:
new_img = PropertyImages(
property=create_new_property,
images=img
)
new_img.save()
except Exception as e:
print(e)
subject = "Dream Homes: Property Added Successfully"
body = ("Hi "+user.first_name+". New Property Added Successfully. Your Property ID: " +
prop_id+". It will be listed once all details are verified.")
send_customise_mail(
subject=subject,
body=body,
email_id=user.email)
messages.add_message(request, messages.WARNING,
"New Property Created Successfully.")
return render(request, 'dashboard_templates/property/add_new_property.html')
@login_required(login_url='login')
def list_uploaded_properties(request):
properties_list_by_user = Property.objects.filter(uploaded_by=request.user)
membership_amount = 50000 # In Paisa = Rs 500
membership_currency = 'INR'
client = razorpay.Client(auth=(razorpay_api_key, razorpay_api_secret_key))
payment_data = {"amount": membership_amount,
"currency": membership_currency, 'payment_capture': '1'}
payment_order = client.order.create(data=payment_data)
payment_order_id = payment_order['id']
context = {
'amount': membership_amount,
'api_key': razorpay_api_key,
'order_id': payment_order_id,
'property_list': properties_list_by_user
}
return render(request, 'dashboard_templates/property/list_uploaded_properties.html', context)
@login_required(login_url='login')
def list_property_contacts(request, id):
property_contacts = PropertyContacts.objects.filter(property=id,
property__membership_purchased=True)
context = {
'property_contacts': property_contacts
}
return render(request, 'dashboard_templates/property/property_contacts.html', context)
@login_required(login_url='login')
def delete_property(request, id):
requested_property = Property.objects.get(id=id)
requested_property.delete()
return redirect('property_list')
@login_required(login_url='login')
def update_property(request, id, view=None):
user = request.user
requested_property = Property.objects.filter(id=id)
if request.method == 'POST':
property_update = Property.objects.filter(id=id).first()
property_sr = request.POST.get('property_sr')
property_type = request.POST.get('property_type')
property_address = request.POST.get('property_address')
property_city = request.POST.get('property_city')
property_state = request.POST.get('property_state')
no_bedrooms = request.POST.get('no_bedrooms')
no_bathrooms = request.POST.get('no_bathrooms')
no_balconies = request.POST.get('no_balconies')
area_details = request.POST.get('area_details')
furnishing_type = request.POST.get('furnishing_type')
open_parking = request.POST.get('open_parking')
covered_parking = request.POST.get('covered_parking')
availability_status = request.POST.get('availability_status')
property_age = request.POST.get('property_age')
property_ownership = request.POST.get('property_ownership')
expected_price = request.POST.get('expected_price')
price_sq_ft = request.POST.get('price_sq_ft')
property_unique_details = request.POST.get('property_unique_details')
zip_code = request.POST.get('zip_code')
amenities = request.POST.get('amenities')
property_update.sell_rent = property_sr
property_update.type = property_type
property_update.address = property_address
property_update.city = property_city
property_update.state = property_state
property_update.bedrooms = no_bedrooms
property_update.bathrooms = no_bathrooms
property_update.balconies = no_balconies
property_update.area = area_details
property_update.furnishing = furnishing_type
property_update.open_parking = open_parking
property_update.covered_parking = covered_parking
property_update.availability = availability_status
property_update.age = property_age
property_update.ownership = property_ownership
property_update.expected_price = expected_price
property_update.area_price = price_sq_ft
property_update.zip_code = zip_code
property_update.details = property_unique_details
property_update.amenities = amenities
try:
updated_blog_image = request.FILES['blog_image']
property_update.blog_image = updated_blog_image
except Exception as e:
print(e)
requested_property_images = PropertyImages.objects.filter(
property=property_update)
try:
property_images = request.FILES.getlist('property_images')
if property_images:
for old_img in requested_property_images:
old_img.delete()
for img in property_images:
new_images = PropertyImages(
property=property_update,
images=img
)
new_images.save()
except Exception as e:
print(e)
property_update.save()
subject = "Dream Homes: Property Updated Successfully"
body = ("Hi "+user.first_name+". Your Property " +
property_update.property_id+" Updated Successfully.")
send_customise_mail(
subject=subject,
body=body,
email_id=user.email)
messages.add_message(request, messages.WARNING,
"Property Details Updated Successfully.")
if view:
context = {'requested_property': requested_property,
'view_property': True}
else:
context = {'requested_property': requested_property}
return render(request, 'dashboard_templates/property/update_property.html', context)
@login_required(login_url='login')
def view_property_images(request, id):
property_images = PropertyImages.objects.filter(property=id)
context = {
'property_images': property_images
}
return render(request, 'dashboard_templates/property/property_images.html', context)
@csrf_exempt
def payment_success_membership(request, id):
user = request.user
if request.method == 'POST':
payment_id = request.POST.get('razorpay_payment_id', '')
property = Property.objects.get(id=id)
property.membership_purchased = True
amount = 500
create_property_membership = PropertyMembership(
property=property,
user=request.user,
property_membership_plan=True,
payment_order_id=payment_id,
property_membership_amount=amount
)
create_property_membership.save()
property.save()
subject = "Dream Homes: Property Membership"
body = ("Hi "+user.first_name+". Thanks for Purchasing Property " +
property.property_id+" Membership.")
send_customise_mail(
subject=subject,
body=body,
email_id=user.email)
return redirect('property_list')
@login_required(login_url='login')
def pending_properties_view(request):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
pending_properties_list = Property.objects.filter(
approved=False)
context = {
'pending_properties_data': pending_properties_list
}
return render(request, 'dashboard_templates/property/pending_properties.html', context)
@login_required(login_url='login')
def approve_property(request, id):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
property = Property.objects.get(id=id)
property.approved = True
property.approved_on = datetime.datetime.now()
property.is_listed = True
property.save()
return redirect('pending_properties')
@login_required(login_url='login')
def unlist_property(request, id):
property = Property.objects.get(id=id)
property.is_listed = False
property.unlisted_date = datetime.datetime.now()
property.save()
return redirect('unlisted_properties')
@login_required(login_url='login')
def listed_properties_view(request):
listed_properties_list = Property.objects.filter(
approved=True, is_listed=True, uploaded_by=request.user)
context = {
'listed_properties_data': listed_properties_list
}
return render(request, 'dashboard_templates/property/listed_properties.html', context)
@login_required(login_url='login')
def unlisted_properties_view(request):
unlisted_properties_list = Property.objects.filter(
approved=True, is_listed=False, uploaded_by=request.user)
context = {
'unlisted_properties_data': unlisted_properties_list
}
return render(request, 'dashboard_templates/property/unlisted_properties.html', context)
@login_required(login_url='login')
def calculate_emi(request):
if request.method == 'POST':
amount = request.POST.get('amount')
interest = request.POST.get('interest')
tenure = request.POST.get('tenure')
if not amount or not interest or not tenure:
messages.add_message(request, messages.WARNING,
"Fill All the Details Properly")
return render(request, 'emi_calculate.html')
else:
rate_of_interest_per_month = float(interest)/(12*100)
monthly_emi = float(amount) * float(rate_of_interest_per_month) * ((1+float(rate_of_interest_per_month))
** float(tenure))/((1+float(rate_of_interest_per_month)) ** float(tenure) - 1)
total_interest_amount = (
float(monthly_emi)*float(tenure)) - float(amount)
context = {
'amount': amount,
'rate_of_interest_per_month': rate_of_interest_per_month,
'tenure': tenure,
'monthly_emi': monthly_emi,
'total_interest_amount': total_interest_amount,
'interest': interest,
'total_amount': round((float(amount)+float(total_interest_amount)), 2),
}
return render(request, 'dashboard_templates/emi_calculate.html', context)
else:
return render(request, 'dashboard_templates/emi_calculate.html')
@login_required(login_url='login')
def agents_list_view(request):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
agents_data = UserProfile.objects.filter(user_type='Agent').all()
context = {
'agents_list': agents_data
}
return render(request, 'dashboard_templates/reports/agents_list.html', context)
@login_required(login_url='login')
def properties_uploaded_by_user(request):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
properties = Property.objects.all()
context = {
'properties': properties
}
return render(request, 'dashboard_templates/reports/user_uploaded_properties.html', context)
@login_required(login_url='login')
def customers_list_view(request):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
customers_data = UserProfile.objects.filter(user_type='Buyer').all()
context = {
'customers_data': customers_data
}
return render(request, 'dashboard_templates/reports/customers_list.html', context)
@login_required(login_url='login')
def total_uploaded_properties(request):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
all_uploaded_properties = Property.objects.all()
context = {
'all_uploaded_properties': all_uploaded_properties
}
return render(request, 'dashboard_templates/reports/total_uploaded_properties.html', context)
@login_required(login_url='login')
def total_listed_properties(request):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
all_listed_properties = Property.objects.filter(is_listed=True)
context = {
'all_listed_properties': all_listed_properties
}
return render(request, 'dashboard_templates/reports/total_listed_properties.html', context)
@login_required(login_url='login')
def total_unlisted_properties(request):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
all_unlisted_properties = Property.objects.filter(
is_listed=False, unlisted_date__isnull=False)
context = {
'all_unlisted_properties': all_unlisted_properties
}
return render(request, 'dashboard_templates/reports/total_unlisted_properties.html', context)
@login_required(login_url='login')
def revenue_details(request):
user = request.user
if not user.is_superuser:
return redirect('index')
else:
if request.method == 'POST':
from_date = request.POST.get('from_date')
to_date = request.POST.get('to_date')
if from_date and to_date:
from_date = datetime.datetime.strptime(from_date, "%Y-%m-%d")
to_date = datetime.datetime.strptime(to_date, "%Y-%m-%d")
to_date = datetime.datetime(
to_date.year, to_date.month, to_date.day, 23, 59, 59)
revenue_details = PropertyMembership.objects.filter(
payment_date__gte=from_date, payment_date__lte=to_date)
context = {
'revenue_details': revenue_details
}
if revenue_details:
messages.add_message(request, messages.SUCCESS,
"Revenue Details From: "+str(from_date)+" To: "+str(to_date))
else:
messages.add_message(request, messages.WARNING,
"No Revenue Details Found !!")
return render(request, 'dashboard_templates/reports/revenue_details.html', context)
else:
return render(request, 'dashboard_templates/reports/revenue_details.html')
else:
return render(request, 'dashboard_templates/reports/revenue_details.html')
def property_comments(request, id):
if request.method == 'POST':
property = Property.objects.get(id=id)
name = request.POST.get('name')
email = request.POST.get('email')
contact = request.POST.get('contact')
comment = request.POST.get('comment')
new_property_contact = PropertyContacts(
name=name, email=email, contact=contact, comments=comment, property=property)
new_property_contact.save()
subject = "Dream Homes: Property Response"
body = ("Hi "+property.uploaded_by.first_name +
". Someone Shows Interest in your Property. Property ID: "+property.property_id+".")
send_customise_mail(
subject=subject,
body=body,
email_id=property.uploaded_by.email)
messages.add_message(request, messages.WARNING,
"Query Submitted Successfully...")
return redirect("property_details", id=id)
else:
return redirect("index")
@login_required(login_url='login')
def view_user_image(request, id):
user_profile_image = UserProfile.objects.filter(user=id)
context = {
'user_profile_image': user_profile_image
}
return render(request, 'dashboard_templates/reports/user_images.html', context)
| karan7864/property_management | pms/views.py | views.py | py | 38,362 | python | en | code | 0 | github-code | 36 |
36478211178 | from django import forms
from ..models import Modelo
class ModeloForm(forms.ModelForm):
class Meta:
model = Modelo
fields = ["marca", "nombre"]
def __init__(self, *args, **kwargs):
super(ModeloForm, self).__init__(*args, **kwargs)
for i, (fname, field) in enumerate(self.fields.iteritems()):
field.widget.attrs['class'] = 'form-control' | xcarlx/Venta | apps/producto/formstotal/modelo.py | modelo.py | py | 390 | python | en | code | 0 | github-code | 36 |
16475137310 | '''
Cognitively Expanding The Game of Life
Spring 2023 Term Project
CS 6795 Intro to Cognitive Science
Team - Swole
Member - Scott Pickthorne
Member - Zackary Clark-Williams
This class is the data form for all the experiments
tracking data.
Information Currently Tracking:
Average Cellurlar Life Span,
...
@license
Copyright [2023] [Scott Pickthorn and Zachary Clark-Williams]
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
'''
import numpy as np
class conclusion:
def getMaxLifespan (grid, N):
max_val = -np.inf
for i in range(len(grid)):
for j in range(len(grid[i])):
max_val = max(max_val, np.max(grid[i][j].avgLifespan))
print(max_val)
return max_val
def getAverageLifeSpan (grid, N):
avg = 0
iWasAlive = 0
for i in range(N):
rowavg = 0
for j in range(N):
rowavg += grid[i][j].avgLifespan
if grid[i][j].avgLifespan > 0: iWasAlive +=1
avg += (rowavg / iWasAlive)
avg = round (avg / N)
print(avg)
return avg | Zclarkwilliams/DiseasedCognitiveGameOfLife | src/conclusion.py | conclusion.py | py | 1,681 | python | en | code | 1 | github-code | 36 |
2881063504 | import glob
import numpy as np
from get_c_point import Point, Final_point
class File_Parser:
"""Create an object from datas that is a list of Points objects from the
different files fed to it.
Attributes:
file_names (list): List of the files used to generate datas.
list_of_points (list): List of the different points across a file.
For more info, see the Point class.
list_of_final_point (list): List of "final points", for all the files in
file_names aggregate all the points corresponding to one given
concentration.
list_of_conc (list): List of each concentration used. For now, it wont
work if the files used to create data have different concentrations
across them.
"""
def __init__(self, input_dic, data=None, user_input=None):
"""Initialise a File_Parser object from a list of files
Args:
input_dic (dict): Dictionary of user inputs(given by GUI)
data (str): A string with the type of data. For now, only 'csv' is
supported. Pandas compatible file will be explored later.
user_input (str): A string for input_dict. Original plan was to
take all file in the same folder that finish with the same text. For
example 'Plate1good' and 'Plate2good" will be parsed together in a
File_Parser object and 'good' should be user_input.
As the program (for now) is built, we expect userinput1 or
userinput2.
"""
# Init lists
self.file_names = []
self.list_of_points = []
self.list_of_final_point = []
self.list_of_conc = []
if data == 'csv':
for files in glob.glob("*%s.csv" % user_input):
self.file_names.append(files)
# This is the delimitation used in the original repository and
# the files i'm using to test the program. We could extend the
# program to let user choose the data input (here it's array)
array = np.genfromtxt(files, delimiter=';',
skip_header=input_dic['user_input3']-1,
usecols=(input_dic['user_input4']-1,
input_dic['user_input5']-1))
list_of_slices = [array[0:3], array[3:6], array[6:9], array[9:12],
array[12:15], array[15:18], array[18:21],
array[21:24]]
for elements in list_of_slices:
point = Point(elements)
self.list_of_points.append(point)
if point.mean[0] not in self.list_of_conc:
self.list_of_conc.append(point.mean[0])
elif data == 'pandas':
# Pandas handling is planned. Pandas is much more easier to use
# than random arrays and would require an formated input with clear
# labels on values.
pass
else:
print('Unknown data format')
self.mask = list(range(len(self.file_names)))
# Take all points of a same concentration and average them into the
# Final_point class
for concentration in self.list_of_conc:
dummy_list = []
for point in self.list_of_points:
if point.mean[0] == concentration:
dummy_list.append(point)
self.list_of_final_point.append(Final_point(dummy_list))
| Elesh-Norn/ELISA_QC | Extract_data.py | Extract_data.py | py | 3,569 | python | en | code | null | github-code | 36 |
70539338983 | from intrinsic_types import intrinsic_types, is_float
from bitstring import Bits, BitArray
import random
from tempfile import NamedTemporaryFile
import os
import subprocess
from interp import interpret
from compiler import compile
from bit_util import *
import math
import z3
import functools
import operator
from spec_serializer import dump_spec, load_spec
src_path = os.path.dirname(os.path.abspath(__file__))
def get_imm_mask(imm8, outs):
'''
Given imm8 and the semantic of the outputs,
figure out a mask that identifies the bits of imm8
that are actually useful
'''
# TODO: don't assume there is only one output
y = outs[0]
mask = (1 << 33)-1
s = z3.Solver()
for i in range(33, 0, -1):
cur_mask = (1<<(i+1))-1
y_masked = z3.substitute(y, (imm8, imm8 & cur_mask))
ok = z3.is_true(z3.simplify(y_masked == y))
if not ok:
return mask
mask = cur_mask
return mask
def extract_float(bv, i, bitwidth):
'''
extract i'th float from bv
bitwidth is the size of a one floating point (either 32 or 64)
'''
if bitwidth == 32:
ty = z3.Float32()
else:
assert bitwidth == 64
ty = z3.Float64()
sub_bv = z3.Extract(i * bitwidth + bitwidth - 1, i * bitwidth, bv)
return z3.fpBVToFP(sub_bv, ty)
def equal(a, b, ty):
if is_float(ty):
if ty.is_float:
elem_bw = 32
else:
elem_bw = 64
assert ty.bitwidth % elem_bw == 0
num_elems = ty.bitwidth // elem_bw
return z3.Or(a == b, z3.And([
z3.fpAbs(extract_float(a, i, elem_bw) - extract_float(b, i, elem_bw)) < 1e-5
for i in range(num_elems)]))
return a == b
def check_compiled_spec_with_examples(param_vals, outs, out_types, inputs, expected_outs):
s = z3.Solver()
s.set(timeout=20000)
constraints = []
for input, expected in zip(inputs, expected_outs):
subs = [(param, z3.BitVecVal(x, param.size())) for param, x in zip(param_vals, input)]
outs_concrete = [z3.simplify(z3.substitute(out, *subs))
for out in outs]
constraints.append(
z3.And([equal(z3.BitVecVal(y_expected, y.size()), y, out_type)
for y_expected, y, out_type in zip(expected, outs_concrete, out_types)]))
#preconditions = [x_sym == x_conc
#for x_sym, x_conc in zip(param_vals, input)]
#postconditions = [equal(z3.BitVecVal(y_expected, y.size()), y, out_type)
# for y_expected, y, out_type in zip(expected, outs, out_types)]
#constraints.append(
# z3.Implies(z3.And(preconditions), z3.And(postconditions)))
spec_correct = z3.And(constraints)
s.add(z3.Not(spec_correct))
correct = s.check() == z3.unsat
#if not correct:
# print(s.model().evaluate(outs[0]), expected_outs[0][0])
return correct
def line_to_bitvec(line, ty):
qwords = list(map(int, line.split()))
if ty.bitwidth <= 64:
assert len(qwords) == 1
[bits] = qwords
mask = (1 << ty.bitwidth) - 1
return bits & mask
assert ty.bitwidth % 64 == 0
components = [bits << (i * 64) for i, bits in enumerate(qwords)]
return functools.reduce(operator.or_, components, 0)
load_intrinsics = {
'_m512i': '_mm512_loadu_si512',
'__m512i': '_mm512_loadu_si512',
'__m256i': '_mm256_loadu_si256',
'__m128i': '_mm_loadu_si128',
# single precision floats
'__m512': '_mm512_loadu_ps',
'__m256': '_mm256_loadu_ps',
'__m128': '_mm_loadu_ps',
'_m512': '_mm512_loadu_ps',
'_m256': '_mm256_loadu_ps',
'_m128': '_mm_loadu_ps',
# double precision floats
'__m512d': '_mm512_loadu_pd',
'__m256d': '_mm256_loadu_pd',
'__m128d': '_mm_loadu_pd',
'_m512d': '_mm512_loadu_pd',
'_m256d': '_mm256_loadu_pd',
'_m128d': '_mm_loadu_pd',
}
# functions that prints these vector registers
printers = {
'_m512i': 'print__m512i',
'__m512i': 'print__m512i',
'__m256i': 'print__m256i',
'__m128i': 'print__m128i',
# single precision floats
'__m512': 'print__m512i',
'__m256': 'print__m256i',
'__m128': 'print__m128i',
'_m512': 'print__m512i',
'_m256': 'print__m256i',
'_m128': 'print__m128i',
# double precision floats
'__m512d': 'print__m512i',
'__m256d': 'print__m256i',
'__m128d': 'print__m128i',
'_m512d': 'print__m512i',
'_m256d': 'print__m256i',
'_m128d': 'print__m128i',
}
def emit_load(outf, dst, src, typename):
if typename in load_intrinsics:
load_intrinsic = load_intrinsics[typename]
outf.write('%s %s = %s((%s *)%s);\n' % (
typename, dst, load_intrinsic, typename, src
))
else:
outf.write('%s %s = *(%s *)(%s);\n' % (
typename, dst, typename, src
))
def gen_rand_data(outf, name, typename):
'''
declare a variable of `data_type` called `name`
print result to `outf` and return the actual bytes in bits
e.g. for ty=__m512i, name = x1, we declare the following
unsigned char x1[64] = { ... };
'''
if typename.endswith('*'):
is_pointer = True
typename = typename[:-1].strip()
else:
is_pointer = False
ty = intrinsic_types[typename]
# generate floats separates for integer because we don't
# want to deal with underflow and other floating point issues
if not is_float(ty):
num_bytes = ty.bitwidth // 8
bytes = [random.randint(0, 255) for _ in range(num_bytes)]
outf.write('unsigned char %s_aux[%d] = { %s };\n' % (
name, num_bytes, ','.join(map(str, bytes))
))
bits = BitArray(length=ty.bitwidth)
for i, byte in enumerate(bytes):
update_bits(bits, i*8, i*8+8, byte)
else:
float_size = 32 if ty.is_float else 64
c_type = 'float' if ty.is_float else 'double'
num_floats = ty.bitwidth // float_size
floats = [random.random() for _ in range(num_floats)]
outf.write('%s %s_aux[%d] = { %s };\n' % (
c_type, name, num_floats, ','.join(map(str, floats))
))
bits = float_vec_to_bits(floats, float_size=float_size)
if not is_pointer:
# in this case we need to load the bytes
emit_load(outf, src='%s_aux'%name, dst=name, typename=typename)
else:
# in this case we just take the address
outf.write('%s *%s = (%s *)(&%s_aux);\n' % (
typename, name, typename, name
))
return bits
def emit_print(outf, var, typename):
if typename.endswith('*'):
typename = typename[:-1].strip()
ty = intrinsic_types[typename]
is_pointer = True
else:
is_pointer = False
ty = intrinsic_types[typename]
if is_pointer:
# need to load the value first first
tmp = get_temp_name()
emit_load(outf, dst=tmp, src=var, typename=typename)
var = tmp
if typename in printers:
# use the predefined printers
printer = printers[typename]
if ty.is_float:
param_ty = 'unsigned long'
elif ty.is_double:
param_ty = 'unsigned long'
else:
param_ty = 'unsigned long'
outf.write('%s((%s *)&%s);\n' % (printer, param_ty, var))
else:
if ty.is_float:
outf.write('printf("%%u\\n", float2int(%s));\n' % var)
elif ty.is_double:
outf.write('printf("%%lu\\n", double2long(%s));\n' % var)
else:
outf.write('printf("%%lu\\n", (unsigned long)%s);\n' % var)
counter = 0
def get_temp_name():
global counter
counter += 1
return 'tmp%d' % counter
def fuzz_intrinsic_once(outf, spec, sema):
'''
1) generate test (in C) that exercises the intrinsic
2) run the interpreter per the spec and return the expected output
'''
xs, ys = sema
# generate random arguments
c_vars = []
arg_vals = []
out_params = []
out_param_types = []
inst_form = spec.inst_form.split(', ')
no_imm8 = 'imm8' not in (param.name for param in spec.params)
# TODO: refactor out this signature parsing logic
for i, param in enumerate(spec.params):
if ((no_imm8 and i < len(inst_form) and inst_form[i] == 'imm') or
param.name == 'imm8'):
param_id = len(arg_vals)
mask = get_imm_mask(xs[param_id], ys)
byte = random.randint(0, 255) & mask
c_vars.append(str(byte))
arg_vals.append(Bits(uint=byte, length=8))
continue
c_var = get_temp_name()
arg_val = gen_rand_data(outf, c_var, param.type)
c_vars.append(c_var)
arg_vals.append(arg_val)
if param.type.endswith('*'):
out_params.append(c_var)
out_param_types.append(param.type[:-1].strip())
# call the intrinsic
has_return_val = spec.rettype != 'void'
if has_return_val:
ret_var = get_temp_name()
outf.write('%s %s = %s(%s);\n' % (
spec.rettype, ret_var, spec.intrin, ','.join(c_vars)
))
# print the result
emit_print(outf, ret_var, spec.rettype)
else:
outf.write('%s(%s);\n' % (
spec.intrin, ','.join(c_vars)
))
out_types = []
for param, param_type in zip(out_params, out_param_types):
emit_print(outf, param, param_type+'*')
return arg_vals, out_param_types, has_return_val
def get_err(a, b, is_float):
err = a - b
if not is_float:
return err
if math.isnan(a) and math.isnan(b):
return 0
return err
def identical_vecs(a, b, is_float):
errs = [get_err(aa, bb, is_float)
for aa,bb in zip(a, b)]
if is_float:
return all(abs(err) <= 1e-6 for err in errs)
return all(err == 0 for err in errs)
def bits_to_vec(bits, typename):
if typename.endswith('*'):
ty = intrinsic_types[typename[:-1]]
else:
ty = intrinsic_types[typename]
if ty.is_float:
return bits_to_float_vec(bits, float_size=32)
elif ty.is_double:
return bits_to_float_vec(bits, float_size=64)
# integer type
return bits_to_long_vec(bits)
def fuzz_intrinsic(spec, num_tests=100):
'''
spec -> (spec correct, can compile)
'''
param_vals, outs = compile(spec)
sema = param_vals, outs
interpreted = []
exe = NamedTemporaryFile(delete=False)
exe.close()
with NamedTemporaryFile(suffix='.c', mode='w') as outf:
outf.write('''
#include <emmintrin.h>
#include <immintrin.h>
#include <nmmintrin.h>
#include <pmmintrin.h>
#include <smmintrin.h>
#include <tmmintrin.h>
#include <wmmintrin.h>
#include <xmmintrin.h>
#include <stdio.h>
#include "printers.h"
#define __int64_t __int64
#define __int64 long long
union float_and_int {
float f;
unsigned int i;
};
union double_and_long {
double d;
unsigned long l;
};
unsigned int float2int(float f) {
union float_and_int x;
x.f = f;
return x.i;
}
unsigned long double2long(double d) {
union double_and_long x;
x.d = d;
return x.l;
}
int main() {
''')
x = []
y = []
for _ in range(num_tests):
arg_vals, out_param_types, has_return_val = fuzz_intrinsic_once(outf, spec, sema)
out_types = [intrinsic_types[ty] for ty in out_param_types]
if spec.rettype != 'void':
out_types = [intrinsic_types[spec.rettype]] + out_types
x.append([val.uint for val in arg_vals])
outf.write('''
return 0;
}
''')
outf.flush()
os.system('cp %s %s' % (outf.name, 'debug.c'))
# TODO: add CPUIDs
try:
subprocess.check_output(
'clang %s -o %s -I%s %s/printers.o >/dev/null 2>/dev/null -mavx -mavx2 -march=native -mfma' % (
outf.name, exe.name, src_path, src_path),
shell=True)
except subprocess.CalledProcessError:
return False, False
num_outputs_per_intrinsic = len(out_types)
stdout = subprocess.check_output([exe.name])
lines = stdout.decode('utf-8').strip().split('\n')
assert(len(lines) == num_tests * num_outputs_per_intrinsic)
os.system('rm '+exe.name)
for i in range(0, len(lines), num_outputs_per_intrinsic):
outputs = []
for ty, line in zip(out_types, lines[i:i+num_outputs_per_intrinsic]):
outputs.append(line_to_bitvec(line, ty))
y.append(outputs)
correct = check_compiled_spec_with_examples(param_vals, outs, out_types, x, y)
return correct, True
if __name__ == '__main__':
import sys
import xml.etree.ElementTree as ET
from manual_parser import get_spec_from_xml
from intrinsic_types import IntegerType
sema = '''
<intrinsic tech="Other" rettype='unsigned int' name='_bextr_u32'>
<type>Integer</type>
<CPUID>BMI1</CPUID>
<category>Bit Manipulation</category>
<parameter type='unsigned int' varname='a' />
<parameter type='unsigned int' varname='start' />
<parameter type='unsigned int' varname='len' />
<description>Extract contiguous bits from unsigned 32-bit integer "a", and store the result in "dst". Extract the number of bits specified by "len", starting at the bit specified by "start".</description>
<operation>
tmp := ZeroExtend_To_512(a)
dst := ZeroExtend(tmp[start[7:0]+len[7:0]-1:start[7:0]])
</operation>
<instruction name='bextr' form='r32, r32, r32'/>
<header>immintrin.h</header>
</intrinsic>
'''
intrin_node = ET.fromstring(sema)
spec = get_spec_from_xml(intrin_node)
ok = fuzz_intrinsic(spec, num_tests=32)
print(ok)
| ychen306/upgraded-succotash | fuzzer.py | fuzzer.py | py | 12,802 | python | en | code | 0 | github-code | 36 |
33938514931 | import pytest
from schema import cities
async def test_database(sqlite_database):
tables_query = "SELECT * FROM sqlite_master where type='table';"
tables = await sqlite_database.fetch_all(query=tables_query)
assert len(tables) != 0
city_query = cities.insert(
values={"name": 'London',
"lattitude": 51.509865,
"longitude": -0.118092})
last_record_id = await sqlite_database.execute(query=city_query)
assert last_record_id == 1
| roman808080/route_planner | tests/test_db_manager.py | test_db_manager.py | py | 497 | python | en | code | 0 | github-code | 36 |
37457505741 | def circle(r): #calculate area of circle
s=3.14*r**2
return s
def rectangle(length,width): #calculate area of rectangle
s=length*width
return s
def square(side): #calculate area of square
s=side**2
return s
def triangle(base,height): #calculate area of triangle
s=base*height/2
return s
def get_func(ls): #vared kardane ashkal dar yek list
print("Enter name of 4 shape:")
for i in range(0,4):
shape=input()
ls.append(shape)
return ls
ls=[]
print(get_func(ls))
choose=input("choose a shape from list:") #entekhabe yek shekl baraye hesab kardan va neshan dadane masahat
if choose=='circle':
r=int(input("Enter Radius:"))
print("Area of circle is:",circle(r))
elif choose=='rectangle':
length=int(input("Enter length of rectangle:"))
width=int(input("Enter width of rectangle:"))
print("Area of rectangle is:",rectangle(length,width))
elif choose=='triangle':
height=int(input("Enter height of triangle:"))
base=int(input("Enter base of triangle:"))
print("Area of triangle is:",triangle(height,base))
elif choose=='square':
side=int(input("Enter side of square:"))
print("Area of square is:",square(side))
else:
print("character you are Entered is invalid")
| matinntb/project1 | soal 1.py | soal 1.py | py | 1,354 | python | en | code | 0 | github-code | 36 |
28613380166 | #!/usr/bin/env python
#Author velociraptor Genjix <aphidia@hotmail.com>
from PySide.QtGui import *
from PySide.QtCore import *
class LightWidget(QWidget):
def __init__(self, colour):
super(LightWidget, self).__init__()
self.colour = colour
self.onVal = False
def isOn(self):
return self.onVal
def setOn(self, on):
if self.onVal == on:
return
self.onVal = on
self.update()
@Slot()
def turnOff(self):
self.setOn(False)
@Slot()
def turnOn(self):
self.setOn(True)
def paintEvent(self, e):
if not self.onVal:
return
painter = QPainter(self)
painter.setRenderHint(QPainter.Antialiasing)
painter.setBrush(self.colour)
painter.drawEllipse(0, 0, self.width(), self.height())
on = Property(bool, isOn, setOn)
class TrafficLightWidget(QWidget):
def __init__(self):
super(TrafficLightWidget, self).__init__()
vbox = QVBoxLayout(self)
self.redLight = LightWidget(Qt.red)
vbox.addWidget(self.redLight)
self.yellowLight = LightWidget(Qt.yellow)
vbox.addWidget(self.yellowLight)
self.greenLight = LightWidget(Qt.green)
vbox.addWidget(self.greenLight)
pal = QPalette()
pal.setColor(QPalette.Background, Qt.black)
self.setPalette(pal)
self.setAutoFillBackground(True)
def createLightState(light, duration, parent=None):
lightState = QState(parent)
timer = QTimer(lightState)
timer.setInterval(duration)
timer.setSingleShot(True)
timing = QState(lightState)
timing.entered.connect(light.turnOn)
timing.entered.connect(timer.start)
timing.exited.connect(light.turnOff)
done = QFinalState(lightState)
timing.addTransition(timer, SIGNAL('timeout()'), done)
lightState.setInitialState(timing)
return lightState
class TrafficLight(QWidget):
def __init__(self):
super(TrafficLight, self).__init__()
vbox = QVBoxLayout(self)
widget = TrafficLightWidget()
vbox.addWidget(widget)
vbox.setContentsMargins(0, 0, 0, 0)
machine = QStateMachine(self)
redGoingYellow = createLightState(widget.redLight, 1000)
redGoingYellow.setObjectName('redGoingYellow')
yellowGoingGreen = createLightState(widget.redLight, 1000)
yellowGoingGreen.setObjectName('redGoingYellow')
redGoingYellow.addTransition(redGoingYellow, SIGNAL('finished()'), yellowGoingGreen)
greenGoingYellow = createLightState(widget.yellowLight, 3000)
greenGoingYellow.setObjectName('redGoingYellow')
yellowGoingGreen.addTransition(yellowGoingGreen, SIGNAL('finished()'), greenGoingYellow)
yellowGoingRed = createLightState(widget.greenLight, 1000)
yellowGoingRed.setObjectName('redGoingYellow')
greenGoingYellow.addTransition(greenGoingYellow, SIGNAL('finished()'), yellowGoingRed)
yellowGoingRed.addTransition(yellowGoingRed, SIGNAL('finished()'), redGoingYellow)
machine.addState(redGoingYellow)
machine.addState(yellowGoingGreen)
machine.addState(greenGoingYellow)
machine.addState(yellowGoingRed)
machine.setInitialState(redGoingYellow)
machine.start()
if __name__ == '__main__':
import sys
app = QApplication(sys.argv)
widget = TrafficLight()
widget.resize(110, 300)
widget.show()
sys.exit(app.exec_())
| pyside/Examples | examples/state-machine/trafficlight.py | trafficlight.py | py | 3,483 | python | en | code | 357 | github-code | 36 |
34993761644 | #!/usr/bin/env python3
# 深さ優先検索
def walk(f, x, y):
# 10*10 のマップ範囲外に出るな！！！！！！禁じられた森に入ってはならん！！！
if not (0 <= x < 10 > y >= 0):
return
i = y * 10 + x
# 海歩くな！！！！！！！！！
if f[i] == "x":
return
# 歩いた所を海に書き換えておこ
f[i] = "x"
# x, y の上下左右を歩いてみよ
# 陸続きなら進むけどそうじゃないんだったらそこで止まるで
walk(f, x, y + 1)
walk(f, x, y - 1)
walk(f, x + 1, y)
walk(f, x - 1, y)
*j, = open(0)
field = "".join(map(str.strip, j))
for i, f in enumerate(field):
# 陸なら無視
if f == "o":
continue
### リセット
walking = list(field)
y, x = divmod(i, 10)
# 海ならそこだけ一旦埋め立ててみるで
walking[i] = "o"
walk(walking, x, y)
# 陸が全て無くなったら陸続きやで。お疲れ様
if "o" not in walking:
print("YES")
exit()
print("NO") | mpses/AtCoder | Contest/ARC031/b/main.py | main.py | py | 1,076 | python | ja | code | 0 | github-code | 36 |
5993595252 | class Solution:
def topKFrequent(self, nums: List[int], k: int) -> List[int]:
counter = defaultdict(int)
for num in nums:
counter[num] += 1
freq = [[] for i in range(len(nums) + 1)]
for key, val in counter.items():
freq[val].append(key)
result = []
for i in reversed(freq):
for n in i:
result.append(n)
if len(result) == k:
return result | alexneysis/leetcode | 347-top-k-frequent-elements/347-top-k-frequent-elements.py | 347-top-k-frequent-elements.py | py | 479 | python | en | code | 0 | github-code | 36 |
9588266467 | import unittest
from tests import PluginTest
from plugins.basketball import basketball
from mock import patch, call
import requests
import datetime
from packages.memory.memory import Memory
class BasketballTest(PluginTest):
"""
Tests For Basketball Plugin
!!! test will be executed only if user has added his own api.basketball.com API_KEY
"""
def setUp(self):
self.test = self.load_plugin(basketball)
m = Memory("basketball.json")
self.unable_to_test_plugin = False
if m.get_data("API_KEY") is None:
self.unable_to_test_plugin = True
else:
self.headers = {"x-rapidapi-host": "api-basketball.p.rapidapi.com", "x-rapidapi-key": m.get_data("API_KEY")}
def test_todays_games(self):
if self.unable_to_test_plugin:
return
with patch.object(requests, 'get', headers=self.headers) as get_mock:
self.test.get_api_key(self.jarvis_api)
self.test.todays_games(self.jarvis_api)
date = datetime.datetime.now().strftime('%Y-%m-%d')
get_mock.assert_called_with(
"https://api-basketball.p.rapidapi.com/games?date={}".format(date), headers=self.headers)
def test_search_team(self):
if self.unable_to_test_plugin:
return
with patch.object(requests, 'get', headers=self.headers) as get_mock:
self.test.get_api_key(self.jarvis_api)
self.queue_input("boston")
self.test.search_team(self.jarvis_api)
get_mock.assert_called_with(
"https://api-basketball.p.rapidapi.com/teams?search=boston", headers=self.headers)
def test_search_league(self):
if self.unable_to_test_plugin:
return
with patch.object(requests, 'get', headers=self.headers) as get_mock:
self.test.get_api_key(self.jarvis_api)
self.queue_input("nba")
self.test.search_league(self.jarvis_api)
get_mock.assert_called_with(
"https://api-basketball.p.rapidapi.com/leagues?search=nba", headers=self.headers)
def test_list_leagues(self):
if self.unable_to_test_plugin:
return
with patch.object(requests, 'get', headers=self.headers) as get_mock:
self.test.get_api_key(self.jarvis_api)
self.test.list_leagues(self.jarvis_api)
get_mock.assert_called_with(
"https://api-basketball.p.rapidapi.com/leagues", headers=self.headers)
if __name__ == '__main__':
unittest.main()
| sukeesh/Jarvis | jarviscli/tests/test_basketball.py | test_basketball.py | py | 2,571 | python | en | code | 2,765 | github-code | 36 |
7919024721 | from __future__ import division
import geojson
from helper import load_geom, degrees_to_radians, get_coord, PRECISION
from math import pow, sqrt, pi, tan, cos, sin
from measurement import rhumb_destination
from transformation import transform_rotate
def ellipse(center, x_semi_axis, y_semi_axis, options={}):
steps = 64
if 'steps' in options:
steps = options['steps']
units = 'kilometers'
units_mapping = {
'miles': 'mi',
'kilometers': 'km',
'meters': 'm',
'degrees': 'degrees',
}
if 'units' in options:
units = options['units']
angle = 0
if 'angle' in options:
angle = options['angle']
# validation
if center is None:
raise Exception('center is required')
if x_semi_axis is None:
raise Exception('x_semi_axis is required')
if y_semi_axis is None:
raise Exception('y_semi_axis is required')
if units not in units_mapping:
raise Exception('non valid units')
units = units_mapping[units]
center = load_geom(center)
center_coords = get_coord(center)
angle_rad = 0
if units == 'degrees':
angle_rad = degrees_to_radians(angle)
else:
x_semi_axis = rhumb_destination(center, x_semi_axis, 90, {'units': units})
y_semi_axis = rhumb_destination(center, y_semi_axis, 0, {'units': units})
x_semi_axis = get_coord(x_semi_axis)[0] - center_coords[0]
y_semi_axis = get_coord(y_semi_axis)[1] - center_coords[1]
coordinates = []
for i in range(0, steps):
step_angle = (i * -360) / steps
x = (x_semi_axis * y_semi_axis) / sqrt(
pow(y_semi_axis, 2) + pow(x_semi_axis, 2) * pow(get_tan_deg(step_angle), 2)
)
y = (
0
if pow(get_tan_deg(step_angle), 2) == 0
else (x_semi_axis * y_semi_axis)
/ sqrt(
pow(x_semi_axis, 2)
+ pow(y_semi_axis, 2) / pow(get_tan_deg(step_angle), 2)
)
)
if step_angle < -90 and step_angle >= -270:
x = -x
if step_angle < -180 and step_angle >= -360:
y = -y
if units == 'degrees':
newx = x * cos(angle_rad) + y * sin(angle_rad)
newy = y * cos(angle_rad) - x * sin(angle_rad)
x = newx
y = newy
coordinates.append([x + center_coords[0], y + center_coords[1]])
coordinates.append(coordinates[0])
if units == 'degrees':
return geojson.dumps(
geojson.Feature(
geometry=geojson.Polygon([coordinates], precision=PRECISION)
)['geometry']
)
else:
return geojson.dumps(
transform_rotate(
geojson.Feature(
geometry=geojson.Polygon([coordinates], precision=PRECISION)
),
angle,
mutate=True,
)['geometry']
)
def get_tan_deg(deg):
rad = (deg * pi) / 180
return tan(rad)
| CartoDB/analytics-toolbox-core | clouds/redshift/libraries/python/lib/constructors/ellipse/__init__.py | __init__.py | py | 3,027 | python | en | code | 181 | github-code | 36 |
6797122561 | import logging
import requests
from django.urls import reverse
from django.conf import settings
from django.core.mail import get_connection
from django.core.mail.backends.base import BaseEmailBackend
from .engine import send_email
from mail.models import Message
logger = logging.getLogger('mails')
def get_admins():
return [mail for name, mail in settings.ADMINS]
class StoreBackend(BaseEmailBackend):
def __get_category_from_header(self, email):
category = None
if settings.MAIL_CATEGORY_HEADER_KEY in email.extra_headers:
category = email.extra_headers.get(settings.MAIL_CATEGORY_HEADER_KEY, None)
email.extra_headers.pop(settings.MAIL_CATEGORY_HEADER_KEY)
return category
def __is_error_or_test_mail(self, subject):
return subject.startswith(settings.MAIL_ERROR_MESAGE_SUBJECT) or subject.startswith(
settings.MAIL_TEST_MESSAGE_SUBJECT)
def send_messages(self, email_messages, notify_webhook=None):
AUTOSEND = getattr(settings, 'MAILER_AUTOSEND', False)
num_sent = 0
for email in email_messages:
if self.__is_error_or_test_mail(email.subject):
email.to = get_admins()
email.connection = get_connection(
backend=settings.MAILER_EMAIL_BACKEND
)
email.send()
else:
msg = Message.objects.create(
subject=email.subject,
to_email=email.to,
from_email=email.from_email,
reply_to=email.reply_to,
cc=email.cc,
bcc=email.bcc,
body=email.body,
category=self.__get_category_from_header(email),
attachment=email.attachments)
if notify_webhook:
mail_url = '{}{}'.format(
settings.DOMAIN_NAME,
reverse('mail:inbox-message', kwargs={'pk': msg.pk}),
)
try:
requests.put(
notify_webhook,
data={
'email_url': mail_url,
'email_status': settings.MAIL_NOTIFY_WEBHOOK_STATUS_OK,
},
)
except Exception as e: # noqa
logger.error('Notify webhook Exception: {}'.format(e))
if AUTOSEND:
send_email(msg)
num_sent += 1
return num_sent
| tomasgarzon/exo-services | service-exo-mail/mail/backend.py | backend.py | py | 2,657 | python | en | code | 0 | github-code | 36 |
15618824234 | #!/usr/bin/env python3
import argparse
from datetime import datetime
import json
import os
import sys
import time
import uuid
from aiosmtpd.controller import Controller
import mailparser
DATA_PATH = 'messages'
class Handler(object):
# noinspection PyPep8Naming,PyMethodMayBeStatic
async def handle_DATA(self, _, session, envelope):
print('Recieved message...')
# noinspection PyBroadException
try:
file_name = os.path.join('messages', str(uuid.uuid4().hex))
with open(file_name, 'w') as open_file:
content = envelope.original_content.decode('utf-8').replace("\r\r\n", "\r\n")
message = mailparser.parse_from_string(content)
json.dump({'mail_from': envelope.mail_from,
'rcpt_tos': envelope.rcpt_tos,
'subject': message.subject,
'body': message.body,
'data': content,
'timestamp': datetime.utcnow().isoformat()},
open_file)
return '250 OK'
except Exception:
return '500 Could not process your message'
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('host', type=str)
parser.add_argument('port', type=int)
args = parser.parse_args()
handler = Handler()
controller = Controller(handler, hostname=args.host, port=args.port)
# noinspection PyBroadException
try:
controller.start()
pid = str(os.getpid())
pidfile = "/run/postoffice/postoffice.pid"
open(pidfile, 'w').write(pid)
print("Running smtpd server on {}:{}\n".format(args.host, args.port))
while True:
time.sleep(3)
except Exception as exc:
print(exc, file=sys.stderr)
controller.stop()
finally:
os.unlink(pidfile)
| OPSnet/PostOffice | smtpd.py | smtpd.py | py | 1,929 | python | en | code | 1 | github-code | 36 |
8346930934 | import os
import random
import tempfile
from copy import copy
from functools import partial
from multiprocessing import cpu_count
import pickle
import numpy as np
import tensorflow as tf
from joblib import Parallel, delayed
from .tokenization import printable_text
from .utils import (BOS_TOKEN, EOS_TOKEN, add_special_tokens_with_seqs,
create_instances_from_document, create_mask_and_padding,
create_masked_lm_predictions, punc_augument,
tokenize_text_with_seqs, truncate_seq_pair)
def create_single_problem_single_instance(problem,
ex_index,
example,
label_encoder,
params,
tokenizer,
mode,
problem_type,
is_seq):
raw_inputs, raw_target = example
# punctuation augumentation
if params.punc_replace_prob > 0 and mode == 'train':
raw_inputs = punc_augument(raw_inputs, params)
# tokenize inputs, now the length is fixed, target == raw_target
if isinstance(raw_inputs, dict):
tokens_a, target = tokenize_text_with_seqs(
tokenizer, raw_inputs['a'], raw_target, is_seq)
tokens_b, _ = tokenize_text_with_seqs(
tokenizer, raw_inputs['b'], raw_target)
else:
tokens_a, target = tokenize_text_with_seqs(
tokenizer, raw_inputs, raw_target, is_seq)
tokens_b = None
if tokens_b is not None and is_seq:
raise NotImplementedError(
'Sequence Labeling with tokens b is not implemented')
if not tokens_a:
return
# check whether tokenization changed the length
if is_seq:
if len(target) != len(tokens_a):
tf.logging.warning('Data %d broken' % ex_index)
return
# truncate tokens and target to max_seq_len
tokens_a, tokens_b, target = truncate_seq_pair(
tokens_a, tokens_b, target, params.max_seq_len, is_seq=is_seq)
# add [SEP], [CLS] tokens
tokens, segment_ids, target = add_special_tokens_with_seqs(
tokens_a, tokens_b, target, is_seq)
# train mask lm as augument task while training
if params.augument_mask_lm and mode == 'train':
rng = random.Random()
(mask_lm_tokens, masked_lm_positions,
masked_lm_labels) = create_masked_lm_predictions(
tokens,
params.masked_lm_prob,
params.max_predictions_per_seq,
list(tokenizer.vocab.keys()), rng)
_, mask_lm_tokens, _, _ = create_mask_and_padding(
mask_lm_tokens,
copy(segment_ids),
copy(target),
params.max_seq_len,
is_seq,
dynamic_padding=params.dynamic_padding)
masked_lm_weights, masked_lm_labels, masked_lm_positions, _ = create_mask_and_padding(
masked_lm_labels, masked_lm_positions, None, params.max_predictions_per_seq)
mask_lm_input_ids = tokenizer.convert_tokens_to_ids(
mask_lm_tokens)
masked_lm_ids = tokenizer.convert_tokens_to_ids(masked_lm_labels)
input_mask, tokens, segment_ids, target = create_mask_and_padding(
tokens, segment_ids, target, params.max_seq_len, is_seq, dynamic_padding=params.dynamic_padding)
# create mask and padding for labels of seq2seq problem
if problem_type in ['seq2seq_tag', 'seq2seq_text']:
# tokenize text if target is text
if problem_type == 'seq2seq_text':
# assign num_classes for text generation problem
params.num_classes[problem] = len(label_encoder.vocab)
target, _ = tokenize_text_with_seqs(
label_encoder, target, None, False)
target, _, _ = truncate_seq_pair(
target, None, None, params.decode_max_seq_len, is_seq=is_seq)
# since we initialize the id to 0 in prediction, we need
# to make sure that BOS_TOKEN is [PAD]
target = [BOS_TOKEN] + target + [EOS_TOKEN]
label_mask, target, _, _ = create_mask_and_padding(
target, [0] * len(target), None, params.decode_max_seq_len)
input_ids = tokenizer.convert_tokens_to_ids(tokens)
if isinstance(target, list):
if problem_type == 'seq2seq_text':
label_id = label_encoder.convert_tokens_to_ids(target)
else:
label_id = label_encoder.transform(target).tolist()
label_id = [np.int32(i) for i in label_id]
else:
label_id = label_encoder.transform([target]).tolist()[0]
label_id = np.int32(label_id)
if not params.dynamic_padding:
assert len(input_ids) == params.max_seq_len
assert len(input_mask) == params.max_seq_len
assert len(segment_ids) == params.max_seq_len, segment_ids
if is_seq:
assert len(label_id) == params.max_seq_len
# logging in debug mode
if ex_index < 5:
tf.logging.debug("*** Example ***")
tf.logging.debug("tokens: %s" % " ".join(
[printable_text(x) for x in tokens]))
tf.logging.debug("input_ids: %s" %
" ".join([str(x) for x in input_ids]))
tf.logging.debug("input_mask: %s" %
" ".join([str(x) for x in input_mask]))
tf.logging.debug("segment_ids: %s" %
" ".join([str(x) for x in segment_ids]))
if is_seq or problem_type in ['seq2seq_tag', 'seq2seq_text']:
tf.logging.debug("%s_label_ids: %s" %
(problem, " ".join([str(x) for x in label_id])))
tf.logging.debug("%s_label: %s" %
(problem, " ".join([str(x) for x in target])))
else:
tf.logging.debug("%s_label_ids: %s" %
(problem, str(label_id)))
tf.logging.debug("%s_label: %s" %
(problem, str(target)))
if params.augument_mask_lm and mode == 'train':
tf.logging.debug("mask lm tokens: %s" % " ".join(
[printable_text(x) for x in mask_lm_tokens]))
tf.logging.debug("mask lm input_ids: %s" %
" ".join([str(x) for x in mask_lm_input_ids]))
tf.logging.debug("mask lm label ids: %s" %
" ".join([str(x) for x in masked_lm_ids]))
tf.logging.debug("mask lm position: %s" %
" ".join([str(x) for x in masked_lm_positions]))
# create return dict
if not params.augument_mask_lm:
return_dict = {
'input_ids': input_ids,
'input_mask': input_mask,
'segment_ids': segment_ids,
'%s_label_ids' % problem: label_id
}
else:
if mode == 'train' and random.uniform(0, 1) <= params.augument_rate:
return_dict = {
'input_ids': mask_lm_input_ids,
'input_mask': input_mask,
'segment_ids': segment_ids,
'%s_label_ids' % problem: label_id,
"masked_lm_positions": masked_lm_positions,
"masked_lm_ids": masked_lm_ids,
"masked_lm_weights": masked_lm_weights,
}
else:
return_dict = {
'input_ids': input_ids,
'input_mask': input_mask,
'segment_ids': segment_ids,
'%s_label_ids' % problem: label_id,
"masked_lm_positions": np.zeros([params.max_predictions_per_seq]),
"masked_lm_ids": np.zeros([params.max_predictions_per_seq]),
"masked_lm_weights": np.zeros([params.max_predictions_per_seq]),
}
if problem_type in ['seq2seq_tag', 'seq2seq_text']:
return_dict['%s_mask' % problem] = label_mask
return return_dict
def _multiprocessing_wrapper(
problem,
example_list,
label_encoder,
params,
tokenizer,
mode,
problem_type,
is_seq):
return_list = []
for ex_index, example in enumerate(example_list):
return_list.append(create_single_problem_single_instance(
problem,
999,
example,
label_encoder,
params,
tokenizer,
mode,
problem_type,
is_seq))
return return_list
def create_single_problem_generator(problem,
inputs_list,
target_list,
label_encoder,
params,
tokenizer,
mode):
"""Function to create iterator for single problem
This function will:
1. Do some text cleaning using original bert tokenizer, if
problem type is sequential tagging, corresponding labels
will be removed.
