text stringlengths 1 93.6k |
|---|
for src_eq, src_tabular_dataset_file_path in zip(src_eqs, src_tabular_dataset_file_paths):
|
p = Process(
|
target=check_if_overlapped if mode == 'overlap' else assess_domain_intersections_if_overlapped,
|
args=(src_tabular_dataset_file_path, src_eq, src_delimiter,
|
dst_eq_trees, dst_tabular_dataset_file_paths, dst_delimiter, result_dict)
|
)
|
p.start()
|
process_list.append(p)
|
for p in process_list:
|
p.join()
|
if mode == 'overlap':
|
print(f'{len(result_dict)} overlapped source datasets')
|
overlapped_list = list()
|
for sub_list in result_dict.values():
|
overlapped_list.extend(sub_list)
|
print(f'{len(overlapped_list)} overlapped destination datasets')
|
unique_overlapped_set = set(overlapped_list)
|
unique_size = len(unique_overlapped_set)
|
print(f'{unique_size} ({unique_size / len(dst_eqs) * 100}%) unique overlapped destination datasets')
|
elif mode == 'intersection':
|
num_keys = len(result_dict)
|
mean_results = np.array([r.mean() for r in result_dict.values()])
|
print(f'{num_keys} source equations match some destination ones')
|
average_results_over_matched_src = mean_results.mean()
|
print(f'Intersection averaged over matched src equations: {average_results_over_matched_src}')
|
average_results_over_all_src = mean_results.sum() / len(src_eqs)
|
print(f'Intersection averaged over all src equations: {average_results_over_all_src}')
|
def main(args):
|
print(args)
|
src_eq_file_paths = get_file_path_list(os.path.expanduser(args.src_eq), is_sorted=True)
|
src_tabular_dataset_file_paths = get_file_path_list(os.path.expanduser(args.src_tabular), is_sorted=True)
|
assert len(src_eq_file_paths) == len(src_tabular_dataset_file_paths)
|
src_eqs = [load_sympy_equation(file_path) for file_path in src_eq_file_paths]
|
dst_eq_file_paths = get_file_path_list(os.path.expanduser(args.dst_eq), is_sorted=True)
|
dst_tabular_dataset_file_paths = get_file_path_list(os.path.expanduser(args.dst_tabular), is_sorted=True)
|
assert len(dst_eq_file_paths) == len(dst_tabular_dataset_file_paths)
|
dst_eqs = [load_sympy_equation(file_path) for file_path in dst_eq_file_paths]
|
compare_datasets(src_eqs, src_tabular_dataset_file_paths, args.src_delim,
|
dst_eqs, dst_tabular_dataset_file_paths, args.dst_delim, args.mode)
|
if __name__ == '__main__':
|
argparser = get_argparser()
|
main(argparser.parse_args())
|
# <FILESEP>
|
# Versoin: 1.2
|
# Author: evilfeonix
|
# Name: WhatsApp Crashing Tool
|
# Website: www.evilfeonix.com
|
# Email: evilfeonix@gmail.com
|
# Latest Update: 10 - FEBUARY - 2025
|
###### Welcoming to WhatsApp Crasher...
|
###### your ultimate tool to crash and sustain any whatsapp users, groups, and channels,
|
###### by just sending them malicious message.
|
import os, sys, time, urllib
|
from socket import *
|
import json
|
ipaddr = gethostbyname(gethostname())
|
max_data = (((707+111+1011)*3)-1396)+5 #4096
|
white="\033[0m"
|
bg="\033[49m"
|
red="\033[91;1m"
|
blue="\033[94;1m"
|
green="\033[92;1m"
|
purple="\033[95;1m"
|
def slow(F3):
|
for a in F3 + '\n':sys.stdout.write(a),sys.stdout.flush(),time.sleep(1./300)
|
def internet():
|
try:
|
s = socket(AF_NET, SOCK_STREAM)
|
s.connect_ex(("www.google.com",80))
|
return True
|
except Exception:return False
|
def aboutus():
|
slow(" Tool Name : Whats Crash")
|
slow(" Version : v[1.2]")
|
slow(" Author : evilfeonix")
|
slow(" Github : Digital Firebird")
|
slow(" Youtube : Digital Firebird")
|
slow(" Latest Update : 10 - FEB - 2025")
|
slow(f"==========================================================={white}\n")
|
def banner():
|
os.system("cls || clear")
|
slow(f"""{red}
|
_ _ _ _ ____ _
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.