Example:
Before: inputs: ['a', '&', 'c'] target: [0, 0, 1]
After: inputs: ['a', 'c'] target: [0, 1]
2. Add [CLS], [SEP] tokens
3. Padding
4. yield result dict
Arguments:
problem {str} -- problem name
inputs_list {list } -- inputs list
target_list {list} -- target list, should have the same length as inputs list
label_encoder {LabelEncoder} -- label encoder
params {Params} -- params
tokenizer {tokenizer} -- Bert Tokenizer
epoch {int} -- Deprecate
"""
problem_type = params.problem_type[problem]
# whether this problem is sequential labeling
# for sequential labeling, targets needs to align with any
# change of inputs
is_seq = problem_type in ['seq_tag']
if not params.multiprocess:
for ex_index, example in enumerate(zip(inputs_list, target_list)):
return_dict = create_single_problem_single_instance(problem,
ex_index,
example,
label_encoder,
params,
tokenizer,
mode,
problem_type,
is_seq)
yield return_dict
else:
return_dict_list = []
pickle_file = os.path.join(
params.tmp_file_dir, '{0}_{1}_data.pkl'.format(problem, mode))
if not os.path.exists(pickle_file):
# params.tmp_file_dir = tempfile.mkdtemp(dir='.')
os.makedirs('tmp', exist_ok=True)
params.tmp_file_dir = 'tmp'
pickle_file = os.path.join(
params.tmp_file_dir, '{0}_{1}_data.pkl'.format(problem, mode))
tf.logging.info(
'Saving preprocessing files to {0}'.format(pickle_file))
partial_fn = partial(_multiprocessing_wrapper, problem=problem, label_encoder=label_encoder,
params=params, tokenizer=tokenizer,
mode=mode, problem_type=problem_type, is_seq=is_seq)
example_list = list(zip(inputs_list, target_list))
num_process = cpu_count()
def split(a, n):
k, m = divmod(len(a), n)
return (a[i * k + min(i, m):(i + 1) * k + min(i + 1, m)] for i in range(n))
example_list = list(split(example_list, num_process))
return_dict_list_list = Parallel(num_process)(delayed(partial_fn)(
example_list=example) for example in example_list
)
pickle.dump(return_dict_list_list, open(pickle_file, 'wb'))
else:
return_dict_list_list = pickle.load(open(pickle_file, 'rb'))
for return_dict_list in return_dict_list_list:
for return_dict in return_dict_list:
yield return_dict
def create_pretraining_generator(problem,
inputs_list,
target_list,
label_encoder,
params,
tokenizer
):
"""Slight modification of original code
Raises:
ValueError -- Input format not right
"""
if not isinstance(inputs_list[0][0], list):
raise ValueError('inputs is expected to be list of list of list.')
all_documents = []
for document in inputs_list:
all_documents.append([])
for sentence in document:
all_documents[-1].append(tokenizer.tokenize('\t'.join(sentence)))
all_documents = [d for d in all_documents if d]
rng = random.Random()
rng.shuffle(all_documents)
vocab_words = list(tokenizer.vocab.keys())
instances = []
print_count = 0
for _ in range(params.dupe_factor):
for document_index in range(len(all_documents)):
instances = create_instances_from_document(
all_documents,
document_index,
params.max_seq_len,
params.short_seq_prob,
params.masked_lm_prob,
params.max_predictions_per_seq,
vocab_words, rng)
for instance in instances:
tokens = instance.tokens
segment_ids = list(instance.segment_ids)
input_mask, tokens, segment_ids, _ = create_mask_and_padding(
tokens, segment_ids, None, params.max_seq_len)
masked_lm_positions = list(instance.masked_lm_positions)
masked_lm_weights, masked_lm_labels, masked_lm_positions, _ = create_mask_and_padding(
instance.masked_lm_labels, masked_lm_positions, None, params.max_predictions_per_seq)
input_ids = tokenizer.convert_tokens_to_ids(tokens)
masked_lm_ids = tokenizer.convert_tokens_to_ids(
masked_lm_labels)
next_sentence_label = 1 if instance.is_random_next else 0
yield_dict = {
"input_ids": input_ids,
"input_mask": input_mask,
"segment_ids": segment_ids,
"masked_lm_positions": masked_lm_positions,
"masked_lm_ids": masked_lm_ids,
"masked_lm_weights": masked_lm_weights,
"next_sentence_label_ids": next_sentence_label
}
if print_count < 3:
tf.logging.debug('%s : %s' %
('tokens', ' '.join([str(x) for x in tokens])))
for k, v in yield_dict.items():
if not isinstance(v, int):
tf.logging.debug('%s : %s' %
(k, ' '.join([str(x) for x in v])))
print_count += 1
yield yield_dict
def create_generator(params, mode):
"""Function to create iterator for multiple problem
This function dose the following things:
1. Create dummy labels for each problems.
2. Initialize all generators
3. Sample a problem to train at this batch. If eval, take turns
4. Create a loss multiplier
5. Tried to generate samples for target problem, if failed, init gen
6. Add dummy label to other problems
Example:
Problem: cws|NER|weibo_ner&weibo_cws
1. Dummy labels: cws_label_ids: [0,0,0] ...
2. Blablabla
3. Sample, say (weibo_ner&weibo_cws)
4. loss multipliers: {'cws_loss_multiplier': 0, ..., 'weibo_ner_loss_multiplier': 1, ...}
...
Arguments:
params {Params} -- params
mode {mode} -- mode
"""
# example
# problem_list: ['NER', 'cws', 'weibo_ner', 'weibo_cws']
# problem_chunk: [['NER'], ['cws'], ['weibo_ner', 'weibo_cws']]
problem_list = []
problem_chunk = []
for problem_dict in params.run_problem_list:
problem_list += list(problem_dict.keys())
problem_chunk.append(list(problem_dict.keys()))
# get dummy labels
def _create_dummpy_label(problem_type):
if problem_type == 'cls':
return 0
elif problem_type == 'seq_tag':
return [0]*params.max_seq_len
else:
return [0]*params.decode_max_seq_len
dummy_label_dict = {problem+'_label_ids': _create_dummpy_label(
params.problem_type[problem]) for problem in problem_list if params.problem_type[problem] != 'pretrain'}
dummy_label_dict.update({problem+'_mask': _create_dummpy_label(
params.problem_type[problem]) for problem in problem_list if params.problem_type[problem] in ['seq2seq_tag', 'seq2seq_text']})
# init gen
try:
gen_dict = {problem: params.read_data_fn[problem](params, mode)
for problem in problem_list}
except KeyError:
not_exist_problem = [
p for p in problem_list if p not in params.read_data_fn]
raise KeyError(
'The preprocessing function of {0} not found, make sure you called params.add_problem. If you\'re using train_bert_multitask, please make sure you provided problem_type_dict and processing_fn_dict.'.format(not_exist_problem))
while gen_dict:
# sample problem to train
if len(problem_chunk) > 1:
data_num_list = [params.data_num_dict[chunk[0]]
for chunk in problem_chunk]
if params.multitask_balance_type == 'data_balanced':
sample_prob = np.array(data_num_list) / np.sum(data_num_list)
current_problem_chunk_ind = np.random.choice(
list(range(len(problem_chunk))), p=sample_prob)
current_problem_chunk = problem_chunk[current_problem_chunk_ind]
elif params.multitask_balance_type == 'problem_balanced':
sample_prob = np.array(
[1]*len(data_num_list)) / np.sum([1]*len(data_num_list))
current_problem_chunk_ind = np.random.choice(
list(range(len(problem_chunk))), p=sample_prob)
current_problem_chunk = problem_chunk[current_problem_chunk_ind]
else:
current_problem_chunk = problem_chunk[0]
# create loss multiplier
loss_multiplier = {
problem+'_loss_multiplier': 0 for problem in problem_list}
for problem in current_problem_chunk:
loss_multiplier[problem+'_loss_multiplier'] = 1
base_dict = {}
base_input = None
for problem in current_problem_chunk:
try:
instance = next(gen_dict[problem])
except StopIteration:
if mode == 'train':
gen_dict[problem] = params.read_data_fn[problem](
params, mode)
instance = next(gen_dict[problem])
else:
del gen_dict[problem]
continue
except KeyError:
continue
if not instance:
continue
base_dict.update(instance)
if base_input is None:
base_input = instance['input_ids']
elif not params.augument_mask_lm:
assert base_input == instance[
'input_ids'], 'Inputs id of two chained problem not aligned. Please double check!'
if not base_dict:
continue
for problem in problem_list:
problem_type = params.problem_type[problem]
problem_label_name = '{0}_label_ids'.format(problem)
if problem_label_name not in base_dict:
if problem_type == 'seq_tag':
base_dict[problem_label_name] = dummy_label_dict[problem_label_name][:len(
base_dict['input_ids'])]
else:
base_dict[problem_label_name] = dummy_label_dict[problem_label_name]
if problem_type in ['seq2seq_tag', 'seq2seq_text']:
base_dict['{0}_mask'.format(
problem)] = dummy_label_dict['{0}_mask'.format(problem)]
# add loss multipliers
base_dict.update(loss_multiplier)
yield base_dict
| hauwenc/bert-multitask-learning | bert_multitask_learning/create_generators.py | create_generators.py | py | 20,858 | python | en | code | null | github-code | 36 |
21891037955 | import json
import logging
import traceback
from django.views import View
from django.http import JsonResponse
from backend.models import AnnotationCategory, Video
# from django.core.exceptions import BadRequest
class AnnoatationCategoryCreate(View):
def post(self, request):
try:
if not request.user.is_authenticated:
return JsonResponse({"status": "error"})
# decode data
try:
body = request.body.decode("utf-8")
except (UnicodeDecodeError, AttributeError):
body = request.body
try:
data = json.loads(body)
except Exception as e:
return JsonResponse({"status": "error", "type": "wrong_request_body"})
if "name" not in data:
return JsonResponse({"status": "error", "type": "missing_values"})
try:
query_args = {"name": data.get("name"), "owner": request.user}
if "video_id" in data:
query_args["video__id"] = data.get("video_id")
annotation_category_db = AnnotationCategory.objects.get(**query_args)
except AnnotationCategory.DoesNotExist:
create_args = {"name": data.get("name"), "owner": request.user}
if "color" in data:
create_args["color"] = data.get("color")
if "video_id" in data:
try:
video_db = Video.objects.get(id=data.get("video_id"))
except Video.DoesNotExist:
return JsonResponse({"status": "error", "type": "not_exist"})
create_args["video"] = video_db
annotation_category_db = AnnotationCategory.objects.create(**create_args)
return JsonResponse({"status": "ok", "entry": annotation_category_db.to_dict()})
except Exception as e:
logging.error(traceback.format_exc())
return JsonResponse({"status": "error"})
class AnnoatationCategoryList(View):
def get(self, request):
try:
if not request.user.is_authenticated:
return JsonResponse({"status": "error"})
query_args = {}
query_args["owner"] = request.user
if "video_id" in request.GET:
query_args["video__id"] = request.GET.get("video_id")
query_results = AnnotationCategory.objects.filter(**query_args)
entries = []
for annotation_category in query_results:
entries.append(annotation_category.to_dict())
return JsonResponse({"status": "ok", "entries": entries})
except Exception as e:
logging.error(traceback.format_exc())
return JsonResponse({"status": "error"})
| TIBHannover/tibava-backend | backend/views/annotation_category.py | annotation_category.py | py | 2,854 | python | en | code | 0 | github-code | 36 |
32331024727 | #!/usr/bin/python3
"""Contains a class named Base"""
import json
class Base:
"""Class named Base"""
__nb_objects = 0
def __init__(self, id=None):
"""initialize Base class"""
if id is None:
Base.__nb_objects += 1
self.id = Base.__nb_objects
else:
self.id = id
@staticmethod
def to_json_string(list_dictionaries):
"""returns JSON string representation of list_dictionaries"""
if not list_dictionaries or list_dictionaries is None:
return "[]"
return json.dumps(list_dictionaries)
@staticmethod
def from_json_string(json_string):
"""returns list of the JSON string json_string"""
if not json_string or json_string is None:
return []
return json.loads(json_string)
@classmethod
def save_to_file(cls, list_objs):
"""writes JSON string of list_objs to a file"""
file_name = cls.__name__ + ".json"
with open(file_name, "w", encoding="utf-8") as f:
if list_objs is None:
f.write("[]")
else:
f.write(cls.to_json_string([i.to_dictionary()
for i in list_objs]))
@classmethod
def create(cls, **dictionary):
"""returns instance with attributes already set"""
if cls.__name__ == "Rectangle":
dummy = cls(1, 1)
if cls.__name__ == "Square":
dummy = cls(1)
dummy.update(**dictionary)
return dummy
@classmethod
def load_from_file(cls):
"""returns a list of instances"""
file_name = cls.__name__ + ".json"
ls = []
try:
with open(file_name, "r", encoding="utf-8") as f:
ls2 = cls.from_json_string(f.read())
for i in ls2:
ls.append(cls.create(**i))
except:
pass
return ls
| ammartica/holbertonschool-higher_level_programming | 0x0C-python-almost_a_circle/models/base.py | base.py | py | 1,956 | python | en | code | 0 | github-code | 36 |
74146205863 | from flair.data import Sentence
from flair.models import SequenceTagger
from flair.embeddings import (DocumentPoolEmbeddings,
FlairEmbeddings, StackedEmbeddings)
from torch import dot, norm, squeeze
from pathlib import Path
import pickle
from odm.nlp.tensors import PCA, plot_embeddings, normalize_tensors
from odm.nlp.parse import parse_veclang
class Model:
modelpath = '/data/model/'
def __init__(self):
# Sequence Tagging Model
tagger_file = self.modelpath + 'tagger.pt'
if Path(tagger_file).is_file():
print('loading tagger from file')
self.tagger = SequenceTagger.load_from_file(tagger_file)
else:
print('downloading pretrained tagger')
self.tagger = SequenceTagger.load('ner-ontonotes')
self.tagger.save(tagger_file)
# Text Embedding Model
embeddings_file = self.modelpath + 'embeddings.pickle'
if Path(embeddings_file).is_file():
print('loading embedder from file')
filestream = open(embeddings_file, 'rb')
self.embeddings = pickle.load(filestream)
else:
print('downloading pretrained embedders')
self.embeddings = [
# WordEmbeddings('glove'),
FlairEmbeddings('multi-forward')
# FlairEmbeddings('multi-backward')
]
filestream = open(embeddings_file, 'wb')
pickle.dump(self.embeddings, filestream)
self.token_embedder = StackedEmbeddings(self.embeddings)
self.doc_embedder = DocumentPoolEmbeddings(self.embeddings)
def parse(self, text):
sentence = Sentence(text)
self.tagger.predict(sentence)
self.token_embedder.embed(sentence)
self.doc_embedder.embed(sentence)
return sentence
def mindmap(self, text):
# parsing
lines, arrows = parse_veclang(text)
sentences = [self.parse(line) for line in lines]
tensors = [s.get_embedding() for s in sentences]
# tensor processing
norm_tensors = normalize_tensors(tensors)
flat_tensors = PCA(norm_tensors)
# plot map
filename = plot_embeddings(lines, flat_tensors, arrows)
return f'Plotted mindmap to {filename}'
def similarity(self, text):
lines = text.split('//')
sentences = [self.parse(line) for line in lines]
vecs = [squeeze(s.embedding) for s in sentences]
sim = dot(vecs[0], vecs[1])/(norm(vecs[0])*norm(vecs[1]))
return f'the similarity is {sim}'
| ixxie/odm | src/odm/nlp/model.py | model.py | py | 2,615 | python | en | code | 0 | github-code | 36 |
34983429354 | #!/usr/bin/env python3
# 2次元累積和 S の [x1, x2) × [y1, y2) 総和
def ac2(s, x1, x2, y1, y2):
return s[x2][y2] - s[x1][y2] - s[x2][y1] + s[x1][y1]
import numpy as np
_, *d = open(0)
n, k = map(int, _.split())
B = np.zeros((2*k, 2*k))
for e in d:
*z, c = e.split()
x, y = map(int, z)
B[x % (2*k)][(y + k * (z == "W")) % (2*k)] += 1
B.cumsum(axis = 0)
B.cumsum(axis = 1)
B = np.tile(B, (2,2))
print(B)
# 書きかけ | mpses/AtCoder | Contest/ABC086/d/main.py | main.py | py | 441 | python | en | code | 0 | github-code | 36 |
13509904582 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Resize and add text to videos
Usage example:
$ python transform.py
"""
import random
import os
import shutil
from moviepy.editor import *
from moviepy.video.tools.subtitles import SubtitlesClip
from sqlite import *
class VideoTransform:
def __init__(self, videos=[]):
print(' ----> {} videos to transform'.format(len(videos)))
for video in videos:
video['clip'] = VideoFileClip(video['filepath'])
self.videos = videos
print(' --> {} videos converted to clips'.format(len(self.videos)))
def adjustSize(self, clip,width,height):
# get current dimensions and ratio
clipWidth,clipHeight = clip.size
ratio = clipWidth / clipHeight
# resize the clip
if ratio > (width/height):
clip2 = clip.resize(width=width)
else:
clip2 = clip.resize(height=height)
return clip2
def adjustSizes(self,width=1920,height=1080):
for video in self.videos:
video['clip'] = self.adjustSize(video['clip'],width,height)
def addSubtitle(self, clip, subtitle, howLong, maxLength=15):
# trim the subtitle if it's too long
if len(subtitle) > maxLength:
subtitle = subtitle[:maxLength] + '...'
# set how long the subtitle will show
howLong = min(howLong,clip.duration)
subs = [((0, howLong), subtitle)]
# create clip with subtitle
subtitles = SubtitlesClip(subs, lambda txt: TextClip(txt, font='Arial', fontsize=72, color='white', stroke_color='black'))
# merge clip and subtitles
result = CompositeVideoClip([clip, subtitles.set_position(('center','bottom'))])
# return resulting clip
return result
def addSubtitles(self, howLong=10):
print(' ----> Adding subtitles')
for index, video in enumerate(self.videos):
video['clip'] = self.addSubtitle(video['clip'],video['title'],howLong)
print(' --> {}/{} subtitles added'.format(index+1,len(self.videos)))
def addSource(self,clip,source,howLong):
howLong = min(howLong,clip.duration)
subs = [((0, howLong), source)]
# create clip with source
subtitles = SubtitlesClip(subs, lambda txt: TextClip(txt, font='Arial', fontsize=24, color='white', bg_color='black'))
# merge clip and text
result = CompositeVideoClip([clip, subtitles.set_position((0,0))])
# return resulting clip
return result
def addSources(self, howLong=10):
print(' ----> Adding sources')
for index, video in enumerate(self.videos):
video['clip'] = self.addSource(video['clip'],video['link'],howLong)
print(' --> {}/{} sources added'.format(index+1,len(self.videos)))
def save(self, clip, filename, threads=1):
filepath = os.path.join(os.getcwd(),filename)
clip.write_videofile(filepath, codec='mpeg4', audio=True, threads=threads)
return filepath
if __name__ == '__main__':
# get videos from DB
sql = Sqlite()
result = sql.run('SELECT * FROM videos WHERE duration IS NULL')
videos = [ row for row in result if os.path.isfile(row['filepath']) ]
# convert them to clips
limit = 10
transform = VideoTransform(videos[:limit])
# resize them
transform.adjustSizes()
# add subtitles
transform.addSubtitles()
# add link to original
transform.addSources()
# backup the original videos
# and save the updated versions
for video in transform.videos:
shutil.move(video['filepath'],video['filepath']+'.original')
transform.save(video['clip'],video['filepath'])
# update their durations and sizes on the DB
for video in transform.videos:
filepath = video['filepath']
duration = video['clip'].duration
width,height = video['clip'].size
sql.run('''
UPDATE videos
SET duration = {duration},
width = {width},
height = {height}
WHERE
filepath = '{filepath}'
'''.format(
duration=duration,
filepath=filepath,
width=width,
height=height
))
| miguel-faggioni/zap-bot | transform.py | transform.py | py | 4,335 | python | en | code | 0 | github-code | 36 |
8415334938 | #!/usr/bin/python3
"""This is a module for the island func
"""
def island_perimeter(grid):
"""This is a function that returns perimeter
of the island:
traverse the grid to find a 1
and then check all four directions
"""
peri = 0
xrows = grid
if grid != []:
ycols = grid[0]
for x in range(len(xrows)):
for y in range(len(ycols)):
if grid[x][y] == 1:
# check the left
if y == 0 or grid[x][y - 1] == 0:
peri += 1
# check the top
if x == 0 or grid[x - 1][y] == 0:
peri += 1
# check the right
if y == len(ycols) - 1 or grid[x][y + 1] == 0:
peri += 1
# check the bottom
if x == len(xrows) - 1 or grid[x + 1][y] == 0:
peri += 1
return peri
| logicalperson0/alx-low_level_programming | 0x1C-makefiles/5-island_perimeter.py | 5-island_perimeter.py | py | 918 | python | en | code | 0 | github-code | 36 |
5340113648 | from globals import *
class MainHandler(webocrat_Request):
@need_registered_user
def get(self):
template_vals = {}
self.render_simple_template('HomePage.django.html', template_vals)
class HartaCainilorHandler(webocrat_Request):
# @need_registered_user
def get(self):
template_vals = {
'login_iframe': LOGIN_IFRAME,
'BASE_URL': BASE_URL,
'lat' : '44.44',
'lng' : '26.1',
'zoom' : 14
}
self.session['redirect_after_login'] = self.request.url
self.render_template('HartaCainilor.django.html', template_vals)
from webapp2_extras import routes
app = webapp2.WSGIApplication([
routes.DomainRoute('localhost',
[webapp2.Route('/hartacainilor', handler=HartaCainilorHandler, name='hartacainilor-home0'),
]),
routes.DomainRoute('hartacainilor.webocrat.com',
[webapp2.Route('/', handler=HartaCainilorHandler, name='hartacainilor-home'),
]),
routes.DomainRoute('www.webocrat.com',
[webapp2.Route('/hartacainilor', handler=HartaCainilorHandler, name='hartacainilor-home'),
]),
routes.DomainRoute('www.webocrat.com',
[webapp2.Route('/', handler=MainHandler, name="webocrat-home"),
]),
routes.DomainRoute(BASE_URL,
[webapp2.Route('/', handler=MainHandler, name="webocrat-home2"),
]),
])
| webocrat/webocrat | py/main.py | main.py | py | 1,451 | python | en | code | 1 | github-code | 36 |
36182217190 | import os
_basedir = os.path.abspath(os.path.dirname(__file__))
DEBUG = True
ADMINS = frozenset(['volodymyr.dehtiarenko@gmail.com'])
SECRET_KEY = 'This string will be replaced with a proper key in production.'
SQLALCHEMY_ECHO = True
SQLALCHEMY_DATABASE_URI = "mysql+pymysql://admin:12345@localhost/24servis"
SQLALCHEMY_TRACK_MODIFICATIONS = False
WTF_CSRF_ENABLED = True
WTF_CSRF_SECRET_KEY = "somethingimpossibletoguess" | volodymyr-dehtiarenko/webservis | config.py | config.py | py | 428 | python | en | code | 0 | github-code | 36 |
35614129449 | import msgpack
import redis
import click
import socket
import pandas as pd
import numpy as np
import ujson as json
#Extra Functions (for enrichment purpose)
df_port_name = pd.read_csv('enrichments/port_name.txt',delimiter=",", names=['port_num','port_name'])
df_ip_proto_name = pd.read_csv('enrichments/ip_proto_name.txt',delimiter=",", names=['proto_num','proto_name'])
@click.group()
def cli():
pass
@click.command()
def receive():
r = redis.StrictRedis(host='localhost', port=6379, db=0)
p = r.pubsub()
p.subscribe('patterns')
try:
# non-blocking
# while True:
# print(p.get_message())
# blocking
for message in p.listen():
if isinstance(message['data'], bytes):
payload = msgpack.unpackb(message['data'], encoding='utf-8')
print(payload)
except KeyboardInterrupt as e:
print('Keyboard interrupt')
def get_ip_proto_name(ip_proto_number):
try:
return df_ip_proto_name[df_ip_proto_name['proto_num']==ip_proto_number]['proto_name'].values[0]
except:
return str(ip_proto_number)
def get_port_name(port_number):
try:
return df_port_name[df_port_name['port_num']==port_number]['port_name'].values[0]+" service port"
except:
return "port "+str(int(port_number))
def get_tcp_flag_name(tcp_flags_str):
tcp_flags=""
try:
tcp_flags += ("FIN" if (tcp_flags_str.find('F') != -1) else next)
except:
next
try:
tcp_flags += ("SYN" if (tcp_flags_str.find('S')!= -1) else next)
except:
next
try:
tcp_flags += ("RST" if tcp_flags_str.find('R') != -1 else next)
except:
next
try:
tcp_flags += ("PUSH" if tcp_flags_str.find('P') != -1 else next)
except:
next
try:
tcp_flags += ("ACK" if tcp_flags_str.find('A') != -1 else next)
except:
next
try:
tcp_flags += ("URG" if tcp_flags_str.find('U') != -1 else next)
except:
next
try:
tcp_flags += ("ECE" if tcp_flags_str.find('E') != -1 else next)
except:
next
try:
tcp_flags += ("CWR" if tcp_flags_str.find('C') != -1 else next)
except:
next
return tcp_flags
def analyse(df):
"""
Analysis only top traffic stream
:param df:
:return:
"""
debug = True
attack_case = "-1"
ttl_variation_threshold = 4
result = {
"reflected":False,
"spoofed":False,
"fragmented":False,
"pattern_traffic_share":0.0,
"pattern_packet_count":0,
"pattern_total_megabytes":0,
"start_timestamp":0,
"end_timestamp":0,
"dst_ports":[], #(port,share)
"src_ports":[], #(port,share)
"ttl_variation":[],
"src_ips":[],
"dst_ips":[],
"packets":[]
}
if debug: print("\n\n\n")
top_ip_dst = df['ip_dst'].value_counts().index[0]
if debug: print("Top dst IP: "+ top_ip_dst)
result["dst_ips"] = top_ip_dst
top_ip_proto = df[df['ip_dst'] == top_ip_dst]['ip_proto'].value_counts().index[0]
if debug: print("Top IP protocol: "+str(top_ip_proto))
####
# Performing a first filter based on the top_ip_dst (target IP), the source IPs canNOT be from the \16 of the
# target IP, and the top IP protocol that targeted the top_ip_dst
df_filtered = df[
(df['ip_dst'] == top_ip_dst) & ~df['ip_src'].str.contains(".".join(top_ip_dst.split('.')[0:2]), na=False) & (
df['ip_proto'] == top_ip_proto)]
####
# Calculating the number of packets after the first filter
total_packets_filtered = len(df_filtered)
if debug: print("Number of packets: "+str(total_packets_filtered))
result["total_nr_packets"] = total_packets_filtered
####
# For attacks in the IP protocol level
attack_label = get_ip_proto_name(top_ip_proto) + "-based attack"
result["transport_protocol"] = get_ip_proto_name(top_ip_proto)
####
# For attacks based on TCP or UDP, which have source and destination ports
if ((top_ip_proto == 6) or (top_ip_proto == 17)):
if debug: print("\n####################\nREMAINING :\n####################")
####
# Calculating the distribution of source ports based on the first filter
percent_src_ports = df_filtered['sport'].value_counts().divide(float(total_packets_filtered) / 100)
if debug: print("\nSource ports frequency")
if debug: print(percent_src_ports.head())
####
# Calculating the distribution of destination ports after the first filter
percent_dst_ports = df_filtered['dport'].value_counts().divide(float(total_packets_filtered) / 100)
if debug: print("\nDestination ports frequency")
if debug: print(percent_dst_ports.head())
#####
## WARNING packets are filtered here again#####
# Using the top 1 (source or destination) port to analyse a pattern of packets
if (len(percent_src_ports) > 0) and (len(percent_dst_ports) > 0):
if percent_src_ports.values[0] > percent_dst_ports.values[0]:
if debug: print('Using top source port: ', percent_src_ports.keys()[0])
df_pattern = df_filtered[df_filtered['sport'] == percent_src_ports.keys()[0]]
result["selected_port"] = "src_" + str(percent_src_ports.keys()[0])
else:
if debug: print('Using top dest port: ', percent_dst_ports.keys()[0])
df_pattern = df_filtered[df_filtered['dport'] == percent_dst_ports.keys()[0]]
result["selected_port"] = "dst_" + str(percent_dst_ports.keys()[0])
else:
if debug: print('no top source/dest port')
return None
if debug: print("\n####################\nPATTERN "+ "\n####################")
#####
# Calculating the total number of packets involved in the attack
pattern_packets = len(df_pattern)
result["pattern_packet_count"] = pattern_packets
#WARNING Can be wrong
result['raw_attack_size_megabytes'] = (df_pattern['raw_size'].sum() /1000000).item()
result["pattern_total_megabytes"] = (df_pattern[df_pattern['fragments'] == 0]['ip_length'].sum() / 1000000).item()
#####
# Calculating the percentage of the current pattern compared to the raw input file
representativeness = float(pattern_packets) * 100 / float(total_packets_filtered)
result["pattern_traffic_share"] = representativeness
attack_label = 'In %.2f' % representativeness + "\n " + attack_label
#####
# Checking the existence of HTTP data
http_data = df_pattern['http_data'].value_counts().divide(float(pattern_packets) / 100)
#####
# Checking the existence of TCP flags
percent_tcp_flags = df_pattern['tcp_flag'].value_counts().divide(float(pattern_packets) / 100)
#####
# Calculating the number of source IPs involved in the attack
ips_involved = df_pattern['ip_src'].unique()
attack_label = attack_label + "\n"+ str(len(ips_involved)) + " source IPs"
result["src_ips"] = ips_involved.tolist()
#####
# Calculating the number of source IPs involved in the attack
result["start_timestamp"] = df_pattern['timestamp'].min().item()
result["end_timestamp"] = df_pattern['timestamp'].max().item()
####
# Calculating the distribution of TTL variation (variation -> number of IPs)
ttl_variations = df_pattern.groupby(['ip_src'])['ip_ttl'].agg(np.ptp).value_counts().sort_index()
if debug: print('TTL variation : NR of source IPs')
if debug: print(ttl_variations)
#use to_json
result["ttl_variation"] = json.loads(ttl_variations.to_json())
####
# Calculating the distribution of IP fragments (fragmented -> percentage of packets)
percent_fragments = df_pattern['fragments'].value_counts().divide(float(pattern_packets) / 100)
####
# Calculating the distribution of source ports that remains
percent_src_ports = df_pattern['sport'].value_counts().divide(float(pattern_packets) / 100)
if debug: print("\nSource ports frequency")
if debug: print(percent_src_ports.head())
#use to_json()
result["src_ports"] = json.loads(percent_src_ports.to_json())
####
# Calculating the distribution of destination ports after the first filter
percent_dst_ports = df_pattern['dport'].value_counts().divide(float(pattern_packets) / 100)
if debug: print("\nDestination ports frequency")
if debug: print(percent_dst_ports.head())
#use to_json
result["dst_ports"] = json.loads(percent_dst_ports.to_json())
####
# There are 3 possibilities of attacks cases!
if (percent_src_ports.values[0] == 100):
if (len(percent_dst_ports) == 1):
# if debug: print("\nCASE 1: 1 source port to 1 destination port") if debug else next
attack_label = attack_label + "; using " + get_port_name(
percent_src_ports.keys()[0]) + "; to target " + get_port_name(
percent_dst_ports.keys()[0]) + "[" + '%.1f' % percent_dst_ports.values[0] + "%]"
else:
# if debug: print("\nCASE 2: 1 source port to a set of destination ports") if debug else next
if (percent_dst_ports.values[0] >= 50):
attack_label = attack_label + "; using " + get_port_name(
percent_src_ports.keys()[0]) + "; to target a set of (" + str(
len(percent_dst_ports)) + ") ports, such as " + get_port_name(
percent_dst_ports.keys()[0]) + "[" + '%.2f' % percent_dst_ports.values[
0] + "%]" + " and " + get_port_name(percent_dst_ports.keys()[1]) + "[" + '%.2f' % \
percent_dst_ports.values[
1] + "%]"
elif (percent_dst_ports.values[0] >= 33):
attack_label = attack_label + "; using " + get_port_name(
percent_src_ports.keys()[0]) + "; to target a set of (" + str(
len(percent_dst_ports)) + ") ports, such as " + get_port_name(
percent_dst_ports.keys()[0]) + "[" + '%.2f' % percent_dst_ports.values[
0] + "%]" + "; " + get_port_name(percent_dst_ports.keys()[1]) + "[" + '%.2f' % \
percent_dst_ports.values[
1] + "%], and " + get_port_name(
percent_dst_ports.keys()[2]) + "[" + '%.2f' % percent_dst_ports.values[2] + "%]"
else:
attack_label = attack_label + "; using " + get_port_name(
percent_src_ports.keys()[0]) + "; to target a set of (" + str(
len(percent_dst_ports)) + ") ports, such as " + get_port_name(
percent_dst_ports.keys()[0]) + "[" + '%.2f' % percent_dst_ports.values[
0] + "%]" + "; " + get_port_name(percent_dst_ports.keys()[1]) + "[" + '%.2f' % \
percent_dst_ports.values[
1] + "%], and " + get_port_name(
percent_dst_ports.keys()[2]) + "[" + '%.2f' % percent_dst_ports.values[2] + "%]"
else:
if (len(percent_src_ports) == 1):
# if debug: print("\nCASE 1: 1 source port to 1 destination port") if debug else next
attack_label = attack_label + "; using " + get_port_name(percent_src_ports.keys()[0]) + "[" + '%.1f' % \
percent_src_ports.values[
0] + "%]" + "; to target " + get_port_name(
percent_dst_ports.keys()[0]) + "[" + '%.1f' % percent_dst_ports.values[0] + "%]"
else:
# if debug: print("\nCASE 3: 1 source port to a set of destination ports") if debug else next
if (percent_src_ports.values[0] >= 50):
attack_label = attack_label + "; using a set of (" + str(
len(percent_src_ports)) + ") ports, such as " + get_port_name(
percent_src_ports.keys()[0]) + "[" + '%.2f' % percent_src_ports.values[
0] + "%] and " + get_port_name(percent_src_ports.keys()[1]) + "[" + '%.2f' % \
percent_src_ports.values[
1] + "%]" + "; to target " + get_port_name(
percent_dst_ports.keys()[0]) + "[" + '%.1f' % percent_dst_ports.values[0] + "%]"
elif (percent_src_ports.values[0] >= 33):
attack_label = attack_label + "; using a set of (" + str(
len(percent_src_ports)) + ") ports, such as " + get_port_name(
percent_src_ports.keys()[0]) + "[" + '%.2f' % percent_src_ports.values[
0] + "%], " + get_port_name(percent_src_ports.keys()[1]) + "[" + '%.2f' % \
percent_src_ports.values[
1] + "%], and " + get_port_name(
percent_src_ports.keys()[2]) + "[" + '%.2f' % percent_src_ports.values[
2] + "%]" + "; to target " + get_port_name(percent_dst_ports.keys()[0]) + "[" + '%.1f' % \
percent_dst_ports.values[
0] + "%]"
else:
attack_label = attack_label + "; using a set of (" + str(
len(percent_src_ports)) + ") ports, such as " + get_port_name(
percent_src_ports.keys()[0]) + "[" + '%.2f' % percent_src_ports.values[
0] + "%], " + get_port_name(percent_src_ports.keys()[1]) + "[" + '%.2f' % \
percent_src_ports.values[
1] + "%], " + get_port_name(
percent_src_ports.keys()[2]) + "[" + '%.2f' % percent_src_ports.values[
2] + "%]" + "; and " + get_port_name(percent_src_ports.keys()[3]) + "[" + '%.2f' % \
percent_src_ports.values[
3] + "%]" + "; to target " + get_port_name(
percent_dst_ports.keys()[0]) + "[" + '%.1f' % percent_dst_ports.values[0] + "%]"
####
# Testing HTTP request
if len(http_data) > 0 and ((percent_dst_ports.index[0] == 80) or (percent_dst_ports.index[0] == 443)):
attack_label = attack_label + "; " + http_data.index[0]
####
# Testing TCP flags
if (len(percent_tcp_flags) > 0) and (percent_tcp_flags.values[0] > 50):
attack_label = attack_label + "; TCP flags: " + get_tcp_flag_name(
percent_tcp_flags.index[0]) + "[" + '%.1f' % percent_tcp_flags.values[0] + "%]"
####
# IP fragmentation
if (percent_fragments.values[0] > 0) and (percent_fragments.index[0] == 1):
attack_label = attack_label + "; involving IP fragmentation"
result["fragmented"] = True
####
# IP spoofing (if (more than 0) src IPs had the variation of the ttl higher than a treshold)
if (ttl_variations[::-1].values[0] > 0) and (ttl_variations[::-1].index[0] >= ttl_variation_threshold):
result["spoofed"]=True
attack_label = attack_label + "; (likely involving) spoofed IPs"
else:
####
# Reflection and Amplification
if percent_src_ports.values[0] >= 1:
result["reflected"]=True
attack_label = attack_label + "; Reflection & Amplification"
if debug: print("\n####################\nATTACK VECTOR LABEL:"+ "\n####################")
if debug: print(attack_label)
result["label"] = attack_label
print(result)
return result
if __name__ == "__main__":
cli.add_command(receive)
cli()
| jdcc2/ddoshackathon | packet_patterns.py | packet_patterns.py | py | 17,497 | python | en | code | 0 | github-code | 36 |
18735221514 | import scrapy
from module.items import HotlineItem
class HotlineSpider(scrapy.Spider):
name = "hotline"
allowed_domains = ["hotline.ua"]
start_urls = [f"https://hotline.ua/ua/bt/holodilniki/?p={page}" for page in range(1, 4)]
def parse(self, response):
catalog = response.xpath('//div[contains(@class, "list-body__content")]').xpath('//div[contains(@class, "list-item ")]')
for item in catalog:
url = item.xpath('.//a[contains(@class, "list-item__title")]/@href').get()
yield scrapy.Request(
url=f"https://hotline.ua" + url,
callback=self.parse_hotline
)
def parse_hotline(self, response):
product_name = response.xpath('.//h1[contains(@class, "title__main")]/text()').get()
store_name = response.xpath('.//div[1][@class="list__item row flex"]//a[@data-eventcategory="Pages Product Prices" and @class="shop__title"]/text()').get()
price = response.xpath('.//div[1][@class="list__item row flex"]//span[@data-eventcategory="Pages Product Prices"]/span[@class="price__value"]/text()').get()
yield HotlineItem(
store_name=store_name,
product_name=product_name,
price=price
)
| Ivan7281/Lab-Data-Scraping | Lab7/module/spiders/hotline.py | hotline.py | py | 1,258 | python | en | code | 0 | github-code | 36 |
70307229865 | import os
import requests
import json
from requests_oauthlib import OAuth1
from dotenv import load_dotenv
load_dotenv()
CONSUMER_KEY = os.getenv("TWITTER_API_KEY")
CONSUMER_SECRET = os.getenv("TWITTER_API_SECRET")
ACCESS_TOKEN = os.getenv("TWITTER_ACCESS_TOKEN")
ACCESS_TOKEN_SECRET = os.getenv("TWITTER_ACCESS_TOKEN_SECRET")
API_KEY = os.getenv("WAKATIME_API_KEY")
auth = OAuth1(CONSUMER_KEY, CONSUMER_SECRET, ACCESS_TOKEN, ACCESS_TOKEN_SECRET)
def get_wakatime_stats():
waka_url = (
f"https://wakatime.com/api/v1/users/current/status_bar/today?api_key={API_KEY}"
)
response = requests.get(waka_url)
if response.status_code != 200:
raise Exception(
f"Request failed with error {response.status_code}, {response.text}"
)
stats = {}
top_3_languages = {}
stats["minutes_coded_today"] = response.json()["data"]["grand_total"]["text"]
for language in response.json()["data"]["languages"][0:3]:
top_3_languages[language["name"]] = language["text"]
return stats, top_3_languages
def update_coding_streak():
with open("coding_streak.txt", "r") as f:
coding_streak = int(f.read().strip())
stats, top_3_languages = get_wakatime_stats()
if stats["minutes_coded_today"]:
coding_streak += 1
else:
coding_streak = 0
with open("coding_streak.txt", "w") as f:
f.write(str(coding_streak))
# If the coding streak is broken, do not tweet and end the program. The streak file will be updated to 0.
if coding_streak == 0:
print("Coding streak broken, not tweeting")
exit()
return coding_streak
def format_tweet(coding_streak, minutes_coded_today, languages):
day_of_streak = coding_streak
tweet_text = f"Day {day_of_streak} of my coding streak: I coded {minutes_coded_today} today!\n\n#100DaysOfCode "
# make the hashtags each language
for language in languages.keys():
tweet_text += f"#{language} "
return tweet_text
def post_tweet(tweet_text):
url = "https://api.twitter.com/2/tweets"
headers = {"Content-Type": "application/json"}
data = {"text": tweet_text}
response = requests.post(url, auth=auth, data=json.dumps(data), headers=headers)
if response.status_code != 201:
raise Exception(
f"Request failed with error {response.status_code}, {response.text}"
)
print("Tweet posted successfully!", response.json())
if __name__ == "__main__":
coding_streak = update_coding_streak()
stats, languages = get_wakatime_stats()
tweet_text = format_tweet(coding_streak, stats["minutes_coded_today"], languages)
post_tweet(tweet_text)
| homeGrownCheese/tweet_waka_daily | tweet_stats.py | tweet_stats.py | py | 2,688 | python | en | code | 1 | github-code | 36 |
5102702223 | """fask_dj URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/1.11/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.conf.urls import url, include
2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls'))
"""
from django.conf.urls import url
from . import views
urlpatterns = [
url(r'^tasks', views.tasks, name = 'tasks'),
url(r'^task/(?P<task_id>[0-9]+)/$', views.task, name = 'task'),
url(r'^task_delete/(?P<task_id>[0-9]+)/$', views.task_delete, name = 'task_delete'),
url(r'^task_project/(?P<task_id>[0-9]+)/(?P<project_id>[0-9]+)/(?P<redirect_name>[a-z]+)$', views.task_project, name = 'task_project'),
]
| ZompaSenior/fask | fask/src/fask_dj/task/urls.py | urls.py | py | 1,085 | python | en | code | 0 | github-code | 36 |
6377162291 | from django.db import models
import uuid
class apiKeys(models.Model):
id = models.CharField(max_length=200, null=False, blank=False)
key = models.TextField(primary_key=True, default=uuid.uuid4().hex)
def __unicode__(self):
return self.id
class ButtonTable(models.Model):
SKRANKE = 0
TELEFON = 1
RANDOM = 2
BUTTON_CHOICES= (
(SKRANKE, 'Skranke'),
(TELEFON, 'Telefon'),
(RANDOM, 'Random')
)
sender = models.ForeignKey(apiKeys, editable=False, null=False)
button = models.IntegerField(choices=BUTTON_CHOICES, default=0)
date_registered = models.DateTimeField(auto_now_add=True, auto_now=False)
def __unicode__(self):
return str(self.button)
class Meta:
verbose_name_plural = 'Case registers'
verbose_name = 'Registered case'
| OrakeltjenestenDragvoll/nix | apps/bujumbura/models.py | models.py | py | 837 | python | en | code | 0 | github-code | 36 |
20869182211 | # coding: utf-8
"""
Django settings for testproject project.
For more information on this file, see
https://docs.djangoproject.com/en/1.7/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.7/ref/settings/
"""
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
import os
import sys
BASE_DIR = os.path.dirname(os.path.dirname(__file__))
sys.path.insert(0, os.path.dirname(BASE_DIR))
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'b2k427m)td!v8h-0@=qd-9pvvu@gd_zl-0^i@6j589uhp=egsx'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
TEMPLATE_DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = (
'modeltranslation',
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'testproject',
'haystack',
'parler',
)
MIDDLEWARE_CLASSES = (
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.middleware.locale.LocaleMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.auth.middleware.SessionAuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
)
ROOT_URLCONF = 'testproject.urls'
WSGI_APPLICATION = 'testproject.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.7/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': 'myapp.sqlite',
}
}
# Internationalization
# https://docs.djangoproject.com/en/1.7/topics/i18n/
LANGUAGE_CODE = 'en'
LANGUAGES = (('en', 'English'),
('de', 'Deutsch'),
('es', 'Spanisch'),
('fr', 'Französisch'),
('cs', 'Tschechisch'),
('ru', 'Russisch'),
)
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.7/howto/static-files/
STATIC_URL = '/static/'
HAYSTACK_CONNECTIONS = {
'default': {
'ENGINE': 'multilingual.elasticsearch_backend.ElasticsearchMultilingualSearchEngine',
'URL': 'http://127.0.0.1:9200/',
'INDEX_NAME': 'testproject',
'SILENTLY_FAIL': False,
'TIMEOUT': 30,
},
}
HAYSTACK_LOGGING = True
LOGGING = {
'version': 1,
'disable_existing_loggers': False,
'handlers': {
'console': {
'class': 'logging.StreamHandler',
},
},
'loggers': {
'django': {
'handlers': ['console'],
'level': os.getenv('DJANGO_LOG_LEVEL', 'INFO'),
},
'haystack': {
'handlers': ['console'],
'level': 'DEBUG'
}
},
}
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'APP_DIRS': True,
},
]
| sbaechler/django-multilingual-search | tests/testproject/settings.py | settings.py | py | 3,166 | python | en | code | 21 | github-code | 36 |
7551769686 | from web3 import Web3, EthereumTesterProvider
from etherscan import Etherscan
import json
class Node:
def __init__(self, name, value, address, children=[]):
self.name = name
self.value = value
self.children = children
self.searched = False
self.address = Web3.toChecksumAddress(address)
class NodeOperations:
def __init__(self, web3, etherscan):
self.web3 = web3
self.etherscan = etherscan
def print_tree(self, node, level=0):
print(' ' * level + node.name + ": \t" + node.address)
for child in node.children:
self.print_tree(child, level+1)
def depth_first_search(self, node, depth, current_depth=0, nodeIterator=0):
if current_depth >= depth: #Escape after depth reached or exceeded
return
if node.searched == True:
return
availibleABI = True
#Handler for non verified smart contracts on etherscan
try:
contractABI = self.etherscan.get_contract_abi(node.address) #Use Etherscan API to get the contracts ABI
except:
print('Problem with the ABI')
availibleABI = False #unavailible ABI (contract code not verified)
if availibleABI: #If contract's ABI is verified
contractInstance = self.web3.eth.contract(address=node.address, abi=contractABI) #Use web3 Library to create an instantiation of the contract
contractABI = json.loads(contractABI) #convert ABI to json format
for i in range(len(contractABI)): #Examine all functions/methods/variables in the ABI
try:
if contractABI[i]['outputs'][0]['type'] == 'address': #Searching exclusively for addresses on the contract
if len(contractABI[i]['inputs']) == 0: #Check function call does not require input
childAddress = eval("contractInstance."+"functions."+contractABI[i]['name']+"()"+".call()") #RPC call to the contract, return the 20byte address
child = Node(contractABI[i]['name'], nodeIterator, childAddress, []) #create node
node.children.append(child) #Append child node
#nodeIterator += 1
#print(f'Searching node...')
elif len(contractABI[i]['inputs']) == 1 and contractABI[i]['inputs'][0]['type'] == 'uint256': #This is an array of addresses:
print('Searching Array Node...')
try:
for j in range(0,10):
#print(j)
childAddress = eval("contractInstance."+"functions."+contractABI[i]['name']+"("+str(j)+ ")"+".call()") #RPC call to the contract, return the 20byte address
child = Node(contractABI[i]['name'], nodeIterator, childAddress, []) #create node
node.children.append(child) #Append child node
nodeIterator += 1
#print(f'Searching node...') #NOTE: Might need to put a check in for 0x0000... etc address.
except:
break
else:
pass
except:
pass
for child in node.children:
child.name
self.depth_first_search(child, depth, current_depth+1, nodeIterator)
node.searched = True
else:
print(node.address)
node.name = 'NO ABI AVAILIBLE'
node.searched = True
pass | DoominEth/Web3DataSandbox | ContractCompossitionNode.py | ContractCompossitionNode.py | py | 3,793 | python | en | code | 0 | github-code | 36 |
7805399024 | from Epulet import Epulet
epuletek = []
def beolvas(fajlnev):
fajl = open(fajlnev, "r", encoding="utf-8")
fajl.readline()
sorok = fajl.readlines()
fajl.close()
i = 0
while i < len(sorok):
sor = sorok[i].strip().split("$")
epulet = Epulet(sor)
epuletek.append(epulet)
i += 1
def epuletek_szama():
return len(epuletek)
def magasabbmint():
magasabb = 0
i = 0
while i < len(epuletek):
if epuletek[i].magassag * 3.280839895 > 555:
magasabb += 1
i += 1
return magasabb
def legoregebb_orszag():
legoregebb = 99999
oregorszag = "hiba"
i = 0
while i < len(epuletek):
if epuletek[i].ev < legoregebb:
legoregebb = epuletek[i].ev
oregorszag = epuletek[i].orszag
i += 1
return oregorszag
| szludora/Szlucska_202302_epuletek | epuletek.py | epuletek.py | py | 854 | python | hu | code | 0 | github-code | 36 |
74540930982 | # -*- coding: utf-8 -*-
from enum import Enum
class SolarTerms(Enum):
the_beginning_of_spring = "the Beginning of Spring", "立春"
rain_water = "Rain Water", "雨水"
the_waking_of_insects = "the Waking of Insects", "惊蛰"
the_spring_equinox = "the Spring Equinox", "春分"
pure_brightness = "Pure Brightness", "清明"
grain_rain = "Grain Rain", "谷雨"
the_beginning_of_summer = "the Beginning of Summer", "立夏"
lesser_fullness_of_grain = "Lesser Fullness of Grain", "小满"
grain_in_beard = "Grain in Beard", "芒种"
the_summer_solstice = "the Summer Solstice", "夏至"
lesser_heat = "Lesser Heat", "小暑"
greater_heat = "Greater Heat", "大暑"
the_beginning_of_autumn = "the Beginning of Autumn", "立秋"
the_end_of_heat = "the End of Heat", "处暑"
white_dew = "White Dew", "白露"
the_autumn_equinox = "the Autumn Equinox", "秋分"
code_dew = "Cold Dew", "寒露"
frost_descent = "Frost's Descent", "霜降"
the_beginning_of_winter = "the Beginning of Winter", "立冬"
lesser_snow = "Lesser Snow", "小雪"
greater_snow = "Greater Snow", "大雪"
the_winter_solstice = "the Winter Solstice", "冬至"
lesser_cold = "Lesser Cold", "小寒"
greater_cold = "Greater Cold", "大寒"
# 计算节气用的 C 值
# 2000年的小寒、大寒、立春、雨水按照20世纪的C值来算
SOLAR_TERMS_C_NUMS = {
# 节气: [20世纪值， 21世纪值]
SolarTerms.the_beginning_of_spring: [4.6295, 3.87],
SolarTerms.rain_water: [19.4599, 18.73],
SolarTerms.the_waking_of_insects: [6.3926, 5.63],
SolarTerms.the_spring_equinox: [21.4155, 20.646],
SolarTerms.pure_brightness: [5.59, 4.81],
SolarTerms.grain_rain: [20.888, 20.1],
SolarTerms.the_beginning_of_summer: [6.318, 5.52],
SolarTerms.lesser_fullness_of_grain: [21.86, 21.04],
SolarTerms.grain_in_beard: [6.5, 5.678],
SolarTerms.the_summer_solstice: [22.2, 21.37],
SolarTerms.lesser_heat: [7.928, 7.108],
SolarTerms.greater_heat: [23.65, 22.83],
SolarTerms.the_beginning_of_autumn: [28.35, 7.5],
SolarTerms.the_end_of_heat: [23.95, 23.13],
SolarTerms.white_dew: [8.44, 7.646],
SolarTerms.the_autumn_equinox: [23.822, 23.042],
SolarTerms.code_dew: [9.098, 8.318],
SolarTerms.frost_descent: [24.218, 23.438],
SolarTerms.the_beginning_of_winter: [8.218, 7.438],
SolarTerms.lesser_snow: [23.08, 22.36],
SolarTerms.greater_snow: [7.9, 7.18],
SolarTerms.the_winter_solstice: [22.6, 21.94],
SolarTerms.lesser_cold: [6.11, 5.4055],
SolarTerms.greater_cold: [20.84, 20.12],
}
# 月份和节气对应关系
SOLAR_TERMS_MONTH = {
1: [SolarTerms.lesser_cold, SolarTerms.greater_cold],
2: [SolarTerms.the_beginning_of_spring, SolarTerms.rain_water],
3: [SolarTerms.the_waking_of_insects, SolarTerms.the_spring_equinox],
4: [SolarTerms.pure_brightness, SolarTerms.grain_rain],
5: [SolarTerms.the_beginning_of_summer, SolarTerms.lesser_fullness_of_grain],
6: [SolarTerms.grain_in_beard, SolarTerms.the_summer_solstice],
7: [SolarTerms.lesser_heat, SolarTerms.greater_heat],
8: [SolarTerms.the_beginning_of_autumn, SolarTerms.the_end_of_heat],
9: [SolarTerms.white_dew, SolarTerms.the_autumn_equinox],
10: [SolarTerms.code_dew, SolarTerms.frost_descent],
11: [SolarTerms.the_beginning_of_winter, SolarTerms.lesser_snow],
12: [SolarTerms.greater_snow, SolarTerms.the_winter_solstice],
}
# 有些节气使用公式计算计算的不够准确，需要进行偏移
SOLAR_TERMS_DELTA = {
(2026, SolarTerms.rain_water): -1,
(2084, SolarTerms.the_spring_equinox): 1,
(1911, SolarTerms.the_beginning_of_summer): 1,
(2008, SolarTerms.lesser_fullness_of_grain): 1,
(1902, SolarTerms.grain_in_beard): 1,
(1928, SolarTerms.the_summer_solstice): 1,
(1925, SolarTerms.lesser_heat): 1,
(2016, SolarTerms.lesser_heat): 1,
(1922, SolarTerms.greater_heat): 1,
(2002, SolarTerms.the_beginning_of_autumn): 1,
(1927, SolarTerms.white_dew): 1,
(1942, SolarTerms.the_autumn_equinox): 1,
(2089, SolarTerms.frost_descent): 1,
(2089, SolarTerms.the_beginning_of_winter): 1,
(1978, SolarTerms.lesser_snow): 1,
(1954, SolarTerms.greater_snow): 1,
(1918, SolarTerms.the_winter_solstice): -1,
(2021, SolarTerms.the_winter_solstice): -1,
(1982, SolarTerms.lesser_cold): 1,
(2019, SolarTerms.lesser_cold): -1,
(2000, SolarTerms.greater_cold): 1,
(2082, SolarTerms.greater_cold): 1,
}
| LKI/chinese-calendar | chinese_calendar/solar_terms.py | solar_terms.py | py | 4,541 | python | en | code | 866 | github-code | 36 |
17299275140 | from django.shortcuts import render, get_object_or_404
from .models import Post, Comment
from django.core.paginator import Paginator, EmptyPage, PageNotAnInteger
from .forms import CommentForm
from django.views.decorators.http import require_POST
from taggit.models import Tag
"""
This is the Count aggregation function of the Django ORM. This function will
allow you to perform aggregated counts of tags. django.db.models includes the
following aggregation functions:
• Avg: The mean value
• Max: The maximum value
• Min: The minimum value
• Count: The total number of objects
"""
from django.db.models import Count
from itertools import chain
# Define the number of elements in one page
page_elements_count = 6
# Define number of similar posts
similar_posts_count = 3
# Create your views here.
def blog_list(request, tag_slug=None):
post_list = Post.published.all()
tag = None
if tag_slug:
tag = get_object_or_404(Tag, slug=tag_slug)
post_list = post_list.filter(tags__in=[tag])
posts_count = post_list.count()
# Pagination with page_elements_count per page
paginator = Paginator(post_list, page_elements_count)
# f the page parameter is not in the GET parameters of the request, we use
# the default value 1 to load the first page of results.
page_number = request.GET.get('page', 1)
# Try get the requested page
try:
posts = paginator.page(page_number)
# If the requests page is out of range, retrun the last page
except EmptyPage:
# If page_number is out of range deliver last page of results
posts = paginator.page(paginator.num_pages)
# If the requests page is not an integer, return the first page
except PageNotAnInteger:
posts = paginator.page(1)
return render(
request,
'blog/blog_home.html',
{
'posts': posts,
'posts_count': posts_count,
'tag': tag,
}
)
def blog_post(request, post_slug):
post = get_object_or_404(
Post,
slug=post_slug,
status=Post.Status.PUBLISHED
)
# List of active comments for this post
comments = post.comments.filter(active=True)
if request.method == 'GET':
# Form for users to comment
form = CommentForm()
else:
# Define a comment variable with the initial value None. This variable will
# be used to store the comment object when it gets created.
comment = None
form = CommentForm(data=request.POST)
if form.is_valid():
comment = form.save(commit=False)
# Assign the post attribute of the comment to the current post
comment.post = post
# Save the comment to the database
comment.save()
# List of similar posts
# retrieve a Python list of IDs for the tags of the current post. The
# values_list() QuerySet returns tuples with the values for the given
# fields. We pass flat=True to it to get single values such as
# [1, 2, 3, ...] instead of one-tuples such as [(1,), (2,), (3,) ...]
post_tags_ids = post.tags.values_list('id', flat=True)
# We get all posts that contain any of these tags, excluding the current
# post itself.
similar_posts = Post.published.filter(tags__in=post_tags_ids).exclude(id=post.id)
# use the Count aggregation function to generate a calculated
# field (same_tags) that contains the number of tags shared with all the
# tags queried.
# We order the result by the number of shared tags (descending order) and
# by publish to display recent posts first for the posts with the same
# number of shared tags. We slice the result to retrieve only the first
# three posts.
similar_posts = similar_posts.annotate(same_tags=Count('tags'))\
.order_by('-same_tags', '-created')[:similar_posts_count]
# Fill similar posts with normal posts; if the similar posts are less than
# the required similar_posts_count
if len(similar_posts) < similar_posts_count:
extra_posts_count = similar_posts_count - len(similar_posts)
extra_posts = Post.published.order_by('-created').exclude(id=post.id)\
.exclude(id__in=similar_posts)[:extra_posts_count]
similar_posts = list(chain(similar_posts, extra_posts))
return render(
request,
'blog/blog_post.html',
{
'post': post,
'form': form,
'comments': comments,
'similar_posts': similar_posts,
}
)
| m-abdelgawad/automagic-developer-django-postgres-docker-compose-stack | automagic-website/blog/views.py | views.py | py | 4,620 | python | en | code | 0 | github-code | 36 |
12185429190 | # Creating a regression line - aka line of best fit
# Y = mx + b
from statistics import mean
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
style.use('fivethirtyeight')
# defined as numpy arrays
xs = np.array([1,2,3,4,5,6], dtype=np.float64)
ys = np.array([5,4,6,5,6,7], dtype=np.float64)
def best_fit_slope_and_intercept(xs,ys):
m = (((mean(xs) * mean(ys)) - mean(xs*ys)) / ( (mean(xs) * mean(xs)) - mean(xs**2) ) )
b = mean(ys) - m*mean(xs)
return m,b;
m,b = best_fit_slope_and_intercept(xs,ys)
#Creating line via for loop
regression_line = [(m*x)+b for x in xs]
#print(m,b)
predict_x = 8
predict_y = (m*predict_x + b)
#Create plots
plt.scatter(xs,ys)
plt.scatter(predict_x,predict_y)
plt.plot(xs, regression_line)
plt.show()
| Wcdunn3/pythonProjects | MachineLearning/MlLesson9LineFit.py | MlLesson9LineFit.py | py | 790 | python | en | code | 0 | github-code | 36 |
15836281042 | with open("day3/input.txt") as f:
s = 0
for l in f:
comp1, comp2 = l[:int(len(l)/2)], l[int(len(l)/2):]
common = list(set(comp1).intersection(set(comp2)))
val = ord(common[0]) - 38 if common[0].isupper() else ord(common[0]) - 96
s += val
print(s)
with open("day3/input.txt") as f:
s = 0
group = []
for l in f:
l = l.replace("\n", "")
group.append(l)
if len(group) == 3:
common = list(set.intersection(set(group[0]), set(group[1]), set(group[2])))
val = ord(common[0]) - 38 if common[0].isupper() else ord(common[0]) - 96
s += val
group = []
print(s)
| jaroddurkin/adventofcode2022 | day3/main.py | main.py | py | 684 | python | en | code | 0 | github-code | 36 |
19866269667 | import numpy as np
#=========================#
# refine the distribution #
#=========================#
def refine_distribution(old_mugrid, old_mumid, old_dist, target_resolution):
# store moments for comparison
old_nmu = len(old_mumid)
old_edens = np.sum(old_dist , axis=(1,2,3))
old_flux = np.sum(old_dist * old_mumid , axis=(1,2,3))
old_press = np.sum(old_dist * old_mumid**2, axis=(1,2,3))
# initially set to old values in case not refining
new_mugrid = old_mugrid
new_mumid = old_mumid
new_dist = old_dist
new_nmu = old_nmu
nref = int(np.log2(target_resolution / old_nmu))
for iref in range(nref):
if(iref>0):
old_dist = new_dist
old_mugrid = new_mugrid
# get the new mugrid
old_nmu = len(old_mugrid)-1
old_dmu = np.array([old_mugrid[i+1]-old_mugrid[i] for i in range(old_nmu)])
new_mugrid = []
for i in range(len(old_mugrid)-1):
new_mugrid.append(old_mugrid[i])
new_mugrid.append(0.5*(old_mugrid[i]+old_mugrid[i+1]))
new_mugrid.append(old_mugrid[-1])
new_nmu = len(new_mugrid)-1
new_dmu = np.array([new_mugrid[i+1]-new_mugrid[i] for i in range(new_nmu)]) # dist between cell faces
print("\tIncreasing from nmu=",old_nmu,"to nmu=",new_nmu)
# get properties & derivatives of the old distribution function
nr = old_dist.shape[0]
ns = old_dist.shape[1]
ne = old_dist.shape[2]
new_dist = np.zeros((nr,ns,ne,new_nmu))
for i in range(old_nmu):
new_dist[:,:,:,2*i+0] = old_dist[:,:,:,i]/2.
new_dist[:,:,:,2*i+1] = old_dist[:,:,:,i]/2.
# new grid structure #
if nref > 0:
new_mumid = np.array([0.5*(new_mugrid[i]+new_mugrid[i+1]) for i in range(new_nmu)])
# calculate error in moments #
new_edens = np.sum(new_dist , axis=(1,2,3))
new_flux = np.sum(new_dist * new_mumid , axis=(1,2,3))
new_press = np.sum(new_dist * new_mumid**2, axis=(1,2,3))
print(" DO Max relative error in net energy density:", np.max(np.abs((new_edens-old_edens)/old_edens)))
print(" DO Max relative error in net flux:", np.max(np.abs((new_flux-old_flux)/old_edens)))
print(" DO Max relative error in net pressure:", np.max(np.abs((new_press-old_press)/old_edens)))
return new_mugrid, new_mumid, new_dist
| srichers/neutrino_linear_stability | discrete_ordinates.py | discrete_ordinates.py | py | 2,433 | python | en | code | 3 | github-code | 36 |
25300892806 | import colorsys
import struct
import math
from pyatem.hexdump import hexdump
class FieldBase:
def _get_string(self, raw):
return raw.split(b'\x00')[0].decode()
def make_packet(self):
header = struct.pack('!H2x 4s', len(self.raw) + 8, self.__class__.CODE.encode())
return header + self.raw
class FirmwareVersionField(FieldBase):
"""
Data from the `_ver` field. This stores the major/minor firmware version numbers
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 2 u16 Major version
2 2 u16 Minor version
====== ==== ====== ===========
After parsing:
:ivar major: Major firmware version
:ivar minor: Minor firmware version
"""
CODE = "_ver"
def __init__(self, raw):
"""
:param raw:
"""
self.raw = raw
self.major, self.minor = struct.unpack('>HH', raw)
self.version = "{}.{}".format(self.major, self.minor)
def __repr__(self):
return '<firmware-version {}>'.format(self.version)
class TimeField(FieldBase):
"""
Data from the `Time` field. This contains the value of the internal clock of the hardware.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 Hours
1 1 u8 Minutes
2 1 u8 Seconds
3 1 u8 Frames
4 1 u8 Is dropframe
5 3 ? unknown
====== ==== ====== ===========
After parsing:
:ivar hours: Timecode hour field
:ivar minutes: Timecode minute field
:ivar seconds: Timecode seconds field
:ivar frames: Timecode frames field
:ivar dropframe: Is dropframe
"""
CODE = "Time"
def __init__(self, raw):
self.raw = raw
self.hours, self.minutes, self.seconds, self.frames, self.dropframe = struct.unpack('>BBBB?3x', raw)
def total_seconds(self):
return self.seconds + (60 * self.minutes) + (60 * 60 * self.hours)
def __repr__(self):
return '<time {}>'.format(f'{self.hours}:{self.minutes}:{self.seconds}:{self.frames}')
class TimeConfigField(FieldBase):
"""
Data from the `TCCc` field. This contains the freerun/time of day setting for the timecode mode.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 Mode [0=freerun, 1=time-of-day]
1 3 ? unknown
====== ==== ====== ===========
After parsing:
:ivar mode: Timecode mode
"""
CODE = "TCCc"
def __init__(self, raw):
self.raw = raw
self.mode = struct.unpack('>Bxxx', raw)
def __repr__(self):
return '<time-config mode={}>'.format(self.mode)
class ProductNameField(FieldBase):
"""
Data from the `_pin` field. This stores the product name of the mixer
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 44 char[] Product name
====== ==== ====== ===========
After parsing:
:ivar name: User friendly product name
"""
CODE = "_pin"
def __init__(self, raw):
self.raw = raw
self.name = self._get_string(raw)
def __repr__(self):
return '<product-name {}>'.format(self.name)
class MixerEffectConfigField(FieldBase):
"""
Data from the `_MeC` field. This stores basic info about the M/E units.
The mixer will send multiple fields, one for each M/E unit.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 M/E index
1 1 u8 Number of keyers on this M/E
2 2 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: 0-based M/E index
:ivar keyers: Number of upstream keyers on this M/E
"""
CODE = "_MeC"
def __init__(self, raw):
self.raw = raw
self.index, self.keyers = struct.unpack('>2B2x', raw)
def __repr__(self):
return '<mixer-effect-config m/e {}: keyers={}>'.format(self.index, self.keyers)
class MediaplayerSlotsField(FieldBase):
"""
Data from the `_mpl` field. This stores basic info about the mediaplayer slots.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 Number of still slots
1 1 u8 Number of clip slots
2 2 ? unknown
====== ==== ====== ===========
After parsing:
:ivar stills: Number of still slots
:ivar clips: Number of clip slots
"""
CODE = "_mpl"
def __init__(self, raw):
self.raw = raw
self.stills, self.clips = struct.unpack('>2B2x', raw)
def __repr__(self):
return '<mediaplayer-slots: stills={} clips={}>'.format(self.stills, self.clips)
class MediaplayerSelectedField(FieldBase):
"""
Data from the `MPCE` field. This defines what media from the media pool is loaded in a specific media player.
There is one MPCE field per mediaplayer in the hardware.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 Mediaplayer index, 0-indexed
1 1 u8 Source type, 1=still, 2=clip
2 1 u8 Source index, 0-indexed
3 1 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: Mediaplayer index
:ivar source_type: 1 for still, 2 for clip
:ivar slot: Source index
"""
CODE = "MPCE"
def __init__(self, raw):
self.raw = raw
self.index, self.source_type, self.slot = struct.unpack('>BBBx', raw)
def __repr__(self):
return '<mediaplayer-selected: index={} type={} slot={}>'.format(self.index, self.source_type, self.slot)
class VideoModeField(FieldBase):
"""
Data from the `VidM` field. This sets the video standard the mixer operates on internally.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 Video mode
1 3 ? unknown
====== ==== ====== ===========
The `Video mode` is an enum of these values:
=== ==========
Key Video mode
=== ==========
0 NTSC (525i59.94)
1 PAL (625i50)
2 NTSC widescreen (525i59.94)
3 PAL widescreen (625i50)
4 720p50
5 720p59.94
6 1080i50
7 1080i59.94
8 1080p23.98
9 1080p24
10 1080p25
11 1080p29.97
12 1080p50
13 1080p59.94
14 4k23.98
15 4k24
16 4k25
17 4k29.97
18 4k50
19 4k59.94
20 8k23.98
21 8k24
22 8k25
23 8k29.97
24 8k50
25 8k59.94
26 1080p30
27 1080p60
=== ==========
After parsing:
:ivar mode: mode number
:ivar resolution: vertical resolution of the mode
:ivar interlaced: the current mode is interlaced
:ivar rate: refresh rate of the mode
"""
CODE = "VidM"
def __init__(self, raw):
self.raw = raw
self.mode, = struct.unpack('>1B3x', raw)
# Resolution, Interlaced, Rate, Widescreen
modes = {
0: (525, True, 59.94, False),
1: (625, True, 50, False),
2: (525, True, 59.94, True),
3: (625, True, 50, True),
4: (720, False, 50, True),
5: (720, False, 59.94, True),
6: (1080, True, 50, True),
7: (1080, True, 59.94, True),
8: (1080, False, 23.98, True),
9: (1080, False, 24, True),
10: (1080, False, 25, True),
11: (1080, False, 29.97, True),
12: (1080, False, 50, True),
13: (1080, False, 59.94, True),
14: (2160, False, 23.98, True),
15: (2160, False, 24, True),
16: (2160, False, 25, True),
17: (2160, False, 29.97, True),
18: (2160, False, 50, True),
19: (2160, False, 59.94, True),
20: (4320, False, 23.98, True),
21: (4320, False, 24, True),
22: (4320, False, 25, True),
23: (4320, False, 29.97, True),
24: (4320, False, 50, True),
25: (4320, False, 59.94, True),
26: (1080, False, 30, True),
27: (1080, False, 60, True),
}
if self.mode in modes:
self.resolution = modes[self.mode][0]
self.interlaced = modes[self.mode][1]
self.rate = modes[self.mode][2]
self.widescreen = modes[self.mode][3]
def get_label(self):
if self.resolution is None:
return 'unknown [{}]'.format(self.mode)
pi = 'p'
if self.interlaced:
pi = 'i'
aspect = ''
if self.resolution < 720:
if self.widescreen:
aspect = ' 16:9'
else:
aspect = ' 4:3'
return '{}{}{}{}'.format(self.resolution, pi, self.rate, aspect)
def get_pixels(self):
w, h = self.get_resolution()
return w * h
def get_resolution(self):
lut = {
525: (720, 480),
625: (720, 576),
720: (1280, 720),
1080: (1920, 1080),
2160: (3840, 2160),
4320: (7680, 4320),
}
return lut[self.resolution]
def __repr__(self):
return '<video-mode: mode={}: {}>'.format(self.mode, self.get_label())
class VideoModeCapabilityField(FieldBase):
"""
Data from the `_VMC` field. This describes all the video modes supported by the hardware and
the associated multiview and downconvert modes.
The first 2 bytes is the number of modes supported, then there's a 13 byte block that's repeated for every
mode that has the mode number, the possible multiview modes in this mode and the possible downconvert modes.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 2 u16 Number of video modes
2 2 ? padding
4 1 u8 Video mode N
5 3 ? padding
8 4 u32 Multiview modes bitfield
12 4 u32 Downconvert modes bitfield
13 1 bool Requires reconfiguration
====== ==== ====== ===========
The `Video mode` is an enum of these values:
=== ==========
Key Video mode
=== ==========
0 NTSC (525i59.94)
1 PAL (625i50)
2 NTSC widescreen (525i59.94)
3 PAL widescreen (625i50)
4 720p50
5 720p59.94
6 1080i50
7 1080i59.94
8 1080p23.98
9 1080p24
10 1080p25
11 1080p29.97
12 1080p50
13 1080p59.94
14 4k23.98
15 4k24
16 4k25
17 4k29.97
18 4k50
19 4k59.94
20 8k23.98
21 8k24
22 8k25
23 8k29.97
24 8k50
25 8k59.94
26 1080p30
27 1080p60
=== ==========
The multiview and downconvert bitfields are the same values as the resultion numbers but the
key is the bit instead.
After parsing:
:ivar mode: mode number
:ivar resolution: vertical resolution of the mode
:ivar interlaced: the current mode is interlaced
:ivar rate: refresh rate of the mode
"""
CODE = "_VMC"
def __init__(self, raw):
self.raw = raw
count, = struct.unpack_from('>H', raw, 0)
self.modes = []
for i in range(0, count):
vidm, multiview, downscale, reconfig = struct.unpack_from('>B3x I I ?', raw, 4 + (i * 13))
self.modes.append({
'modenum': vidm,
'mode': self._int_to_mode(vidm),
'multiview': self._bitfield_to_modes(multiview),
'downscale': self._bitfield_to_modes(downscale),
'reconfigure': reconfig,
})
def _bitfield_to_modes(self, bitfield):
result = []
for i in range(0, 32):
if bitfield & (2 ** i):
result.append(self._int_to_mode(i))
return result
def _int_to_mode(self, mode):
return VideoModeField(struct.pack('>1B3x', mode))
def __repr__(self):
modenames = []
for mode in self.modes:
modenames.append(mode['mode'].get_label())
lst = ' '.join(modenames)
return '<video-mode-capability: {}>'.format(lst)
class InputPropertiesField(FieldBase):
"""
Data from the `InPr` field. This stores information about all the internal and external inputs.
The mixer will send multiple fields, one for each input
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 2 u16 Source index
2 20 char[] Long name
22 4 char[] Short name for button
26 1 u8 Source category 0=input 1=output
27 1 u8 ? bitfield
28 1 u8 same as byte 26
29 1 u8 port
30 1 u8 same as byte 26
31 1 u8 same as byte 29
32 1 u8 port type
33 1 u8 bitfield
34 1 u8 bitfield
35 1 u8 direction
====== ==== ====== ===========
===== =========
value port type
===== =========
0 external
1 black
2 color bars
3 color generator
4 media player
5 media player key
6 supersource
7 passthrough
128 M/E output
129 AUX output
131 Multiview output, or a dedicated status window (audio, recording, streaming)
===== =========
===== ===============
value available ports
===== ===============
0 SDI
1 HDMI
2 Component
3 Composite
4 S/Video
===== ===============
===== =============
value selected port
===== =============
0 internal
1 SDI
2 HDMI
3 Composite
4 Component
5 S/Video
===== =============
After parsing:
:ivar index: Source index
:ivar name: Long name
:ivar short_name: Short name for button
:ivar port_type: Integer describing the port type
:ivar available_aux: Source can be routed to AUX
:ivar available_multiview: Source can be routed to multiview
:ivar available_supersource_art: Source can be routed to supersource
:ivar available_supersource_box: Source can be routed to supersource
:ivar available_key_source: Source can be used as keyer key source
:ivar available_aux1: Source can be sent to AUX1 (Extreme only)
:ivar available_aux2: Source can be sent to AUX2 (Extreme only)
:ivar available_me1: Source can be routed to M/E 1
:ivar available_me2: Source can be routed to M/E 2
"""
PORT_EXTERNAL = 0
PORT_BLACK = 1
PORT_BARS = 2
PORT_COLOR = 3
PORT_MEDIAPLAYER = 4
PORT_MEDIAPLAYER_KEY = 5
PORT_SUPERSOURCE = 6
PORT_PASSTHROUGH = 7
PORT_ME_OUTPUT = 128
PORT_AUX_OUTPUT = 129
PORT_KEY_MASK = 130
PORT_MULTIVIEW_OUTPUT = 131
CODE = "InPr"
def __init__(self, raw):
self.raw = raw
fields = struct.unpack('>H 20s 4s 10B', raw)
self.index = fields[0]
self.name = self._get_string(fields[1])
self.short_name = self._get_string(fields[2])
self.source_category = fields[3]
self.port_type = fields[9]
self.source_ports = fields[6]
self.available_aux = fields[11] & (1 << 0) != 0
self.available_multiview = fields[11] & (1 << 1) != 0
self.available_supersource_art = fields[11] & (1 << 2) != 0
self.available_supersource_box = fields[11] & (1 << 3) != 0
self.available_key_source = fields[11] & (1 << 4) != 0
self.available_aux1 = fields[11] & (1 << 5) != 0
self.available_aux2 = fields[11] & (1 << 6) != 0
self.available_me1 = fields[12] & (1 << 0) != 0
self.available_me2 = fields[12] & (1 << 1) != 0
def __repr__(self):
return '<input-properties: index={} name={} button={}>'.format(self.index, self.name, self.short_name)
class ProgramBusInputField(FieldBase):
"""
Data from the `PrgI` field. This represents the active channel on the program bus of the specific M/E unit.
The mixer will send a field for every M/E unit in the mixer.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 M/E index
1 1 ? unknown
2 2 u16 Source index
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar source: Input source index, refers to an InputPropertiesField index
"""
CODE = "PrgI"
def __init__(self, raw):
self.raw = raw
self.index, self.source = struct.unpack('>BxH', raw)
def __repr__(self):
return '<program-bus-input: me={} source={}>'.format(self.index, self.source)
class PreviewBusInputField(FieldBase):
"""
Data from the `PrvI` field. This represents the active channel on the preview bus of the specific M/E unit.
The mixer will send a field for every M/E unit in the mixer.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 M/E index
1 1 ? unknown
2 2 u16 Source index
4 1 u8 1 if preview is mixed in program during a transition
5 3 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar source: Input source index, refers to an InputPropertiesField index
:ivar in_program: Preview source is mixed into progam
"""
CODE = "PrvI"
def __init__(self, raw):
self.raw = raw
self.index, self.source, in_program = struct.unpack('>B x H B 3x', raw)
self.in_program = in_program == 1
def __repr__(self):
in_program = ''
if self.in_program:
in_program = ' in-program'
return '<preview-bus-input: me={} source={}{}>'.format(self.index, self.source, in_program)
class TransitionSettingsField(FieldBase):
"""
Data from the `TrSS` field. This stores the config of the "Next transition" and "Transition style" blocks on the
control panels.
The mixer will send a field for every M/E unit in the mixer.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 M/E index
1 1 u8 Transition style
2 1 u8 Next transition layers
3 1 u8 Next transition style
4 1 u8 Next transition next transition layers
====== ==== ====== ===========
There are two sets of style/layer settings. The first set is the active transition settings. The second one
will store the transitions settings if you change any of them while a transition is active. These settings will be
applied as soon as the transition ends. This is signified by blinking transition settings buttons in the official
control panels.
After parsing:
:ivar index: M/E index in the mixer
:ivar style: Active transition style
:ivar style_next: Transition style for next transition
:ivar next_transition_bkgd: Next transition will affect the background layer
:ivar next_transition_key1: Next transition will affect the upstream key 1 layer
:ivar next_transition_key2: Next transition will affect the upstream key 2 layer
:ivar next_transition_key3: Next transition will affect the upstream key 3 layer
:ivar next_transition_key4: Next transition will affect the upstream key 4 layer
:ivar next_transition_bkgd_next: Next transition (after current) will affect the background layer
:ivar next_transition_key1_next: Next transition (after current) will affect the upstream key 1 layer
:ivar next_transition_key2_next: Next transition (after current) will affect the upstream key 2 layer
:ivar next_transition_key3_next: Next transition (after current) will affect the upstream key 3 layer
:ivar next_transition_key4_next: Next transition (after current) will affect the upstream key 4 layer
"""
STYLE_MIX = 0
STYLE_DIP = 1
STYLE_WIPE = 2
STYLE_DVE = 3
STYLE_STING = 4
CODE = "TrSS"
def __init__(self, raw):
self.raw = raw
self.index, self.style, nt, self.style_next, ntn = struct.unpack('>B 2B 2B 3x', raw)
self.next_transition_bkgd = nt & (1 << 0) != 0
self.next_transition_key1 = nt & (1 << 1) != 0
self.next_transition_key2 = nt & (1 << 2) != 0
self.next_transition_key3 = nt & (1 << 3) != 0
self.next_transition_key4 = nt & (1 << 4) != 0
self.next_transition_bkgd_next = ntn & (1 << 0) != 0
self.next_transition_key1_next = ntn & (1 << 1) != 0
self.next_transition_key2_next = ntn & (1 << 2) != 0
self.next_transition_key3_next = ntn & (1 << 3) != 0
self.next_transition_key4_next = ntn & (1 << 4) != 0
def __repr__(self):
return '<transition-settings: me={} style={}>'.format(self.index, self.style)
class TransitionPreviewField(FieldBase):
"""
Data from the `TsPr` field. This represents the state of the "PREV TRANS" button on the mixer.
The mixer will send a field for every M/E unit in the mixer.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 M/E index
1 1 bool Enabled
2 2 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar enabled: True if the transition preview is enabled
"""
CODE = "TsPr"
def __init__(self, raw):
self.raw = raw
self.index, self.enabled = struct.unpack('>B ? 2x', raw)
def __repr__(self):
return '<transition-preview: me={} enabled={}>'.format(self.index, self.enabled)
class TransitionPositionField(FieldBase):
"""
Data from the `TrPs` field. This represents the state of the transition T-handle position
The mixer will send a field for every M/E unit in the mixer.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 M/E index
1 1 bool In transition
2 1 u8 Frames remaining
3 1 ? unknown
4 2 u16 Position
6 1 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar in_transition: True if the transition is active
:ivar frames_remaining: Number of frames left to complete the transition on auto
:ivar position: Position of the transition, 0-9999
"""
CODE = "TrPs"
def __init__(self, raw):
self.raw = raw
self.index, self.in_transition, self.frames_remaining, position = struct.unpack('>B ? B x H 2x', raw)
self.position = position
def __repr__(self):
return '<transition-position: me={} frames-remaining={} position={:02f}>'.format(self.index,
self.frames_remaining,
self.position)
class TallyIndexField(FieldBase):
"""
Data from the `TlIn`. This is the status of the tally light for every input in order of index number.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 2 u16 Total of tally lights
n 1 u8 Bitfield, bit0=PROGRAM, bit1=PREVIEW, repeated for every tally light
====== ==== ====== ===========
After parsing:
:ivar num: number of tally lights
:ivar tally: List of tally values, every tally light is represented as a tuple with 2 booleans for PROGRAM and PREVIEW
"""
CODE = "TlIn"
def __init__(self, raw):
self.raw = raw
offset = 0
self.num, = struct.unpack_from('>H', raw, offset)
self.tally = []
offset += 2
for i in range(0, self.num):
tally, = struct.unpack_from('>B', raw, offset)
self.tally.append((tally & 1 != 0, tally & 2 != 0))
offset += 1
def __repr__(self):
return '<tally-index: num={}, val={}>'.format(self.num, self.tally)
class TallySourceField(FieldBase):
"""
Data from the `TlSr`. This is the status of the tally light for every input, but indexed on source index
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 2 u16 Total of tally lights
n 2 u16 Source index for this tally light
n+2 1 u8 Bitfield, bit0=PROGRAM, bit1=PREVIEW
====== ==== ====== ===========
After parsing:
:ivar num: number of tally lights
:ivar tally: Dict of tally lights, every tally light is represented as a tuple with 2 booleans for PROGRAM and PREVIEW
"""
CODE = "TlSr"
def __init__(self, raw):
self.raw = raw
offset = 0
self.num, = struct.unpack_from('>H', raw, offset)
self.tally = {}
offset += 2
for i in range(0, self.num):
source, tally, = struct.unpack_from('>HB', raw, offset)
self.tally[source] = (tally & 1 != 0, tally & 2 != 0)
offset += 3
def __repr__(self):
return '<tally-source: num={}, val={}>'.format(self.num, self.tally)
class KeyOnAirField(FieldBase):
"""
Data from the `KeOn`. This is the on-air state of the upstream keyers
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 M/E index
1 1 u8 Keyer index
2 1 bool On-air
3 1 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar keyer: Upstream keyer number
:ivar enabled: Wether the keyer is on-air
"""
CODE = "KeOn"
def __init__(self, raw):
self.raw = raw
self.index, self.keyer, self.enabled = struct.unpack('>BB?x', raw)
def __repr__(self):
return '<key-on-air: me={}, keyer={}, enabled={}>'.format(self.index, self.keyer, self.enabled)
class ColorGeneratorField(FieldBase):
"""
Data from the `ColV`. This is color set in the color generators of the mixer
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 Color generator index
1 1 ? unknown
2 2 u16 Hue [0-3599]
4 2 u16 Saturation [0-1000]
6 2 u16 Luma [0-1000]
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar keyer: Upstream keyer number
:ivar enabled: Wether the keyer is on-air
"""
CODE = "ColV"
def __init__(self, raw):
self.raw = raw
self.index, self.hue, self.saturation, self.luma = struct.unpack('>Bx 3H', raw)
self.hue = self.hue / 10.0
self.saturation = self.saturation / 1000.0
self.luma = self.luma / 1000.0
def get_rgb(self):
return colorsys.hls_to_rgb(self.hue / 360.0, self.luma, self.saturation)
def __repr__(self):
return '<color-generator: index={}, hue={} saturation={} luma={}>'.format(self.index, self.hue, self.saturation,
self.luma)
class AuxOutputSourceField(FieldBase):
"""
Data from the `AuxS`. The routing for the AUX outputs of the hardware.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 AUX output index
1 1 ? unknown
2 2 u16 Source index
====== ==== ====== ===========
After parsing:
:ivar index: AUX index
:ivar rate: Source index
"""
CODE = "AuxS"
def __init__(self, raw):
self.raw = raw
self.index, self.source = struct.unpack('>BxH', raw)
def __repr__(self):
return '<aux-output-source: aux={}, source={}>'.format(self.index, self.source)
class FadeToBlackStateField(FieldBase):
"""
Data from the `FtbS`. This contains the information about the fade-to-black transition.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 M/E index
1 1 bool Fade to black done
2 1 bool Fade to black is in transition
3 1 u8 Frames remaining in transition
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar done: Fade to black is completely done (blinking button state in the control panel)
:ivar transitioning: Fade to black is fading, (Solid red in control panel)
:ivar frames_remaining: Frames remaining in the transition
"""
CODE = "FtbS"
def __init__(self, raw):
self.raw = raw
self.index, self.done, self.transitioning, self.frames_remaining = struct.unpack('>B??B', raw)
def __repr__(self):
return '<fade-to-black-state: me={}, done={}, transitioning={}, frames-remaining={}>'.format(self.index,
self.done,
self.transitioning,
self.frames_remaining)
class MediaplayerFileInfoField(FieldBase):
"""
Data from the `MPfe`. This is the metadata about a single frame slot in the mediaplayer
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 type
1 1 ? unknown
2 2 u16 index
4 1 bool is used
5 16 char[] hash
21 2 ? unknown
23 ? string name of the slot, first byte is number of characters
====== ==== ====== ===========
After parsing:
:ivar index: Slot index
:ivar type: Slot type, 0=still
:ivar is_used: Slot contains data
:ivar hash: 16-byte md5 hash of the slot data
:ivar name: Name of the content in the slot
"""
CODE = "MPfe"
def __init__(self, raw):
self.raw = raw
namelen = max(0, len(raw) - 23)
self.type, self.index, self.is_used, self.hash, self.name = struct.unpack('>Bx H ? 16s 2x {}p'.format(namelen),
raw)
def __repr__(self):
return '<mediaplayer-file-info: type={} index={} used={} name={}>'.format(self.type, self.index, self.is_used,
self.name)
class TopologyField(FieldBase):
"""
Data from the `_top` field. This describes the internal video routing topology.
=================== ========= ======= ======
spec Atem Mini 1M/E 4k TVS HD
=================== ========= ======= ======
M/E units 1 1 1
upstream keyers 1 1 1
downstream keyers 1 2 2
dve 1 1 1
stinger 0 1 0
supersources 0 0 0
multiview 0 1 1
rs485 0 1 1
=================== ========= ======= ======
====== ==== ====== ========= ========= ======= ======= ====== ===========
Offset Size Type Atem Mini Mini Pro 1M/E 4k Prod 4k TVS HD Description
====== ==== ====== ========= ========= ======= ======= ====== ===========
0 1 u8 1 1 1 1 1 Number of M/E units
1 1 u8 14 15 31 24 24 Sources
2 1 u8 1 1 2 2 2 Downstream keyers
3 1 u8 1 1 3 1 1 AUX busses
4 1 u8 0 0 0 0 4 MixMinus Outputs
5 1 u8 1 1 2 2 2 Media players
6 1 u8 0 1 1 1 1 Multiviewers
7 1 u8 0 0 1 0 1 rs485
8 1 u8 4 4 4 4 4 Hyperdecks
9 1 u8 1 1 1 0 1 DVE
10 1 u8 0 0 1 0 0 Stingers
11 1 u8 0 0 0 0 0 supersources
12 1 u8 0 0 1 1 1 ? Multiview routable?
13 1 u8 0 0 0 0 1 Talkback channels
14 1 u8 0 0 0 0 4 ?
15 1 u8 1 1 0 0 0 ?
16 1 u8 0 0 0 0 0 ?
17 1 u8 0 0 1 1 0 ?
18 1 u8 1 1 1 1 1 Camera Control
19 1 u8 0 0 1 0 1 ?
20 1 u8 0 0 1 0 1 ?
21 1 u8 0 0 1 1 1 ? Multiview routable?
22 1 u8 1 1 0 0 0 Advanced chroma keyers
23 1 u8 1 1 0 0 0 Only configurable outputs
24 1 u8 1 1 0 0 0 ?
25 1 u8 0x20 0x2f 0x20 0 0x10 ?
26 1 u8 3 108 0 0 0 ?
27 1 u8 0xe8 0x69 0x00 0 0x0 ?
====== ==== ====== ========= ========= ======= ======= ====== ===========
After parsing:
:ivar me_units: Number of M/E units in the mixer
:ivar sources: Number of internal and external sources
:ivar downstream_keyers: Number of downstream keyers
:ivar aux_outputs: Number of routable AUX outputs
:ivar mixminus_outputs: Number of ouputs with MixMinus
:ivar mediaplayers: Number of mediaplayers
:ivar multiviewers: Number of multiview ouputs
:ivar rs485: Number of RS-485 outputs
:ivar hyperdecks: Number of hyperdeck slots
:ivar dve: Number of DVE blocks
:ivar stingers: Number of stinger blocks
:ivar supersources: Number of supersources
"""
CODE = "_top"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>28B', raw)
self.me_units = field[0]
self.sources = field[1]
self.downstream_keyers = field[2]
self.aux_outputs = field[3]
self.mixminus_outputs = field[4]
self.mediaplayers = field[5]
self.multiviewers = field[6]
self.rs485 = field[7]
self.hyperdecks = field[8]
self.dve = field[9]
self.stingers = field[10]
self.supersources = field[11]
self.multiviewer_routable = field[12] == 1
def __repr__(self):
return '<topology, me={} sources={} aux={}>'.format(self.me_units, self.sources, self.aux_outputs)
class DkeyPropertiesBaseField(FieldBase):
"""
Data from the `DskB`. Downstream keyer base info.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 Downstream keyer index, 0-indexed
1 1 ? unknown
2 2 u16 Fill source index
4 2 u16 Key source index
6 2 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: DSK index
:ivar fill_source: Source index for the fill input
:ivar key_source: Source index for the key input
"""
CODE = "DskB"
def __init__(self, raw):
self.raw = raw
self.index, self.fill_source, self.key_source = struct.unpack('>BxHH2x', raw)
def __repr__(self):
return '<downstream-keyer-base: dsk={}, fill={}, key={}>'.format(self.index, self.fill_source, self.key_source)
class DkeyPropertiesField(FieldBase):
"""
Data from the `DskP`. Downstream keyer info.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 Downstream keyer index, 0-indexed
1 1 bool Tie enabled
2 1 u8 Transition rate in frames
3 1 bool Mask is pre-multiplied alpha
4 2 u16 Clip [0-1000]
6 2 u16 Gain [0-1000]
8 1 bool Invert key
9 1 bool Enable mask
10 2 i16 Top [-9000 - 9000]
12 2 i16 Bottom [-9000 - 9000]
14 2 i16 Left [-9000 - 9000]
16 2 i16 Right [-9000 - 9000]
18 2 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar done: Fade to black is completely done (blinking button state in the control panel)
:ivar transitioning: Fade to black is fading, (Solid red in control panel)
:ivar frames_remaining: Frames remaining in the transition
"""
CODE = "DskP"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>B?B ?HH? ?4h 2B', raw)
self.index = field[0]
self.tie = field[1]
self.rate = field[2]
self.premultiplied = field[3]
self.clip = field[4]
self.gain = field[5]
self.invert_key = field[6]
self.masked = field[7]
self.top = field[8]
self.bottom = field[9]
self.left = field[10]
self.right = field[11]
def __repr__(self):
return '<downstream-keyer-mask: dsk={}, tie={}, rate={}, masked={}>'.format(self.index, self.tie, self.rate,
self.masked)
class DkeyStateField(FieldBase):
"""
Data from the `DskS`. Downstream keyer state.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 Downstream keyer index, 0-indexed
1 1 bool On air
2 1 bool Is transitioning
3 1 bool Is autotransitioning
4 1 u8 Frames remaining
5 3 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: Downstream keyer index
:ivar on_air: Keyer is on air
:ivar is_transitioning: Is transitioning
:ivar is_autotransitioning: Is transitioning due to auto button
:ivar frames_remaining: Frames remaining in transition
"""
CODE = "DskS"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>B 3? B 3x', raw)
self.index = field[0]
self.on_air = field[1]
self.is_transitioning = field[2]
self.is_autotransitioning = field[3]
self.frames_remaining = field[4]
def __repr__(self):
return '<downstream-keyer-state: dsk={}, onair={}, transitioning={} autotrans={} frames={}>'.format(self.index,
self.on_air,
self.is_transitioning,
self.is_autotransitioning,
self.frames_remaining)
class TransitionMixField(FieldBase):
"""
Data from the `TMxP`. Settings for the mix transition.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 M/E index
1 1 u8 rate in frames
2 2 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar rate: Number of frames in the transition
"""
CODE = "TMxP"
def __init__(self, raw):
self.raw = raw
self.index, self.rate = struct.unpack('>BBxx', raw)
def __repr__(self):
return '<transition-mix: me={}, rate={}>'.format(self.index, self.rate)
class FadeToBlackField(FieldBase):
"""
Data from the `FtbP`. Settings for the fade-to-black transition.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 M/E index
1 1 u8 rate in frames
2 2 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar rate: Number of frames in transition
"""
CODE = "FtbP"
def __init__(self, raw):
self.raw = raw
self.index, self.rate = struct.unpack('>BBxx', raw)
def __repr__(self):
return '<fade-to-black: me={}, rate={}>'.format(self.index, self.rate)
class TransitionDipField(FieldBase):
"""
Data from the `TDpP`. Settings for the dip transition.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 M/E index
1 1 u8 rate in frames
2 2 u16 Source index for the DIP source
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar rate: Number of frames in transition
:ivar source: Source index for the dip
"""
CODE = "TDpP"
def __init__(self, raw):
self.raw = raw
self.index, self.rate, self.source = struct.unpack('>BBH', raw)
def __repr__(self):
return '<transition-dip: me={}, rate={} source={}>'.format(self.index, self.rate, self.source)
class TransitionWipeField(FieldBase):
"""
Data from the `TWpP`. Settings for the wipe transition.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 M/E index
1 1 u8 Rate in frames
2 1 u8 Pattern id
3 1 ? unknown
4 2 u16 Border width
6 2 u16 Border fill source index
8 2 u16 Symmetry
10 2 u16 Softness
12 2 u16 Origin position X
14 2 u16 Origin position Y
16 1 bool Reverse
16 1 bool Flip flop
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar rate: Number of frames in transition
:ivar source: Source index for the dip
"""
CODE = "TWpP"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>BBBx 6H 2? 2x', raw)
self.index = field[0]
self.rate = field[1]
self.pattern = field[2]
self.width = field[3]
self.source = field[4]
self.symmetry = field[5]
self.softness = field[6]
self.positionx = field[7]
self.positiony = field[8]
self.reverse = field[9]
self.flipflop = field[10]
def __repr__(self):
return '<transition-wipe: me={}, rate={} pattern={}>'.format(self.index, self.rate, self.pattern)
class TransitionDveField(FieldBase):
"""
Data from the `TDvP`. Settings for the DVE transition.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 M/E index
1 1 u8 Rate in frames
2 1 ? unknown
3 1 u8 DVE style
4 2 u16 Fill source index
6 2 u16 Key source index
8 1 bool Enable key
9 1 bool Key is premultiplied
10 2 u16 Key clip [0-1000]
12 2 u16 Key gain [0-1000]
14 1 bool Key invert
15 1 bool Reverse
16 1 bool Flip flop
17 3 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: M/E index in the mixer
:ivar rate: Number of frames in transition
:ivar style: Style or effect index for the DVE
:ivar fill_source: Fill source index
:ivar key_source: Key source index
:ivar key_premultiplied: Key is premultiplied alpha
:ivar key_clip: Key clipping point
:ivar key_gain: Key Gain
:ivar key_invert: Invert key source
:ivar reverse: Reverse transition
:ivar flipflop: Flip flop transition
"""
CODE = "TDvP"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>BBx B 2H 2? 2H 3? 3x', raw)
self.index = field[0]
self.rate = field[1]
self.style = field[2]
self.fill_source = field[3]
self.key_source = field[4]
self.key_enable = field[5]
self.key_premultiplied = field[6]
self.key_clip = field[7]
self.key_gain = field[8]
self.key_invert = field[9]
self.reverse = field[10]
self.flipflop = field[11]
def __repr__(self):
return '<transition-dve: me={}, rate={} style={}>'.format(self.index, self.rate, self.style)
class AudioMixerMasterPropertiesField(FieldBase):
"""
Data from the `AMMO`. Settings for the master bus on legacy audio units.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Program Gain
2 2 ? unknown
4 1 bool Follow fade to black
5 1 ? unknown
====== ==== ====== ===========
After parsing:
:ivar volume: Master volume for the mixer, unsigned int which maps [? - ?] to +10dB - -100dB (inf)
:ivar afv: Wether the master volume follows the fade-to-bloack
"""
CODE = "AMMO"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>H 2x ?x 2x', raw)
self.volume = field[0]
self.afv = field[1]
def __repr__(self):
return '<audio-master-properties: volume={} afv={}>'.format(self.volume, self.afv)
class AudioMixerMonitorPropertiesField(FieldBase):
"""
Data from the `AMmO`. Settings for the monitor bus on legacy audio units.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 bool Monitoring enabled
1 1 ? unknown
2 2 u16 Volume
4 1 bool Mute
5 1 bool Solo
6 2 u16 Solo source index
8 1 bool Dim
10 2 u16 Dim volume
====== ==== ====== ===========
After parsing:
:ivar volume: Master volume for the mixer, unsigned int which maps [? - ?] to +10dB - -100dB (inf)
"""
CODE = "AMmO"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>?xH? ?H ?x H', raw)
self.enabled = field[0]
self.volume = field[1]
self.mute = field[2]
self.solo = field[3]
self.solo_source = field[4]
self.dim = field[5]
self.dim_volume = field[6]
def __repr__(self):
return '<audio-monitor-properties: volume={}>'.format(self.volume)
class AudioMixerInputPropertiesField(FieldBase):
"""
Data from the `AMIP`. Settings for a channel strip on legacy audio units.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Audio source index
2 1 u8 Type [0: External Video, 1: Media Player, 2: External Audio]
3 3 ? unknown
6 1 bool From Media Player
7 1 u8 Plug Type [0: Internal, 1: SDI, 2: HDMI, 3: Component, 4: Composite, 5: SVideo, 32: XLR, 64, AES/EBU, 128 RCA]
8 1 u8 Mix Option [0: Off, 1: On, 2: AFV]
9 1 u8 unknown
10 2 u16 Volume [0 - 65381]
12 2 i16 Pan [-10000 - 10000]
14 1 u8 unknown
====== ==== ====== ===========
After parsing:
:ivar volume: Master volume for the mixer, signed int which maps [-10000 - 1000] to +10dB - -100dB (inf)
:ivar afv: Enable/disabled state for master audio-follow-video (for fade-to-black)
"""
CODE = "AMIP"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>H B 2x ? B B x H h x x x', raw)
self.index = field[0]
self.type = field[1]
self.is_media_player = field[2]
self.number = field[3]
self.mix_option = field[4]
self.volume = field[5]
self.balance = field[6]
self.strip_id = str(self.index) + '.0'
def __repr__(self):
return '<audio-mixer-input-properties: index={} volume={} balance={} >'.format(self.strip_id, self.volume,
self.balance)
class AudioMixerTallyField(FieldBase):
"""
Data from the `AMTl`. Encodes the state of tally lights on the audio mixer
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Number of tally lights
2 2 u16 Audio Source
4 1 bool IsMixedIn (On/Off)
====== ==== ====== ===========
"""
CODE = "AMTl"
def __init__(self, raw):
self.raw = raw
offset = 0
self.num, = struct.unpack_from('>H', raw, offset)
self.tally = {}
offset += 2
for i in range(0, self.num):
source, tally, = struct.unpack_from('>H?', raw, offset)
strip_id = '{}.{}'.format(source, 0)
self.tally[strip_id] = tally
offset += 3
def __repr__(self):
return '<audio-mixer-tally {}>'.format(self.tally)
class FairlightMasterPropertiesField(FieldBase):
"""
Data from the `FAMP`. Settings for the master bus on fairlight audio units.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 ? unknown
1 1 bool Enable master EQ
2 4 ? unknown
6 2 i16 EQ gain [-2000 - 2000]
8 2 ? unknown
10 2 u16 Dynamics make-up gain [0 - 2000]
12 4 i32 Master volume [-10000 - 1000]
16 1 bool Audio follow video
17 3 ? unknown
====== ==== ====== ===========
After parsing:
:ivar volume: Master volume for the mixer, signed int which maps [-10000 - 1000] to +10dB - -100dB (inf)
:ivar eq_enable: Enabled/disabled state for the master EQ
:ivar eq_gain: Gain applied after EQ, [-2000 - 2000] maps to -20dB - +20dB
:ivar dynamics_gain: Make-up gain for the dynamics section, [0 - 2000] maps to 0dB - +20dB
:ivar afv: Enable/disabled state for master audio-follow-video (for fade-to-black)
"""
CODE = "FAMP"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>x ? 4x h 2x H i ? 3x', raw)
self.eq_enable = field[0]
self.eq_gain = field[1]
self.dynamics_gain = field[2]
self.volume = field[3]
self.afv = field[4]
def __repr__(self):
return '<fairlight-master-properties: volume={} make-up={} eq={}>'.format(self.volume, self.dynamics_gain,
self.eq_gain)
class FairlightStripPropertiesField(FieldBase):
"""
Data from the `FASP`. Settings for a channel strip on fairlight audio units.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Audio source index
14 1 u8 Split indicator? [01 for normal, FF for split]
15 1 u8 Subchannel index
18 1 u8 Delay in frames
22 2 i16 Gain [-10000 - 600]
29 1 bool Enable EQ
34 2 i16 EQ Gain
38 2 u16 Dynamics gain
40 2 i16 Pan [-10000 - 10000]
46 2 i16 Volume [-10000 - 1000]
49 1 u8 AFV bitfield? 1=off 2=on 4=afv
====== ==== ====== ===========
The way byte 14 and 15 work is unclear at the moment, this need verification on a mixer with an video input that has
more than 2 embedded channels, of of these bytes might be a channel count.
After parsing:
:ivar volume: Master volume for the mixer, signed int which maps [-10000 - 1000] to +10dB - -100dB (inf)
:ivar eq_enable: Enabled/disabled state for the master EQ
:ivar eq_gain: Gain applied after EQ, [-2000 - 2000] maps to -20dB - +20dB
:ivar dynamics_gain: Make-up gain for the dynamics section, [0 - 2000] maps to 0dB - +20dB
:ivar afv: Enable/disabled state for master audio-follow-video (for fade-to-black)
"""
CODE = "FASP"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>H 12xBBxB 4x h 5x ? 4x h 2x Hh 4x h x B 2x', raw)
self.index = field[0]
self.is_split = field[1]
self.subchannel = field[2]
self.delay = field[3]
self.gain = field[4]
self.eq_enable = field[5]
self.eq_gain = field[6]
self.dynamics_gain = field[7]
self.pan = field[8]
self.volume = field[9]
self.state = field[10]
self.strip_id = str(self.index)
if self.is_split == 0xff:
self.strip_id += '.' + str(self.subchannel)
else:
self.strip_id += '.0'
def __repr__(self):
extra = ''
if self.eq_enable:
extra += ' EQ {}'.format(self.eq_gain)
return '<fairlight-strip-properties: index={} gain={} volume={} pan={} dgn={} {}>'.format(self.strip_id,
self.gain,
self.volume,
self.pan,
self.dynamics_gain,
extra)
class FairlightStripDeleteField(FieldBase):
"""
Data from the `FASD`. Fairlight strip delete, received only when changing the source routing in fairlight to remove
channels that have changed.
"""
CODE = "FASD"
def __init__(self, raw):
self.raw = raw
def __repr__(self):
return '<fairlight-strip-delete {}>'.format(self.raw)
class FairlightAudioInputField(FieldBase):
"""
Data from the `FAIP`. Describes the inputs to the fairlight mixer
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Audio source index
2 1 u8 Input type
3 2 ? unknown
5 1 u8 Index in group
10 1 u8 Changes when stereo is split into dual mono
12 1 u8 Analog audio input level [1=mic, 2=line]
====== ==== ====== ===========
=== ==========
Val Input type
=== ==========
0 External video input
1 Media player audio
2 External audio input
=== ==========
After parsing:
:ivar volume: Master volume for the mixer, signed int which maps [-10000 - 1000] to +10dB - -100dB (inf)
"""
CODE = "FAIP"
def __init__(self, raw):
self.raw = raw
self.index, self.type, self.number, self.split, self.level = struct.unpack('>HB 2x B xxxx B x B 3x', raw)
def __repr__(self):
return '<fairlight-input index={} type={}>'.format(self.index, self.type)
class FairlightTallyField(FieldBase):
"""
Data from the `FMTl`. Encodes the state of tally lights on the audio mixer
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Number of tally lights
2 1 u8 Input type
3 2 ? unknown
5 1 u8 Index in group
10 1 u8 Changes when stereo is split into dual mono
12 1 u8 Analog audio input level [1=mic, 2=line]
====== ==== ====== ===========
=== ==========
Val Input type
=== ==========
0 External video input
1 Media player audio
2 External audio input
=== ==========
After parsing:
:ivar volume: Master volume for the mixer, signed int which maps [-10000 - 1000] to +10dB - -100dB (inf)
"""
CODE = "FMTl"
def __init__(self, raw):
self.raw = raw
offset = 0
self.num, = struct.unpack_from('>H', raw, offset)
self.tally = {}
offset += 15
for i in range(0, self.num):
subchan, source, tally, = struct.unpack_from('>BH?', raw, offset)
strip_id = '{}.{}'.format(source, subchan)
self.tally[strip_id] = tally
offset += 11
def __repr__(self):
return '<fairlight-tally {}>'.format(self.tally)
class FairlightHeadphonesField(FieldBase):
"""
Data from the `FMHP`, phones output volume and mute
This doesn't get triggered when soloing channels.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 4 i32 Volume in 0.01 dB (-60.00 to +6.00 dB)
5 4 ? Unknown
8 1 bool Muted (0) / Umuted (1)
9 1 u8 Last soloed channel (just the main part)
10 22 ? Unknown
"""
def __init__(self, raw):
self.raw = raw
self.volume, self.unmuted = struct.unpack('> i 4x ? 23x', raw)
def __repr__(self):
return '<fairlight-headphones volume={} unmuted={}>'.format(self.volume, self.unmuted)
class FairlightSoloField(FieldBase):
"""
Data from the `FAMS`, soloing channels to phones
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 bool Anything soloed?
1 7 ? Unknown
8 1 u8 Unknown: 0x00 for HDMI channels, 0x05 for 3.5mm jack
9 1 u8 Soloed channel (main)
10 12 ? Unknown
22 1 u8 No subchannels (0x01), split into L/R (0xff)
23 1 u8 Soloed channel (subchannel)
"""
def __init__(self, raw):
self.raw = raw
self.solo, self.channel, self.is_split_lr, self.subchannel = struct.unpack('> ? 8x B 12x BB', raw)
def __repr__(self):
return '<fairlight-solo active={} source={}>'.format(
self.solo,
self.channel if self.is_split_lr == 0x01 else '{}.{}'.format(self.channel, self.subchannel),
)
class AtemEqBandPropertiesField(FieldBase):
"""
Data from the `AEBP` field. This encodes the EQ settings in the fairlight mixer. For every channel there will
be 6 off these fields sent, one for every band of the EQ. The "possible band filters" differentiates the first
and last band which have a different option list for the filter dropdown in the UI.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Audio source index
2 2 ? unknown
4 4 ? unknown
14 1 u8 Split indicator? [01 for normal, FF for split]
15 1 u8 subchannel index
16 1 u8 bond index
17 1 bool band enabled
18 1 u8 possible band filters
19 1 u8 band filter
20 1 ? ?
21 1 ? band frequency range
26 2 u16 band frequency
28 4 i32 band gain
32 2 u16 band Q
====== ==== ====== ===========
=== ==========
Val Band filter
=== ==========
01 Low shelf
02 Low pass
04 Bell
08 Notch
10 High pass
20 High shelf
=== ==========
After parsing:
:ivar volume: Master volume for the mixer, signed int which maps [-10000 - 1000] to +10dB - -100dB (inf)
"""
CODE = "AEBP"
def __init__(self, raw):
self.raw = raw
values = struct.unpack('>H 2x 4x 6x BB B ? B B x B 4x H i H 2x', raw)
self.index = values[0]
self.is_split = values[1]
self.subchannel = values[2]
self.band_index = values[3]
self.band_enabled = values[4]
self.band_possible_filters = values[5]
self.band_filter = values[6]
self.band_freq_range = values[7]
self.band_frequency = values[8]
self.band_gain = values[9]
self.band_q = values[10]
self.strip_id = str(self.index)
if self.is_split == 0xff:
self.strip_id += '.' + str(self.subchannel)
else:
self.strip_id += '.0'
def __repr__(self):
desc = ''
filters = {
0x01: 'low-shelf',
0x02: 'low-pass',
0x04: 'bell',
0x08: 'notch',
0x10: 'high-pass',
0x20: 'high-shelf'
}
if self.band_filter in filters:
desc += filters[self.band_filter]
else:
desc += 'filter ' + str(self.band_filter)
if self.band_enabled:
desc += '[on]'
else:
desc += '[off]'
desc += ' freq ' + str(self.band_frequency)
desc += ' gain ' + str(self.band_gain)
desc += ' Q ' + str(self.band_q)
return '<atem-eq-band-properties {} band {} {}>'.format(self.strip_id, self.band_index, desc)
class AudioInputField(FieldBase):
"""
Data from the `AMIP`. Describes the inputs to the atem audio mixer
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Audio source index
2 1 u8 Input type
3 2 ? unknown
5 1 u8 Index in group
6 1 ? ?
7 1 u8 Input plug
8 1 u8 State [0=off, 1=on, 2=afv]
10 2 u16 Channel volume
12 2 i16 Channel balance [-10000 - 10000]
====== ==== ====== ===========
=== ==========
Val Input type
=== ==========
0 External video input
1 Media player audio
2 External audio input
=== ==========
=== =========
Val Plug type
=== =========
0 Internal
1 SDI
2 HDMI
3 Component
4 Composite
5 SVideo
32 XLR
64 AES/EBU
128 RCA
=== =========
After parsing:
:ivar volume: Master volume for the mixer, signed int which maps [-10000 - 1000] to +10dB - -100dB (inf)
"""
CODE = "AMIP"
def __init__(self, raw):
self.raw = raw
self.index, self.type, self.number, self.plug, self.state, self.volume, self.balance = struct.unpack(
'>HB 2x B x BB x Hh 2x', raw)
self.strip_id = str(self.index) + '.0'
def plug_name(self):
"""Return the display name for the connector"""
lut = {
0: "Internal",
1: "SDI",
2: "HDMI",
3: "Component",
4: "Composite",
5: "SVideo",
32: "XLR",
64: "AES",
128: "RCA",
}
if self.plug in lut:
return lut[self.plug]
else:
return 'Analog'
def __repr__(self):
return '<audio-input index={} type={} plug={}>'.format(self.index, self.type, self.plug)
class KeyPropertiesBaseField(FieldBase):
"""
Data from the `KeBP`. The upstream keyer base properties.
"""
CODE = "KeBP"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>BBB Bx B HH ?x 4h', raw)
self.index = field[0]
self.keyer = field[1]
self.type = field[2]
self.enabled = field[3]
self.fly_enabled = field[4]
self.fill_source = field[5]
self.key_source = field[6]
self.mask_enabled = field[7]
self.mask_top = field[8]
self.mask_bottom = field[9]
self.mask_left = field[10]
self.mask_right = field[11]
def __repr__(self):
return '<key-properties-base me={}, key={}, type={}>'.format(self.index, self.keyer, self.type)
class KeyPropertiesDveField(FieldBase):
"""
Data from the `KeDV`. The upstream keyer DVE-specific properties.
"""
CODE = "KeDV"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>BBxx 5i ??Bx HH BBBBBx 4HB? 4hB 3x', raw)
self.index = field[0]
self.keyer = field[1]
self.size_x = field[2]
self.size_y = field[3]
self.pos_x = field[4]
self.pos_y = field[5]
self.rotation = field[6]
self.border_enabled = field[7]
self.shadow_enabled = field[8]
self.border_bevel = field[9]
self.border_outer_width = field[10]
self.border_inner_width = field[11]
self.border_outer_softness = field[12]
self.border_inner_softness = field[13]
self.border_bevel_softness = field[14]
self.border_bevel_position = field[15]
self.border_opacity = field[16]
self.border_hue = field[17] / 10.0
self.border_saturation = field[18] / 1000.0
self.border_luma = field[19] / 1000.0
self.light_angle = field[20]
self.light_altitude = field[21]
self.mask_enabled = field[22]
self.mask_top = field[23]
self.mask_bottom = field[24]
self.mask_left = field[25]
self.mask_right = field[26]
self.rate = field[27]
def get_border_color_rgb(self):
return colorsys.hls_to_rgb(self.border_hue / 360.0, self.border_luma, self.border_saturation)
def __repr__(self):
return '<key-properties-dve me={}, key={}>'.format(self.index, self.keyer)
class KeyPropertiesLumaField(FieldBase):
"""
Data from the `KeLm`. The upstream keyer luma-specific properties.
"""
CODE = "KeLm"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>BB?x HH ?3x', raw)
self.index = field[0]
self.keyer = field[1]
self.premultiplied = field[2]
self.clip = field[3]
self.gain = field[4]
self.key_inverted = field[5]
def __repr__(self):
return '<key-properties-luma me={}, key={}>'.format(self.index, self.keyer)
class KeyPropertiesAdvancedChromaField(FieldBase):
"""
Data from the `KACk` field. This contains the data about the settings in the upstream advanced chroma keyer.
"""
CODE = "KACk"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>BBH HH HH hhHhhh', raw)
self.index = field[0]
self.keyer = field[1]
self.foreground = field[2]
self.background = field[3]
self.key_edge = field[4]
self.spill_suppress = field[5]
self.flare_suppress = field[6]
self.brightness = field[7]
self.contrast = field[8]
self.saturation = field[9]
self.red = field[10]
self.green = field[11]
self.blue = field[12]
def __repr__(self):
return '<key-properties-advanced-chroma me={}, key={}>'.format(self.index, self.keyer)
class KeyPropertiesAdvancedChromaColorpickerField(FieldBase):
"""
Data from the `KACC` field. This contains the data about the color picker in the upstream advanced chroma keyer.
"""
CODE = "KACC"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>BB?? hhH HHH', raw)
self.index = field[0]
self.keyer = field[1]
self.cursor = field[2]
self.preview = field[3]
self.x = field[4]
self.y = field[5]
self.size = field[6]
self.Y = (field[7] - 625) / 8544
self.Cb = (field[8] - 5000) / 5000
self.Cr = (field[9] - 5000) / 5000
def get_rgb(self):
r = self.Y + (self.Cr * 1.5748)
g = self.Y + (self.Cb * -0.1873) + (self.Cr * -0.4681)
b = self.Y + (self.Cb * 1.8556)
r = max(0, min(1, r))
g = max(0, min(1, g))
b = max(0, min(1, b))
return r, g, b
def __repr__(self):
return '<key-properties-advanced-chroma-colorpicker me={}, key={}>'.format(self.index, self.keyer)
class RecordingDiskField(FieldBase):
"""
Data from the `RTMD`. Info about an attached recording disk.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 4 u32 Disk index
4 4 u32 Recording time available in seconds
8 2 u16 Status bitfield
10 64 char[] Volume name
====== ==== ====== ===========
=== ==========
Bit Status value
=== ==========
0 Idle
1 Unformatted
2 Ready
3 Recording
4 ?
5 Deleted
=== ==========
"""
CODE = "RTMD"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>IIH 64s 2x', raw)
self.index = field[0]
self.time_available = field[1]
self.status = field[2]
self.volumename = self._get_string(field[3])
self.is_attached = field[2] & 1 << 0 > 0
self.is_attached = field[2] & 1 << 1 > 0
self.is_ready = field[2] & 1 << 2 > 0
self.is_recording = field[2] & 1 << 3 > 0
self.is_deleted = field[2] & 1 << 5 > 0
def __repr__(self):
return '<recording-disk disk={} label={} status={} available={}>'.format(self.index, self.volumename,
self.status, self.time_available)
class RecordingSettingsField(FieldBase):
"""
Data from the `RMSu`. The settings for the stream recorder.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 128 char[] Audio source index
128 4 i32 Disk slot 1 index, or -1 for no disk
132 4 i32 Disk slot 2 index, or -1 for no disk
136 1 bool Trigger recording in cameras
137 3 ? ?
====== ==== ====== ===========
The recorder settings has 2 slots to select attached USB disks. If no disk is selected the i32 will be -1 otherwise
it will be the disk number referring a RTMD field
"""
CODE = "RMSu"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>128s ii ?3x', raw)
self.filename = self._get_string(field[0])
self.disk1 = field[1] if field[1] != -1 else None
self.disk2 = field[2] if field[2] != -1 else None
self.record_in_cameras = field[3]
def __repr__(self):
return '<recording-settings filename={} disk1={} disk2={} in-camera={}>'.format(self.filename, self.disk1,
self.disk2,
self.record_in_cameras)
class RecordingStatusField(FieldBase):
"""
Data from the `RTMS`. The status for the stream recorder and total space left in the target device.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Recording status
4 4 i32 Total recording time available
====== ==== ====== ===========
=== ==========
Bit Status value
=== ==========
0 Recording
1 ?
2 Disk full
3 Disk error
4 Disk unformatted
5 Frames dropped
6 ?
7 Stopping
=== ==========
"""
CODE = "RMTS"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>H2xi', raw)
self.status = field[0]
self.time_available = field[1] if field[1] != -1 else None
self.is_recording = field[0] & 1 << 0 > 0
self.is_stopping = field[0] & 1 << 7 > 0
self.disk_full = field[0] & 1 << 2 > 0
self.disk_error = field[0] & 1 << 3 > 0
self.disk_unformatted = field[0] & 1 << 4 > 0
self.has_dropped = field[0] & 1 << 5 > 0
def __repr__(self):
return '<recording-status status={} time-available={}>'.format(self.status, self.time_available)
class RecordingDurationField(FieldBase):
"""
Data from the `RTMR`. The current recording duration, this does not update very often. The dropped
frames field signifies that the disk cannot keep up with writing the data and triggers the warning in the
UI.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 Hours
1 1 u8 Minutes
2 1 u8 Seconds
3 1 u8 Frames
4 1 bool Has dropped frames
5 3 ? unknown
====== ==== ====== ===========
"""
CODE = "RTMR"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>4B ?3x', raw)
self.hours = field[0]
self.minutes = field[1]
self.seconds = field[2]
self.frames = field[3]
self.has_dropped_frames = field[4]
def __repr__(self):
drop = ''
if self.has_dropped_frames:
drop = ' dropped-frames'
return '<recording-duration {}:{}:{}:{}{}>'.format(self.hours, self.minutes, self.seconds, self.frames, drop)
class MultiviewerPropertiesField(FieldBase):
"""
Data from the `MvPr`. The layout preset for the multiviewer output.
The multiviewer is divided in 4 quadrants and the layout bitfield describes which of those quadrants are
subdivided again in 4 more viewers. The default layout will have the top 2 quadrants not divided and the bottom
quadrants used for small viewers.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 Multiviewer index, 0-indexed
1 1 u8 Layout bitfield
1 1 bool Flip program/preview
1 1 ? unknown
====== ==== ====== ===========
=== ==========
Bit Layout value
=== ==========
0 Top left small
1 Top right small
2 Bottom left small
4 Bottom right small
=== ==========
After parsing:
:ivar index: Multiviewer index, 0-indexed
:ivar layout: Layout number from the enum above
:ivar flip: Swap the program/preview window
"""
CODE = "MvPr"
def __init__(self, raw):
self.raw = raw
field = struct.unpack('>BB?B', raw)
self.index = field[0]
self.layout = field[1]
self.flip = field[2]
self.u1 = field[3]
self.top_left_small = field[1] & 0x01 > 0
self.top_right_small = field[1] & 0x02 > 0
self.bottom_left_small = field[1] & 0x04 > 0
self.bottom_right_small = field[1] & 0x08 > 0
def __repr__(self):
return '<multiviewer-properties mv={} layout={} flip={} u1={}>'.format(self.index, self.layout, self.flip,
self.u1)
class MultiviewerInputField(FieldBase):
"""
Data from the `MvIn`. The input routing for the multiviewer.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 Multiviewer index, 0-indexed
1 1 u8 Window index 0-9
2 2 u16 Source index
4 1 bool Supports enabling the VU meter
5 1 bool Supports enabling the safe area overlay
6 2 ? unknown
====== ==== ====== ===========
Window numbering differs between switcher families. For example, on Atem
Mini Extreme, windows are numbered on a row-by-row basis, starting at upper
left. If a quadrant is not split, it gets the number of its upper left
mini-window. This is an example of a layout on Atem Mini Extreme:
+----+----+---------+
| 0 | 1 | 2 |
| 4 | 5 | |
+----+----+----+----+
| 8 | 10 | 11 |
| | 14 | 15 |
+---------+----+----+
On the non-Extreme Mini switchers, the window layout does not appear to be
configurable, and therefore the numbers are allocated on a contiguous
basis:
+----+----+---------+
| 0 | 1 |
+----+----+----+----+
| 2 | 3 | 4 | 5 |
+----+----+----+----+
| 6 | 7? | 8? | 9? |
+----+----+----+----+
Since the windows marked '?' are not configurable on non-Extreme Minis,
these numbers are just an educated guess.
Audio VU meters appear to be supported on small and big windows alike, but
only on those which show a video input or the Program output. The safe area
overlay appears to only work on full-sized Preview.
After parsing:
:ivar index: Multiviewer index, 0-indexed
:ivar window: Window number inside the multiview
:ivar source: Source index for this window
:ivar vu: True if VU meter overlays can be enabled
:ivar safearea: True if safe area overlays can be enabled
"""
CODE = "MvIn"
def __init__(self, raw):
self.raw = raw
self.index, self.window, self.source, self.vu, self.safearea = struct.unpack('>BBH??2x', raw)
def __repr__(self):
return '<multiviewer-input mv={} win={} source={}>'.format(self.index, self.window, self.source)
class MultiviewerVuField(FieldBase):
"""
Data from the `VuMC`. This describes if a multiview window has the VU meter overlay enabled.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 Multiviewer index, 0-indexed
1 1 u8 Window index 0-9
2 1 bool VU enabled
3 1 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: Multiviewer index, 0-indexed
:ivar window: Window number inside the multiview
:ivar enabled: True if the VU meter overlay is enabled for this window
"""
CODE = "VuMC"
def __init__(self, raw):
self.raw = raw
self.index, self.window, self.enabled = struct.unpack('>BB?x', raw)
def __repr__(self):
return '<multiviewer-vu mv={} win={} enabled={}>'.format(self.index, self.window, self.enabled)
class MultiviewerSafeAreaField(FieldBase):
"""
Data from the `SaMw`. This describes if a multiview window has the safe area overlay enabled. This is generally
only enabled on the preview window.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 1 u8 Multiviewer index, 0-indexed
1 1 u8 Window index 0-9
2 1 bool safe area enabled
3 1 ? unknown
====== ==== ====== ===========
After parsing:
:ivar index: Multiviewer index, 0-indexed
:ivar window: Window number inside the multiview
:ivar enabled: True if the safe area meter overlay is enabled for this window
"""
CODE = "SaMw"
def __init__(self, raw):
self.raw = raw
self.index, self.window, self.enabled = struct.unpack('>BB?x', raw)
def __repr__(self):
return '<multiviewer-safe-area mv={} win={} enabled={}>'.format(self.index, self.window, self.enabled)
class LockObtainedField(FieldBase):
"""
Data from the `LKOB`. This signals that a datastore lock has been successfully obtained for
a specific datastore index. Used for data transfers.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Store id
2 2 ? Unknown
====== ==== ====== ===========
After parsing:
:ivar store: Store index
= """
CODE = "LKOB"
def __init__(self, raw):
self.raw = raw
self.store, = struct.unpack('>H2x', raw)
def __repr__(self):
return '<lock-obtained store={}>'.format(self.store)
class LockStateField(FieldBase):
"""
Data from the `LKST`. This updates the state of the locks.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Store id
2 1 bool State
3 1 ? unknown
====== ==== ====== ===========
After parsing:
:ivar store: Store index
:ivar state: True if a lock is held
"""
CODE = "LKST"
def __init__(self, raw):
self.raw = raw
self.store, self.state, self.u1 = struct.unpack('>H?B', raw)
def __repr__(self):
state = 'locked' if self.state else 'unlocked'
return '<lock-state store={} state={}>'.format(self.store, state)
class FileTransferDataField(FieldBase):
"""
Data from the `FTDa`. This is an incoming chunk of data for a running file transfer.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Transfer id
2 2 u16 Data length
? ? bytes The rest of the packet contains [Data length] bytes of data
====== ==== ====== ===========
After parsing:
:ivar transfer: Transfer index
:ivar size: Length of the transfer chunk
:ivar data: Contents of the transfer chunk
"""
CODE = "FTDa"
def __init__(self, raw):
self.raw = raw
self.transfer, self.size = struct.unpack('>HH', raw[0:4])
self.data = raw[4:(4 + self.size)]
def __repr__(self):
return '<file-transfer-data transfer={} size={}>'.format(self.transfer, self.size)
class FileTransferErrorField(FieldBase):
"""
Data from the `FTDE`. Something went wrong with a file transfer and it has been aborted.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Transfer id
2 1 u8 Error code
3 1 ? unknown
====== ==== ====== ===========
========== ===========
Error code Description
========== ===========
1 try-again, Try the transfer again
2 not-found, The requested store/slot index doesn't contain data
5 no-lock, You didn't obtain the lock before doing the transfer
========== ===========
After parsing:
:ivar transfer: Transfer index
:ivar status: Status id from the enum above
"""
CODE = "FTDE"
def __init__(self, raw):
self.raw = raw
self.transfer, self.status = struct.unpack('>HBx', raw)
def __repr__(self):
errors = {
1: 'try-again',
2: 'not-found',
5: 'no-lock'
}
if self.status in errors:
status = errors[self.status]
else:
status = f'unknown ({self.status})'
return '<file-transfer-error transfer={} status={}>'.format(self.transfer, status)
class FileTransferDataCompleteField(FieldBase):
"""
Data from the `FTDC`. Sent after pushing a file.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Transfer id
2 1 u8 ? (always 1)
3 1 u8 ? (always 2 or 6)
====== ==== ====== ===========
After parsing:
:ivar transfer: Transfer index that has completed
"""
CODE = "FTDC"
def __init__(self, raw):
self.raw = raw
self.transfer, self.u1, self.u2 = struct.unpack('>HBB', raw)
def __repr__(self):
return '<file-transfer-complete transfer={} u1={} u2={}>'.format(self.transfer, self.u1, self.u2)
class FileTransferContinueDataField(FieldBase):
"""
Data from the `FTCD`. This is an field telling the client what chunk size to use to continue the upload
of data to the hardware.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 u16 Transfer id
2 4 ? unknown
6 2 u16 Chunk size
8 2 u16 Chunk count
10 2 ? unknown
====== ==== ====== ===========
After parsing:
:ivar transfer: Transfer index
:ivar size: Length of the transfer chunk
:ivar count: Contents of the transfer chunk
"""
CODE = "FTCD"
def __init__(self, raw):
self.raw = raw
self.transfer, self.size, self.count = struct.unpack('>H 4x HH 2x', raw)
def __repr__(self):
return '<file-transfer-continue transfer={} size={} count={}>'.format(self.transfer, self.size, self.count)
class MacroPropertiesField(FieldBase):
"""
Data from the `MPrp`. This is the metadata about a stored macro
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 2 u16 Macro slot index
2 1 bool is used
3 1 bool has invalid commands
4 2 u16 Name length
6 2 u16 Description length
8 ? char[] Name
? ? char[] Description
====== ==== ====== ===========
After parsing:
:ivar index: Macro slot index
:ivar is_used: Slot contains data
:ivar is_invalid: Slot contains invalid data
:ivar name: Name of the macro
:ivar description: Description of the macro
"""
CODE = "MPrp"
def __init__(self, raw):
self.raw = raw
field = struct.unpack_from('>H ?? H H', raw, 0)
self.index = field[0]
self.is_used = field[1]
self.is_invalid = field[2]
name_length = field[3]
desc_length = field[4]
self.name, self.description = struct.unpack_from('>{}s {}s'.format(name_length, desc_length), raw, 8)
def __repr__(self):
return '<macro-properties: index={} used={} name={}>'.format(self.index, self.is_used,
self.name)
class AudioMeterLevelsField(FieldBase):
"""
Data from the `AMLv`. This contains the realtime audio levels for the audio mixer
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 2 u16 Number of input channels
2 2 ? padding
4 4 u32 Master left level
8 4 u32 Master right level
12 4 u32 Master left peak
16 4 u32 Master right peak
20 4 u32 Monitor left level
24 4 u32 Monitor right level
28 4 u32 Monitor left peak
32 4 u32 Monitor right peak
? 4 u32 Input left level [These 4 repeat for the number of channels above]
? 4 u32 Input right level
? 4 u32 Input left peak
? 4 u32 Input right peak
====== ==== ====== ===========
After parsing:
The levels are tuples in the format (left level, right level, left peak, right peak).
:ivar count: Number of channels
:ivar master: Master levels
:ivar monitor: Monitor levels
:ivar input: All input levels as a dict, the key is the channel number and the value a level tuple
"""
CODE = "AMLv"
def __init__(self, raw):
self.raw = raw
field = struct.unpack_from('>H2x 4I 4I', raw, 0)
self.count = field[0]
self.master = (
self._level(field[1]),
self._level(field[2]),
self._level(field[3]),
self._level(field[4])
)
self.monitor = (
self._level(field[5]),
self._level(field[6]),
self._level(field[7]),
self._level(field[8])
)
self.input = {}
offset = struct.calcsize('>H2x 4I 4I')
sources = struct.unpack_from('>{}H'.format(self.count), raw, offset)
offset = int(math.ceil((offset + (2 * self.count)) / 4.0) * 4)
field = struct.unpack_from('>{}I'.format(self.count * 4), raw, offset)
for i in range(0, self.count * 4, 4):
level = (
self._level(field[i]),
self._level(field[i + 1]),
self._level(field[i + 2]),
self._level(field[i + 3])
)
self.input[sources[i // 4]] = level
def _level(self, value):
if value == 0:
return -60
val = math.log10(value / (128 * 65536)) * 20
return val
def __repr__(self):
return '<audio-meter-levels count={}>'.format(self.count)
class FairlightMeterLevelsField(FieldBase):
"""
Data from the `FMLv`. This contains the realtime audio levels for the fairlight audio mixer
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 6 ? Unknown
6 1 u8 is_split, 255 when split or 0 when it isn't
7 1 u8 subchannel index
8 2 u16 source index
10 2 i16 Input level left, -10000 to 0
12 2 i16 Input level right, -10000 to 0
14 2 i16 Input peak left, -10000 to 0
16 2 i16 Input peak right, -10000 to 0
18 2 i16 Expander gain reduction, -10000 to 0
20 2 i16 Compressor gain reduction, -10000 to 0
22 2 i16 Limiter gain reduction, -10000 to 0
24 2 i16 Output level left, -10000 to 0
26 2 i16 Output level right, -10000 to 0
28 2 i16 Output peak left, -10000 to 0
30 2 i16 Output peak right, -10000 to 0
32 2 i16 Fader level left, -10000 to 0
34 2 i16 Fader level right, -10000 to 0
36 2 i16 Fader peak left, -10000 to 0
38 2 i16 Fader peak right, -10000 to 0
====== ==== ====== ===========
After parsing:
:ivar index: Channel source index
:ivar is_split: Stereo channel is split into dual mono
:ivar subchannel: Channel index after splitting
:ivar strip_id: Strip identifier in {source}.{subchannel} format
:ivar input: Volume level before dynamics
:ivar output: Volume level after dynamics
:ivar level: Volume level after fader
:ivar expander_gr: Gain reduction by the expander
:ivar compressor_gr: Gain reduction by the compressor
:ivar limiter_gr: Gain reduction by the limiter
"""
CODE = "FMLv"
COEFF = 10 ** (40 / 20)
def __init__(self, raw):
self.raw = raw
field = struct.unpack_from('>6xBBH 15h', raw, 0)
self.index = field[2]
self.is_split = field[0]
self.subchannel = field[1]
if self.is_split == 0xff:
self.strip_id = f"{self.index}.{self.subchannel}"
else:
self.strip_id = f"{self.index}.0"
self.input = (
self._level(field[3]),
self._level(field[4]),
self._level(field[5]),
self._level(field[6])
)
self.expander_gr = self._level(field[7])
self.compressor_gr = self._level(field[8])
self.limiter_gr = self._level(field[9])
self.output = (
self._level(field[10]),
self._level(field[11]),
self._level(field[12]),
self._level(field[13])
)
self.level = (
self._level(field[14]),
self._level(field[15]),
self._level(field[16]),
self._level(field[17])
)
def _level(self, value):
if value == 0:
return 0
value += 10000
value /= 10000
if value == 0:
return -60
val = (math.exp((math.log(self.COEFF + 1) * value)) - 1) / self.COEFF
val = val * 60 - 60
return val
def __repr__(self):
return '<fairlight-meter-levels source={}>'.format(self.strip_id)
class FairlightMasterLevelsField(FieldBase):
"""
Data from the `FDLv`. This contains the realtime audio levels for the master channel of the fairlight mixer
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 2 i16 Input level left, -10000 to 0
2 2 i16 Input level right, -10000 to 0
4 2 i16 Input peak left, -10000 to 0
6 2 i16 Input peak right, -10000 to 0
8 2 i16 Compressor gain reduction, -10000 to 0
10 2 i16 Limiter gain reduction, -10000 to 0
12 2 i16 Output level left, -10000 to 0
14 2 i16 Output level right, -10000 to 0
16 2 i16 Output peak left, -10000 to 0
18 2 i16 Output peak right, -10000 to 0
20 2 i16 Fader level left, -10000 to 0
22 2 i16 Fader level right, -10000 to 0
24 2 i16 Fader peak left, -10000 to 0
26 2 i16 Fader peak right, -10000 to 0
====== ==== ====== ===========
After parsing:
:ivar input: Volume level before dynamics
:ivar output: Volume level after dynamics
:ivar level: Volume level after fader
:ivar compressor_gr: Gain reduction by the compressor
:ivar limiter_gr: Gain reduction by the limiter
"""
CODE = "FDLv"
COEFF = 10 ** (40 / 20)
def __init__(self, raw):
self.raw = raw
field = struct.unpack_from('>14h', raw, 0)
self.input = (
self._level(field[0]),
self._level(field[1]),
self._level(field[2]),
self._level(field[3])
)
self.compressor_gr = self._level(field[4])
self.limiter_gr = self._level(field[5])
self.output = (
self._level(field[6]),
self._level(field[7]),
self._level(field[8]),
self._level(field[9])
)
self.level = (
self._level(field[10]),
self._level(field[11]),
self._level(field[12]),
self._level(field[13])
)
def _level(self, value):
if value == 0:
return 0
value += 10000
value /= 10000
if value == 0:
return -60
val = (math.exp((math.log(self.COEFF + 1) * value)) - 1) / self.COEFF
val = val * 60 - 60
return val
def __repr__(self):
return '<fairlight-master-levels>'
class CameraControlDataPacketFieldDisabled(FieldBase):
"""
!! This parser is not production ready !!
The packet length is somewhat inconsistent which can cause the TCP protocol to fail due to the alignment in the
protocol breaking
Data from the `CCdP`. This contains a single packet for the remote shading unit in the blackmagic cameras. This
protocol seems to roughly match up to the official BMD SDI camera control documentation with the bytes packed
differently.
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 u8 Destination, 255 = broadcast to all
1 1 u8 Category
2 1 u8 Parameter
3 1 u8 Data type
4 12 ? padding
16 8 ? variable data, absent for commands.
====== ==== ====== ===========
========== ===========
Data type Description
========== ===========
0 Boolean, or no data
1 Signed byte
2 Signed short
3 Signed integer
4 Signed long
5 UTF-8 data
128 16-bit Fixed point
========== ===========
========== ======== ======== ===========
Command DataType Elements Description
========== ======== ======== ===========
0.0 fixed16 1 Focus 0=near 1=far
0.1 - 0 Trigger autofocus
0.2 fixed16 1 Aperture f-stop
0.3 fixed16 1 Aperture normalized 0=closed 1=open
0.4 fixed16 1 Aperture by index 0...n
0.5 - 0 Trigger auto aperture
0.6 boolean 1 Enable optical image stabilisation
0.7 int16 1 Zoom, focal length in mm
0.8 fixed16 1 Zoom, normalized 0.0...1.0
0.9 fixed16 1 Zoom, rate -1.0...1.0
1.0 int8 5 Frame rate, M-rate, dimensions, interlaced, colorpsace
1.1 int8 1 Gain, absolute iso as ISO/100
1.2 int16 2 White balance, temperature 2500...10000, tint -50...50
1.3 - 0 Trigger auto whitebalance
1.4 - 0 Restore previous auto whitebalance
1.5 int32 1 Exposure time in us
1.6 int16 1 Exposure by index 0...n
1.7 int8 1 Dynamic range mode, 0=film 1=video
1.8 int8 1 Sharpening level, 0=off, 1=low, 2=medium, 3=high
1.9 int16 1 Recording format
1.10 int8 1 Auto exposure mode, 0=manual trigger, 1=iris, 2=shutter, 3=iris+shutter, 4=shutter+iris
1.11 int32 1 Shutter angle in degrees*100 100...36000
1.12 int32 1 Shutter speed in 1/n, 24...2000
1.13 int8 1 Gain in dB, -128...127
1.14 int32 1 Gain in iso value
2.0 fixed16 1 Mic level 0.0...1.0
2.1 fixed16 1 Headphone level 0.0...1.0
2.2 fixed16 1 Headphone program mix 0.0...1.0
2.3 fixed16 1 Speaker level 0.0...1.0
2.4 int8 1 Input type, 0=internal mic, 1=line in, 2=low gain mic in, 3=high gain mic in
2.5 fixed16 2 Input levels, one element per channel. 0.0...1.0
2.6 boolean 1 Phantom power enabled
3.0 uint16 1 Enable overlays, undocumented bitfield
3.1 int8 1 Frame guide style, enum
3.2 fixed16 1 Frame guide opacity
3.3 int8 4 Overlay settings
4.0 fixed16 1 Display brightness 0.0...1.0
4.1 uint16 1 Display overlay enable, undocumented
4.2 fixed16 1 Display zebra level, 0.0...1.0
4.3 fixed16 1 Display peaking levle, 0.0...1.0
4.4 int8 1 Enable bars with timeout, 0=disable, 1...30=seconds
4.5 int8 2 Display focus assist, first element is method and second element is color
5.0 fixed16 1 Tally brightness, 0.0...1.0
5.1 fixed16 1 Tally front brightness, 0.0...1.0
5.2 fixed16 1 Tally rear brightness, 0.0...1.0
6.0 int8 1 Reference source, 0=internal, 1=program, 2=external
6.1 int32 1 Reference offset in pixels
7.0 int32 2 Real time clock value
7.1 utf8 1 System language
7.2 int32 1 Timezone offset, minute from UTC
7.3 int64 2 Location, latitude and longitude
8.0 fixed16 4 Primary color corrector lift, RGBY
8.1 fixed16 4 Primary color corrector gamma, RGBY
8.2 fixed16 4 Primary color corrector gain, RGBY
8.3 fixed16 4 Primary color corrector offset, RGBY
8.4 fixed16 2 Contrast, pivot 0.0..1.0, adjustment 0.0...2.0
8.5 fixed16 1 Luma mix, 0.0...1.0
8.6 fixed16 2 Color adjust, hue -1.0...1.0, saturation 0.0...2.0
8.7 - 0 Reset color corrector to defaults
10.0 int8 2 Codec enum
10.1 int8 4 Transport mode
11.0 fixed16 2 PTZ Control, pan velocity -1.0...1.0, tilt velocity -1.0...1.0
11.1 int8 2 PTZ memory preset. command 0=reset, 1=store, 2=recall. Slot ID 0...5
========== ===========
After parsing:
:ivar destination: Command destination address
:ivar category: First number of the command
:ivar parameter: Second number of the command
:ivar datatype: Data type
:ivar data: Data attached to the command
"""
CODE = "CCdP"
def __init__(self, raw):
self.raw = raw
self.destination, self.category, self.parameter, self.datatype, *weird = struct.unpack_from('>4B 4B 4B', raw, 0)
num_elements = sum(weird)
num_overrides = {
(0, 0): 1,
(0, 1): 0,
(0, 2): 1,
(0, 3): 1.,
(0, 4): 1,
(0, 6): 1,
(1, 2): 2
}
if (self.category, self.parameter) in num_overrides:
num_elements = num_overrides[(self.category, self.parameter)]
self.length = num_elements
self.data = None
if len(raw) > 16:
dfmt = '>'
if self.datatype == 0: # Boolean
dfmt += '?' * num_elements
elif self.datatype == 1: # Signed byte
dfmt += 'b' * num_elements
elif self.datatype == 2: # Signed short
dfmt += 'h' * num_elements
elif self.datatype == 3: # Signed int
dfmt += 'i' * num_elements
elif self.datatype == 4: # Signed long
dfmt += 'q' * num_elements
elif self.datatype == 5: # UTF-8
pass
elif self.datatype == 128: # Fixed 16
dfmt += 'h' * num_elements
self.data = struct.unpack_from(dfmt, raw, 16)
if self.datatype == 128:
self.data = self.unpack_fixed16(self.data)
def unpack_fixed16(self, raw):
result = []
for f16 in raw:
result.append(f16 / (2 ** 11))
return result
def __repr__(self):
return '<camera-control-data-packet dest={} command={}.{} type={} data={}>'.format(self.destination,
self.category,
self.parameter,
self.datatype,
self.data)
class StreamingAudioBitrateField(FieldBase):
"""
Data from the `STAB`. This is the audio bitrate for the internal encoder used for recording and streaming
This is always 128k for min and max on tested devices.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 4 u32 Min bitrate
4 4 u32 Max bitrate
====== ==== ====== ===========
"""
CODE = "STAB"
def __init__(self, raw):
self.raw = raw
self.min, self.max = struct.unpack('>II', raw)
def __repr__(self):
return '<streaming-audio-bitrate min={} max={}>'.format(self.min, self.max)
class StreamingServiceField(FieldBase):
"""
Data from the `SRSU`. This the settings for the live stream output, it also sets the video bitrate for
the internal encoder which is shared with the recorder component so this influences recording quality.
The ATEM Software Control application only uses the rtsp URL to display the streaming service name and
has a preset list of rtsp urls for various streaming services.
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 64 char[] Service display name
65 512 char[] Target rtsp url
557 512 char[] Stream key/secret
1089 4 u32 Video bitrate minimum
1093 4 u32 Video bitrate maximum
====== ==== ====== ===========
"""
CODE = "SRSU"
def __init__(self, raw):
self.raw = raw
field = struct.unpack_from('>64s512s512sII', raw, 0)
self.name = self._get_string(field[0])
self.url = self._get_string(field[1])
self.key = self._get_string(field[2])
self.min = field[3]
self.max = field[4]
def __repr__(self):
return '<streaming-service {} url={} min={} max={}>'.format(self.name, self.url, self.min,
self.max)
class StreamingStatusField(FieldBase):
"""
Data from the `StRS`. The displayed status of the live stream
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 2 i16 Status
2 2 ? unknown
====== ==== ====== ===========
====== =====
Status Value
====== =====
-1 unknown
0 nothing?
1 idle
2 connecting
4 on-air
22 stopping
36 stopping
====== =====
"""
CODE = "StRS"
def __init__(self, raw):
self.raw = raw
self.status, = struct.unpack('>h 2x', raw)
def __repr__(self):
return '<streaming-status status={}>'.format(self.status)
class StreamingStatsField(FieldBase):
"""
Data from the `SRSS`. The displayed status of the live stream
====== ==== ====== ===========
Offset Size Type Descriptions
====== ==== ====== ===========
0 4 u32 Bitrate
4 2 u16 Cache used
====== ==== ====== ===========
"""
CODE = "SRSS"
def __init__(self, raw):
self.raw = raw
self.bitrate, self.cache = struct.unpack('>IHxx', raw)
def __repr__(self):
return '<streaming-stats bitrate={} cache={}>'.format(self.bitrate, self.cache)
class AutoInputVideoModeField(FieldBase):
"""
Data from the `AiVM`. This field only exists for hardware that can auto-detect a video mode from the input signal.
This defines wether the auto detection is enabled and shows if it has actually detected a signal
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 1 bool Enabled
1 1 bool Detected
2 2 ? unknown
====== ==== ====== ===========
After parsing:
:ivar enabled: Auto mode detection is enabled
:ivar detected: A video mode has been detected from an input
"""
CODE = "AiVM"
def __init__(self, raw):
self.raw = raw
self.enabled, self.detected = struct.unpack('>??2x', raw)
def __repr__(self):
return '<auto-input-video-mode: enabled={} detected={}>'.format(self.enabled, self.detected)
class InitCompleteField(FieldBase):
"""
Data from the `InCm`. This notifies the app that all the initial state has been sent
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 4 ? unknown
====== ==== ====== ===========
"""
CODE = "InCm"
def __init__(self, raw):
self.raw = raw
def __repr__(self):
return '<init-complete>'
class TransferCompleteField(FieldBase):
"""
Data from the `*XFC`. This is an command that's part of OpenSwitcher for the TCP protocol and not part
of the actual ATEM protocol. This command is send over the TCP connection when the upstream atem has completed
a file transfer
====== ==== ====== ===========
Offset Size Type Description
====== ==== ====== ===========
0 2 u16 Store
2 2 u16 Slot
4 1 bool Is upload
5 3 x padding
====== ==== ====== ===========
After parsing:
:ivar store: Transfer store index
:ivar slot: Transfer slot index
:ivar upload: True if the transfer was an upload, False if the transfer was a download
"""
CODE = "*XFC"
def __init__(self, raw):
self.raw = raw
self.store, self.slot, self.upload = struct.unpack('>HH ?xxx', raw)
def __repr__(self):
return '<*transfer-complete: store={} slot={} upload={}>'.format(self.store, self.slot, self.upload)
| seanmichnowski/CalvaryVenturaBroadcast | docs/AtemStatuses.py | AtemStatuses.py | py | 108,948 | python | en | code | 1 | github-code | 36 |
23565614159 | #!/usr/bin/python3
import sys
import pyvips
im = pyvips.Image.new_from_file(sys.argv[1], access="sequential")
text = pyvips.Image.text(f"<span color=\"red\">{sys.argv[3]}</span>",
width=500,
dpi=100,
align="centre",
rgba=True)
# scale the alpha down to make the text semi-transparent
text = (text * [1, 1, 1, 0.3]).cast("uchar")
text = text.rotate(45)
# tile to the size of the image page, then tile again to the full image size
text = text.embed(10, 10, text.width + 20, text.width + 20)
page_height = im.get_page_height()
text = text.replicate(1 + im.width / text.width, 1 + page_height / text.height)
text = text.crop(0, 0, im.width, page_height)
text = text.replicate(1, 1 + im.height / text.height)
text = text.crop(0, 0, im.width, im.height)
# composite the two layers
im = im.composite(text, "over")
im.write_to_file(sys.argv[2])
| libvips/pyvips | examples/watermark.py | watermark.py | py | 945 | python | en | code | 558 | github-code | 36 |
8024534491 | """
Given a 2D board and a word, find if the word exists in the grid.
The word can be constructed from letters of sequentially adjacent cell, where "adjacent" cells are those horizontally or vertically neighboring. The same letter cell may not be used more than once.
For example,
Given
```
board = [ ["ABCE"],
["SFCS"],
["ADEE"]
]
```
word = "ABCCED", -> returns true,
word = "SEE", -> returns true,
word = "ABCB", -> returns false.
"""
class Solution:
# @param board, a list of lists of 1 length string
# @param word, a string
# @return a boolean
def exist(self, board, word):
M = len(board)
N = len(board[0])
for i in range(M):
for j in range(N):
if board[i][j] == word[0] and self.isWord(board, i, j, 0, word):
return True
return False
def isWord(self, board, i, j, index, word):
if index == len(word):
return True
M = len(board)
N = len(board[0])
if i < 0 or i >= M or j < 0 or j >= N or board[i][j] != word[index]:
return False
board[i][j] = '#'
if self.isWord(board, i+1, j, index+1, word) or \
self.isWord(board, i-1, j, index+1, word) or \
self.isWord(board, i, j+1, index+1, word) or \
self.isWord(board, i, j-1, index+1, word):
return True
board[i][j] = word[index]
return False
# Note:
# 1. Keep in mind the declare of matrix, M, N, board, board[0]
# 2. Line 28 check board[i][j] == word[0]
# 3. Use in place make board[i][j] = '#' and recover later
# 4. Line 43 line break use \
# 5. Very important, must remark the 'visisted' part
| cyandterry/Python-Study | Ninja/Leetcode/79_Word_Search.py | 79_Word_Search.py | py | 1,760 | python | en | code | 62 | github-code | 36 |
20336422398 | # -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.6.2)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
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def qInitResources():
QtCore.qRegisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data)
qInitResources()
| NIRVANALAN/TU_rcm | resources.py | resources.py | py | 612,926 | python | ja | code | 2 | github-code | 36 |
35478168713 | #!/usr/bin/env python3
# -*- coding: UTF-8 -*-
import argparse
import codecs
import sys
import openapc_toolkit as oat
ARG_HELP_STRINGS = {
"csv_file": "The csv file where rows should be reordered",
"column": "The numerical index of the column to be used as sorting key",
"encoding": "The encoding of the CSV file. Setting this argument will " +
"disable automatic guessing of encoding.",
"quotemask": "A quotemask to apply to the result file after the action " +
"has been performed. A quotemask is a string consisting " +
"only of the letters 't' and 'f' (true/false) and has " +
"the same length as there are columns in the (resulting) " +
"csv file. Only the columns where the index is 't' will be " +
"quoted.",
"openapc_quote_rules": "Determines if the special openapc quote rules " +
"should be applied, meaning that the keywords " +
"NA, TRUE and FALSE will never be quoted. If in " +
"conflict with a quotemask, openapc_quote_rules " +
"will take precedence.",
"other_csv_file": "An optional second csv file. If given, the rows in " +
"the first file will not be sorted alphabetically. " +
"Instead, they will be rearranged so that the values in " +
"the denoted column mirror their order " +
"of occurence in the given column of the second file " +
"(this will obviously only make sense if the columns " +
"have common values and the values represent some sort " +
"of key). Rows with a column value not occuring in the " +
"second file will be appended to the end of the " +
"output file in original order.",
"other_column": "The numerical index of the column to use in the second " +
"file. If omitted, the same index as in the first file " +
"is used.",
"other_encoding": "The optional encoding of the second CSV file.",
"ignore_case": "Ignore case when comparing values for reordering between two files"
}
def main():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", help=ARG_HELP_STRINGS["csv_file"])
parser.add_argument("column", type=int, help=ARG_HELP_STRINGS["column"])
parser.add_argument("other_csv_file", nargs="?", help=ARG_HELP_STRINGS["other_csv_file"])
parser.add_argument("other_column", type=int, nargs="?", help=ARG_HELP_STRINGS["other_column"])
parser.add_argument("-e2", "--other_encoding", help=ARG_HELP_STRINGS["other_encoding"])
parser.add_argument("-e", "--encoding", help=ARG_HELP_STRINGS["encoding"])
parser.add_argument("-i", "--ignore_case", action="store_true", default=False,
help=ARG_HELP_STRINGS["ignore_case"])
parser.add_argument("-q", "--quotemask", help=ARG_HELP_STRINGS["quotemask"])
parser.add_argument("-o", "--openapc_quote_rules",
help=ARG_HELP_STRINGS["openapc_quote_rules"],
action="store_true", default=False)
args = parser.parse_args()
quote_rules = args.openapc_quote_rules
encs = [] #CSV file encodings
for encoding in [args.encoding, args.other_encoding]:
if encoding:
try:
codec = codecs.lookup(encoding)
msg = "Encoding '{}' found in Python's codec collection as '{}'"
print(msg.format(encoding, codec.name))
except LookupError:
print("Error: '" + encoding + "' not found Python's " +
"codec collection. Either look for a valid name here " +
"(https://docs.python.org/2/library/codecs.html#standard-" +
"encodings) or omit this argument to enable automated " +
"guessing.")
sys.exit()
encs.append(encoding)
mask = None
if args.quotemask:
reduced = args.quotemask.replace("f", "").replace("t", "")
if reduced:
print("Error: A quotemask may only contain the letters 't' and 'f'!")
sys.exit()
mask = [True if x == "t" else False for x in args.quotemask]
header, content = oat.get_csv_file_content(args.csv_file, enc=encs[0])
column = args.column
if not args.other_csv_file:
rearranged_content = header + sorted(content, key=lambda x: x[column])
else:
rearranged_content = []
_, second_content = oat.get_csv_file_content(args.other_csv_file, enc=encs[1])
other_column = column # default: use same column index as in first file
if args.other_column:
other_column = args.other_column
for other_row in second_content:
if args.ignore_case:
matching_rows = [row for row in content if row[column].lower() == other_row[other_column].lower()]
else:
matching_rows = [row for row in content if row[column] == other_row[other_column]]
rearranged_content += matching_rows
for matching_row in matching_rows:
content.remove(matching_row)
unmatched_msg = ("{} rows could not be rearranged (unmatched in second csv file) " +
"and were appended to the end of the result file " +
"in original order.")
if content:
oat.print_y(unmatched_msg.format(len(content)))
else:
oat.print_g("All rows matched.")
rearranged_content = header + rearranged_content + content # append any unmatched rows
with open('out.csv', 'w') as out:
writer = oat.OpenAPCUnicodeWriter(out, mask, quote_rules, False)
writer.write_rows(rearranged_content)
if __name__ == '__main__':
main()
| OpenAPC/openapc-de | python/csv_row_reorder.py | csv_row_reorder.py | py | 6,006 | python | en | code | 114 | github-code | 36 |
5029822148 | """
Tuplas- Diferença entre elas e listas é q elas não são modificaveis
"""
t1 = 1, 3, 4, 5
t2 = 2, 5, 7527, 27, 5
t3 = t1 + t2
print(type(t1))
print(type(t2))
print(t3)
t1 = list(t1)
t1[2] = 2
t1 = tuple(t1)
print(t1, type(t1)) | hdtorrad/Estudos-Python3 | Aulas & Desafios/Aula020-Tuplas e dicionarios/Tuplas.py | Tuplas.py | py | 235 | python | pt | code | 1 | github-code | 36 |
24770123438 | #!/usr/bin/python3
import requests # pip3 install requests
import sys
from lxml import etree # pip3 install lxml
import re
class Item:
category = ''
detName = ''
detDesc = ''
link = ''
def __init__(self, category, detName, detDesc, link):
self.category = category
self.detName = detName
self.detDesc = detDesc
self.link = link
def parseHtmlForItems(html):
items = []
trs = html.xpath('//table[@id="searchResult"]/tr')
for tr in trs:
cInfo = tr.xpath('./td[@class="vertTh"]/center/a/text()')
cStr = _paresCategoryInfo(cInfo)
if cStr != None:
detName = tr.xpath('.//a[@class="detLink"]/text()')[0].strip()
detDescTailNode = tr.xpath('.//font[@class="detDesc"]/a/text()')
detDescTail = ""
if len(detDescTailNode) > 0:
detDescTail = detDescTailNode[0]
detDesc = (tr.xpath('.//font[@class="detDesc"]/text()')[0] + detDescTail).strip()
link = tr.xpath('.//a[@title="Download this torrent using magnet"]/@href')[0].strip()
items.append(Item(cStr, detName, detDesc, link))
return items
def _paresCategoryInfo(categoryInfo):
if len(categoryInfo) != 2:
return None
return "{0}({1})".format(categoryInfo[0].strip(), categoryInfo[1].strip())
def showItems(items):
for i, item in enumerate(items):
print(i, item.category, item.detName, item.detDesc, sep=" | ")
def showItem(items, i):
if (i < 0) | (i >= len(items)):
print("无指定条目!")
return
item = items[i]
print(i, item.category, item.detName, item.detDesc, sep=" | ", end=" :\n")
print(item.link)
class Searcher:
searchName = ''
pageNum = 1
orderBy = 99
category = "0"
categoryStr = "All"
categoryNode = None
begin = 0
end = 0
totle = 0
count = 0
items = []
def search(self):
if (self.searchName == "") | (self.searchName.isspace()):
return
# 搜索
url = "https://thepiratebay10.org/search/{0}/{1}/{2}/{3}".format(self.searchName, self.pageNum, self.orderBy, self.category)
resp = requests.get(url)
if resp.status_code != 200:
print("网络请求出错, 请检查网络或访问的地址!!")
sys.exit(1)
resp.encoding = "utf-8"
html = etree.HTML(resp.text)
# 设置page信息
countInfo = html.xpath('//body/h2[1]/text()')[0].strip()
self._parseCountInfo(countInfo)
# 设置categoryNode
categoryNodes = html.xpath('//select[@id="category"]')
if len(categoryNodes) > 0:
self.categoryNode = categoryNodes[0]
else:
self.categoryNode = None
# 设置items
self.items = parseHtmlForItems(html)
def _parseCountInfo(self, countInfo):
matchObj = re.match(r"Displaying hits from (\d+) to (\d+) \(approx (\d+) found\)", countInfo, re.I)
if matchObj != None:
self.begin = int(matchObj.group(1))
self.end = int(matchObj.group(2))
self.totle = int(matchObj.group(3))
self.count = (self.totle + 29) // 30
else:
self.begin = 0
self.end = 0
self.totle = 0
self.count = 0
def setupCategory(self):
buf = {"0": "All"}
gBuf = {}
print("0 : All")
if self.categoryNode != None:
optgroups = self.categoryNode.xpath('./optgroup')
for optgroup in optgroups:
gCode = optgroup.xpath('./option[1]/@value')[0][:1] + "00"
gDesc = optgroup.xpath('./@label')[0]
print("[ {0} : {1} ]:".format(gCode, gDesc))
gBuf[gCode] = gDesc
opts = optgroup.xpath('./option')
for opt in opts:
code = opt.xpath('./@value')[0]
desc = opt.xpath('./text()')[0].strip()
buf[code] = desc
print("{0} : {1}".format(code, desc))
print("当前类型: {0}({1})".format(self.category, self.categoryStr))
while True:
inputStr = input("请输出类别编码(可以使用','分隔以同时输入多个组编码; 输入'q'将取消设置): ").strip()
if "q" == inputStr:
return
elif inputStr in buf:
self.category = inputStr
self.categoryStr = buf[inputStr]
return
else:
gCodes = inputStr.split(",")
cs = self._getCategoryStrByGCodes(gBuf, gCodes)
if cs != None:
self.category = inputStr
self.categoryStr = cs
return
else:
print("输入有误!")
def _getCategoryStrByGCodes(self, gBuf, gCodes):
gDescs = []
for gc in gCodes:
if gc in gBuf:
gDescs.append(gBuf[gc])
else:
return None
return ",".join(gDescs)
def showMeta(self):
print("类别: {0}, 搜索: {1}, 页码: {2}, 总条数: {3}, 总页数: {4}, 显示条码: [{5},{6})".format(
self.categoryStr, self.searchName, self.pageNum, self.totle, self.count, self.begin, self.end))
def searchAndShow(self):
self.search()
showItems(self.items)
self.showMeta()
def setPageNum(self, pageNum):
if pageNum < 1:
pageNum = 1
elif pageNum > self.count:
if self.count == 0:
pageNum = 1
else:
pageNum = self.count
self.pageNum = pageNum
class TopCategory:
title = ""
url = ""
ended = False
def __init__(self, title, url, ended = False):
self.title = title
self.url = url
self.ended = ended
class Toper:
categories = []
index = 0
items = []
def __init__(self):
url = "https://thepiratebay10.org/top"
resp = requests.get(url)
if resp.status_code != 200:
print("网络请求出错, 请检查网络或访问的地址!!")
sys.exit(1)
resp.encoding = "utf-8"
html = etree.HTML(resp.text)
nodes = html.xpath('//table[@id="categoriesTable"]/tr/td/dl/*')
for node in nodes:
if node.tag == "dt":
title = node.xpath('./a[1]/text()')[0].strip()
url = node.xpath('./a[1]/@href')[0]
self.categories.append(TopCategory("[ {0} ] ".format(title), "https://thepiratebay10.org"+url))
title2 = "[ {0}({1}) ]".format(title, node.xpath('./a[2]/text()')[0].strip())
url2 = node.xpath('./a[2]/@href')[0]
self.categories.append(TopCategory(title2, "https://thepiratebay10.org"+url2, True))
elif node.tag == "dd":
subNodes = node.xpath('.//a')
for subNode in subNodes:
title = subNode.xpath('./text()')[0].strip()
url = subNode.xpath('./@href')[0]
self.categories.append(TopCategory(title, "https://thepiratebay10.org"+url))
self.categories[-1].ended = True
def showCategories(self):
for i, v in enumerate(self.categories):
print(i , v.title, sep=":", end=" ")
if v.ended:
print()
def setCategoryIndex(self, index):
if (index < 0) | (index >= len(self.categories)):
return False
else:
self.index = index
return True
def getTop(self):
url = self.categories[self.index].url
resp = requests.get(url)
resp.encoding = "utf-8"
html = etree.HTML(resp.text)
# 设置items
self.items = parseHtmlForItems(html)
def getAndShow(self):
self.getTop()
showItems(self.items)
def runSearcher(searcher):
inputStr = input("请输入搜索关键词(输出空白字符将退出): ").strip()
if inputStr == "":
return
searcher.searchName = inputStr
searcher.searchAndShow()
while True:
ops = input("i <item> 查看指定条目详情; g <page> 跳转到指定页码; p 上一页; n 下一页; s <keyword> 搜索指定关键词; r 刷新; c 设置查询类型; q 退出;\n")
op = ops[:1]
arg = ops[1:].strip()
if op == "i":
showItem(searcher.items, (int(arg)))
elif op == "g":
searcher.setPageNum(int(arg))
searcher.searchAndShow()
elif op == "p":
searcher.setPageNum(searcher.pageNum - 1)
searcher.searchAndShow()
elif op == "n":
searcher.setPageNum(searcher.pageNum + 1)
searcher.searchAndShow()
elif op == "s":
if arg == "":
print("输入有误(不允许为空)!")
else:
searcher.searchName = arg
searcher.pageNum = 1
searcher.searchAndShow()
elif op == "r":
searcher.searchAndShow()
elif op == "c":
searcher.setupCategory()
elif op == "q":
return
def runToper(toper):
toper.showCategories()
while True:
inputStr = input("请输入类别编号[0, {0})(输入'q'将退出): ".format(len(toper.categories))).strip()
if inputStr == "q":
return
index = int(inputStr)
flag = toper.setCategoryIndex(index)
if flag:
toper.getAndShow()
break
else:
print("输入有误!")
while True:
ops = input("i <item> 查看指定条目详情; g <no> 查询指定类别编号的热门条目; r 刷新; c 查看类别目录; q 退出;\n")
op = ops[:1]
arg = ops[1:].strip()
if op == "i":
showItem(toper.items, int(arg))
elif op == "g":
flag = toper.setCategoryIndex(int(arg))
if flag:
toper.getAndShow()
else:
print("输入有误!")
elif op == "r":
toper.getAndShow()
elif op == "c":
toper.showCategories()
elif op == "q":
return
if __name__ == "__main__":
searcher = None
toper = None
while True:
m = input("请输入模式('s'(搜索), 't'(热门))(输入'q'将退出): ").strip()
if m == "q":
break
elif m == "s":
if searcher == None:
searcher = Searcher()
runSearcher(searcher)
elif m == "t":
if toper == None:
toper = Toper()
runToper(toper)
| echcz/sak | piratebay-cli.py | piratebay-cli.py | py | 10,776 | python | en | code | 2 | github-code | 36 |
34087877175 | data = [int(x) for x in open('input.txt').read().split(',')]
jump = {1:4, 2:4, 3:2, 4:2}
i = 0
while data[i] != 99:
opcode = '{:0>4}'.format(data[i])
op = int(opcode[2:])
if op == 1:
v1 = (data[data[i+1]] if int(opcode[1]) == 0 else data[i+1])
v2 = (data[data[i+2]] if int(opcode[0]) == 0 else data[i+2])
data[data[i+3]] = v1 + v2
elif op == 2:
v1 = data[data[i+1]] if int(opcode[1]) == 0 else data[i+1]
v2 = data[data[i+2]] if int(opcode[0]) == 0 else data[i+2]
data[data[i+3]] = v1 * v2
elif op == 3:
j = int(input('Please enter code '))
data[data[i+1]] = j
elif op == 4:
v1 = data[data[i+1]] if int(opcode[1]) == 0 else data[i+1]
if v1 != 0: print('Output: ', v1)
if op < 3:
i += 4
else:
i += 2
print('Finished')
| ajclarkin/AdventofCode2019 | day05/opcode.py | opcode.py | py | 848 | python | en | code | 2 | github-code | 36 |
74297991462 | from collections import defaultdict
from itertools import product, chain
class Rule:
def __init__(self, registry):
self.registry = registry
self.or_rules = []
self._generated = None
def __iter__(self):
for r in self.value:
yield r
def parse_rule(self, rule):
self.raw_rule = rule
for or_def in rule.split(" | "):
or_rule = []
for dependency in or_def.split(" "):
if dependency in '"a""b"':
or_rule.append([dependency[1]])
continue
or_rule.append(self.registry[dependency])
self.or_rules.append(or_rule)
@property
def value(self):
if not self._generated:
for idx, rules in enumerate(self.or_rules):
for i, rule in enumerate(rules):
if isinstance(rule, Rule):
rules[i] = rule.value
self.or_rules[idx] = ["".join(comb) for comb in product(*rules)]
self._generated = list(chain(*self.or_rules))
return self._generated
def parse_input(lines):
messages = []
rules = defaultdict(lambda: Rule(rules))
for line in lines:
if not line:
continue
if ':' in line:
index, rule = line.split(': ')
rules[index].parse_rule(rule)
else:
messages.append(line)
return rules, messages
def solve1(puzzle_input):
rules, messages = parse_input(puzzle_input)
valid_counter = 0
for message in messages:
if message in rules["0"].value:
valid_counter += 1
return valid_counter
def solve2(puzzle_input):
rules, messages = parse_input(puzzle_input)
valid_messages = 0
invalid_message = []
for message in messages:
if message in rules["0"].value:
valid_messages += 1
else:
invalid_message.append(message)
# I'm not smart enough for this (yet ;)) So imma just hack it.
def find_start(message):
for start in rules["8"].value:
if message.startswith(start):
return message[len(start):]
def find_end(message):
for start in rules["42"].value:
for end in rules["31"].value:
if message.startswith(start) and message.endswith(end):
return message[len(start): -len(end)]
msgs = 0
for message in invalid_message:
candidates = []
while message:
message = find_start(message)
if message:
candidates.append(message)
for message in candidates:
while message:
message = find_end(message)
if message == '':
msgs += 1
return valid_messages + msgs
| maarten-dp/adventofcode2020 | solvers/day19.py | day19.py | py | 2,835 | python | en | code | 2 | github-code | 36 |
72225859944 | #!/usr/bin/python3
"""Tests for 'State' class that inherits from 'BaseModel'
with unittest module"""
import unittest
import models
from models.base_model import BaseModel
from models.state import State
class TestUser(unittest.TestCase):
"""Testing our methods of 'BaseModel' for 'State'"""
def test_doc_module(self):
"""Testing all class documentation"""
self.assertTrue(models.state.__doc__)
self.assertTrue(State.__doc__)
def test_is_instance(self):
"""Creating an instance of 'State'"""
Model = State()
self.assertIsInstance(Model, State)
def test_id(self):
"""Testing if there is a different id (uuid4)"""
instance_0 = State()
instance_1 = State()
self.assertNotEqual(instance_0, instance_1)
def test_str(self):
"""Testing the '__str__' method"""
Model = State()
str = f"[{Model.__class__.__name__}] ({Model.id}) {Model.__dict__}"
str2 = Model.__str__()
self.assertEqual(str, str2)
def test_type_objects_State(self):
"""Testing the 'State' public attributes"""
Model = State()
self.assertIsInstance(Model, State)
self.assertIsInstance(Model.name, str)
self.assertTrue(issubclass(State, BaseModel))
def test_instances_of_State(self):
"""Testing the 'State' public attributes"""
Model = State()
self.assertTrue(hasattr(Model, "name"))
if __name__ == '__main__':
unittest.main()
| DevPacho/holbertonschool-AirBnB_clone | tests/test_models/test_state.py | test_state.py | py | 1,517 | python | en | code | 0 | github-code | 36 |
22143984130 | from art import logo
def greet(name, location, time):
print(f"Hi {name} from {location}. Good {time}.")
print(f"Hey {name} from {location}. Good {time}.")
print(f"Hello {name} from {location}. Good {time}.")
#greet("Angela", location="London", time="evening")
def caeser(direction, text, shift):
caeser_text =""
shift = shift % 26
if direction == "encode":
shift = 26 - shift
for letter in text:
if letter in alphabet:
caeser_text += alphabet[alphabet.index(letter)-shift]
else:
caeser_text += letter
print(caeser_text)
def encrypt(text, shift):
encrypt_text =""
for letter in text:
encrypt_text += alphabet[alphabet.index(letter)+shift-26]
print(encrypt_text)
def decrypt(text, shift):
decrypt_text =""
for letter in text:
decrypt_text += alphabet[alphabet.index(letter)-shift]
print(decrypt_text)
print(logo)
alphabet = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z']
run = "y"
while run == "y":
direction = input("Type 'encode' to encrypt, type 'decode' to decrypt:\n")
text = input("Type your message:\n").lower()
shift = int(input("Type the shift number:\n"))
caeser(direction, text, shift)
run = input('Type "y" to continue. Type any other key to end.\n').lower()
print("Goodbye from Caeser") | tarunchandel/python-ceaser-cipher | main.py | main.py | py | 1,367 | python | en | code | 0 | github-code | 36 |
16746507107 | import os
import sys
import gensim
import smart_open
import collections
import random
import json
import os.path
from gensim.models.doc2vec import Doc2Vec, TaggedDocument
from gensim.test.utils import get_tmpfile
import time
from corpus_indexer import CorpusIndexer
class CorpusModeler:
def __init__(self, model_name, corpus_name=""):
self.model_name = model_name
self.corpus_name = corpus_name
self.corpus_file = f"{self.corpus_name}.cor"
self.corpus_index = f"{self.corpus_name}.json"
self.settings_file = f"/models/{self.model_name}.json"
self.model_file = f"/models/{self.model_name}.model"
self.load()
def build(self):
self.__build_model()
def load(self):
self.__load_or_create_settings()
self.__load_model()
def save(self):
self.__save_settings()
self.__save_model()
def __load_or_create_settings(self):
if(os.path.exists(self.settings_file)):
with open(self.settings_file) as f:
content = f.read()
self.settings = json.loads(content)
self.corpus_file = self.settings["corpus_file"]
self.corpus_index = self.settings["corpus_index"]
self.model_file = self.settings["model_file"]
self.corpus_name = self.settings["corpus_name"]
self.model_name = self.settings["model_name"]
else:
with open(self.settings_file, "w+") as f:
empty_content = json.dumps({})
f.write(empty_content)
self.settings = {
"vector_size": 70,
"min_count":2,
"epochs":20,
"dm":0,
"corpus_name": self.corpus_name,
"corpus_file": self.corpus_file,
"corpus_index": self.corpus_index,
"model_file": self.model_file,
"model_name": self.model_name
}
self.__save_settings()
def __save_settings(self):
content = json.dumps(self.settings)
with open(self.settings_file, "w") as f:
f.write(content)
def __save_model(self):
fname = get_tmpfile(self.model_file)
self.model.save(fname)
def __read_corpus(self, fname, tokens_only=False):
with smart_open.open(fname, encoding="iso-8859-1") as f:
for i, line in enumerate(f):
tokens = gensim.utils.simple_preprocess(line)
if tokens_only:
yield tokens
else:
# For training data, add tags
yield gensim.models.doc2vec.TaggedDocument(tokens, [i])
def __build_model(self):
train_corpus = list(self.__read_corpus(self.corpus_file))
model = gensim.models.doc2vec.Doc2Vec(vector_size=self.settings["vector_size"],
min_count=self.settings["min_count"],
epochs=self.settings["epochs"],
dm=self.settings["dm"])
model.build_vocab(train_corpus)
model.train(train_corpus, total_examples=model.corpus_count, epochs=model.epochs)
self.model = model
def __load_model(self):
if (os.path.exists(self.model_file)):
self.model = Doc2Vec.load(self.model_file)
else:
model = None
def gen_data(self, test_file):
if(self.model == None):
print("Must Load of Build a Model to test")
else:
self.__gen_data(test_file)
def __gen_data(self, test_file):
test_corpus = list(self.__read_corpus(test_file, tokens_only=True))
data = []
for doc in test_corpus:
inferred_vector = self.model.infer_vector(doc)
sims = self.model.docvecs.most_similar([inferred_vector], topn=len(self.model.docvecs))
ranks = self.__build_ranks(sims)
data.append({"doc": doc, "ranks": ranks})
self.__save_data(data)
#print('Test Document ({}): «{}»\n'.format(doc_id, ' '.join(test_corpus[doc_id])))
#print(u'SIMILAR/DISSIMILAR DOCS PER MODEL %s:\n' % self.model)
#for label, index in [('MOST', 0), ('MEDIAN', len(sims)//2), ('LEAST', len(sims) - 1)]:
# print(u'%s %s: «%s»\n' % (label, sims[index], ' '.join(train_corpus[sims[index][0]].words)))
def __save_data(self, data):
content = json.dumps(data)
with open(f"/outputs/{self.model_name}-{time.time()}output.json", "w") as f:
f.write(content)
def __build_ranks(self, sims):
corpus_indexer = CorpusIndexer(self.corpus_index)
data = []
for sim in sims:
desc = corpus_indexer.get_description(sim[0])
point = {"id": int(sim[0]), "rank": float(sim[1]), "description": desc}
data.append(point)
return data
| kcculhwch/prayer2vec | build/scripts/corpus_modeler.py | corpus_modeler.py | py | 5,038 | python | en | code | 0 | github-code | 36 |
24192841460 | import requests
def check_security_headers(url):
headers_to_check = [
'Strict-Transport-Security',
'Content-Security-Policy',
'X-Content-Type-Options',
'X-Frame-Options',
'X-XSS-Protection',
'Referrer-Policy',
'Permissions-Policy'
]
missing_headers = []
try:
response = requests.get(url)
response_headers = response.headers
for header in headers_to_check:
if header not in response_headers:
missing_headers.append(header)
except requests.exceptions.RequestException as e:
print(f"Error: {e}")
return missing_headers
if __name__ == "__main__":
url = input("Enter the URL of the web app: ").strip()
missing_headers = check_security_headers(url)
if missing_headers:
print("Missing security headers:")
for header in missing_headers:
print(f"- {header}")
else:
print("All security headers are present.")
| hexodotsh/WebSite_Header_Scanner | headers-security-check.py | headers-security-check.py | py | 999 | python | en | code | 0 | github-code | 36 |
4242736127 | from .__init__ import *
def gen_func(maxBase=3, maxVal=8, format='string'):
a = random.randint(1, maxVal)
b = random.randint(2, maxBase)
c = pow(b, a)
if format == 'string':
problem = "log" + str(b) + "(" + str(c) + ")"
solution = str(a)
return problem, solution
elif format == 'latex':
problem = "\\(\\log_{" + str(b) + "}" + str(c) + "\\)"
solution = "\\(" + str(a) + "\\)"
return problem, solution
else:
return b, c, a
log = Generator("Logarithm", 12, gen_func, ["maxBase=3", "maxVal=8"])
| KrishayR/academix | venv/lib/python3.8/site-packages/mathgenerator/funcs/algebra/log.py | log.py | py | 577 | python | en | code | 1 | github-code | 36 |
14144674644 | import numpy as np
from PIL import Image
import torch
class GenericDataset:
def __init__(self):
self.patch_width = None
self.image_height = None
def add(self, dataset):
return SummedDataset(self, dataset)
def resize_image(self, image):
original_width, original_height = image.size
original_height = max(original_height, 1)
original_width = max(original_width, 1)
scale = self.image_height / original_height
resized_width = int(round(scale * original_width, 0))
new_width = resized_width + (self.patch_width - (resized_width % self.patch_width)) # Adjusted this line
return image.resize((new_width, self.image_height))
def __add__(self, dataset):
return self.add(dataset)
class SummedDataset(GenericDataset):
def __init__(self, dataset_left, dataset_right) -> None:
self.left = dataset_left
self.right = dataset_right
def __len__(self):
return len(self.left) + len(self.right)
def __getitem__(self, idx):
if idx > (len(self.left) - 1):
idx_corrected = idx % len(self.left)
return self.right[idx_corrected]
return self.left[idx]
class DummyDataset(GenericDataset):
def __init__(self, number=30, name='dummy_v1', split='test') -> None:
self.samples = list(range(number))
self.name = name
self.split = split
def __len__(self):
return len(self.samples)
def __getitem__(self, idx):
return {
'dataset_name': self.name,
'split': self.split,
'image': self.samples[idx]
}
class CollateFNs:
def __init__(self, patch_width, image_height, character_tokenizer, seq2seq_same_size=False, max_size=224,
transforms=lambda x: x) -> None:
self.patch_width = patch_width
self.image_height = image_height
self.character_tokenizer = character_tokenizer
self.visual_padding_token = torch.zeros((3, self.image_height, self.patch_width))
self.total_visual_padding = torch.zeros((3, max_size, max_size))
self.same_size = seq2seq_same_size
self.max_size = max_size
self.transforms = transforms
def collate(self, batch):
max_tokens = max([len(x['tokens']) for x in batch])
max_patches = max([x['input_tensor'].shape[2] // self.patch_width for x in batch])
max_tokens_both = max(max_patches, max_tokens)
visual_tokens = []
text_tokens = []
raw_texts = []
sources = []
resized_images = []
original_images = []
images_tensor_full = []
patched_images = []
masks = []
images_full_resized = []
simply_padded_labels = []
for item in batch:
original_image, image, text_token, raw_text, split, dataset, resized_image = item['original_image'], item[
'input_tensor'], item['tokens'], item['annotation'], item['split'], item['dataset'], item[
'resized_image']
original_images.append(original_image)
resized_image = resize_to_max_size(resized_image, self.max_size)
image_to_be_patched = self.transforms(resized_image)
images_full_resized.append(self.transforms(resized_image.resize((self.max_size, self.max_size))))
_, w, h = image_to_be_patched.shape
final_image = self.total_visual_padding.clone()
# mask = self.total_visual_padding.clone()
final_image[:, :w, :h] = image_to_be_patched
# mask[:, w:, h:] = 1
# mask = 1 - mask
# masks.append(mask)
patched_images.append(final_image)
resized_images.append(resized_image)
sources.append(f"{split}_ {dataset}")
raw_texts.append(raw_text.lower())
patches = list(image.chunk(image.shape[2] // self.patch_width, dim=-1))
patches = patches + [self.visual_padding_token] * (max_tokens_both - len(patches))
text_tokenized = torch.from_numpy(
self.character_tokenizer(
text_token + [self.character_tokenizer.padding_token] * (max_tokens_both - len(text_token))
)
)
text_simply_tokenized = torch.from_numpy(
self.character_tokenizer(
text_token + [self.character_tokenizer.padding_token] * (max_tokens - len(text_token))
)
)
simply_padded_labels.append(text_simply_tokenized)
text_tokens.append(text_tokenized)
visual_tokens.append(
torch.stack(
patches
)
)
images_tensor_full.append(
torch.cat(patches, dim=2)
)
return {
'input_visual_seq': torch.stack(visual_tokens),
'images_tensor': torch.stack(images_tensor_full),
'padded_labels_to_text': torch.stack(simply_padded_labels),
'labels': torch.stack(text_tokens),
'raw_text_gt': raw_texts,
'sources': sources,
# 'original_images': resized_images,
'input_lengths': [x.size[0] // self.patch_width for x in resized_images],
'output_lengths': [len([char for char in x]) for x in raw_texts],
# 'pre_resize_images': original_images,
'totally_padded_image': torch.stack(patched_images),
'input_lengths_clip': [224 // self.patch_width for _ in resized_images],
'masks': masks,
'square_full_images': torch.stack(images_full_resized)
}
def collate_while_debugging(self, batch):
try:
return self.collate(batch)
except:
print(batch)
import pdb
pdb.set_trace()
def resize_to_max_size(image, max_size):
width, height = image.size
return image.resize((min(max_size, width), min(max_size, height)))
if __name__ == '__main__':
dataset_0_3 = DummyDataset(3, name='dataset_1', split='test')
dataset_3_5 = DummyDataset(2, name='dataset_2', split='test')
dataset_5_10 = DummyDataset(5, name='dataset_3', split='val')
dataset_0_5 = dataset_0_3 + dataset_3_5
dataset_0_10 = dataset_0_5 + dataset_5_10
print(dataset_0_10[0]) # Prints dataset_1: 0
print(dataset_0_10[3]) # Prints dataset_2: 0
print(dataset_0_10[5]) # Prints dataset_3: 0
print(dataset_0_10[2]) # Prints dataset_1: 2
print(dataset_0_10[4]) # Prints dataset_2: 1
print(dataset_0_10[9]) # Prints dataset_3: 4
| EauDeData/oda_ocr | src/dataloaders/summed_dataloader.py | summed_dataloader.py | py | 6,678 | python | en | code | 0 | github-code | 36 |
21017643306 |
class Solution:
def addStrings(self, num1: str, num2: str) -> str:
res = []
carry = 0
n1 = len(num1) - 1
n2 = len(num2) - 1
while n1 >= 0 or n2 >= 0:
x1 = ord(num1[n1]) - ord('0') if n1 >= 0 else 0
x2 = ord(num2[n2]) - ord('0') if n2 >= 0 else 0
value = (x1 + x2 + carry) % 10
carry = (x1 + x2 + carry) // 10
res.append(value)
n1 -= 1
n2 -= 1
if carry:
res.append(carry)
return ''.join(str(x) for x in res[::-1])
| EveChen/Leetcode_Practice | 415_add-strings/solution1.py | solution1.py | py | 644 | python | en | code | 2 | github-code | 36 |
1252994742 | class UncommonWordsfromTwoSentences(object):
def uncommonFromSentences(self, A, B):
count = {}
for word in A.split():
count[word] = count.get(word, 0) + 1
for word in B.split():
count[word] = count.get(word, 0) + 1
# Alternatively:
# count = collections.Counter(A.split())
# count += collections.Counter(B.split())
return [word for word in count if count[word] == 1]
if __name__ == '__main__':
a = UncommonWordsfromTwoSentences()
print(a.uncommonFromSentences(A = "this apple is sweet", B = "this apple is sour"))
print(a.uncommonFromSentences(A = "apple apple", B = "banana")) | lyk4411/untitled | beginPython/leetcode/UncommonWordsfromTwoSentences.py | UncommonWordsfromTwoSentences.py | py | 676 | python | en | code | 0 | github-code | 36 |
30872218901 | # -*- coding: utf-8 -*-
# from rest_framework.generics import ListAPIView, CreateAPIView, UpdateAPIView, RetrieveAPIView, DestroyAPIView
# from django.shortcuts import render
# from django.views import View
# from rest_framework.views import APIView
from rest_framework.authentication import BasicAuthentication, SessionAuthentication
from rest_framework.permissions import IsAuthenticatedOrReadOnly, IsAuthenticated
from rest_framework.generics import GenericAPIView
from rest_framework.response import Response
from rest_framework.mixins import ListModelMixin, CreateModelMixin
from django.http import JsonResponse
from django.http.request import QueryDict
from rest_framework.viewsets import GenericViewSet, ModelViewSet
from crawlers.models import Book as Book_model, Comment as Comment_model
from book_drf.serializer import BookSerializer, CommentSerializer
# Create your views here.
class Books(GenericAPIView):
queryset = Book_model.objects.all()
serializer_class = BookSerializer
def get_res(self):
temp = {'result': False, 'data': None, 'msg': ''}
return dict(**temp)
def get(self, request):
# print(request.data, request.query_params)
# books = Book_model.objects.all()
books = self.get_queryset()
# c1 = BookContent.objects.get(id=1)
# print(c1.book_name.book_name)
# 关联查询 主表对象.(foreign_model.lower())_set
# book1 = Book_model.objects.get(book_id=1)
# contents = BookContent.objects.filter(book_name_id=book_id)
# contents = book1.bookcontent_set.all()
# print(contents)
ser = self.get_serializer(books, many=True)
# ser = BookSerializer(books, many=True)
res = self.get_res()
res['data'] = ser.data
res['result'] = True
# return JsonResponse(ser.data, safe=False, json_dumps_params={
# 'ensure_ascii': False})
return Response(data=res)
# class Book(GenericAPIView):
# queryset = Book_model.objects.all()
# serializer_class = BookSerializer
#
# def get_res(self):
# temp = {'result': False, 'data': None, 'msg': ''}
# return dict(**temp)
#
# def get(self, request, book_id):
# print(request.data, request.query_params)
# res = self.get_res()
# try:
# book1 = Book_model.objects.get(book_id=book_id)
# print('121:', book_id, book1)
# # books = self.get_queryset()
#
# ser = BookSerializer(book1, many=False)
# # ser.is_valid()
#
# res['result'] = True
# res['data'] = ser.data
#
# except Book_model.DoesNotExist:
# res['msg'] = 'not found'
# return JsonResponse(res, json_dumps_params={
# 'ensure_ascii': False}, status=404)
#
# # return JsonResponse(res, json_dumps_params={
# # 'ensure_ascii': False})
# return Response(data=res)
class Book(ModelViewSet):
authentication_classes = (BasicAuthentication, SessionAuthentication)
permission_classes = (IsAuthenticated, )
queryset = Book_model.objects.all()
serializer_class = BookSerializer
class Comment(GenericAPIView, ListModelMixin, CreateModelMixin):
queryset = Comment_model.objects.all()
serializer_class = CommentSerializer
def get(self, request):
return self.list(request)
# comments = self.get_queryset().filter(book_id=book_id, chapter_count=chapter_count)
# ser = self.get_serializer(comments, many=True)
# return Response(data=ser.data)
# def post(self, request: QueryDict, book_id, chapter_count):
def post(self, request: QueryDict):
try:
return self.create(request)
except Exception as e:
import traceback
traceback.print_exc()
# print(e)
return Response({'msg': str(e)}, 400)
# c = self.get_object()
# print('c=', c)
data = request.data
print(data, type(data))
temp = {'book_id': book_id, 'chapter_count': chapter_count}
temp.update(data)
print('temp:', temp)
# new_comment = Comment_model.objects.create()
ser = self.get_serializer(data=temp)
if ser.is_valid():
ser.save()
return Response(data=ser.data)
else:
# ser.save()
res = {'msg': 'invalid',
'data': ser.errors}
return Response(data=res, status=400)
| ietar/huluobei | book_drf/views2.py | views2.py | py | 4,527 | python | en | code | 0 | github-code | 36 |
36748155431 | from collections import OrderedDict
from fudge.index import Index, read_index, write_index
from fudge.object import Object, load_object, store_object
from fudge.parsing.builder import Builder
from fudge.parsing.parser import Parser
from fudge.utils import FudgeException
class Node(object):
def __init__(self, name, mode, object_id):
self.name = name
self.mode = mode
self.object_id = object_id
self.children = OrderedDict()
def __iter__(self):
for child in self.children.values():
yield child
def add(self, child):
self.children[child.name] = child
def get(self, name):
return self.children.get(name)
@property
def is_branch(self):
return len(self.children) > 0
@property
def is_leaf(self):
return len(self.children) == 0
def get_node(root, path):
path = path.split('/')
current = root
for dirname in path:
current = current.get(dirname)
if not current:
break
return current
def walk_tree2(root, recurse, basepath):
for child in root:
path = basepath + child.name
yield path, child
if child.is_branch and recurse:
yield from walk_tree2(child, recurse, path + '/')
def walk_tree(root, recurse):
return walk_tree2(root, recurse, '')
def print_tree(root, recurse):
types = {
'100644': 'blob',
'100755': 'blob',
'40000': 'tree',
'160000': 'commit',
}
for path, node in walk_tree(root, recurse):
if node.is_branch and recurse:
continue
node_type = types.get(node.mode) or 'unknown'
print('{:0>6} {} {} {}'.format(node.mode, node_type, node.object_id, path))
def build_tree_from_object2(root):
obj = load_object(root.object_id)
if obj.type != 'tree':
raise FudgeException('the specified object is not a tree')
parser = Parser(obj.contents, padding=False)
while not parser.eof:
info = parser.get_utf8()
mode, name = info.split()
object_id = parser.get_sha1()
node = Node(name, mode, object_id)
root.add(node)
if mode == '40000':
build_tree_from_object2(node)
return root
def build_tree_from_object(object_id):
root = Node('root', None, object_id)
return build_tree_from_object2(root)
def read_tree2(index, root, basepath):
for child in root:
path = basepath + child.name
if child.is_branch:
read_tree2(index, child, path + '/')
else:
index.add_object(child.mode, child.object_id, path)
def read_tree(object_id):
index = Index()
root = build_tree_from_object(object_id)
read_tree2(index, root, '')
write_index(index)
def build_tree_from_index():
root = Node('root', None, None)
index = read_index()
for entry in index:
parts = entry.path.split('/')
if len(parts) == 1:
path, filename = [], parts[0]
else:
path, filename = parts[:-1], parts[-1]
current = root
for dirname in path:
if not current.get(dirname):
node = Node(dirname, '40000', None)
current.add(node)
current = current.get(dirname)
node = Node(filename, entry.perms, entry.object_id)
current.add(node)
return root
def write_tree2(root):
builder = Builder(padding=False)
for child in root:
if child.is_branch:
object_id = write_tree2(child)
child.object_id = object_id
info = '{} {}'.format(child.mode, child.name)
builder.set_utf8(info)
builder.set_sha1(child.object_id)
data = builder.data
obj = Object('tree', len(data), data)
store_object(obj)
return obj.id
def write_tree():
root = build_tree_from_index()
return write_tree2(root)
| QuantamKawts/fudge | fudge/tree.py | tree.py | py | 3,926 | python | en | code | 0 | github-code | 36 |
24428229816 | import numpy as np
import matplotlib.pyplot as plt
import random
class Tuihuo:
path = []
def __init__(self, graph, num, value=0): # 初始化类
self.num = num
self.graph = graph
self.value = 0
def output_graph(self): # 输出初始图
for i in self.graph:
for j in i:
print(j, end=',')
print()
def distance(self, tuihuocurrent):
valuenow = 0
for i in range(self.num - 1):
valuenow += self.graph[tuihuocurrent[i]][tuihuocurrent[i + 1]]
valuenow += self.graph[tuihuocurrent[self.num - 1]][0]
return valuenow
def threetuihuo(self, tuihuocurrent, x, y, w):
if x > y:
x, y = y, x
if w > y:
w, y = y, w
if w > x:
w, x = x, w
temp1 = tuihuocurrent[x:y + 1] + tuihuocurrent[w + 1:x]
tuihuocurrent[w + 1:y + 1] = temp1
return tuihuocurrent
def calculate(self): # 计算近似最短路径并且将路径存储在path中
result = [] # 用于生成可视化图表
tuihuosolution = list(range(self.num))
valuenow = 0
valuenow = self.distance(tuihuosolution)
valuebest = valuenow
tuihuocurrent = tuihuosolution.copy()
tuihuonow = tuihuosolution.copy()
t = 100000 # 初始温度
t1 = 1 # 最后底线温度
r = 0.99999 # 降温参数
while t > t1:
# 使用两路扰乱和三路扰乱两种方式
p1 = np.random.rand()
if p1 > 0.5: # 使用二路扰乱
while 1:
x = random.randrange(1, self.num - 1)
y = random.randrange(1, self.num - 1) # 生成交换坐标点
if x != y:
break
tuihuocurrent[x], tuihuocurrent[y] = tuihuocurrent[y], tuihuocurrent[x]
else: # 使用三路扰乱
while 1:
x = random.randrange(1, self.num - 1)
y = random.randrange(1, self.num - 1)
w = random.randrange(1, self.num - 1) # 生成交换坐标点
if x != y and x != w and y != w:
break
tuihuocurrent = self.threetuihuo(tuihuocurrent, x, y, w)
valuethen = self.distance(tuihuocurrent)
# 判断是否接受该解
if valuethen < valuenow:
tuihuonow = tuihuocurrent.copy()
valuenow = valuethen
if valuethen < valuebest:
tuihuosolution = tuihuocurrent.copy()
valuebest = valuethen
elif np.random.rand() < np.exp(-(valuethen - valuebest) / t): # 一定概率在不是优解的情况下接受
valuenow = valuethen
tuihuonow = tuihuocurrent.copy()
else:
tuihuocurrent = tuihuonow.copy()
t = t * r
result.append(valuenow)
plt.plot(np.array(result))
plt.ylabel("valuenow")
plt.xlabel("t")
plt.show()
self.value = valuebest
return tuihuosolution
def print_outcome(self):
num = self.calculate()
print("模拟退火算法近似最短路径为",end='')
print(0, end='')
for i in range(len(num)):
if i != 0:
print("->%d" % num[i], end='')
print("-> 0")
print("模拟退火算法近似最短路径长度为" + str(self.value))
| blue-vegetable/AI_TSP_HOMEWORK | SA.py | SA.py | py | 3,558 | python | en | code | 0 | github-code | 36 |
6255434476 |
# write a program that takes your full name as input and displays the abbreviations of the first and
# middle names except the last name whitch is displayed as it is.
# for example, if yoy name is Robert Brett Roser, then the output should be R.B.Roser
fullName = input("Ingresa tu nombre: ").split(" ")
nombre = fullName[0]
nombre2 = fullName[1]
apellido = fullName[2]
print(f"Tu nombre es: + {nombre[:1].capitalize()}.{nombre2[:1].capitalize()}.{apellido.title()}") | yonch100/python | ProyectoJavi/Ejercicio21_apellido.py | Ejercicio21_apellido.py | py | 472 | python | en | code | 0 | github-code | 36 |
70177206504 | # Understanding how computers work with binary currents with bitwise operations AND how arithmatic operations work on that, by developing a calculator that can do the same.
# What is binary numbers? => 0 and 1, they are simply like a switch, either on or off, 1 or 0.
# What is a bit? => A bit is a single binary digit, 0 or 1.
# What is a byte? => A byte is a group of 8 bits, 8 binary digits, 8 switches, 8 0s and 1s.
# ----------------------------------------------------------------------------------------------------------------------------------------------
# LIMITATIONS:
# 1. For Positive Integers Only
# ----------------------------------------------------------------------------------------------------------------------------------------------
# Converting a decimal number to binary number.
def decimal_to_binary(decimal_number):
# Brute Code First Try:
# counting how many bits will be needed to form string or you can say allocating space
count = 1
while True:
measurable = ((2**count)-1)
if decimal_number > measurable:
count += 1
else:
break
# allocating space
bin = [] # How can I overwrite bin, because bin is python built-in function not a operator neither keyword...
for i in range(count):
bin.append("0")
# not playing with main argument, a good habit, maybe I'll need in future
temp = decimal_number
# real algorithm
def biggest(num):
return 2**num
for i in range(len(bin)):
j = len(bin) - 1 - i # just to get number of positing in reverse order, because in binary integer data left hand side has greater value
if temp >= biggest(j):
bin[i] = "1" # i is not disturbed here to assign bits in right order, otherwise I have to reverse the list afterwards
temp = temp - biggest(j) # what I'm doing is iterating through every bit and finding it's turned on value, if greater than value remained from decimal value will turn that bit on and subtract that value from decimal value and loop it further until reached zero
return ''.join(bin) # str is immutable so I had to convert str into list and then vice-versa
# ------------------------------------------------------------------------------------------------------------------------------------------
# Better Version
# Best from co-pilot or research
# ----------------------------------------------------------------------------------------------------------------------------------------------
# Building Gates and with the help of different gates, building complex logic circuits for various operation.
# Firstly, there is an AND and a NOT gate which can't be build via code, I mean it can but it'll require if else and other high level language stuff which already build upon logic circuits, So using them don't make sense. AND and NOT can made via physical circuit easily for ex: A circuit with two switch and a led in series is a example of a AND gate with led indicating binary.
# First, I'll build NAND, OR, XOR which will be helpful in building Binary Adder...
def AND(a, b):
return a and b
def NAND(a, b):
'''
Not of And
Truth Table
0, 0 | 1
0, 1 | 1
1, 0 | 1
1, 1 | 0
'''
return int(not (AND(a, b)))
def OR(a, b):
'''
Not of inputs of Nand
Truth Table
0, 0 | 0
0, 1 | 1
1, 0 | 1
1, 1 | 1
'''
return int(NAND(not(a), not(b)))
def XOR(a,b):
'''
And of Nand and Or
Truth Table
0, 0 | 0
0, 1 | 1
1, 0 | 1
1, 1 | 0
XOR is Basically Adder of Binary Numbers but Without Carry because if both inputs/binary are 1 it give zero but this 1 should be carry to next bit
'''
return int(AND(NAND(a, b), OR(a, b)))
# ----------------------------------------------------------------------------------------------------------------------------------------------
# Logic To Add Binary Numbers
'''
THEORY:
How bits add?
First, We need to understand that what bits depicts naturally it's just 0 and 1, true or false, but true or false of what. So, according to the place of the bit, it means something, A Value, 0 means that value is neglected and 1 means take that value into consideration.
For Example, in a 4 bit system:
1st 0,1 depicts -> 1
22t 0,1 depicts -> 2
3rd 0,1 depicts -> 4
4th 0,1 depicts -> 8
This depiction is based on binary counting system not much different then the decimal counting system we follow.
So 1st bit can show upto 2 possibility or two possible outcomes, so it can count upto 2 and so on.
For Example: 0101 represent 5 in binary. [0*8 + 1*4 + 0*2 + 1*1]
Moving forward with Binary, Coming to our main topic how does binary actually add?
As we discussed above, every bit depicts a number and same place bits will represent same number but if you have noticed closely, you'll observe that every next place is double of the previous, Means If I add two same place bit it's also say double of that bit which we just see that is the next place bit. So, If I take two 1's of same place like this: 0010 and 0010, It'll turn next bit up, but in return value of the current bit turns off, like this --> 0010 + 0010 => 0100. Just like this if I have 4 bit of same place it turns out 2 bit of next place which further mean 1 bit of even next to next bit. like this --> 0010(2) + 0010(2) + 0010(2) + 0010(2) --> 0100(4) + 0100(4) => 1000(8).
'''
def two_bit_adder(bit1, bit2, carry = 0):
'''
Need only XOR and AND Gates:
XOR -> will act as the Result Finder for current bit, And
AND -> will act as Carry Finder
'''
curr_bit = XOR(XOR(bit1, bit2), carry) # XOR for 3 bit system
# carry = OR(OR(AND(bit1, bit2), AND(bit2, carry)), AND(carry, bit1)) # there are 3 posibilities of AND gate for 3 bit system, ab, bc and ca. This system is equivalent of, IF there are 2 or 3 bits turned on(1), then return 1, IF less then 2 bit is one or no bit is turned 1 return false.
# A Better Way
carry = OR(AND(XOR(bit1, bit2), carry), AND(bit1, bit2)) # According to A Better Carry Calculation Theory, there are two possibility for carry two result 1, rather than three as shown in previous example, First, If both Bits are True Return True, OR, Secondly, If one Bit is True and Carry is True Return True. This is just a simulation of that.
return [curr_bit, carry]
def largest_len(ls):
'''To find largest length of string from strings in given list'''
temp = len(ls[0])
for i in range(1, len(ls)):
if len(ls[i]) > temp:
temp = len(ls[i])
return temp
def binary_adder_two_bit(a, b):
# Equalising all binary numbers lengths. Like If one is 1 and other if 010 then first one should be 001 for optimal addition
l_len = largest_len([a, b])
if len(a) < l_len:
diff = l_len - len(a)
a = ("0"*diff) + a
if len(b) < l_len:
diff = l_len - len(b)
b = ("0"*diff) + b
# Actually Adding
total = ""
carry = 0
for i in range(l_len-1, -1, -1): # Getting bits from reverse because binary number start from reverse
bit, carry = two_bit_adder(int(a[i]), int(b[i]), int(carry)) # using two bit adder for every bit
total += str(bit)
return (str(carry) + total[::-1]) # We need to reverse the total as we perform addition rightfully(reversed), but don't add it to start of str but just normally to the end
# EXAMPLE:
# print(decimal_to_binary(17))
# print(binary_adder_two_bit("111", "100"))
# ----------------------------------------------------------------------------------------------------------------------------------------------
def many_bit_adder(bits_in_list, carry=0):
'''
THEORY:
Every next bit is of double value of the previous bit, so two previous bit of same position will be a single bit of next position,
We'll just take exploit this scenario, we'll just shift the to next position by reducing it to half if even or first make it even by storing one value in current bit.
For Example:
0001
+0001
+0001
+0001
If we have a bit number system like this, Indicating 4, What we can do is turning off all the one's value bits and turn a single 4 value bit. CONGRATULATIONS, we have invented Addition.
Theoretically, We'll first reduce all the four bit into two bit of next position and secondly that two bit into even next to next position, So It'll become like this -> 0001+0001+0001+0001 -> 0010+0010 => 0100.
It's also discussed in Main THEORY Section, Please Refer to That.
'''
# Calculating Current Bit
bit = 0
ones = bits_in_list.count(1) + carry
if ones%2 == 0:
bit = 0
else:
bit = 1
ones -= 1
# Calculating Carry
carry = ones / 2
return [bit, int(carry)]
def binary_adder_many_bit(*bin):
# Equalising all binary number lengths
ls = []
l_len = largest_len(bin)
for i in bin:
if len(i) < l_len:
diff = l_len - len(i)
ls.append(("0"*diff) + i)
else:
ls.append(i)
# Actually Adding
total = ""
carry = 0
for i in range(l_len-1, -1, -1): # Getting bits from reverse because binary number start from reverse
bits = []
for j in ls:
bits.append(int(j[i]))
bit, carry = many_bit_adder(bits, int(carry))
total += str(bit)
# If iteration number get finished before calculation getting over as it's only set to length of binary number, In short What If resultant result is grater in length then the inputs, Therefore this while loop to take care of that
while carry > 0: # Will run until it'll resolve carry, Refer to THEORY <-- many_bit_adder
bit, carry = many_bit_adder([], int(carry))
total += str(bit)
return (total[::-1]) # We need to reverse the total as we perform addition rightfully(reversed), but don't add it to start of str but just normally to the end
# EXAMPLE
# print(binary_adder_many_bit('1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1'))
| krishna-kush/Bit-Calculator | bit-calculator.py | bit-calculator.py | py | 10,410 | python | en | code | 0 | github-code | 36 |
69904854506 | from flask import Flask, request, jsonify
from config import Config
from flask_cors import CORS, cross_origin
from database import db
def create_app(config_class=Config):
app = Flask(__name__)
app.config.from_object(config_class)
app.config['CORS_HEADERS'] = 'Content-Type'
db.init_app(app)
# import controllers
from controllers.weo.weo_controller import weo_bp
from controllers.econ.econ_controller import econ_bp
from controllers.money_supply.money_supply_controller import money_supply_bp
from controllers.oil.oil_controller import oil_production_bp
# register controllers
app.register_blueprint(weo_bp)
app.register_blueprint(econ_bp, url_prefix='/econ')
app.register_blueprint(money_supply_bp)
app.register_blueprint(oil_production_bp, url_prefix='/oil')
# test route
@app.route('/')
def hello_world():
return "Izzy is pretty"
# error handler
@app.errorhandler(404)
def not_found(error):
return jsonify({"error": "Not Found"}), 404
return app
app = create_app()
cors = CORS(app, resources={r"/*": {"origins": "*"}})
@app.after_request
def add_cors_headers(response):
response.headers.add('Access-Control-Allow-Origin', '*')
response.headers.add('Access-Control-Allow-Headers', 'Content-Type,Authorization')
response.headers.add('Access-Control-Allow-Methods', 'GET,PUT,POST,DELETE,OPTIONS')
return response
if __name__ == '__main__':
app.run() | danme-l/website-v2-backend | app.py | app.py | py | 1,479 | python | en | code | 0 | github-code | 36 |
39941333480 | z=0.00
cant=input()
l1=[]
l2=[]
def masa(p,h):
z = float(p) / float(h)**2
return z
for i in range(0,int(cant)):
x=0.00
adata=input()
p,h=adata.split(" ")
x=masa(p,h)
if x>=30.0:
y="obese"
elif x<30.0 and x>=25.0:
y="over"
elif x<25 and x>=18.5:
y="normal"
else:
y="under"
l2.append(y)
print (*l2)
| carloscondore/python-codeabbey | python/028/condoreca.py | condoreca.py | py | 317 | python | en | code | 1 | github-code | 36 |
6357753937 | import pandas as pd
import functions as fn
import numpy as np
#USDMXN = fn.descarga_data(["USDMXN"])['USDMXN']
#USDMXN_train = USDMXN[(USDMXN['time'] >= '2020-01-01') & (USDMXN['time'] <='2021-01-01')]
#USDMXN_test = USDMXN[(USDMXN['time'] >= '2021-02-01') & (USDMXN['time'] <='2022-02-01')]
#EURUSD = fn. descarga_data(["EURUSD"])["EURUSD"]
#EURUSD_train = EURUSD[(EURUSD['time'] >= '2020-01-01') & (EURUSD['time'] <='2021-01-01')]
#EURUSD_test = EURUSD[(EURUSD['time'] >= '2021-02-01') & (EURUSD['time'] <='2022-02-01')]
indicador = pd.read_csv('./files/Gross Domestic Product Annualized.csv')
USDMXN = pd.read_csv('./files/USDMXN.csv')
USDMXN_train = pd.read_csv('./files/USDMXN_train.csv')
USDMXN_test = pd.read_csv('./files/USDMXN_test.csv')
EURUSD = pd.read_csv('./files/EURUSD.csv')
EURUSD_train = pd.read_csv('./files/EURUSD_train.csv')
EURUSD_test = pd.read_csv('./files/EURUSD_test.csv')
print(len(USDMXN_train))
print(len(EURUSD_train))
print(len(USDMXN_test))
print(len(EURUSD_test))
capital_inicial = 100000
max_perdida_cap = 1000
capital_acumulado_ent = []
capital_actual = capital_inicial
min_length = min(len(USDMXN_train), len(EURUSD_train), len(USDMXN_test), len(EURUSD_test))
capital_acumulado_ent = []
capital_actual = capital_inicial
# Calcular de capital acumulado periodo entrenamiento
for i in range(min_length):
precio_actual_USDMXN = USDMXN_train.iloc[i]['close']
precio_anterior_USDMXN = USDMXN_train.iloc[i-1]['close']
cambio_precio_USDMXN = precio_actual_USDMXN - precio_anterior_USDMXN
precio_actual_EURUSD = EURUSD_train.iloc[i]['close']
precio_anterior_EURUSDN = EURUSD_train.iloc[i-1]['close']
cambio_precio_EURUSD = precio_actual_EURUSD - precio_anterior_EURUSDN
# Calculo de capital actualizado
cambio_capital = cambio_precio_USDMXN + cambio_precio_EURUSD
capital_actual += cambio_capital
# Ajuste si excede el limite de perdida max
if cambio_capital < 0:
capital_actual = max(capital_actual, capital_actual - max_perdida_cap)
capital_acumulado_ent.append(capital_actual)
capital_acumulado_prueba = []
capital_actual = capital_inicial
# Calculo de capital acumulado periodo prueba
for i in range(min_length):
precio_actual_USDMXN = USDMXN_test.iloc[i]['close']
precio_anterior_USDMXN = USDMXN_test.iloc[i-1]['close']
cambio_precio_USDMXN = precio_actual_USDMXN - precio_anterior_USDMXN
precio_actual_EURUSD = EURUSD_test.iloc[i]['close']
precio_anterior_EURUSDN = EURUSD_test.iloc[i-1]['close']
cambio_precio_EURUSD = precio_actual_EURUSD - precio_anterior_EURUSDN
# Calculo de capital actualizado
cambio_capital = cambio_precio_USDMXN + cambio_precio_EURUSD
capital_actual += cambio_capital
# Ajuste si excede el limite de perdida max
if cambio_capital < 0:
capital_actual = max(capital_actual, capital_actual - max_perdida_cap)
capital_acumulado_prueba.append(capital_actual)
# Calculo diferencias absolutas
dif_absolutas = abs(np.array(capital_acumulado_ent[:min_length]) - np.array(capital_acumulado_prueba[:min_length]))
# MAD
mad1 = dif_absolutas.mean()
mad2 = np.median(dif_absolutas)
mad3 = np.mean(np.abs(dif_absolutas - np.mean(dif_absolutas)))
tabla = pd.DataFrame({'MAD1': [mad1], 'MAD2': [mad2], 'MAD3': [mad3]})
print(tabla)
#Generación de señal de compra o de venta.
import pandas as pd
import numpy as np
# Define las variables y carga los datos
capital_inicial = 100000
max_perdida_cap = 1000
nivel_entrada = 30
nivel_salida = 70
rsi = fn.cal_rsi(USDMXN_train['close']) # Correr primero functions
indicador = pd.read_csv('./files/Gross Domestic Product Annualized.csv')
min_length = min(len(USDMXN_train), len(EURUSD_train), len(USDMXN_test), len(EURUSD_test), len(indicador))
rsi = rsi[:min_length]
indicador = indicador[:min_length]
posicion_abierta = False
capital_actual = capital_inicial
cantidad_posicion = 0
precio_apertura = 0
precio_cierre = 0
capital_acumulado = []
operaciones = []
tickets = []
# Itera sobre los datos y realiza las operaciones
for i in range(len(rsi)):
if rsi[i] > nivel_entrada and not posicion_abierta and indicador.iloc[i]['actual'] > 0:
# Generar señal de compra
precio_apertura = precio_actual_USDMXN
cantidad_posicion = (capital_actual * max_perdida_cap) / precio_apertura
capital_actual -= cantidad_posicion * precio_apertura
posicion_abierta = True
operaciones.append('Compra')
tickets.append(f'Compra Ticket {i+1}')
capital_acumulado.append(capital_actual)
elif rsi[i] < nivel_salida and posicion_abierta and indicador.iloc[i]['actual'] < 0:
# Generar señal de venta
precio_cierre = precio_actual_USDMXN
capital_actual += cantidad_posicion * precio_cierre
posicion_abierta = False
operaciones.append('Venta')
tickets(f'Vende Ticket {i+1}')
capital_acumulado.append(capital_actual)
if posicion_abierta and (precio_cierre - precio_actual_USDMXN) < -max_perdida_cap:
# Cierre de posición por pérdida máxima alcanzada
capital_actual += cantidad_posicion * precio_actual_USDMXN
posicion_abierta = False
operaciones.append('Venta')
tickets(f'Vende Ticket {i+1} (maxima perdida)')
capital_acumulado.append(capital_actual)
rendimiento_acumulado = capital_actual - capital_inicial
rendimiento_promedio = rendimiento_acumulado / len(rsi)
# Imprime la tabla de resultados
tabla_rsi = pd.DataFrame({'Operación': operaciones, 'Ticket':tickets})
print(tabla_rsi)
| andres1999iteso/ProyectoFinal | data.py | data.py | py | 5,597 | python | es | code | 0 | github-code | 36 |
18338901118 | import os
import wave
import numpy as np
import calRMSE
import dsp
import pylab as pl
import scipy.signal as signal
import numpy as np
import cv2
import matplotlib.pyplot as plt
import scipy
from scipy.fftpack import fft
from scipy.io import wavfile as wav
from scipy import signal as sig
from scipy.signal import windows
'''
1.录取敲击声音频，音频中包含多个敲击声
2.将数据流中的多个敲击声切割出来，转换为stft矩阵，进行组合为3通道
3.load模型
4.将数据输入进模型进行测试
5.输出识别结果
'''
def read_wav_scipy(wav_path):
"""[使用scipy读取wav]
Args:
wav_path ([str]): [路径]
Returns:
[np.array, numeric]: [信号及采样率]
"""
wf = wave.open(wav_path, "rb") # 打开wav
params = wf.getparams() # 参数获取
nchannels, sampwidth, framerate, nframes = params[:4] #nframes指bufsize
#声道数, 量化位数（byte单位）, 采样频率,
#采样点数, 压缩类型, 压缩类型的描述
str_data = wf.readframes(nframes)
wf.close() # 关闭wave
#####2.将波形数据转换为数组
# N-1 一维数组，右声道接着左声道
wave_data = np.fromstring(str_data, dtype=np.short)
# 2-N N维数组
wave_data.shape = -1, 1
# 将数组转置为 N-2 目标数组
wave_data = wave_data.T
#
#fs, signal = wav.read(wav_path)
#if(len(signal.shape) > 1):
#signal = signal[:,0]
#return_signal = signal
#
return_signal=wave_data[0];
if return_signal.dtype.name == "int16":
return_signal = return_signal / 32767
fs=framerate
return return_signal, fs
def enframe(x, win, inc):
nx = len(x) # 取数据长度
nwin = len(win) # 取窗长
if nwin == 1: # 判断窗长是否为1，若为1，即表示没有设窗函数
len_temp = win # 是，帧长=win
else:
len_temp = nwin # 否，帧长=窗长
if inc is None: # 如果只有两个参数，设帧inc=帧长
inc = len_temp
nf = int(np.fix((nx-len_temp+inc)/inc)) # 计算帧数
frameout = np.zeros((nf, len_temp)) # 初始化
indf = np.reshape(inc * np.arange(0, nf), (nf, 1))
inds = np.reshape(np.arange(0, len_temp), (1, len_temp))
## 此处没有matlab的语法糖，无法做到简单复制
## Caution: 此处数值已经产生了细微的不同
# frameout = x[indf[:, np.ones((1, len_temp))] + inds[np.ones((nf, 1)), :]]
def myfunc(a):
return x[a]
# 方式1: 使用vectorize来映射
# vfunc = np.vectorize(myfunc)
# frameout = vfunc(np.repeat(indf, len_temp, axis=1) + np.repeat(inds, nf, axis=0))
# 方式2: 直接遍历来映射
temp = np.repeat(indf, len_temp, axis=1) + np.repeat(inds, nf, axis=0)
frameout = np.zeros(np.shape(temp))
for idx,i in enumerate(temp):
for idxx,j in enumerate(i):
frameout[idx, idxx] = myfunc(j)
if nwin > 1:
frameout = frameout * win
return frameout
def vad_specEn(x, wnd, inc, NIS, th1, th2, fs):
frames = enframe(x, wnd, inc).T # 分帧
fn = np.size(frames, axis=1) # 求帧数
if len(wnd) == 1:
wlen = wnd # 求出帧长
else:
wlen = len(wnd)
df = fs / wlen # 求出FFT后频率分辨率
fx1 = int(np.fix(250 / df) + 1)
fx2 = int(np.fix(3500 / df) + 1) # 找出250Hz和3500Hz的位置
km = int(np.floor(wlen / 8)) # 计算出子带个数
K = 0.5 # 常数K
Hb = np.zeros((fn))
for i in range(fn):
A = np.abs(fft(frames[:, i])) # 取来一帧数据FFT后取幅值
E = A[fx1 + 1 : fx2 - 1] # 只取250～3500Hz之间的分量
E = E * E # 计算能量
P1 = E / np.sum(E) # 幅值归一化? -> 应该是计算概率
index = np.argwhere(P1 >= 0.9) # 寻找是否有分量的概率大于0.9
if len(index) != 0:
E[index] = 0 # 若有,该分量置0
Eb = np.zeros((km))
for m in range(km): # 计算子带能量
Eb[m] = np.sum(E[4 * m : 4 * (m + 1)])
prob = (Eb + K) / np.sum(Eb + K) # 计算子带概率
Hb[i] = -np.sum(prob * np.log(prob + 10 ** -23))
Enm = sig.medfilt(Hb, 5) # 1次平滑处理
for i in range(9):
Enm = sig.medfilt(Enm, 5) # 9次平滑处理
Me = np.min(Enm) # 设置阈值
eth = np.mean(Enm[1:NIS])
Det = eth - Me
T1 = th1 * Det + Me
T2 = th2 * Det + Me
voiceseg, vsl, SF, NF = vad_revr(Enm, T1, T2)
return voiceseg, vsl, SF, NF, Enm
def vad_revr(dst1, T1, T2):
fn = len(dst1) # 取得帧数
maxsilence = 8 # 初始化
minlen = 5
status = 0
count = [0]
silence = [0]
x1 = [0]
x2 = [0]
# 开始端点检测
xn = 0
for n in range(1, fn):
if status == 0 or status == 1: # 0 = 静音, 1 = 可能开始
if dst1[n] < T2: # 确信进入语音段
x1[xn] = np.max((n - count[xn] - 1, 1))
status = 2
silence[xn] = 0
count[xn] += 1
elif dst1[n] < T1: # 可能处于语音段
status = 1
count[xn] += 1
else: # 静音状态
status = 0
count[xn] = 0
x1[xn] = 0
x2[xn] = 0
elif status == 2: # 2 = 语音段
if dst1[n] < T1: # 保持在语音段
count[xn] += 1
else: # 语音将结束
silence[xn] += 1
if silence[xn] < maxsilence: # 静音还不够长，尚未结束
count[xn] += 1
elif count[xn] < minlen: # 语音长度太短，认为是噪声
status = 0
silence[xn] = 0
count[xn] = 0
else:
status = 3
x2[xn] = x1[xn] + count[xn]
elif status == 3: # 语音结束，为下一个语音准备
status = 0
xn += 1
count.append(0)
silence.append(0)
x1.append(0)
x2.append(0)
el = len(x1) - 1
if x1[el] == 0:
el = el - 1 # 获得x1的实际长度
if el == 0:
return None,None,None,None
if x2[el] == 1: # 如果x2最后一个值为0，对它设置为fn
print("Error: Not find endding point!")
x2[el] = fn
SF = np.zeros((1, fn))
NF = np.ones((1, fn))
for i in range(el+1): # 按x1和x2，对SF和NF赋值
SF[0, x1[i] : x2[i]] = 1
NF[0, x1[i] : x2[i]] = 0
speechIndex = np.argwhere(SF == 1)
voiceseg = findSegment(speechIndex) # 计算voiceseg
vsl = len(voiceseg)
return voiceseg, vsl, SF, NF
def findSegment(express):
express_temp = [e[0] if e[0] != 0 else e[1] for e in express]
express = express_temp
if express[0] == 0:
voiceIndex = np.argwhere(express != 0) # 寻找express中为1的位置
else:
voiceIndex = express
class seg_object(object):
"""
保存begin/end/duration属性
"""
def __init__(self) -> None:
pass
soundSegment = [seg_object()]
k = 0
soundSegment[k].begin = voiceIndex[0] # 设置第一组有话段的起始位置
for i in range(len(voiceIndex)-1):
if voiceIndex[i + 1] - voiceIndex[i] > 1: # 本组有话段结束
soundSegment[k].end = voiceIndex[i] # 设置本组有话段的结束位置
soundSegment.append(seg_object())
soundSegment[k + 1].begin = voiceIndex[i + 1] # 设置下一组有话段的起始位置
k += 1
soundSegment[k].end = voiceIndex[-1] # 最后一组有话段的结束位置
# 计算每组有话段的长度
for i in range(k+1):
soundSegment[i].duration = soundSegment[i].end - soundSegment[i].begin + 1
return soundSegment
def FrameTimeC(frameNum, framelen, inc, fs):
frameTime = ((np.arange(1, frameNum + 1) - 1) * inc + framelen / 2) / fs
return frameTime
def read_data(i):
global list1;
x=list1[i];
return np.array(x,float);
def seg_data(wavfile,th1,th2,tap_num = 3,threshold = 30):
global list1;
list1=[];
# 遍历文件开始处理
signal, fs = read_wav_scipy(wavfile)
# step2.0: 变量使用及预处理
IS = 0.7 # 设置前导无话段长度
wlen = 200 # 设置帧长为25ms
inc = 80 # 求帧移
signal = signal[int(np.round(0.25 * fs))-1:] # 去除开头的硬件噪声?
signal_normalized = signal / np.max(np.abs(signal)) # 幅值非严格归一 -> [-1, 1]
N = len(signal_normalized) # 信号长度
time = np.arange(0, N) / fs
wnd = sig.windows.hamming(wlen, sym=False) # 此处matlab的显示精度需要设置，数值应该是一样的
overlap = wlen - inc
NIS = int(np.fix((IS * fs - wlen) / inc + 1))
#th1=0.7;
#th2=0.8;
'''
# step2.1: 阈值选取
material_list = ["6061", "yCu", "bxg304"]
# assert material_type in material_list, "材料类型不在列表中，请更换材料类型参数；Material_type not in the list... Please change the \"material_type\" parameter."
if material_type in material_list:
th1 = 0.35
th2 = 0.3
# th1 = 0.25
# th2 = 0.2
else:
th1 = 0.7
th2 = 0.8
'''
# step3.0: 谱熵法计算
voiceseg, vsl, SF, NF, Enm = vad_specEn(
signal_normalized, wnd, inc, NIS, th1, th2, fs
) # 谱熵法
if voiceseg==None and vsl==None:
return np.array([[[1]]], float)
fn = np.max(np.size(SF))
frameTime = FrameTimeC(fn, wlen, inc, fs) # 计算各帧对应的时间
# step3.1: 切分开始
up_cut_time_point = []
down_cut_time_point = []
for k in range(vsl):
nx1 = voiceseg[k].begin
nx2 = voiceseg[k].end
up_cut_time_point.append(frameTime[nx1])
down_cut_time_point.append(frameTime[nx2])
multi_data=[];
for i in range(vsl):
'''
if loc.find("10cm") + 1:
t1 = up_cut_time_point[i] - 0.0025
else:
t1 = up_cut_time_point[i] - 0.001
'''
t1 = up_cut_time_point[i] - 0.001
t2 = t1 + 0.009
touchsound = signal[int(np.round(t1 * fs)) : int(np.round(t2 * fs))]
# 观察结果
N_final = len(touchsound)
time_final = N_final / fs
Xtime_final = np.linspace(0, time_final, N_final, endpoint=True)
"""
plt.close()
plt.figure()
touchsound_final=touchsound
plt.plot(Xtime_final, touchsound_final)
touchsound_final2=touchsound_final.reshape(1,-1);
list1.append(Xtime_final);
list1.append(touchsound_final2[0]);
plt.title("touchsound_final")
plt.show()
"""
# 求切割完成的信号的STFT得到时频分析的矩阵，进行多通道的组合
# window_size = 32
#window_size = 32
#stft_stride = 10
window_size = 64
stft_stride = 10
#window_size = 128
#stft_stride = 5
stft_n_downsample = 1
stft_no_log = False
log_alpha = 0.1
#print(touchsound)
# [f, t, Zxx] = signal.spectrogram(touchsound_final, 44100, window="hamm", nperseg=window_size, noverlap=stft_stride, detrend=False)
spectrum = dsp.signal2spectrum(touchsound, window_size,stft_stride, stft_n_downsample, not stft_no_log)
#plt.close()#############
#plt.figure()############
# y_max = np.max(spectrum)
#plt.xlim([2, spectrum.shape[1]])########
#plt.ylim([0, spectrum.shape[0]])#######
# plt.axis("off")
#plt.imshow(spectrum)#########
# plt.savefig();
#print(spectrum)
multi_data.append(spectrum)
multi_data1 = np.array(multi_data, dtype = np.float32)
ch = 3
print("vsl : "+str(vsl))
if vsl<ch :
return np.array([[[0]]], float)
#for i in range(ch):
#print (multi_data1[i]);
#multi_data1[i] = normliaze(multi_data[i], mode = 'z-score', truncated=5)
#print (multi_data1[i])
return np.array(multi_data1,float)
def normliaze(data, mode = 'z-score', sigma = 0, dtype=np.float32, truncated = 2):
'''
mode: norm | std | maxmin | 5_95
dtype : np.float64,np.float16...
'''
data = data.astype(dtype)
data_calculate = data.copy()
if mode == 'norm':
result = (data-np.mean(data_calculate))/sigma
elif mode == 'z-score':
mu = np.mean(data_calculate)
sigma = np.std(data_calculate)
print(np.mean(data_calculate))
print(np.std(data_calculate))
result = (data - mu) / sigma
return result.astype(dtype)
| wzt1512978386/Surtify | app/src/main/python/DataPreprocessing2.py | DataPreprocessing2.py | py | 12,746 | python | en | code | 1 | github-code | 36 |
40660876105 | # -*- coding:utf-8 -*-
import os
import sys
import time
import tensorflow as tf
import seq2seqModel
import getConfig
import io
gConfig = {}
gConfig=getConfig.get_config(config_file='seq2seq.ini')
vocab_inp_size = gConfig['enc_vocab_size']
vocab_tar_size = gConfig['dec_vocab_size']
embedding_dim=gConfig['embedding_dim']
units=gConfig['layer_size']
BATCH_SIZE=gConfig['batch_size']
max_length_inp,max_length_tar=20,20
def preprocess_sentence(w):
w ='start '+ w + ' end'
#print(w)
return w
def create_dataset(path, num_examples):
lines = io.open(path, encoding='UTF-8').read().strip().split('\n')
word_pairs = [[preprocess_sentence(w)for w in l.split('\t')] for l in lines[:num_examples]]
return zip(*word_pairs)
def max_length(tensor):
return max(len(t) for t in tensor)
def read_data(path,num_examples):
input_lang,target_lang=create_dataset(path,num_examples)
input_tensor,input_token=tokenize(input_lang)
target_tensor,target_token=tokenize(target_lang)
return input_tensor,input_token,target_tensor,target_token
def tokenize(lang):
lang_tokenizer = tf.keras.preprocessing.text.Tokenizer(num_words=gConfig['enc_vocab_size'], oov_token=3)
lang_tokenizer.fit_on_texts(lang)
tensor = lang_tokenizer.texts_to_sequences(lang)
tensor = tf.keras.preprocessing.sequence.pad_sequences(tensor, maxlen=max_length_inp,padding='post')
return tensor, lang_tokenizer
input_tensor,input_token,target_tensor,target_token= read_data(gConfig['seq_data'], gConfig['max_train_data_size'])
def train():
print("Preparing data in %s" % gConfig['train_data'])
steps_per_epoch = len(input_tensor) // gConfig['batch_size']
print(steps_per_epoch)
enc_hidden = seq2seqModel.encoder.initialize_hidden_state()
checkpoint_dir = gConfig['model_data']
ckpt=tf.io.gfile.listdir(checkpoint_dir)
if ckpt:
print("reload pretrained model")
seq2seqModel.checkpoint.restore(tf.train.latest_checkpoint(checkpoint_dir))
BUFFER_SIZE = len(input_tensor)
dataset = tf.data.Dataset.from_tensor_slices((input_tensor,target_tensor)).shuffle(BUFFER_SIZE)
dataset = dataset.batch(BATCH_SIZE, drop_remainder=True)
checkpoint_dir = gConfig['model_data']
checkpoint_prefix = os.path.join(checkpoint_dir, "ckpt")
start_time = time.time()
while True:
start_time_epoch = time.time()
total_loss = 0
for (batch, (inp, targ)) in enumerate(dataset.take(steps_per_epoch)):
batch_loss = seq2seqModel.train_step(inp, targ,target_token, enc_hidden)
total_loss += batch_loss
print(batch_loss.numpy())
step_time_epoch = (time.time() - start_time_epoch) / steps_per_epoch
step_loss = total_loss / steps_per_epoch
current_steps = +steps_per_epoch
step_time_total = (time.time() - start_time) / current_steps
print('训练总步数: {} 每步耗时: {} 最新每步耗时: {} 最新每步loss {:.4f}'.format(current_steps, step_time_total, step_time_epoch,
step_loss.numpy()))
seq2seqModel.checkpoint.save(file_prefix=checkpoint_prefix)
sys.stdout.flush()
def predict(sentence):
checkpoint_dir = gConfig['model_data']
seq2seqModel.checkpoint.restore(tf.train.latest_checkpoint(checkpoint_dir))
sentence = preprocess_sentence(sentence)
inputs = [input_token.word_index.get(i,3) for i in sentence.split(' ')]
inputs = tf.keras.preprocessing.sequence.pad_sequences([inputs],maxlen=max_length_inp,padding='post')
inputs = tf.convert_to_tensor(inputs)
result = ''
hidden = [tf.zeros((1, units))]
enc_out, enc_hidden = seq2seqModel.encoder(inputs, hidden)
dec_hidden = enc_hidden
dec_input = tf.expand_dims([target_token.word_index['start']], 0)
for t in range(max_length_tar):
predictions, dec_hidden, attention_weights = seq2seqModel.decoder(dec_input, dec_hidden, enc_out)
predicted_id = tf.argmax(predictions[0]).numpy()
if target_token.index_word[predicted_id] == 'end':
break
result += target_token.index_word[predicted_id] + ' '
dec_input = tf.expand_dims([predicted_id], 0)
return result
if __name__ == '__main__':
if len(sys.argv) - 1:
gConfig = getConfig.get_config(sys.argv[1])
else:
gConfig = getConfig.get_config()
print('\n>> Mode : %s\n' %(gConfig['mode']))
if gConfig['mode'] == 'train':
train()
elif gConfig['mode'] == 'serve':
print('Serve Usage : >> python3 app.py')
| zhangzhiqiangccm/NLP-project | chineseChatbotWeb/execute.py | execute.py | py | 4,645 | python | en | code | 120 | github-code | 36 |
18034729277 | class Solution:
def minDifficulty(self, A: List[int], d: int) -> int:
n = len(A)
dp = [[float('inf')] * n + [0] for _ in range(d+1)]
for d in range(1, d+1):
for i in range(n-d+1):
maxd = 0
for j in range(i, n-d+1):
maxd = max(maxd, A[j])
dp[d][i] = min(dp[d][i], maxd + dp[d-1][j+1])
return dp[d][0] if dp[d][0] < float('inf') else -1 | LittleCrazyDog/LeetCode | 1335-minimum-difficulty-of-a-job-schedule/1335-minimum-difficulty-of-a-job-schedule.py | 1335-minimum-difficulty-of-a-job-schedule.py | py | 454 | python | en | code | 2 | github-code | 36 |
37338865985 | from distutils.core import setup
import os.path
import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="python_obfuscator",
packages=setuptools.find_packages(),
version="0.0.2",
license="MIT",
description="It's a python obfuscator.",
author="David Teather",
author_email="contact.davidteather@gmail.com",
url="https://github.com/davidteather/python-obfuscator",
long_description=long_description,
long_description_content_type="text/markdown",
download_url="https://github.com/davidteather/python-obfuscator/tarball/master",
keywords=["obfuscator"],
install_requires=["regex"],
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"Topic :: Software Development :: Build Tools",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
],
entry_points={"console_scripts": ["pyobfuscate=python_obfuscator.cli:cli"]},
)
| davidteather/python-obfuscator | setup.py | setup.py | py | 1,182 | python | en | code | 133 | github-code | 36 |
33815850991 | from django.shortcuts import get_object_or_404
from rest_framework.decorators import api_view, permission_classes
from rest_framework.response import Response
from rest_framework import status
from rest_framework.permissions import IsAdminUser, IsAuthenticated
from .models import Exercise
from .serializers import ExerciseSerializer
import requests
import os
from workouts.models import Workout
# Create your views here.
@api_view(['GET'])
@permission_classes([IsAuthenticated])
def api_exercises_list(request):
if request.method == 'GET':
url = 'https://exercisedb.p.rapidapi.com/exercises'
headers = {
'X-RapidAPI-Key': os.environ.get("EXERCISE_DB_RAPID_API_KEY"),
'X-RapidAPI-Host': 'exercisedb.p.rapidapi.com'
}
response = requests.get(url=url, headers=headers)
return Response(response.json(), status=status.HTTP_200_OK)
return Response(status=status.HTTP_400_BAD_REQUEST)
@api_view(['GET', 'POST'])
@permission_classes([IsAdminUser])
def admin_exercise_list(request):
if request.method == 'GET':
workout_id = request.query_params.get('workout_id')
if workout_id is not None:
exercises = Workout.objects.get(pk=workout_id).exercise_set.all()
serializer = ExerciseSerializer(exercises, many=True)
return Response(serializer.data)
if request.method == 'POST':
workout_id = request.data.pop('workouts_id')
serializer = ExerciseSerializer(data=request.data)
serializer.is_valid(raise_exception=True)
serializer.save()
new_exercise = get_object_or_404(
Exercise, pk=serializer.data.get('id'))
if new_exercise is not None:
workout = get_object_or_404(Workout, id=workout_id)
new_exercise.workouts.add(workout)
new_exercise = get_object_or_404(
Exercise, pk=serializer.data.get('id'))
serializer = ExerciseSerializer(new_exercise)
return Response(serializer.data, status=status.HTTP_201_CREATED)
return Response(status=status.HTTP_400_BAD_REQUEST)
@api_view(['GET', 'PATCH', 'DELETE'])
@permission_classes([IsAuthenticated])
def exercise_detail(request, pk):
exercise = get_object_or_404(Exercise, pk=pk)
if request.method == 'GET':
serializer = ExerciseSerializer(exercise)
return Response(serializer.data, status=status.HTTP_200_OK)
elif request.method == 'PATCH' and request.user.is_staff:
serializer = ExerciseSerializer(
exercise, data=request.data, partial=True)
serializer.is_valid(raise_exception=True)
serializer.save()
return Response(serializer.data, status=status.HTTP_200_OK)
elif request.method == 'DELETE' and request.user.is_staff:
exercise.delete()
return Response(status=status.HTTP_204_NO_CONTENT)
return Response(status=status.HTTP_400_BAD_REQUEST)
| christianbeckham/capstone-app | backend/exercises/views.py | views.py | py | 2,944 | python | en | code | 0 | github-code | 36 |
22782711018 | #
# @lc app=leetcode id=1721 lang=python3
#
# [1721] Swapping Nodes in a Linked List
#
# https://leetcode.com/problems/swapping-nodes-in-a-linked-list/description/
#
# algorithms
# Medium (66.34%)
# Likes: 2015
# Dislikes: 81
# Total Accepted: 116.7K
# Total Submissions: 174.9K
# Testcase Example: '[1,2,3,4,5]\n2'
#
# You are given the head of a linked list, and an integer k.
#
# Return the head of the linked list after swapping the values of the k^th node
# from the beginning and the k^th node from the end (the list is 1-indexed).
#
#
# Example 1:
#
#
# Input: head = [1,2,3,4,5], k = 2
# Output: [1,4,3,2,5]
#
#
# Example 2:
#
#
# Input: head = [7,9,6,6,7,8,3,0,9,5], k = 5
# Output: [7,9,6,6,8,7,3,0,9,5]
#
#
#
# Constraints:
#
#
# The number of nodes in the list is n.
# 1 <= k <= n <= 10^5
# 0 <= Node.val <= 100
#
#
#
# @lc code=start
# Definition for singly-linked list.
# class ListNode:
# def __init__(self, val=0, next=None):
# self.val = val
# self.next = next
class Solution:
def swapNodes(self, head: Optional[ListNode], k: int) -> Optional[ListNode]:
if not head:
return head
curr = head
for i in range(k - 1):
curr = curr.next
slow = head
fast = curr
while fast.next:
slow = slow.next
fast = fast.next
slow.val, curr.val = curr.val, slow.val
return head
# @lc code=end
| Zhenye-Na/leetcode | python/1721.swapping-nodes-in-a-linked-list.py | 1721.swapping-nodes-in-a-linked-list.py | py | 1,454 | python | en | code | 17 | github-code | 36 |
4748854183 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
class Solution(object):
def heap_sort(self, nums):
"""
:type nums: List[int] ex:[3,2,-4,6,4,2,19],[5,1,1,2,0,0]
:rtype: List[int] ex:[-4,2,2,3,4,6,19],[0,0,1,1,2,5]
"""
n = len(nums)
for i in range(n-1,-1,-1):
Solution().heapify(nums,i,n)
for i in range(n-1,0,-1):
nums[i],nums[0] = nums[0],nums[i]
Solution().heapify(nums,0,i)
return nums
def heapify(self,nums,i,n):
root = i
left = i*2+1
right = i*2+2
if left < n and nums[left] > nums[root]:
root = left
if right < n and nums[right] > nums[root]:
root = right
if i != root:
nums[i],nums[root] = nums[root],nums[i]
Solution().heapify(nums,root,n)
| samuel80402/sam | HW2/heap_sort_06170224.py | heap_sort_06170224.py | py | 877 | python | en | code | 0 | github-code | 36 |
74477215464 | from rdflib import Graph, RDF, Literal, RDFS, plugin, OWL, XSD, SKOS, PROV
plugin.register('json-ld', 'Serializer', 'rdfextras.serializers.jsonld', 'JsonLDSerializer')
import csv
import pandas as pd
from collections import Counter
from nltk.tag import StanfordNERTagger
import spacy
import jellyfish as jf
import json
import validators
import re
csv_links = "../results/yago-links.csv"
csv_node_labels = "../results/yago-node-labels.csv"
csv_nodes = "../results/yago-nodes.csv"
entity_file = "../results/entities_nodes.csv"
data_type_json = "../results/data-type-validation.json"
csv_with_features = "../results/features_selected_yago_nodes.csv"
############################Triple Features############################################################################
def pred_occur():
#counts the no. of times a predicate occurs within the entire dataset
print("inside pred_occur")
df_node_labels = pd.read_csv(csv_node_labels)
df_node_labels['CountPredOccur'] = df_node_labels['predicate'].map(Counter(list(df_node_labels['predicate'])))
df_node_labels.to_csv(csv_node_labels, index=False)
subj_pred_occur()
def subj_pred_occur():
# counts the no. of times a predicate occurs within the entity's group
print("inside subj_pred_occur")
df_node_labels = pd.read_csv(csv_node_labels)
total_groups = df_node_labels.groupby(['subject', 'predicate'])
label_count = {}
for group in total_groups.groups:
label_count[group] = len(total_groups.get_group(group))
df_node_labels['CountPredOccurofSubject'] = df_node_labels.set_index(['subject', 'predicate']).index.map(label_count.get)
df_node_labels.to_csv(csv_node_labels, index=False)
dup_triples()
def dup_triples():
# counts the no. of times a predicate occurs within the entity's group
print("inside dup_triples")
df_node_labels = pd.read_csv(csv_node_labels)
total_groups = df_node_labels.groupby(['subject', 'predicate', 'object'])
label_count = {}
for group in total_groups.groups:
try:
label_count[group] = len(total_groups.get_group(group))
except:
continue
df_node_labels['CountDupTriples'] = df_node_labels.set_index(['subject', 'predicate', 'object']).index.map(label_count.get)
df_node_labels.to_csv(csv_node_labels, index=False)
cal_haslabel_similarity()
def cal_haslabel_similarity():
# Calculate the similarity between two labels given a has_label predicate
print("inside cal_haslabel_similarity")
df_node_labels = pd.read_csv(csv_node_labels)
label_count = {}
for index, row in df_node_labels.iterrows():
if row['predicate'] == "has_label":
entity_split = row['subject'].split("/")[-1]
underscore_removed = entity_split.replace("_", " ")
wordnet_removed = underscore_removed.replace('wordnet', "")
wikicat_removed = wordnet_removed.replace('wikicategory', "")
subject_final = "".join(filter(lambda x: not x.isdigit(), wikicat_removed))
subject_final = subject_final.strip()
print(subject_final)
similarity = jf.jaro_distance(subject_final, row['object'])
label_count[(row['subject'], row['object'])] = round(similarity,2)
else:
label_count[(row['subject'], row['object'])] = "na"
df_node_labels['SimSubjectObject'] = df_node_labels.set_index(['subject', 'object']).index.map(label_count.get)
df_node_labels.to_csv(csv_node_labels, index=False)
tot_literals()
def entity_recognition():
print("inside entity_recognition")
web_sm = spacy.load(r'/Users/asara/Documents/data_enrichment/assets/en_core_web_sm-3.0.0/en_core_web_sm/en_core_web_sm-3.0.0')
st = StanfordNERTagger('assets/stanford-ner-4.2.0/classifiers/english.all.3class.distsim.crf.ser.gz',
'assets/stanford-ner-4.2.0/stanford-ner-4.2.0.jar', encoding='utf-8')
df_node_labels = pd.read_csv(csv_node_labels)
dict_entity_type = {}
entities = set(list(df_node_labels['subject']) + list(df_node_labels['object']))
total_entities = len(entities)
print("total_entities: " ,total_entities)
count=0
with open(entity_file, "a") as outfile:
writer = csv.writer(outfile)
writer.writerow(["entity", "entity_type"])
for entity in entities:
try:
count = count + 1
print("entity number: ", count)
print("more to go number: ", total_entities-count)
entity_types = []
entity_split = entity.split("/")[-1]
underscore_removed = entity_split.replace("_", " ")
wordnet_removed = underscore_removed.replace('wordnet', "")
wikicat_removed = wordnet_removed.replace('wikicategory', "")
entity_final = "".join(filter(lambda x: not x.isdigit(), wikicat_removed))
entity_final = entity_final.strip()
print(entity_final)
spacy_ner = [(X.text, X.label_) for X in web_sm(entity_final).ents]
if spacy_ner:
for item in spacy_ner:
entity_types.append(item[1])
else:
stanford_ner = st.tag([entity_final])
for item in stanford_ner + spacy_ner:
entity_types.append(item[1])
replacements = {"ORG": "ORGANIZATION", "GPE": "LOCATION", "LOC": "LOCATION"}
replacer = replacements.get # For faster gets.
entity_types = [replacer(n, n) for n in entity_types]
dict_entity_type[entity] = set(entity_types)
writer.writerow([entity, set(entity_types)])
except:
dict_entity_type[entity] = "{O}"
writer.writerow([entity, set(entity_types)])
df_node_labels['SubjectEntityType'] = df_node_labels.set_index(['subject']).index.map(dict_entity_type.get)
df_node_labels['ObjectEntityType'] = df_node_labels.set_index(['object']).index.map(dict_entity_type.get)
df_node_labels.to_csv(csv_node_labels, index=False)
pred_entity_type_occur()
def pred_entity_type_occur():
#this method counts the no. of times a particular predicate occurs with the two given entity types of subject and object
print("inside pred_entity_type_occur")
df_node_labels = pd.read_csv(csv_node_labels)
total_groups = df_node_labels.groupby(['SubjectEntityType','ObjectEntityType','predicate'])
label_count = {}
for group in total_groups.groups:
try:
label_count[group] = len(total_groups.get_group(group))
except:
continue
df_node_labels['CountPredOccurEntityType'] = df_node_labels.set_index(['SubjectEntityType','ObjectEntityType','predicate']).index.map(label_count.get)
df_node_labels.to_csv(csv_node_labels, index=False)
find_com_rare_entity_type()
def validate_literal_data_type():
print("inside validate_literal_data_type")
df_node_labels = pd.read_csv(csv_node_labels)
json_file = open(data_type_json,)
data_type_dict = json.load(json_file)
print(data_type_dict)
validity_score = []
for index, row in df_node_labels.iterrows():
pred_extracted = row['predicate']
if validators.url(pred_extracted):
pred_extracted = row['predicate'].split("/")[-1]
validity = "na"
for key in data_type_dict.keys():
if key in pred_extracted.lower():
data_type = data_type_dict[key]
try:
if data_type == "url":
validity = is_url(row['object'])
break
if data_type == "date":
validity = is_date(row['object'])
break
if data_type == 'integer':
validity = row['object'].isnumeric()
break
if data_type == 'time':
validity = re.match('\d{2}:\d{2}:\d{2}', row['object'])
break
if data_type == 'string':
validity = ((not row['object'].isnumeric()) and (not row['object'] == "") and (not validators.url(row['object'])\
and (not is_date(row['object']))))
break
except:
validity = 0
validity_score.append(validity)
df_node_labels['ValidityOfLiteral'] = validity_score
df_node_labels.to_csv(csv_node_labels, index=False)
count_occur_dup_triples()
############################Node Features############################################################################
def tot_literals():
#count total number of literal based triples an entity has
print("inside tot_predicates")
df_node_labels = pd.read_csv(csv_node_labels)
total_groups = df_node_labels.groupby(['subject'])
label_count = {}
for group in total_groups.groups:
try:
label_count[group] = len(total_groups.get_group(group))
except:
continue
data = {'node':list(label_count.keys()), 'CountLiterals': list(label_count.values()) }
df_nodes = pd.DataFrame.from_dict(data)
df_nodes.to_csv(csv_nodes, index=False)
count_dif_literal_types()
def count_dif_literal_types():
#count different types of predicates an entity has got where the object is a literal
print("inside count_dif_literal_types")
df_node_labels = pd.read_csv(csv_node_labels)
df_nodes = pd.read_csv(csv_nodes)
total_groups = df_node_labels.groupby(['subject'])
label_count = {}
for group in total_groups.groups:
fetched_group = total_groups.get_group(group)
print(fetched_group)
count_dif_literals = len(fetched_group['predicate'].unique())
label_count[group] = count_dif_literals
df_nodes['CountDifLiteralTypes'] = df_nodes.set_index(['node']).index.map(label_count.get)
df_nodes.to_csv(csv_nodes, index=False)
count_isa_triples()
def count_isa_triples():
#count different types of predicates an entity has got where the object is a literal
print("inside count_isa_triples")
df_node_labels = pd.read_csv(csv_node_labels)
df_nodes = pd.read_csv(csv_nodes)
total_groups = df_node_labels.groupby(['subject'])
label_count = {}
for group in total_groups.groups:
fetched_group = total_groups.get_group(group)
print(fetched_group)
count_dif_literals = len(fetched_group[fetched_group['predicate']=='isa'])
label_count[group] = count_dif_literals
df_nodes['CountIsaPredicate'] = df_nodes.set_index(['node']).index.map(label_count.get)
df_nodes.to_csv(csv_nodes, index=False)
count_haslabel_triples()
def count_haslabel_triples():
#count different types of predicates an entity has got where the object is a literal
print("inside count_haslabel_triples")
df_node_labels = pd.read_csv(csv_node_labels)
df_nodes = pd.read_csv(csv_nodes)
total_groups = df_node_labels.groupby(['subject'])
label_count = {}
for group in total_groups.groups:
fetched_group = total_groups.get_group(group)
print(fetched_group)
count_dif_literals = len(fetched_group[fetched_group['predicate']=='has_label'])
label_count[group] = count_dif_literals
df_nodes['CountHaslabelPredicate'] = df_nodes.set_index(['node']).index.map(label_count.get)
df_nodes.to_csv(csv_nodes, index=False)
count_subclassof_triples()
def count_subclassof_triples():
#count different types of predicates an entity has got where the object is a literal
print("inside count_subclassof_triples")
df_node_labels = pd.read_csv(csv_node_labels)
df_nodes = pd.read_csv(csv_nodes)
total_groups = df_node_labels.groupby(['subject'])
label_count = {}
for group in total_groups.groups:
fetched_group = total_groups.get_group(group)
print(fetched_group)
count_dif_literals = len(fetched_group[fetched_group['predicate']=='subClassOf'])
label_count[group] = count_dif_literals
df_nodes['CountSubclassofPredicate'] = df_nodes.set_index(['node']).index.map(label_count.get)
df_nodes.to_csv(csv_nodes, index=False)
count_subpropertyof_triples()
def count_subpropertyof_triples():
#count different types of predicates an entity has got where the object is a literal
print("inside count_subpropertyof_triples")
df_node_labels = pd.read_csv(csv_node_labels)
df_nodes = pd.read_csv(csv_nodes)
total_groups = df_node_labels.groupby(['subject'])
label_count = {}
for group in total_groups.groups:
fetched_group = total_groups.get_group(group)
print(fetched_group)
count_dif_literals = len(fetched_group[fetched_group['predicate']=='subPropertyOf'])
label_count[group] = count_dif_literals
df_nodes['CountSubpropofPredicate'] = df_nodes.set_index(['node']).index.map(label_count.get)
df_nodes.to_csv(csv_nodes, index=False)
count_high_sim_labels()
def count_high_sim_labels():
#count different types of predicates an entity has got where the object is a literal
print("inside count_high_sim_labels")
df_node_labels = pd.read_csv(csv_node_labels)
df_nodes = pd.read_csv(csv_nodes)
total_groups = df_node_labels.groupby(['subject'])
label_count = {}
for group in total_groups.groups:
fetched_group = total_groups.get_group(group)
count = 0
for index, row in fetched_group.iterrows():
if row['SimSubjectObject'] != 'na' and float(row['SimSubjectObject']) >=0.5:
count+=1
label_count[group] = count
df_nodes['CountHighSimLabels'] = df_nodes.set_index(['node']).index.map(label_count.get)
df_nodes.to_csv(csv_nodes, index=False)
count_low_sim_labels()
def count_low_sim_labels():
#count different types of predicates an entity has got where the object is a literal
print("inside count_low_sim_labels")
df_node_labels = pd.read_csv(csv_node_labels)
df_nodes = pd.read_csv(csv_nodes)
total_groups = df_node_labels.groupby(['subject'])
label_count = {}
for group in total_groups.groups:
fetched_group = total_groups.get_group(group)
count = 0
for index, row in fetched_group.iterrows():
if row['SimSubjectObject'] != 'na' and float(row['SimSubjectObject']) <0.5:
count+=1
label_count[group] = count
df_nodes['CountLowSimLabels'] = df_nodes.set_index(['node']).index.map(label_count.get)
df_nodes.to_csv(csv_nodes, index=False)
tot_outgoing_links()
def tot_outgoing_links():
print("inside tot_incoming_links")
df_node_labels = pd.read_csv(csv_node_labels)
df_nodes = pd.read_csv(csv_nodes)
df_links = pd.read_csv(csv_links)
groups_in_node_labels = df_node_labels.groupby(['subject'])
groups_in_links = df_links.groupby(['subject'])
label_count = {}
for group in df_nodes['node']:
try:
fetched_node_label_groups = len(groups_in_node_labels.get_group(group))
except:
fetched_node_label_groups = 0
try:
fetched_link_groups = len(groups_in_links.get_group(group))
except:
fetched_link_groups = 0
label_count[group] = fetched_node_label_groups + fetched_link_groups
df_nodes['OutDegree'] = df_nodes.set_index(['node']).index.map(label_count.get)
df_nodes.to_csv(csv_nodes, index=False)
tot_incoming_links()
def tot_incoming_links():
print("inside tot_outgoing_links")
df_nodes = pd.read_csv(csv_nodes)
df_links = pd.read_csv(csv_links)
groups_in_links = df_links.groupby(['object'])
label_count = {}
for group in df_nodes['node']:
try:
fetched_link_groups = len(groups_in_links.get_group(group))
except:
fetched_link_groups = 0
label_count[group] = fetched_link_groups
df_nodes['InDegree'] = df_nodes.set_index(['node']).index.map(label_count.get)
df_nodes.to_csv(csv_nodes, index=False)
validate_literal_data_type()
def find_com_rare_entity_type():
# counts the no. of times a predicate occurs within the entity's group
print("inside find_com_rare_entity_type")
df_node_links = pd.read_csv(csv_node_labels)
df_nodes = pd.read_csv(csv_nodes)
total_groups = df_node_links.groupby(['subject'])
entity_count_node_max, entity_count_node_min = {}, {}
for group in total_groups.groups:
entity_count = {}
sub_group = total_groups.get_group(group).groupby(['SubjectEntityType','ObjectEntityType'])
for entity_group in sub_group.groups:
entity_count[entity_group] = len(sub_group.get_group(entity_group))
key_max = max(entity_count.keys(), key=(lambda k: entity_count[k]))
key_min = min(entity_count.keys(), key=(lambda k: entity_count[k]))
entity_count_node_max[group] = [key_max]
entity_count_node_min[group] = [key_min]
df_nodes['CommonPredType'] = df_nodes.set_index(['node']).index.map(entity_count_node_max.get)
df_nodes['RarePredType'] = df_nodes.set_index(['node']).index.map(entity_count_node_min.get)
df_nodes.to_csv(csv_nodes, index=False)
def count_occur_dup_triples():
# counts the no. of duplicate triples a node has got
print("inside count_occur_dup_triples")
df_node_labels = pd.read_csv(csv_node_labels)
df_nodes = pd.read_csv(csv_nodes)
total_groups = df_node_labels.groupby(['subject'])
label_count = {}
for group in total_groups.groups:
count=0
for index, row in total_groups.get_group(group).iterrows():
if row['CountDupTriples'] > 1:
count+=row['CountDupTriples']
label_count[group] = count
df_nodes['CountDupTriples'] = df_nodes.set_index(['node']).index.map(label_count.get)
df_nodes.to_csv(csv_nodes, index=False)
count_invalid_literals()
def count_invalid_literals():
print("inside count_invalid_literals")
df_node_labels = pd.read_csv(csv_node_labels)
df_nodes = pd.read_csv(csv_nodes)
total_groups = df_node_labels.groupby(['subject'])
label_count = {}
for group in total_groups.groups:
count=0
for index, row in total_groups.get_group(group).iterrows():
if row['ValidityOfLiteral'] == False:
count+=1
label_count[group] = count
df_nodes['CountInvalidTriples'] = df_nodes.set_index(['node']).index.map(label_count.get)
df_nodes.to_csv(csv_nodes, index=False)
entity_recognition()
########################################Special Functions###################################
def is_date(string, fuzzy=False):
"""
Return whether the string can be interpreted as a date.
:param string: str, string to check for date
:param fuzzy: bool, ignore unknown tokens in string if True
"""
from dateutil.parser import parse
try:
parse(string, fuzzy=fuzzy)
return True
except ValueError:
return False
def is_url(url):
#check for valid URL
if not validators.url(url):
return False
else:
return True
def feature_reduction():
print("Inside feature reduction")
df = pd.read_csv(csv_node_labels)
df_fileterd = df.iloc[:,3:]
for feature in df_fileterd.columns:
if df_fileterd.dtypes[feature] != np.int64 or df_fileterd.dtypes[feature] != np.float64:
df_fileterd[feature].replace(['1','0','True','False',True,False],[1,0,1,0,1,0], inplace=True)
df_fileterd[feature] = df_fileterd[feature].astype(np.float)
for col in df_fileterd.columns:
count_unique = len(df[col].unique())
if count_unique == 1:
print(col)
df_fileterd.drop(col, inplace=True, axis=1)
columns = list(df_fileterd.columns)
corr_feature_list = []
for i in range(0, len(columns)-1):
for j in range(i+1, len(columns)):
print(columns[i],columns[j])
correlation = df_fileterd[columns[i]].corr(df_fileterd[columns[j]])
if correlation == 1:
print(columns[i], columns[j])
corr_feature_list.append(columns[i])
corr_feature_list.append(columns[j])
remove_corr_features(corr_feature_list, df_fileterd, df)
def remove_corr_features(corr_feature_list, df_fileterd, df):
print("Correlated Features: ", corr_feature_list)
features_to_remove = [input("Enter the features to remove seperated by a comma without spaces: ")]
if features_to_remove[0] == '':
gen_binary_feature(df_fileterd, df)
else:
for feature in features_to_remove:
df_fileterd.drop(feature, inplace=True, axis=1)
gen_binary_feature(df_fileterd, df)
def gen_binary_feature(df_fileterd, df):
print("inside binary_features")
columns = df_fileterd.columns
for column in columns:
new_col = []
new_col_name = "Freq" + column
for index, row in df_fileterd.iterrows():
if row[column] > df_fileterd[column].median():
new_col.append(1)
else:
new_col.append(0)
df[new_col_name] = new_col
df.to_csv(csv_with_features, index=False)
| AsaraSenaratne/anomaly-detection-kg | source-files/yago_nodes.py | yago_nodes.py | py | 21,397 | python | en | code | 2 | github-code | 36 |
70442787624 | #coding: utf-8
# __author__ = jqy
import logging
class Logger(object):
def __init__(self, log_file):
"""Initialize logging module."""
# disable requests log
logging.getLogger("requests").setLevel(logging.DEBUG)
logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
formatter = logging.Formatter('%(asctime)s %(filename)s[line:%(lineno)d] %(levelname)s %(message)s')
# Create a file handler to store error messages
fh = logging.FileHandler(log_file, mode='w')
fh.setLevel(logging.DEBUG)
fh.setFormatter(formatter)
# Create a stream handler to print all messages to console
ch = logging.StreamHandler()
ch.setLevel(logging.WARNING)
ch.setFormatter(formatter)
logger.addHandler(fh)
logger.addHandler(ch)
self.logger = logger
def getLogger(self):
return self.logger
| stkaeljason/TjgbSpider | logdealer.py | logdealer.py | py | 932 | python | en | code | 1 | github-code | 36 |
25946748198 | from data_access_layer.abstract_classes.customer_dao import CustomerDAO
from entities.customer import Customer
from util.database_connection import connection
class CustomerPostgresDAO(CustomerDAO):
def create_new_customer(self, customer: Customer) -> Customer:
sql = "insert into customer values(%s, %s, default) returning customer_id"
cursor = connection.cursor()
cursor.execute(sql, (customer.first_name, customer.last_name))
connection.commit()
generated_id = cursor.fetchone()[0]
customer.customer_id = generated_id
return customer
def get_customer_by_id(self, customer_id: int) -> Customer:
sql = "select * from customer where customer_id = %s"
cursor = connection.cursor()
cursor.execute(sql, [customer_id])
customer_record = cursor.fetchone()
customer = Customer(*customer_record)
return customer
def get_all_customers(self) -> list[Customer]:
sql = "select * from customer"
cursor = connection.cursor()
cursor.execute(sql)
customer_records = cursor.fetchall()
customer_list = []
for customer in customer_records:
customer_list.append(Customer(*customer))
return customer_list
def update_customer_by_id(self, customer: Customer) -> Customer:
sql = "update customer set first_name = %s, last_name = %s where customer_id = %s"
cursor = connection.cursor()
cursor.execute(sql, (customer.first_name, customer.last_name, customer.customer_id))
connection.commit()
return customer
def delete_customer_by_id(self, customer_id: int) -> bool:
sql = "delete from customer where customer_id = %s"
cursor = connection.cursor()
cursor.execute(sql, [customer_id])
connection.commit()
return True
| dZazulak/Project0 | project0/data_access_layer/implementation_classes/customer_postgres_dao.py | customer_postgres_dao.py | py | 1,869 | python | en | code | 0 | github-code | 36 |
72172630823 | """
Inventarios Componentes v3, CRUD (create, read, update, and delete)
"""
from typing import Any
from sqlalchemy.orm import Session
from lib.exceptions import MyIsDeletedError, MyNotExistsError
from lib.safe_string import safe_string
from ...core.inv_componentes.models import InvComponente
from ..inv_categorias.crud import get_inv_categoria
from ..inv_equipos.crud import get_inv_equipo
def get_inv_componentes(
database: Session,
inv_categoria_id: int = None,
inv_equipo_id: int = None,
generacion: str = None,
) -> Any:
"""Consultar los componentes activos"""
consulta = database.query(InvComponente)
if inv_categoria_id is not None:
inv_categoria = get_inv_categoria(database, inv_categoria_id=inv_categoria_id)
consulta = consulta.filter(InvComponente.inv_categoria == inv_categoria)
if inv_equipo_id is not None:
inv_equipo = get_inv_equipo(database, inv_equipo_id=inv_equipo_id)
consulta = consulta.filter(InvComponente.inv_equipo == inv_equipo)
if generacion is not None:
generacion = safe_string(generacion)
if generacion != "":
consulta = consulta.filter_by(generacion=generacion)
return consulta.filter_by(estatus="A").order_by(InvComponente.id.desc())
def get_inv_componente(database: Session, inv_componente_id: int) -> InvComponente:
"""Consultar un componente por su id"""
inv_componente = database.query(InvComponente).get(inv_componente_id)
if inv_componente is None:
raise MyNotExistsError("No existe ese componente")
if inv_componente.estatus != "A":
raise MyIsDeletedError("No es activo ese componente, está eliminado")
return inv_componente
| PJECZ/pjecz-plataforma-web-api-key | plataforma_web/v4/inv_componentes/crud.py | crud.py | py | 1,709 | python | es | code | 0 | github-code | 36 |
37853605555 | #!/usr/bin/env python
#
#
import common
import os, sys, re, random, itertools, functools
from atoslib import utils
from atoslib import atos_lib
from atoslib import generators
from atoslib import process
TEST_CASE = "ATOS generators - pruning"
args = common.atos_setup_args(ATOS_DEBUG_FILE="debug.log")
# ####################################################################
#
# creation of fake atos-config directory
#
atos_config = "atos-configurations"
process.commands.mkdir(atos_config)
db = atos_lib.atos_db.db(atos_config)
process.commands.touch("sha1-c")
atos_lib.generate_script(
"profile.sh", ";" "true", {})
process.commands.mkdir("csv")
process.commands.touch("plugin.so")
with open('atos-configurations/flags.inline.cfg', 'w') as flagsf:
print >>flagsf, '-fgood1|-fbad1'
print >>flagsf, '-fgood2|-fgood2'
print >>flagsf, '-fbad2|-fbad2'
print >>flagsf, '-fnone1|-fnone1'
with open('atos-configurations/flags.loop.cfg', 'w') as flagsf:
print >>flagsf, '-fgood3|-fbad3'
print >>flagsf, '-fgood4|-fbad4'
print >>flagsf, '-fnone2|-fnone2'
with open('atos-configurations/flags.optim.cfg', 'w') as flagsf:
print >>flagsf, '-fgood5|-fbad5'
print >>flagsf, '-fnone3|-fnone3'
print >>flagsf, '-fcrash1|-fnone4'
#
# generation of profile files (fctmap.out, oprof.out)
#
def profile_gen():
with open('fctmap.out', 'w') as flagsf:
print >>flagsf, 'sha1.o SHA1Reset'
print >>flagsf, 'sha1.o SHA1Result'
print >>flagsf, 'sha1.o SHA1PadMessage'
print >>flagsf, 'sha1.o SHA1Input'
print >>flagsf, 'sha1.o SHA1ProcessMessageBlock'
print >>flagsf, 'sha.o main'
print >>flagsf, 'sha.o usage'
with open('oprof.out', 'w') as flagsf:
print >>flagsf, 'vma samples % linenr_info image_name symbol_name'
print >>flagsf, '0000000000400b93 353965337 52.2748 (no localization information) sha1-c SHA1ProcessMessageBlock'
print >>flagsf, '0000000000400a86 260243456 38.4336 (no localization information) sha1-c SHA1Input'
print >>flagsf, '00000000004006e4 62914627 9.2914 (no localization information) sha1-c main'
print >>flagsf, '0000000000400f6c 732 0.0001 (no localization information) sha1-c SHA1PadMessage'
print >>flagsf, '0000000000401110 25 0.0000 (no localization information) sha1-c __libc_csu_init'
print >>flagsf, '00000000004009c8 25 0.0000 (no localization information) sha1-c SHA1Reset'
print >>flagsf, '0000000000400a3f 20 0.0000 (no localization information) sha1-c SHA1Result'
#
# estimation of time/size results given a set of flags
#
def get_cfg_result(cfg):
good_flags = [
["-fgood1"], ["-fgood2"], ["-fgood3"], ["-fgood4"], ["-fgood5"],
["-fgood-g1-1", "-fgood-g1-2"],
["-fgood-g2-1", "-fgood-g2-2", "-fgood-g2-3"],
]
bad_flags = [
["-fbad1"], ["-fbad2"], ["-fbad3"], ["-fbad4"], ["-fbad5"],
["-fbad-g1-1", "-fbad-g1-2"],
["-fbad-g2-1", "-fbad-g2-2", "-fbad-g2-3"],
]
crash_flags = [["-fcrash1"]]
#
flag_list = generators.optim_flag_list.parse_line(cfg.flags)
nb_good = len(
filter(lambda f: (len(set(f) - set(flag_list)) == 0), good_flags))
nb_bad = len(
filter(lambda f: (len(set(f) - set(flag_list)) == 0), bad_flags))
nb_crash = len(
filter(lambda f: (len(set(f) - set(flag_list)) == 0), crash_flags))
if nb_crash: return None, None
# file-by-file acf flag
acf_file_flag = filter(
functools.partial(re.search, '--atos-optfile'),
flag_list)
if acf_file_flag:
fbf_file = acf_file_flag[0][14:].strip('= ')
fbf_config = (
generators.gen_file_by_file_cfg.read_config_csv(fbf_file))
for (obj, flags) in fbf_config.items():
flags = generators.optim_flag_list.parse_line(flags)
acf_nb_good = len(
filter(lambda f: (len(set(f) - set(flags)) == 0), good_flags))
acf_nb_bad = len(
filter(lambda f: (len(set(f) - set(flags)) == 0), bad_flags))
nb_good += acf_nb_good * 0.2
nb_bad += acf_nb_bad * 0.2
# function-by-function acf flag
acf_func_flag = filter(
functools.partial(re.search, '-fplugin-arg-acf_plugin-csv_file'),
flag_list)
if acf_func_flag:
fbf_file = re.search(
'-fplugin-arg-acf_plugin-csv_file=([^ ]*)',
acf_func_flag[0]).group(1)
fbf_config = (
generators.gen_function_by_function_cfg.read_config_csv(fbf_file))
for (obj, flags) in fbf_config.items():
flags = generators.optim_flag_list.parse_line(flags)
acf_nb_good = len(
filter(lambda f: (len(set(f) - set(flags)) == 0), good_flags))
acf_nb_bad = len(
filter(lambda f: (len(set(f) - set(flags)) == 0), bad_flags))
nb_good += acf_nb_good * 0.2
nb_bad += acf_nb_bad * 0.2
score = 1000 - ((nb_good - nb_bad) * 100)
return float(score), score
#
# exploration loop and database update
#
def db_add_result(cfg, variant_id=None):
db = atos_lib.atos_db.db(atos_config)
time, size = get_cfg_result(cfg)
if None in [time, size]:
return None
new_entry = {
'variant': variant_id or atos_lib.variant_id(options=cfg.flags),
'target': 'target',
'conf': cfg.flags or '', 'time': time, 'size': size,
'cookies': ','.join(cfg.cookies or [])
}
db.add_results([new_entry])
return new_entry
def generator_loop(generator):
all_results = []
for cfg in generator:
if cfg.profile: profile_gen()
new_res = db_add_result(cfg)
if new_res: all_results.append(new_res)
return all_results
# ####################################################################
#
#
#
ref_entry = db_add_result(
generators.config())
new_entry = db_add_result(
generators.config(
flags="-fgood1 -fbad1 -fgood-g1-1 -fgood2 "
"-fgood-g1-2 -fbad-g1-1 -fbad-g1-2 -fgood3 -fbad-g2-1"),
variant_id="VAR-1")
# good: 4: fgood1 fgood2 fgood3 fgood-g1-1_fgood-g1-2
# bad : 2: -fbad1 fbad-g1-1_fbad-g1-2
# score = 4 - 2 = 2 -> 1000 - 2 * 100 -> 800
assert new_entry['size'] == 800
assert new_entry['time'] == 800.0
generator = generators.gen_flags_pruning(
variant_id='VAR-1',
tradeoff=5.0, threshold=0.0,
configuration_path=atos_config)
generator_loop(generator)
assert generator.final_flags == [
'-fgood1', '-fgood2']
generator = generators.gen_flags_pruning(
variant_id='VAR-1',
update_reference=True,
tradeoff=5.0, threshold=0.0,
configuration_path=atos_config)
generator_loop(generator)
assert generator.final_flags == [
'-fgood1', '-fgood-g1-1', '-fgood2', '-fgood-g1-2', '-fgood3']
generator = generators.gen_flags_pruning(
variant_id='VAR-1',
one_by_one=True,
tradeoff=5.0, threshold=0.0,
configuration_path=atos_config)
generator_loop(generator)
assert generator.final_flags == [
'-fgood1', '-fgood-g1-1', '-fgood2', '-fgood-g1-2', '-fgood3']
generator = generators.gen_flags_pruning(
variant_id='VAR-1',
tradeoff=5.0, threshold=0.0,
selection_size=2,
configuration_path=atos_config)
generator_loop(generator)
assert generator.final_flags == [
'-fgood2', '-fgood3', '-fbad-g2-1']
generator = generators.gen_flags_pruning(
variant_id='VAR-1',
tradeoff=5.0, threshold=0.0,
random_selection=1,
configuration_path=atos_config)
generator_loop(generator)
generator = generators.gen_flags_pruning(
variant_id='VAR-1',
tradeoff=5.0, threshold=-10,
configuration_path=atos_config)
generator_loop(generator)
generator = generators.gen_flags_pruning(
variant_id='VAR-1',
tradeoff=5.0, threshold=-10,
keep_opt_level=1,
configuration_path=atos_config)
generator_loop(generator)
#
# ACF FUNCTION
#
generator = generators.gen_function_by_function(
acf_plugin_path="plugin.so", hwi_size="8",
prof_script="./profile.sh", imgpath=".",
csv_dir="csv", hot_th="70", cold_opts="-Os",
base_flags="-O2", per_func_nbiters=100, optim_levels="-O2",
configuration_path=atos_config)
results = generator_loop(generator)
generator = generators.gen_flags_pruning(
variant_id=results[-1]['variant'],
update_reference=True,
tradeoff=5.0, threshold=0.0,
configuration_path=atos_config)
generator_loop(generator)
#
# ACF FILE
#
generator = generators.gen_file_by_file(
imgpath=".", csv_dir="csv", hot_th="70", cold_opts="-Os",
base_flags="-O2", per_file_nbiters=100, optim_levels="-O2",
configuration_path=atos_config)
results = generator_loop(generator)
generator = generators.gen_flags_pruning(
variant_id=results[-1]['variant'],
update_reference=True,
tradeoff=5.0, threshold=0.0,
configuration_path=atos_config)
generator_loop(generator)
| atos-tools/atos-utils | tests/test116.py | test116.py | py | 9,009 | python | en | code | 5 | github-code | 36 |
6508918488 | import numpy as np
import csv
import chainer
import chainer.functions as F
import chainer.links as L
import sys
import matplotlib.pyplot as plt
class LaughNeuralNet(chainer.Chain):
def __init__(self):
super(LaughNeuralNet, self).__init__(
l1=L.Linear(None, 200),
l2=L.Linear(None, 100),
l3=L.Linear(None, 2)
)
def __call__(self, x):
h = F.dropout(F.relu(self.l1(x)))
h = F.dropout(F.relu(self.l2(h)))
h = self.l3(h)
return h
class LaughNeuralNet2(chainer.Chain):
def __init__(self):
super(LaughNeuralNet2, self).__init__(
l1=L.Linear(None, 1000),
b1=L.BatchNormalization(1000),
l2=L.Linear(None, 1000),
b2=L.BatchNormalization(1000),
l3=L.Linear(None, 1000),
l4=L.Linear(None, 500),
b3=L.BatchNormalization(500),
l5=L.Linear(None, 500),
l6=L.Linear(None, 2)
)
def __call__(self, x):
h = F.dropout(self.b1(F.relu(self.l1(x))))
h = F.dropout(self.b2(F.relu(self.l2(h))))
h = F.dropout(F.relu(self.l3(h)))
h = F.dropout(self.b3(F.relu(self.l4(h))))
h = F.dropout(F.relu(self.l5(h)))
h = self.l6(h)
return h
class LaughNet(chainer.Chain):
def __init__(self):
super(LaughNet, self).__init__(
l1=L.LSTM(None, 200),
l2=L.Linear(None, 100),
l3=L.Linear(None, 2)
)
def __call__(self, x):
self.l1.reset_state()
h = self.l1(x)
h = F.dropout(self.l2(h))
h = self.l3(h)
return h
class LaughNet2(chainer.Chain):
def __init__(self):
super(LaughNet2, self).__init__(
l1=L.Linear(None, 200),
l2=L.Linear(None, 100),
l3=L.Linear(None, 2)
)
def __call__(self, x):
h = F.dropout(F.relu(self.l1(x)))
h = F.dropout(F.relu(self.l2(h)))
h = self.l3(h)
return h
# test predicting
def test_predict(path='movie_model'):
model = LaughNet()
chainer.serializers.load_npz(path, model)
with open('confused_data/Raw/v_0.csv', 'r') as f:
reader = csv.reader(f)
csv0 = [(np.array(row, dtype=np.float32), 0) for row in reader]
with open('confused_data/Raw/v_1.csv', 'r') as f:
reader = csv.reader(f)
csv1 = [(np.array(row, dtype=np.float32), 1) for row in reader]
all_ary = csv0 + csv1
ans_counts = 0
incorrect = 0
question_num = len(all_ary)
plt_ary = []
for data in all_ary:
correct = data[1]
np_data = data[0].reshape(1, 50)
y = np.argmax(F.softmax(model(np_data)).data)
if y == correct:
ans_counts += 1
plt_ary.append((model(np_data).data, y, 1))
else:
incorrect += 1
plt_ary.append((model(np_data).data, y, 0))
print('accuracy:', str(ans_counts / question_num))
print('incorrect rate:', str(incorrect / question_num))
# ｐｌｔ
x_ary0 = []
y_ary0 = []
x_ary1 = []
y_ary1 = []
incorrect_x0 = []
incorrect_y0 = []
incorrect_x1 = []
incorrect_y1 = []
for dt in plt_ary:
if dt[2] == 0:
if dt[1] == 0:
incorrect_x0.append(dt[0][0][0])
incorrect_y0.append(dt[0][0][1])
continue
else:
incorrect_x1.append(dt[0][0][0])
incorrect_y1.append(dt[0][0][1])
continue
if dt[1] == 0:
x_ary0.append(dt[0][0][0])
y_ary0.append(dt[0][0][1])
else:
x_ary1.append(dt[0][0][0])
y_ary1.append(dt[0][0][1])
np_plt_x0 = np.array(x_ary0, dtype=np.float32)
np_plt_y0 = np.array(y_ary0, dtype=np.float32)
np_plt_x1 = np.array(x_ary1, dtype=np.float32)
np_plt_y1 = np.array(y_ary1, dtype=np.float32)
np_incorrectx0 = np.array(incorrect_x0, dtype=np.float32)
np_incorrecty0 = np.array(incorrect_y0, dtype=np.float32)
np_incorrectx1= np.array(incorrect_x1, dtype=np.float32)
np_incorrecty1 = np.array(incorrect_y1, dtype=np.float32)
plt.plot(np_plt_x1, np_plt_y1, 'o', color='r', alpha=0.5)
plt.plot(np_plt_x0, np_plt_y0, 'o', color='b', alpha=0.5)
plt.plot(np_incorrectx0, np_incorrecty0, 'o', color='g', alpha=0.5)
plt.plot(np_incorrectx1, np_incorrecty1, 'o', color='m', alpha=0.5)
plt.show()
# predict
test_predict()
| awkrail/laugh_maker | validation_src/predict.py | predict.py | py | 4,519 | python | en | code | 0 | github-code | 36 |
30846787707 | # image/views.py
from rest_framework.response import Response
from rest_framework import generics, status, filters
from rest_framework.views import APIView
from django.shortcuts import get_object_or_404
from django.core.serializers.json import DjangoJSONEncoder
from django.contrib.auth.models import User
from django.http import HttpResponse, HttpResponseNotFound
from azure.storage.blob import BlobServiceClient, BlobClient, ContainerClient
import json
import os
import google_streetview.api
import random
import secrets
import base64
from .serializers import ImageSerializer, ProfileSerializer, UserSerializer
from .models import Image, Profile
#SendView: sends blob to backend and backend sends blob to azure
#ReceiveView: front end sends request for blob, backend uses request to get blob from azure and sends it to frontend
#Load: front end sends streetview info and backend saves jpg to blob
def sendToBlob(blob, blob_name):
connect_str = "DefaultEndpointsProtocol=https;AccountName=blupix;AccountKey=8KBz2PiH671bmhUYvjO+iAs1mh+TIx31DVgnGKzygcv8ItnRgyGtewwZkVgS7aaQ8VB6z6qY/Gqh9lTTTkrx/g==;EndpointSuffix=core.windows.net"
blob_service_client = BlobServiceClient.from_connection_string(connect_str)
container_client = blob_service_client.get_container_client("blupix-app")
blob_client = blob_service_client.get_blob_client(container="blupix-app", blob=blob_name)
blob_client.upload_blob(blob)
blob_list = container_client.list_blobs()
for blob in blob_list:
print("\t" + blob.name)
class SendView(APIView):
def post(self, request):
try:
blob = request.data['file']
blob_name = request.data['blob_name']
sendToBlob(blob, blob_name)
except Exception as ex:
print('Exception:')
print(ex)
return Response({"Error": "Problem with SendView"})
return Response({"blob_name": request.data['blob_name']})
class ReceiveView(APIView):
def post(self, request):
connect_str = "DefaultEndpointsProtocol=https;AccountName=blupix;AccountKey=8KBz2PiH671bmhUYvjO+iAs1mh+TIx31DVgnGKzygcv8ItnRgyGtewwZkVgS7aaQ8VB6z6qY/Gqh9lTTTkrx/g==;EndpointSuffix=core.windows.net"
try:
blob_service_client = BlobServiceClient.from_connection_string(connect_str)
blob_client = blob_service_client.get_blob_client(container="blupix-app", blob=request.data['blob_name'])
blob = blob_client.download_blob()
return HttpResponse(blob.readall(), content_type="image/jpeg")
except Exception as ex:
print('Exception:')
print(ex)
return Response({"Error": "Problem with ReceiveView"})
class KeyView(APIView):
def get(self, request):
return Response({"key": "AIzaSyD7blO0Y7Z-Jf2rRFyuo2CrQa7kEXRy1po"})
class LoadView(APIView):
def post(self, request):
data = request.data
params = [{
'size': data["size"], # max 640x640 pixels
'location': data["location"],
'heading': data["heading"],
'pitch': data["pitch"],
"fov": data["fov"],
'key': "AIzaSyD7blO0Y7Z-Jf2rRFyuo2CrQa7kEXRy1po"
}]
# Create a results object
results = google_streetview.api.results(params)
image_file = "media/pre_images"
results.download_links(image_file)
random.seed(secrets.token_bytes(4))
new_file_name = str(random.randint(0, 99999))
print("load: " + new_file_name)
os.rename("media/pre_images/gsv_0.jpg", "media/pre_images/" + new_file_name + ".jpg")
os.remove("media/pre_images/metadata.json")
upload_file_path = os.getcwd()+ "/" + "/media/pre_images/" + new_file_name + ".jpg"
with open(upload_file_path, "rb") as data:
encoded = base64.b64encode(data.read())
img = b'data:image/jpg;base64,' + encoded
sendToBlob(img, new_file_name)
os.remove(upload_file_path)
return Response({"blob_name": new_file_name})
class LoginView(APIView):
def get(self, request):
return Response({"Failure": "Incorrect URL"})
def post(self, request):
password = request.data["password"]
profile = None
if "username" in request.data:
username = request.data["username"]
try:
user = User.objects.get(username=username)
profile = Profile.objects.get(user=user)
except:
return Response({"Failure": "Can't find username"})
elif "phone_number" in request.data:
phone_number = request.data["phone_number"]
try:
profile = Profile.objects.get(phone_number=phone_number)
except:
return Response({"Failure": "Can't find phone_number"})
else:
return Response({"Failure": "Incorrect information sent"})
if profile.banned == True:
return Response({"Failure": "this user is banned!"})
correct_pw = profile.user.check_password(password)
if correct_pw:
prof_dict = {
"id": profile.id,
"username": profile.user.username,
"phone_number": profile.phone_number,
"is_admin": profile.is_admin,
"approved_by_admin": profile.approved_by_admin,
"banned": profile.banned
}
profiles = []
profiles.append(prof_dict)
return Response(json.loads(json.dumps(profiles, cls=DjangoJSONEncoder)))
else:
return Response({"Failure!": "Incorrect Password"})
class ProfileApproveView(generics.ListCreateAPIView):
def get(self, request): #returns all profiles not approved by admin
unapproved_profiles = Profile.objects.filter(approved_by_admin=False)
profiles = []
for p in unapproved_profiles:
prof_dict = {
"id": p.id,
"username": p.user.username,
"phone_number": p.phone_number,
"is_admin": p.is_admin,
"approved_by_admin": p.approved_by_admin,
"banned": p.banned
}
profiles.append(prof_dict)
return Response({"unapproved_profiles": json.loads(json.dumps(profiles, cls=DjangoJSONEncoder))})
class ProfileView(generics.ListCreateAPIView):
serializer_class = ProfileSerializer
queryset = Profile.objects.all()
def get(self, requset, pk=None): #used to get a list of all users
q = []
profiles = []
if pk == None:
q = self.get_queryset()
else:
q.append(get_object_or_404(Profile.objects.all(), pk=pk))
for p in q:
prof_dict = {
"id": p.id,
"username": p.user.username,
"phone_number": p.phone_number,
"is_admin": p.is_admin,
"approved_by_admin": p.approved_by_admin,
"banned": p.banned
}
print(prof_dict)
profiles.append(prof_dict)
return Response(json.loads(json.dumps(profiles, cls=DjangoJSONEncoder)))
def post(self, request): #used to create a new user
q = request.data
username = q["username"]
password = q["password"]
phone_number = q["phone_number"]
is_admin = q["is_admin"]
approved_by_admin = q["approved_by_admin"]
if User.objects.filter(username=username).exists():
return Response({"Failure!": "A user with this username already exists"})
if Profile.objects.filter(phone_number=phone_number).exists():
return Response({"Failure!": "A user with this phone_number already exists"})
profile = self.serializer_class.create_object(self,username, password, phone_number, is_admin, approved_by_admin)
return Response({"Success!": "User {} was created!".format(profile.user.username)})
def put(self, request, pk): #updated profile information
profile = get_object_or_404(Profile.objects.all(), pk=pk)
data = request.data
updated_profile = self.serializer_class.update_profile(self, profile, data)
return Response({"Success!": "User {} was updated!".format(updated_profile.user.username)}, status=204)
def delete(self, request, pk):
profile = get_object_or_404(Profile.objects.all(), pk=pk)
username = profile.user.username
profile.user.delete()
profile.delete()
return Response({"Profile for {} was deleted".format(username)}, status=204)
class ImageView(APIView):
def get(self, request, pk = None): #either returns one image (by id number) or all images
if pk == None:
images = Image.objects.all()
serializer_class = ImageSerializer(images, many = True)
else:
image = get_object_or_404(Image.objects.all(), pk=pk)
serializer_class = ImageSerializer(image, many = False)
return Response({"images": serializer_class.data})
def post(self, request):
image_serializer = ImageSerializer(data=request.data)
if image_serializer.is_valid():
image_serializer.save()
return Response(image_serializer.data, status=status.HTTP_201_CREATED)
else:
print('error', image_serializer.errors)
return Response(image_serializer.errors, status=status.HTTP_400_BAD_REQUEST)
def put(self, request, pk):
saved_image = get_object_or_404(Image.objects.all(), pk=pk)
data = request.data.get('image')
serializer_class = ImageSerializer(instance=saved_image, data=data, partial=True)
if serializer_class.is_valid(raise_exception=True):
image_saved = serializer_class.save()
return Response({"success": "Image '{}' has been updated successfully".format(image_saved)})
def delete(self, request, pk):
image = get_object_or_404(Image.objects.all(), pk=pk)
try:
blob_name = image.blob_name
connect_str = "DefaultEndpointsProtocol=https;AccountName=blupix;AccountKey=8KBz2PiH671bmhUYvjO+iAs1mh+TIx31DVgnGKzygcv8ItnRgyGtewwZkVgS7aaQ8VB6z6qY/Gqh9lTTTkrx/g==;EndpointSuffix=core.windows.net"
blob_service_client = BlobServiceClient.from_connection_string(connect_str)
blob_client = blob_service_client.get_blob_client(container="blupix-app", blob=blob_name)
blob_client.delete_blob()
except:
pass
image.delete()
return Response({"success": "Image '{}' has been updated deleted".format(pk)}, status=204)
class DataSearch(generics.ListCreateAPIView):
def createJSONObj(self, post_images):
JSONList = []
for post in post_images:
try:
#post_user = get_object_or_404(Profile, id=post.user_id_of_upload)
post_user = Profile.objects.get(id=post.user_id_of_upload)
image_dict = {
"postID" : post.id,
"post_blob_name" : post.blob_name,
"position": {
"lat" : post.latitude,
"lng" : post.longitude
},
"address" : post.address,
"floodDate" : post.flood_date,
"postSource" : post.source,
"pairAttempted" : post.pair_attempted,
"username_of_post": post_user.user.username,
"approved_user": post_user.approved_by_admin
}
except:
image_dict = {
"postID" : post.id,
"post_blob_name" : post.blob_name,
"position": {
"lat" : post.latitude,
"lng" : post.longitude
},
"address" : post.address,
"floodDate" : post.flood_date,
"postSource" : post.source,
"pairAttempted" : post.pair_attempted,
"username_of_post": "null",
"approved_user": "null"
}
try:
pre_image = Image.objects.get(id=post.pair_index)
#pre_profile = get_object_or_404(Profile, id=pre_image.user_id_of_upload)
image_dict["preID"] = pre_image.id
image_dict["pre_blob_name"] = pre_image.blob_name
image_dict["preSource"] = pre_image.source
image_dict["map_url"] = pre_image.Maps_URL
if pre_image.approved_by_admin == True:
image_dict["isPaired"] = "True"
else:
image_dict["isPaired"] = "False"
try:
pre_profile = Profile.objects.get(id=pre_image.user_id_of_upload)
image_dict["username_of_pre"] = pre_profile.user.username
except Profile.DoesNotExist:
image_dict["username_of_pre"] = "null"
except Image.DoesNotExist:
image_dict["username_of_pre"] = "null"
image_dict["predID"] = "null"
image_dict["pre_blob_name"] = "null"
image_dict["preSource"] = "null"
image_dict["isPaired"] = "False"
JSONList.append(image_dict)
return(json.loads(json.dumps(JSONList, cls=DjangoJSONEncoder)))
def get(self, request): #return all unapproved images
post_images = Image.objects.filter(pre_post = True, approved_by_admin="False")
return Response(self.createJSONObj(post_images))
def post(self, request):
q = request.data.get("data")
post_images = []
post_images = Image.objects.filter(pre_post = True, latitude__gte=q["MinLat"], latitude__lte=q["MaxLat"], longitude__gte=q["MinLong"],
longitude__lte=q["MaxLong"], flood_date__gte=q["MinDate"], flood_date__lte=q["MaxDate"])
images = []
if q["PairingStatus"] == "paired":
for p in post_images:
if p.approved_by_admin == True:
try:
pre_image = Image.objects.get(id=p.pair_index)
if pre_image.approved_by_admin == True:
images.append(p)
except:
print("problem with paired")
continue
elif q["PairingStatus"] == "unpaired":
for p in post_images:
try:
pre_image = Image.objects.get(id=p.pair_index)
if p.approved_by_admin != pre_image.approved_by_admin:
images.append(p)
except Image.DoesNotExist:
images.append(p)
continue
else:
for p in post_images:
if p.approved_by_admin == True:
images.append(p)
try:
pre_image = Image.objects.get(id=p.pair_index)
if p.approved_by_admin == False and pre_image.approved_by_admin == True:
images.append(p)
except Image.DoesNotExist:
print("You are trying to access a pre_image that does not exist")
continue
approved_user_images = []
for i in images:
try:
#profile = get_object_or_404(Profile, id=i.user_id_of_upload)
profile = Profile.objects.get(id=i.user_id_of_upload)
if profile.approved_by_admin == True:
approved_user_images.append(i)
except:
print("user doesn't exit")
continue
return Response(self.createJSONObj(approved_user_images))
| ngade98/waterlogged_heroku | waterlogged/views.py | views.py | py | 16,109 | python | en | code | 0 | github-code | 36 |
71001878825 | # Напишите программу, которая на вход принимает два числа A и B, и возводит число А в целую степень B с помощью рекурсии.
def exponent(a, b):
if b == 0:
return 1
else:
if b > 0:
return a * exponent(a, b-1)
else:
return 1 / a * exponent(a, b+1)
while True:
try:
a = int(input("Введите число А: "))
b = int(input("Введите число B: "))
print(f"число {a} возведенное в степень {b} = {exponent(a, b)}")
break
except:
print("Ошибка ввода. Введено не число!")
| IgorVGoncharov/Python_start | Lesson_5/Task_26.py | Task_26.py | py | 726 | python | ru | code | 0 | github-code | 36 |
15442973460 | from __future__ import absolute_import, print_function
import json
import os
import tempfile
import mock
import mesos.cli.cfg
import mesos.cli.cmds.config
from .. import utils
config_path = os.path.normpath(os.path.join(
os.path.dirname(__file__), "..", "data", "config.json"))
class TestConfig(utils.MockState):
@mock.patch('os.environ', {"MESOS_CLI_CONFIG": config_path})
@utils.patch_args(["mesos-config"])
def test_output(self):
mesos.cli.cmds.config.CFG = mesos.cli.cfg.Config()
mesos.cli.cmds.config.main()
out = json.loads(self.stdout)
assert "master" in out["test"]
@mock.patch('os.environ', {"MESOS_CLI_CONFIG": config_path})
@utils.patch_args([
"mesos-config",
"master"
])
def test_get_key(self):
mesos.cli.cmds.config.CFG = mesos.cli.cfg.Config()
mesos.cli.cmds.config.main()
assert "zk://localhost:2181/mesos" in self.stdout
@utils.patch_args([
"mesos-config",
"master",
"zk://localhost:2181/mesos"
])
def test_set_key(self):
fd, fname = tempfile.mkstemp()
with open(fname, "w") as fobj:
fobj.write("{}")
try:
with mock.patch('os.environ', {"MESOS_CLI_CONFIG": fname}):
mesos.cli.cmds.config.CFG = mesos.cli.cfg.Config()
mesos.cli.cmds.config.main()
with open(fname, "r") as fobj:
assert "zk://localhost:2181" in json.loads(
fobj.read())["default"]["master"]
finally:
os.remove(fname)
| mesosphere-backup/mesos-cli | tests/integration/test_config.py | test_config.py | py | 1,613 | python | en | code | 116 | github-code | 36 |
15958452776 | import os
#from numpy import where, zeros
import re
#from itertools import repeat
def build_depend_dict(data):
depend_dict = {}
for (i, d) in data:
if d in depend_dict:
depend_dict[d].append(i)
else:
depend_dict[d] = [i]
return depend_dict
findRoutes = re.compile(r'((?<=\s)[A-Z](?=\s))')
workPath = os.path.expanduser("~/Documents/Code/Advent_of_code")
os.chdir(workPath)
with open(os.path.join(workPath, "day_7_input.txt"), "r") as inFile:
lines = [findRoutes.findall(s.strip()) for s in inFile]
line_dict = {}
for (i, d) in lines:
if i in line_dict:
line_dict[i].append(d)
else:
line_dict[i] = [d]
for k, v in line_dict.items():
line_dict[k] = sorted(v)
depend_dict = build_depend_dict(lines)
independant, dependant = zip(*lines)
independant = sorted(set(independant))
dependant = sorted(set(dependant))
numTasks = len(set(independant + dependant))
#vals = sorted(set([i for i in independant if i not in dependant]))
#vals += sorted([i for i in independant if i not in vals])
#vals += sorted([d for d in dependant if d not in independant])
#vals = iter(vals)
vals = sorted(set([i for i in independant if i not in dependant]))
# ['G', 'M', 'W', 'Z']
result = ''
while len(vals) > 0:
next_val = vals[0]
result += next_val
vals = vals[1:]
if next_val in line_dict:
for p in line_dict[next_val]:
if p in depend_dict:
depend_dict[p].remove(next_val)
if len(depend_dict[p]) == 0:
vals += [p]
vals = sorted(set(vals))
# Answer = GLMVWXZDKOUCEJRHFAPITSBQNY
# Part 2: 1105
speed = 60
num_workers = 5
numTasks = len(set(independant + dependant))
task_duration = lambda c : 60 + ord(c.lower()) - 96
depend_dict = build_depend_dict(lines)
vals = sorted(set([i for i in independant if i not in dependant]))
workers = {w:0 for w in range(num_workers)}
worker_pool = list(workers.keys())
task_in_process = {}
result = ''
clock = 0
while len(result) < numTasks:
# working
try:
time_worked = min([v for v in workers.values() if v > 0])
except:
time_worked = 0
clock += time_worked
for w in set(workers.keys()).difference(set(worker_pool)):
workers[w] -= time_worked
if workers[w] <= 0:
worker_pool.append(w)
finished_task = task_in_process[w]
result += finished_task
if finished_task in line_dict:
for p in line_dict[finished_task]:
if p in depend_dict:
depend_dict[p].remove(finished_task)
if len(depend_dict[p]) == 0:
vals += [p]
vals = sorted(set(vals))
while len(worker_pool) > 0 and len(vals) > 0:
# Assign work
next_val = vals[0]
vals = vals[1:]
elf = worker_pool.pop()
workers[elf] = task_duration(next_val)
task_in_process[elf] = next_val
| jdmuss/advent_of_code | 2018/day_7.py | day_7.py | py | 3,022 | python | en | code | 0 | github-code | 36 |
11568085044 | ### 4
import time
import RPi.GPIO as gpio
import numpy as np
#### initialize GPIO pins ####
def init():
gpio.setmode(gpio.BOARD)
gpio.setup(31, gpio.OUT) # in 1
gpio.setup(33, gpio.OUT) # in 2
gpio.setup(35, gpio.OUT) # in 3
gpio.setup(37, gpio.OUT) # in 4
gpio.setup(7, gpio.IN, pull_up_down=gpio.PUD_UP)
gpio.setup(12, gpio.IN, pull_up_down=gpio.PUD_UP)
def shutdown():
gpio.output(31, False) # close in 1
gpio.output(33, False) # close in 2
gpio.output(35, False) # close in 3
gpio.output(37, False) # close in 4
gpio.cleanup()
def main():
init()
counter_front_left = np.uint64(0)
counter_back_right = np.uint64(0)
button_front_left = int(0)
button_back_right = int(0)
# independent motor control via pwm
pwm_back_right = gpio.PWM(31, 50)
pwm_front_left = gpio.PWM(37, 50)
val = 22
pwm_back_right.start(val)
pwm_front_left.start(val)
time.sleep(0.1)
### save encoder state to txt file
filename_br = 'encoderStateBR.txt'
filename_fl = 'encoderStateFL.txt'
file_br = open(filename_br, 'w')
file_fl = open(filename_fl, 'w')
for i in range(0, 100000):
print('counter back right', counter_back_right, 'counter front left', counter_front_left, "BR state: ", gpio.input(12), "FL state: ", gpio.input(7))
file_br.write(str(int(gpio.input(12))) + ' ' + str(counter_back_right) +' \n')
file_fl.write(str(int(gpio.input(7))) + ' ' + str(counter_front_left) + ' \n')
if int(gpio.input(12)) != int(button_back_right):
button_back_right = int(gpio.input(12))
counter_back_right += 1
if int(gpio.input(7)) != int(button_front_left):
button_front_left = int(gpio.input(7))
counter_front_left += 1
if counter_front_left >= 960:
pwm_front_left.stop()
if counter_back_right >= 960:
pwm_back_right.stop()
if button_front_left >= 960 and button_back_right >= 960:
shutdown()
print("endcoder count finished, encoder state recorded at", filename_br)
break
file_br.close()
file_fl.close()
if __name__ == '__main__':
main()
| StrikerCC/RaspberryPi_autonomousRobotics_ENPM809T | A7/encodercontrol04.py | encodercontrol04.py | py | 2,306 | python | en | code | 0 | github-code | 36 |
5603104189 | import discord
cogs_list = [
"help",
"unveil",
"bet",
"account"
]
class Dealer(discord.Bot):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
for cog in cogs_list:
self.load_extension(f"cogs.{cog}")
async def on_ready(self):
print(f"{self.user} has connected to Discord!")
| liang799/rivenDealer | bot.py | bot.py | py | 359 | python | en | code | 1 | github-code | 36 |
16237300867 | """
This is the place that takes the basic configuration of your LaTeX
build project.
"""
# The name of our main LaTeX source, e. g. 'thesis' or a file 'thesis.tex'.
LATEX_PROJECT = 'report'
# Default target.
DEFAULT_TARGET = 'pdf'
# --- Things below should mostly not need touching. ---
# Some rather fixed configurations.
IMAGES_DIRECTORY = 'images'
GENERATED_DIRECTORY = 'generated'
CHAPTER_DIRECTORY = 'chapters'
FILE_EXTENSIONS = {'tex': '.tex',
'eps': '.eps',
'pdf': '.pdf',
'md': '.md',
'png': '.png',
'jpg': '.jpg',
'graffle': '.graffle',
'gnuplot': '.gnuplot'}
MAKEINDEX_EXTENSIONS = ['.glg', '.glo', '.gls']
| alexbowe/keyphrase | report/build_config.py | build_config.py | py | 758 | python | en | code | 14 | github-code | 36 |
22530028718 | """Implementation of a space that represents textual strings."""
from typing import Any, Dict, FrozenSet, Optional, Set, Tuple, Union
import numpy as np
from gym.spaces.space import Space
alphanumeric: FrozenSet[str] = frozenset(
"abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
)
class Text(Space[str]):
r"""A space representing a string comprised of characters from a given charset.
Example::
>>> # {"", "B5", "hello", ...}
>>> Text(5)
>>> # {"0", "42", "0123456789", ...}
>>> import string
>>> Text(min_length = 1,
... max_length = 10,
... charset = string.digits)
"""
def __init__(
self,
max_length: int,
*,
min_length: int = 1,
charset: Union[Set[str], str] = alphanumeric,
seed: Optional[Union[int, np.random.Generator]] = None,
):
r"""Constructor of :class:`Text` space.
Both bounds for text length are inclusive.
Args:
min_length (int): Minimum text length (in characters). Defaults to 1 to prevent empty strings.
max_length (int): Maximum text length (in characters).
charset (Union[set], str): Character set, defaults to the lower and upper english alphabet plus latin digits.
seed: The seed for sampling from the space.
"""
assert np.issubdtype(
type(min_length), np.integer
), f"Expects the min_length to be an integer, actual type: {type(min_length)}"
assert np.issubdtype(
type(max_length), np.integer
), f"Expects the max_length to be an integer, actual type: {type(max_length)}"
assert (
0 <= min_length
), f"Minimum text length must be non-negative, actual value: {min_length}"
assert (
min_length <= max_length
), f"The min_length must be less than or equal to the max_length, min_length: {min_length}, max_length: {max_length}"
self.min_length: int = int(min_length)
self.max_length: int = int(max_length)
self._char_set: FrozenSet[str] = frozenset(charset)
self._char_list: Tuple[str, ...] = tuple(charset)
self._char_index: Dict[str, np.int32] = {
val: np.int32(i) for i, val in enumerate(tuple(charset))
}
self._char_str: str = "".join(sorted(tuple(charset)))
# As the shape is dynamic (between min_length and max_length) then None
super().__init__(dtype=str, seed=seed)
def sample(
self, mask: Optional[Tuple[Optional[int], Optional[np.ndarray]]] = None
) -> str:
"""Generates a single random sample from this space with by default a random length between `min_length` and `max_length` and sampled from the `charset`.
Args:
mask: An optional tuples of length and mask for the text.
The length is expected to be between the `min_length` and `max_length` otherwise a random integer between `min_length` and `max_length` is selected.
For the mask, we expect a numpy array of length of the charset passed with `dtype == np.int8`.
If the charlist mask is all zero then an empty string is returned no matter the `min_length`
Returns:
A sampled string from the space
"""
if mask is not None:
assert isinstance(
mask, tuple
), f"Expects the mask type to be a tuple, actual type: {type(mask)}"
assert (
len(mask) == 2
), f"Expects the mask length to be two, actual length: {len(mask)}"
length, charlist_mask = mask
if length is not None:
assert np.issubdtype(
type(length), np.integer
), f"Expects the Text sample length to be an integer, actual type: {type(length)}"
assert (
self.min_length <= length <= self.max_length
), f"Expects the Text sample length be between {self.min_length} and {self.max_length}, actual length: {length}"
if charlist_mask is not None:
assert isinstance(
charlist_mask, np.ndarray
), f"Expects the Text sample mask to be an np.ndarray, actual type: {type(charlist_mask)}"
assert (
charlist_mask.dtype == np.int8
), f"Expects the Text sample mask to be an np.ndarray, actual dtype: {charlist_mask.dtype}"
assert charlist_mask.shape == (
len(self.character_set),
), f"expects the Text sample mask to be {(len(self.character_set),)}, actual shape: {charlist_mask.shape}"
assert np.all(
np.logical_or(charlist_mask == 0, charlist_mask == 1)
), f"Expects all masks values to 0 or 1, actual values: {charlist_mask}"
else:
length, charlist_mask = None, None
if length is None:
length = self.np_random.integers(self.min_length, self.max_length + 1)
if charlist_mask is None:
string = self.np_random.choice(self.character_list, size=length)
else:
valid_mask = charlist_mask == 1
valid_indexes = np.where(valid_mask)[0]
if len(valid_indexes) == 0:
if self.min_length == 0:
string = ""
else:
# Otherwise the string will not be contained in the space
raise ValueError(
f"Trying to sample with a minimum length > 0 ({self.min_length}) but the character mask is all zero meaning that no character could be sampled."
)
else:
string = "".join(
self.character_list[index]
for index in self.np_random.choice(valid_indexes, size=length)
)
return "".join(string)
def contains(self, x: Any) -> bool:
"""Return boolean specifying if x is a valid member of this space."""
if isinstance(x, str):
if self.min_length <= len(x) <= self.max_length:
return all(c in self.character_set for c in x)
return False
def __repr__(self) -> str:
"""Gives a string representation of this space."""
return (
f"Text({self.min_length}, {self.max_length}, characters={self.characters})"
)
def __eq__(self, other) -> bool:
"""Check whether ``other`` is equivalent to this instance."""
return (
isinstance(other, Text)
and self.min_length == other.min_length
and self.max_length == other.max_length
and self.character_set == other.character_set
)
@property
def character_set(self) -> FrozenSet[str]:
"""Returns the character set for the space."""
return self._char_set
@property
def character_list(self) -> Tuple[str, ...]:
"""Returns a tuple of characters in the space."""
return self._char_list
def character_index(self, char: str) -> np.int32:
"""Returns a unique index for each character in the space's character set."""
return self._char_index[char]
@property
def characters(self) -> str:
"""Returns a string with all Text characters."""
return self._char_str
@property
def is_np_flattenable(self) -> bool:
"""The flattened version is an integer array for each character, padded to the max character length."""
return True
| openai/gym | gym/spaces/text.py | text.py | py | 7,660 | python | en | code | 33,110 | github-code | 36 |
8919279602 | import subprocess
import json
import argparse
import os
import requests
args = None
def main():
global args
parser = argparse.ArgumentParser(
description='update cloudflare dns records')
parser.add_argument('Domain',
metavar='domain',
type=str,
help='domain to update')
parser.add_argument('--dryrun',
action='store_true',
help='dry run')
parser.add_argument('--kind',
action='store',
type=str,
default='A',
help='type of record, e.g. A')
parser.add_argument('--zone',
action='store',
type=str,
help='dns zone')
parser.add_argument('--id',
action='store',
type=str,
help='ID of record to update')
parser.add_argument('--email',
action='store',
type=str,
help='email')
parser.add_argument('--api-token',
action='store',
type=str,
help='API token')
parser.add_argument('--api-key',
action='store',
type=str,
help='API key')
parser.add_argument('--a-name',
action='store',
type=str,
help='record A name')
parser.add_argument('--a-ip',
action='store',
type=str,
help='record A IP')
args = parser.parse_args()
domain = args.Domain
if (args.api_token == None):
atoken = os.getenv('CF_API_TOKEN')
if (atoken == None):
print("can't find CF_API_TOKEN")
os.exit(1)
args.api_token = atoken
if (args.api_key == None):
akey = os.getenv('CF_API_KEY')
if (akey == None):
print("can't find CF_API_KEY")
os.exit(1)
args.api_key = akey
if (args.zone== None):
azone = os.getenv('CF_ZONE_ID')
if (azone== None):
print("can't find CF_ZONE_ID")
os.exit(1)
args.zone = azone
find_gcp_vms_ip(callback1)
def find_gcp_vms_ip(cb):
instances = subprocess.Popen(['gcloud', 'compute', 'instances', 'list', '--format=json'], stdout=subprocess.PIPE).communicate()[0]
instances2 = json.loads(instances.decode('utf-8').replace('\n', ' '))
for inst in instances2:
name = inst['name']
interface = inst['networkInterfaces'][0]
if (interface == None):
return
accessConfigs = interface['accessConfigs']
if (accessConfigs == None):
return
externalIP = accessConfigs[0]['natIP']
if (externalIP == None):
return
cb(name,externalIP)
def cloudflare_update(name,ip,domain):
url = f"https://api.cloudflare.com/client/v4/zones/{args.zone}/dns_records"
# print(url)
bearer_token = f"Bearer {args.api_token}"
headers = {
'Authorization': bearer_token,
'Content-Type': 'application/json',
'Accept': 'application/json'
}
# print(bearer_token)
# 'X-Auth-Email': f"{args.email}",
# 'X-Auth-Key': f"{args.api_key}",
response = requests.post(
url,
headers=headers,
data = {
'type': args.kind,
'name': name,
'content': ip,
'priority': 10,
'ttl':120,
'proxied':'false'
}
)
print(response.json())
def callback1(name,externalIP):
#print(args)
#print(name,externalIP)
cloudflare_update(name,externalIP,args.Domain)
if __name__ == "__main__":
main()
| bobbae/examples-2021 | Python/cloudflare/update_dns.py | update_dns.py | py | 4,011 | python | en | code | 3 | github-code | 36 |
34168133396 | from bs4 import BeautifulSoup
import requests
def wsearch(word):
word = word.replace(" ", "-")
url = f"https://dictionary.cambridge.org/dictionary/english/{word}"
user_agent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/42.0.2311.135 Safari/537.36 Edge/12.246'
headers = {'User-Agent': user_agent}
page = requests.get(url, headers=headers).text
doc = BeautifulSoup(page, 'html.parser')
try:
entries = doc.find(
class_="hfl-s lt2b lmt-10 lmb-25 lp-s_r-20 x han tc-bd lmt-20 english").find_all(class_="pr entry-body__el")
if entries == []:
# for a single entry
entries = doc.find(
class_="hfl-s lt2b lmt-10 lmb-25 lp-s_r-20 x han tc-bd lmt-20 english").find_all(class_="pr di superentry")
return entries
except AttributeError:
return None
def compileResult(entries):
id = 0
res = list()
for entry in entries:
# get the word
word = entry.find(class_="di-title").text
# get the word type
try:
wordType = entry.find(
True, class_="pos dpos").text
except AttributeError:
wordType = ''
# get the list of audio tags
audioTags = []
for tag in entry.find_all(class_="region dreg"):
audioTags.append(tag.text)
# get the list of audio links
audioLinks = []
for tag in entry.find_all('source', {"type": "audio/mpeg"}):
audioLinks.append("https://dictionary.cambridge.org" + tag['src'])
# merge the two lists
mergedAudioList = []
for tag, link in zip(audioTags, audioLinks):
mergedAudioList.append({"tag": tag,
"link": link})
groups = entry.find_all(class_="def-block ddef_block")
explanation = list()
for group in groups:
groupList = list()
groupText = group.find_all(
True, {"class": ["def ddef_d db", "eg deg"]})
for text in groupText:
c = ' '.join(text['class'])
if c == "def ddef_d db":
groupList.append(
{
"type": "main",
"content": text.text
}
)
elif c == "eg deg":
groupList.append(
{
"type": "example",
"content": text.text
}
)
explanation.append(groupList)
res.append(
{"id": id,
"word": word,
"wordType": wordType,
"audioLinks": mergedAudioList,
"explanation": explanation
}
)
id += 1
return res
if __name__ == "__main__":
entries = wsearch("hi")
res = compileResult(entries)
| Chris4496/TheDictionaryHubAPI | app/scrapers/cambridge.py | cambridge.py | py | 3,117 | python | en | code | 0 | github-code | 36 |
4134038538 | from random import sample
import numpy as np
from Dataset import *
from Vocabulary import *
from Config import *
class Generator:
@staticmethod
def data_generator(voc, gui_path,img_paths,batch_size,generate_binary_sequences=False,verbose=False,loop_only_once=False):
assert len(gui_path) == len(img_paths)
voc.binaryConvert()
while True:
batch_input_images = []
batch_partial_sequences = []
batch_next_words = []
sample_in_batch_counter = 0
for i in range(0,len(gui_path)):
if img_paths[i].find(".png") != -1:
img = Utils.imgPreprocess(img_paths[i],IMAGE_SIZE)
else:
img = np.load(img_paths[i])["features"]
gui = open(gui_path[i],'r')
token_sequence = [START_TOKEN]
for line in gui:
line = line.replace("," ," ,").replace("\n"," \n")
tokens = line.split(" ")
for token in tokens:
voc.append(token)
token_sequence.append(token)
token_sequence.append(END_TOKEN)
suffix = [PLACEHOLDER] * CONTEXT_LENGTH
a = np.concatenate([suffix,token_sequence])
for j in range(0,len(a) - CONTEXT_LENGTH):
context = a[j:j+CONTEXT_LENGTH]
label = a[j+CONTEXT_LENGTH]
batch_input_images.append(img)
batch_partial_sequences.append(context)
batch_next_words.append(label)
sample_in_batch_counter +=1
if sample_in_batch_counter == batch_size or (loop_only_once and i == len(gui_path)-1):
if verbose:
print("Generating sparse vectors...")
batch_next_words = Dataset.makeSparseLabels(batch_next_words,voc)
if generate_binary_sequences:
batch_partial_sequences = Dataset.createBinary(batch_partial_sequences,voc)
else:
batch_partial_sequences = Dataset.makeIndices(batch_partial_sequences,voc)
if verbose:
print("Converting things.. ")
batch_input_images = np.array(batch_input_images)
batch_partial_sequences = np.array(batch_partial_sequences)
batch_next_words = np.array(batch_next_words)
if verbose:
print("Yield batch...")
yield ([batch_input_images,batch_partial_sequences],batch_next_words)
batch_input_images = []
batch_partial_sequences = []
batch_next_words = []
sample_in_batch_counter = 0
| TismeetSingh14/AutoCode | Generator.py | Generator.py | py | 3,060 | python | en | code | 1 | github-code | 36 |
24855579355 | from ROOT import TFile, TH3D
import numpy as np
def SelectParticleMomentumFromHist() :
# Open file containing particle momentum distribution
file = TFile("threeD.root", "READ")
# Retrieve momentum distribution
hist = file.Get("threeDHist")
# Normalise histogram so that bin height represent probabilities
hist.Scale(1./hist.Integral())
# Pick a random number [0, 1) to use to select bin in momentum histogram
randomNum = np.random.uniform(0,1)
# Find associated bin in momentum histogram
cumulativeProb = 0
momentumXBinIndex = 0
momentumYBinIndex = 0
momentumZBinIndex = 0
found = False
for xBin in range(1, hist.GetXaxis().GetNbins() + 1, 1) :
if found :
break
for yBin in range(1, hist.GetYaxis().GetNbins() + 1, 1) :
if found :
break
for zBin in range(1, hist.GetZaxis().GetNbins() + 1, 1) :
cumulativeProb += hist.GetBinContent(xBin, yBin, zBin)
print("Bin Content: ", hist.GetBinContent(xBin, yBin, zBin))
print("Cumulative Prob: ", cumulativeProb)
if(cumulativeProb > randomNum) :
momentumXBinIndex = xBin
momentumYBinIndex = yBin
momentumZBinIndex = zBin
found = True
break;
# Select random momentum within this bin
xMomentum = np.random.uniform(hist.GetXaxis().GetBinLowEdge(momentumXBinIndex), hist.GetXaxis().GetBinLowEdge(momentumXBinIndex) + hist.GetXaxis().GetBinWidth(momentumXBinIndex))
yMomentum = np.random.uniform(hist.GetYaxis().GetBinLowEdge(momentumYBinIndex), hist.GetYaxis().GetBinLowEdge(momentumYBinIndex) + hist.GetYaxis().GetBinWidth(momentumYBinIndex))
zMomentum = np.random.uniform(hist.GetZaxis().GetBinLowEdge(momentumZBinIndex), hist.GetZaxis().GetBinLowEdge(momentumZBinIndex) + hist.GetZaxis().GetBinWidth(momentumZBinIndex))
print("X Momentum: ", xMomentum)
print("Y Momentum: ", yMomentum)
print("Z Momentum: ", zMomentum)
| imawby/EventGeneration | momentumFromHist.py | momentumFromHist.py | py | 2,093 | python | en | code | 0 | github-code | 36 |
70606542505 | import json
from wsgiref import simple_server
from wsgiref.simple_server import make_server
def load_html(file_name,**kwargs):
try:
with open(file_name,'r',encoding='utf-8') as file:
content = file.read()
if kwargs: # kwargs = {'username ': 'zhangsan ', 'age':19, 'gender': 'male'}
content = content.format(**kwargs)
# {username}, 迎回来,你今年{age}岁,你的性别是(gender}.format(**kwargs)
return content
except FileExistsError:
print('文件未找到')
# 第1个参数，表示环境（电脑的环境；请求路径相关的环境）
# 第2个参数，是一个函数，用来返回响应头
# 这个函数需要一个返回值，返回值是一个列表
# 列表里有一个元素，是一个二进制，表示返回给浏览器的数据
def demo_app(environ,start_response):
print(environ) # environ是一个字典，保存了很多数据
# 其中重要的一个是 PATH_INFO 能够获取到用户的访问路径
path = environ['PATH_INFO']
# print(environ. get('QUERY-STRING')) # QUERY_STRING ==> 获取到客户端GET请求方式传递的参数
# POST 请求数据的方式
# 状态码: RESTFUL ==> 前后端分离
# 2xx：请求响应成功
# 3Xx:重定向
# 4xx：客户端的错误。404客户端访问了一个不存在的地址 405:请求方式不被允许
# 5xx：服务器的错误。
status_code = '200 OK' # 默认状态码
if path == '/':
response = '欢迎来到我的首页'
elif path == '/test':
response = json.dumps({'name':'zhagnsna','age':18})
elif path == '/demo':
with open('hello1.txt','r',encoding='utf-8') as file:
response = file.read()
elif path == '/info':
# html 文件查询数据库，获取用户名
name = 'jack'
with open('info.html','r',encoding='utf-8') as file:
# '{username}，欢迎回来'.format(username=name)
# flask django 模块，渲染引擎
response = file.read().format(username=name,age=18,gender='男')
else:
status_code = '404 Not Found'
response = '页面走丢了'
print('path={}'.format(path))
start_response(status_code, [('Content-Type', 'text/plain; charset=utf-8'),('Connection', 'keep-alive')])
return [response.encode("utf-8")] # 浏览器显示的内容
if __name__ == '__main__':
# demo_app 是一个函数，用来处理用户的请求
httpd = make_server('', 8000, demo_app)
sa = httpd.socket.getsockname()
print("Serving HTTP on", sa[0], "port", sa[1], "...")
# 代码的作用是打开电脑的浏览器，并在浏览器里输入 http://localhost:8000/xyz?abc
# import webbrowser
# webbrowser.open('http://localhost:8000/xyz?abc')
# httpd.handle_request() # 只处理一次请求
httpd.serve_forever() # 服务器在后台一直运行 | cgyPension/pythonstudy_space | 01_base/$05_wsg服务器.py | $05_wsg服务器.py | py | 2,943 | python | zh | code | 7 | github-code | 36 |
36041433257 | #!/usr/bin/python
import httplib
import random
import argparse
import sys
#Get options
parser = argparse.ArgumentParser(
description='Testing vote app')
parser.add_argument(
'-port',
type=int,
help='port of server',
default=8000)
parser.add_argument(
'-host',
type=str,
help='server name/ip',
default="localhost")
args = parser.parse_args()
#Color table
colorList = ["blue", "orange", "red", "green", "yellow" ]
colorSize = len(colorList) - 1
#Connect with server
conn = httplib.HTTPConnection(args.host, args.port)
#initial request
conn.request("GET", "/")
r1 = conn.getresponse()
#print(r1.status, r1.reason)
print(r1.read())
#vote loop
count = 0
while count < 100 :
count = count + 1
nColor = random.randint(0, colorSize)
conn.request("GET", "/v1/vote?color="+colorList[nColor])
r1 = conn.getresponse()
#print(r1.read())
print
# view current results
conn.request("GET", "/v1/listVotes")
r1 = conn.getresponse()
print(r1.read())
conn.request("GET", "/v1/listWorkers")
r1 = conn.getresponse()
print(r1.read())
conn.close() | JoseIbanez/testing | redis/p02-vote/client/c02.py | c02.py | py | 1,136 | python | en | code | 3 | github-code | 36 |
16252978279 | #!/usr/bin/env python3
import time, RPi.GPIO as GPIO
GPIO.setmode(GPIO.BCM)
GPIO.setup(26, GPIO.OUT)
i=0
while True:
while i<10:
i+=1
LEDon = GPIO.output(26, 1)
time.sleep(0.5)
LEDoff = GPIO.output(26,0)
time.sleep(0.5)
| jack23574372/Adafruit_Python_DHT2 | blink11.py | blink11.py | py | 234 | python | en | code | 0 | github-code | 36 |
27940912517 | #!/usr/bin/env python3
"""A mere list of phrases that may be used for the game"""
#Phrases were taken from: https://wofanswers.com/phrase
string_list = [
"ALONE IN A CROWD",
"WITHIN THE REALM OF POSSIBILITY",
"YOU READ MY MIND",
"YOUVE NEVER LOOKED BETTER",
"ZERO GRAVITY",
]
| Sebastiaan35/Techdegree-developer---Project-3 | phrasehunter/phrase_list.py | phrase_list.py | py | 313 | python | en | code | 0 | github-code | 36 |
23331780439 | from utility_functions import *
import matplotlib.pyplot as plt
def lemke_optimizer_sparse(eco, payoff_matrix = None, dirac_mode = True):
A = np.zeros((eco.populations.size, eco.populations.size * eco.layers))
for k in range(eco.populations.size):
A[k, k * eco.layers:(k + 1) * eco.layers] = -1
q = np.zeros(eco.populations.size + eco.populations.size * eco.layers)
q[eco.populations.size * eco.layers:] = -1
q = q.reshape(-1, 1)
if payoff_matrix is None:
payoff_matrix = total_payoff_matrix_builder(eco)
H = np.block([[-payoff_matrix, A.T], [-A, np.zeros((A.shape[0], eco.populations.size))]])
lcp = sn.LCP(H, q)
ztol = 1e-8
#solvers = [sn.SICONOS_LCP_PGS, sn.SICONOS_LCP_QP,
# sn.SICONOS_LCP_LEMKE, sn.SICONOS_LCP_ENUM]
z = np.zeros((eco.layers*eco.populations.size+eco.populations.size,), np.float64)
w = np.zeros_like(z)
options = sn.SolverOptions(sn.SICONOS_LCP_PIVOT)
#sn.SICONOS_IPARAM_MAX_ITER = 10000000<
options.iparam[sn.SICONOS_IPARAM_MAX_ITER] = 1000000
options.dparam[sn.SICONOS_DPARAM_TOL] = 10**(-5)
info = sn.linearComplementarity_driver(lcp, z, w, options)
if sn.lcp_compute_error(lcp,z,w, ztol) > 10**(-5):
print(sn.lcp_compute_error(lcp,z,w, ztol), "Error")
return z
#@njit(parallel = True)
def total_payoff_matrix_builder_sparse(eco, current_layered_attack = None, dirac_mode = False):
total_payoff_matrix = np.zeros((eco.populations.size*eco.layers, eco.populations.size*eco.layers))
if current_layered_attack is None:
current_layered_attack = eco.parameters.layered_attack
for i in range(eco.populations.size):
for j in range(eco.populations.size):
if i != j:
i_vs_j = payoff_matrix_builder(eco, i, j, current_layered_attack = current_layered_attack, dirac_mode = dirac_mode)
elif i == j:
i_vs_j = np.zeros((eco.layers, eco.layers))
#if i == 1:
# total_payoff_matrix[i*eco.layers:(i+1)*eco.layers, j*eco.layers: (j+1)*eco.layers] = i_vs_j.T
#else:
total_payoff_matrix[i * eco.layers:(i + 1) * eco.layers, j * eco.layers: (j + 1) * eco.layers] = i_vs_j
# print("MAXIMM PAYDAY ORIGINAL", np.max(total_payoff_matrix))
total_payoff_matrix[total_payoff_matrix != 0] = total_payoff_matrix[total_payoff_matrix != 0] - np.max(total_payoff_matrix) #- 1 #Making sure everything is negative #- 0.00001
#total_payoff_matrix = total_payoff_matrix/np.max(-total_payoff_matrix)
print(np.where(total_payoff_matrix == 0))
return total_payoff_matrix
depth = 45
layers = 100
segments = 1
size_classes = 2
lam = 100
simulate = False
verbose = True
l2 = False
min_attack_rate = 10**(-3)
mass_vector = np.array([0.05, 0.05*408]) # np.array([1, 30, 300, 400, 800, 16000])
obj = spectral_method(depth, layers, segments=segments)
logn = stats.lognorm.pdf(obj.x, 1, 0)
norm_dist = stats.norm.pdf(obj.x, loc=0, scale=3)
res_start = 4*norm_dist # 0.1*(1-obj.x/depth)
res_max = 8*norm_dist
water_start = water_column(obj, res_start, layers=layers * segments, resource_max=res_max, replacement=lam, advection=0,
diffusion=0, logistic = True)
params = ecosystem_parameters(mass_vector, obj, lam=0.3, min_attack_rate = min_attack_rate, forage_mass = 0.05/408)
params.handling_times = np.zeros(2)
eco = ecosystem_optimization(mass_vector, layers * segments, params, obj, water_start, l2=l2, movement_cost=0)
eco.population_setter(np.array([1, 0.05]))
eco.heat_kernel_creator(10**(-1))
eco.heat_kernels[1] = eco.heat_kernels[0]
S = lemke_optimizer_sparse(eco, total_payoff_matrix_builder_sparse(eco))
S1 = lemke_optimizer(eco)
plt.plot(eco.spectral.x, S[0:layers]@eco.heat_kernels[0])
plt.plot(eco.spectral.x, S[layers:2*layers]@eco.heat_kernels[0])
S2 = quadratic_optimizer(eco, payoff_matrix=total_payoff_matrix_builder_sparse(eco))
S3 = quadratic_optimizer(eco)
plt.show()
plt.plot(eco.spectral.x, S1[0:layers]@eco.heat_kernels[0])
plt.plot(eco.spectral.x, S1[layers:2*layers]@eco.heat_kernels[0])
plt.show()
plt.plot(eco.spectral.x, S2[0:layers]@eco.heat_kernels[0])
plt.plot(eco.spectral.x, S2[layers:2*layers]@eco.heat_kernels[0])
plt.show()
plt.plot(eco.spectral.x, S3[0:layers]@eco.heat_kernels[0])
plt.plot(eco.spectral.x, S3[layers:2*layers]@eco.heat_kernels[0])
plt.show() | jemff/food_web | old_sims/sparse_testing.py | sparse_testing.py | py | 4,391 | python | en | code | 0 | github-code | 36 |
43231808566 | """
<风格>复古</风格>的旗袍款式
1. 先分词，再标签。
"""
import os
import re
from transformers import BertTokenizer
from collections import defaultdict, Counter
PATTEN_BIO = re.compile('<?.*>?')
def parse_tag_words(subwords):
""" HC<领型>圆领</领型><风格>拼接</风格>连衣裙 """
tags = []
new_subwords = []
i = 0
entity = ''
while i < len(subwords):
if subwords[i] == '<':
if entity == '': # <领型>
for j in range(i + 1, len(subwords)):
if subwords[j] == '>':
break
entity += subwords[j]
else: # </领型>
for j in range(i + 1, len(subwords)):
if subwords[j] == '>':
break
entity = ''
i = j + 1
continue
if entity != '': # 圆领
for j in range(i, len(subwords)):
if subwords[j] == '<':
i = j
break
new_subwords.append(subwords[j])
if j == i:
tags.append('B-' + entity)
else:
tags.append('I-' + entity)
continue
tags.append('O')
new_subwords.append(subwords[i])
i = i + 1
return new_subwords, tags
def bpe(part='train', export_dict=False):
all_tags = []
data_dir = '/workspace/fairseq/data/JD/kb_ner'
bpe_dir = data_dir + '/bpe'
bpe = BertTokenizer('/workspace/fairseq/data/vocab/vocab.jd.txt') # never_split参数对tokenizer不起作用
f_src = open(os.path.join(bpe_dir, part + '.src'), 'w', encoding='utf-8')
f_tgt = open(os.path.join(bpe_dir, part + '.tgt'), 'w', encoding='utf-8')
for line in open(data_dir + '/raw/jdai.jave.fashion.' + part, 'r', encoding='utf-8'):
cid, sid, sent, tag_sent = line.strip().split('\t')
subwords = bpe._tokenize(tag_sent)
subwords, tags = parse_tag_words(subwords)
f_src.write(' '.join(subwords) + '\n')
f_tgt.write(' '.join(tags) + '\n')
all_tags += tags
if export_dict:
with open(os.path.join(bpe_dir, 'vocab.tgt.txt'), 'w', encoding='utf-8') as f_out:
f_out.write('\n'.join([k for k, cnt in Counter(all_tags).items()]) + '\n')
def find_all_entity():
all_tag_sent = []
for line in open('raw/jdai.jave.fashion.train', 'r', encoding='utf-8'):
cid, sid, sent, tag_sent = line.strip().split('\t')
all_tag_sent.append(tag_sent)
entity_list = re.findall('<.*?>', ''.join(all_tag_sent))
aa = Counter(entity_list)
f_out = open('raw/vocab_bioattr.txt', 'w', encoding='utf-8')
f_out.write(''.join(['{}\t{}\n'.format(k, cnt) for k, cnt in aa.items()]))
if __name__ == "__main__":
bpe('train', export_dict=True)
bpe('valid')
bpe('test')
| WaveLi123/m-kplug | m_kplug/data_process/bpe_kb_encoder.py | bpe_kb_encoder.py | py | 2,910 | python | en | code | 4 | github-code | 36 |
16132606164 | # -*- coding: utf-8 -*-
"""
Created on Tue Feb 18 10:01:52 2020
@author: Ferhat
"""
from flask import Flask, jsonify, json, Response,make_response,request
from flask_cors import CORS
# =============================================================================
# from flask_cors import cross_origin
# =============================================================================
import numpy as np
import cv2
#from flask.ext.httpauth import HTTPBasicAuth
# =============================================================================
# from luminoso_api import LuminosoClient
# from luminoso_api.errors import LuminosoError, LuminosoClientError
# from luminoso_api.json_stream import open_json_or_csv_somehow
# from werkzeug.datastructures import ImmutableMultiDict
# =============================================================================
import logging
import random
app = Flask(__name__, static_url_path = "")
CORS(app)
file_handler = logging.FileHandler('app.log')
app.logger.addHandler(file_handler)
app.logger.setLevel(logging.INFO)
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)
def return_img(new_img,name):
random_value = random.randrange(1000)
path1 ='newImage'+str(random_value)+'.png'
path2 = 'C:/xampp/htdocs/python/'+path1
cv2.imwrite(path2,new_img)
data = {
'imgNew' : path1,
'desc' : name
}
return data
def convol(img):
kernel = np.ones((5,5),np.float32)/25
dst = cv2.filter2D(img,-1,kernel)
return return_img(dst,"Convolution")
def averaging(img):
blur = cv2.blur(img,(5,5))
return return_img(blur,"Averaging")
def gaus_filter(img):
blur = cv2.GaussianBlur(img,(5,5),0)
return return_img(blur,"Gaussian Filtering")
def median(img):
median = cv2.medianBlur(img,5)
return return_img(median,"Median Filtering")
def bilateral(img):
blur = cv2.bilateralFilter(img,9,75,75)
return return_img(blur,"Bilateral Filtering")
def binary(img):
ret,thresh_binary = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
return return_img(thresh_binary,"THRESH_BINARY ")
def binary_inv(img):
ret,thresh_binary_inv= cv2.threshold(img,127,255,cv2.THRESH_BINARY_INV)
return return_img(thresh_binary_inv,"THRESH Binary Inv")
def tozero(img):
ret,thresh_tozero = cv2.threshold(img,127,255,cv2.THRESH_TOZERO)
return return_img(thresh_tozero,"THRESH Tozero")
def trunc(img):
ret,thresh_trunc = cv2.threshold(img,127,255,cv2.THRESH_TRUNC)
return return_img(thresh_trunc,"THRESH Trunc")
def trunc_inv(img):
ret,thresh_trunc_inv = cv2.threshold(img,127,255,cv2.THRESH_TOZERO_INV)
return return_img(thresh_trunc_inv,"THRESH Tozero Inv")
@app.errorhandler(400)
def not_found(error):
app.logger.error('Bad Request - 400')
return make_response(jsonify( { 'error': 'Bad request' } ), 400)
@app.route('/image_process', methods = ['GET','POST'])
def get_test():
img_Path = request.args.get('img_path')
img_type = request.args.get('img_type')
image = cv2.imread(img_Path,0)
if img_type == "convol":
data = convol(image)
elif img_type == "averaging":
data = averaging(image)
elif img_type == "gaus_filter":
data = gaus_filter(image)
elif img_type == "median":
data = median(image)
elif img_type == "bilateral":
data = bilateral(image)
elif img_type == "binary":
data = binary(image)
elif img_type == "binary_inv":
data = binary_inv(image)
elif img_type == "trunc":
data = trunc(image)
elif img_type == "tozero":
data = tozero(image)
elif img_type == "trunc_inv":
data = trunc_inv(image)
else:
data = return_img(image,"No Image")
js = json.dumps(data)
resp = Response(js, status=200, mimetype='application/json')
resp.headers['Link'] = 'https://localhost/python/'
return resp
# return "ECHO: GET\n"
if __name__ == "__main__":
app.run(debug=True)
| RamazanFerhatSonmez/Image-Processing-Python | rest-server.py | rest-server.py | py | 4,161 | python | en | code | 0 | github-code | 36 |
10663938377 | # -*- coding: utf-8 -*-
"""
Created on Fri Sep 16 22:56:22 2016
@author: Neo
Rotation Componets fitting.
Fitting Equation:
d_pmRA = -w_x*sin(DE)*cos(RA) - w_y*sin(DE)*sin(RA) + w_z*cos(DE)
d_pmDE = +w_x*sin(RA) - w_y*cos(RA)
Oct 21 2016: updated by Niu
"""
import numpy as np
sin = np.sin
cos = np.cos
pi = np.pi
def RotationFit(pmRA,pmDE,e_pmRA,e_pmDE,RA,DE):
## Notice !!!
## unit for RA and DE are rad.
## partial of d_pmRA, d_pmDE with respect to w_x, w_y, w_z
N = pmRA.size
parx1 = -sin(DE)*cos(RA)
pary1 = -sin(DE)*sin(RA)
parz1 = cos(DE)
parx2 = sin(RA)
pary2 = -cos(RA)
parz2 = np.zeros(N)
wei1 = np.diag(e_pmRA**-2)
wei2 = np.diag(e_pmDE**-2)
F1T = np.vstack((parx1, pary1, parz1))
F1 = np.transpose(F1T)
F2T = np.vstack((parx2, pary2, parz2))
F2 = np.transpose(F2T)
a1 = np.dot(np.dot(F1T, wei1), F1)
b1 = np.dot(np.dot(F1T, wei1), pmRA)
a2 = np.dot(np.dot(F2T, wei2), F2)
b2= np.dot(np.dot(F2T, wei2), pmDE)
A = a1 + a2
b = b1 + b2
w = np.linalg.solve(A, b)
cov = np.linalg.inv(A)
sig = np.sqrt(cov.diagonal())
corrcoef = np.array([ cov[i,j]/sig[i]/sig[j] \
for j in range(len(w)) for i in range(len(w))])
corrcoef.resize((len(w), len(w)))
return w, sig, corrcoef
def Elim(pmRAs,pmDEs, e_pmRA,e_pmDE, n):
a = np.abs(pmRAs) - n*e_pmRA
b = np.abs(pmDEs) - n*e_pmDE
indice1 = np.where(a<0)
indice2 = np.where(b<0)
indice = np.intersect1d(indice1, indice2)
return indice
#def NormalRotation(pmRA,pmDE,e_pmRA,e_pmDE,RA,DE):
# w, sig, corrcoef = RotationFit(pmRA,pmDE,e_pmRA,e_pmDE,RA,DE)
### Calculate the fitting values.
# wx = w[0]
# wy = w[1]
# wz = w[2]
# pmRAf = -sin(DE)*cos(RA)*wx-sin(DE)*sin(RA)*wy+cos(DE)*wz
# pmDEf = sin(RA)*wx-cos(RA)*wy
### residuals
# pmRAs = pmRAf - pmRA
# pmDEs = pmDEf - pmDE
# ## generate the new array after eliminating outliers
# n = 2.6
# indice = Elim(pmRAs,pmDEs, e_pmRA,e_pmDE, n)
# npmRA = np.take(pmRA, indice)
# npmDE = np.take(pmDE, indice)
# nRA = np.take(RA, indice)
# nDE = np.take(DE, indice)
# ne_pmRA = np.take(e_pmRA, indice)
# ne_pmDE = np.take(e_pmDE, indice)
# w, sig, corrcoef = RotationFit(npmRA,npmDE,ne_pmRA,ne_pmDE,nRA,nDE)
# return w, sig, corrcoef
def MeanWeiRotation(pmRA,pmDE, RA,DE):
### First Loop, calculate the mean error without weights.
N = pmRA.size
w, sig, corrcoef = RotationFit(pmRA,pmDE,np.ones(N),np.ones(N),RA,DE)
## Calculate the residuals
wx = w[0]
wy = w[1]
wz = w[2]
pmRAf = -sin(DE)*cos(RA)*wx -sin(DE)*sin(RA)*wy +cos(DE)*wz
pmDEf = sin(RA)*wx -cos(RA)*wy
## residuals
pmRAs = pmRAf - pmRA
pmDEs = pmDEf - pmDE
wrmsRA = np.sqrt(np.sum(pmRAs**2)/(len(pmRAs)-1))
wrmsDE = np.sqrt(np.sum(pmDEs**2)/(len(pmRAs)-1))
wrms = np.sqrt((wrmsRA**2 + wrmsDE**2)/2)
## generate the new array after eliminating outliers
n = 2.6
indice = Elim(pmRAs,pmDEs, wrms*np.ones(len(pmRAs)),wrms*np.ones(len(pmRAs)), n)
npmRA = np.take(pmRA, indice)
npmDE = np.take(pmDE, indice)
nRA = np.take(RA, indice)
nDE = np.take(DE, indice)
w, sig, corrcoef = RotationFit(npmRA,npmDE,np.ones(len(npmRA)),np.ones(len(npmDE)),nRA,nDE)
## Calculate the residuals
wx = w[0]
wy = w[1]
wz = w[2]
pmRAf = -sin(DE)*cos(RA)*wx -sin(DE)*sin(RA)*wy +cos(DE)*wz
pmDEf = sin(RA)*wx -cos(RA)*wy
## residuals
pmRAs = pmRAf - pmRA
pmDEs = pmDEf - pmDE
wrmsRA = np.sqrt(np.sum(pmRAs**2)/(len(pmRAs)-1))
wrmsDE = np.sqrt(np.sum(pmDEs**2)/(len(pmRAs)-1))
wrms = np.sqrt((wrmsRA**2 + wrmsDE**2)/2)
merr = wrms
# ## Next, apply the weigths of 1/M_err**2
w, sig, corrcoef = RotationFit(pmRA,pmDE,np.ones(len(pmRA))*merr,\
np.ones(len(pmRA))*merr, RA, DE)
# ## Calculate the residuals
# wx = w[0]
# wy = w[1]
# wz = w[2]
#
# pmRAf = -sin(DE)*cos(RA)*wx-sin(DE)*sin(RA)*wy+cos(DE)*wz
# pmDEf = sin(RA)*wx-cos(RA)*wy
#
# ## residuals
# pmRAs = pmRAf - pmRA
# pmDEs = pmDEf - pmDE
#
# ## eliminating outliers again
# n = 2.6
# indice = Elim(pmRAs,pmDEs, np.ones(len(pmRA))*merr, np.ones(len(pmRA))*merr, n)
# npmRA = np.take(pmRA, indice)
# npmDE = np.take(pmDE, indice)
# nRA = np.take(RA, indice)
# nDE = np.take(DE, indice)
# w, sig, corrcoef = RotationFit(npmRA,npmDE,np.ones(len(npmRA))*merr,np.ones(len(npmDE))*merr,nRA,nDE)
return w, sig, corrcoef | Niu-Liu/thesis-materials | sou-selection/progs/RotationFit.py | RotationFit.py | py | 4,791 | python | en | code | 0 | github-code | 36 |
4836908641 | import socket
fwq = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
fwq.bind(('localhost', 9090))
print('Начать чат! ')
while True:
data, addr = fwq.recvfrom(1024)
recvmsg = data.decode('utf-8')
if recvmsg == 'exit!':
print("Участник" + str(addr) + "добровольно закончил чат с тобой, пока!")
continue
elif recvmsg == 'login!':
print("Пользователь " + str(addr) + " регистрируется")
print(str(addr) + ' client msg: ' + recvmsg)
replymsg = input('Ответить: ')
fwq.sendto(replymsg.encode('utf-8'), addr)
fwq.close()
| wwatchenjoy/python-practic-2-BogdanovDA | server.py | server.py | py | 685 | python | ru | code | 0 | github-code | 36 |
36840226069 | """Test hook for verifying data consistency across a replica set.
Unlike dbhash.py, this version of the hook runs continously in a background thread while the test is
running.
"""
import os.path
from buildscripts.resmokelib import errors
from buildscripts.resmokelib.testing.hooks import jsfile
from buildscripts.resmokelib.testing.hooks.background_job import _BackgroundJob, _ContinuousDynamicJSTestCase
class CheckReplDBHashInBackground(jsfile.JSHook):
"""A hook for comparing the dbhashes of all replica set members while a test is running."""
IS_BACKGROUND = True
def __init__(self, hook_logger, fixture, shell_options=None):
"""Initialize CheckReplDBHashInBackground."""
description = "Check dbhashes of all replica set members while a test is running"
js_filename = os.path.join("jstests", "hooks", "run_check_repl_dbhash_background.js")
jsfile.JSHook.__init__(self, hook_logger, fixture, js_filename, description,
shell_options=shell_options)
self._background_job = None
def before_suite(self, test_report):
"""Start the background thread."""
client = self.fixture.mongo_client()
# mongos does not provide storageEngine information. And the hook
# run_check_repl_dbhash_background.js will check whether the storage engine of the CSRS and
# replica set shards supports snapshot reads.
if not client.is_mongos:
server_status = client.admin.command("serverStatus")
if not server_status["storageEngine"].get("supportsSnapshotReadConcern", False):
self.logger.info(
"Not enabling the background check repl dbhash thread because '%s' storage"
" engine doesn't support snapshot reads.",
server_status["storageEngine"]["name"])
return
self._background_job = _BackgroundJob("CheckReplDBHashInBackground")
self.logger.info("Starting the background check repl dbhash thread.")
self._background_job.start()
def after_suite(self, test_report, teardown_flag=None):
"""Signal the background thread to exit, and wait until it does."""
if self._background_job is None:
return
self.logger.info("Stopping the background check repl dbhash thread.")
self._background_job.stop()
def before_test(self, test, test_report):
"""Instruct the background thread to run the dbhash check while 'test' is also running."""
if self._background_job is None:
return
hook_test_case = _ContinuousDynamicJSTestCase.create_before_test(
test.logger, test, self, self._js_filename, self._shell_options)
hook_test_case.configure(self.fixture)
self.logger.info("Resuming the background check repl dbhash thread.")
self._background_job.resume(hook_test_case, test_report)
def after_test(self, test, test_report): # noqa: D205,D400
"""Instruct the background thread to stop running the dbhash check now that 'test' has
finished running.
"""
if self._background_job is None:
return
self.logger.info("Pausing the background check repl dbhash thread.")
self._background_job.pause()
if self._background_job.exc_info is not None:
if isinstance(self._background_job.exc_info[1], errors.TestFailure):
# If the mongo shell process running the JavaScript file exited with a non-zero
# return code, then we raise an errors.ServerFailure exception to cause resmoke.py's
# test execution to stop.
raise errors.ServerFailure(self._background_job.exc_info[1].args[0])
else:
self.logger.error(
"Encountered an error inside the background check repl dbhash thread.",
exc_info=self._background_job.exc_info)
raise self._background_job.exc_info[1]
| mongodb/mongo | buildscripts/resmokelib/testing/hooks/dbhash_background.py | dbhash_background.py | py | 4,041 | python | en | code | 24,670 | github-code | 36 |
37697513017 |
import streamlit as st
from streamlit_option_menu import option_menu
from pages import home, dashboard, login
class MultiApp:
def __init__(self):
self.apps = []
def add_app(self, title, func):
self.apps.append({
"title": title,
"function": func
})
def run():
# app = st.sidebar(
with st.sidebar:
app = option_menu(
menu_title='Navigation',
options=['Home','Dashboard','Login'],
icons=['house','book','envelope'],
menu_icon='cast',
default_index=0,
)
if app == "Home":
home.app()
if app == "Dashboard":
dashboard.app()
if app == "Login":
login.app()
run()
| Ashwani132003/Attendace-Tracker-using-Face-recognition | main.py | main.py | py | 976 | python | en | code | 0 | github-code | 36 |
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