Правильно ли я генерирую список случайно назначенных пар с исключениями в Python? ⇐ Python

[Anonymous]

У меня есть множество имен и ролей людей в компании:
пример массив: < /p>
names_and_titles = [
("Samantha Reyes", "Innovation", "Product Owner"),
("Ethan McAllister", "Data Scientist"),
("Priya Deshmukh", "Data Architect", "SMT"),
("Marcus Liu", "Stream 3"),
("Elena Petrova", "SMT", "Stream 3"),
]
< /code>
У меня также есть файл CSV со всеми предыдущими парами, которые были сгенерированы. «Маркус Лю» и «Елена Петрова» не могут быть соединены вместе, поскольку они разделяют ту же роль «Поток 3».import random
import pandas as pd

# An array of all names and titles
names_and_titles = [
("Samantha Reyes", "Innovation", "Product Owner"),
("Ethan McAllister", "Data Scientist"),
("Priya Deshmukh", "Data Architect", "SMT"),
("Marcus Liu", "Stream 3"),
("Elena Petrova", "SMT", "Stream 3"),
]

# Load previously generated pairs from the CSV file
def load_seen_pairs_from_csv(prev_pairs2):
df = pd.read_csv(prev_pairs2)
seen_pairs = set()
for _, row in df.iterrows():
pair = (row['name1'], row['name2'])
reverse_pair = (row['name2'], row['name1'])
seen_pairs.add(pair)
seen_pairs.add(reverse_pair)
return seen_pairs

# Save new pairs to the CSV file
def save_pairs_to_csv(prev_pairs2, pairs):
df = pd.DataFrame(pairs, columns=['name1', 'name2'])
df.to_csv(prev_pairs2, index=False, mode='a', header=False)

# Path to the CSV file containing previously generated pairs
csv_file_path = 'prev_pairs2.csv'

# Initialize the seen_pairs set with previously created pairs
seen_pairs = load_seen_pairs_from_csv(csv_file_path)

# Excluded pairs for pairing logic
excluded_pairs = []

def create_unique_pairs_with_debugging_and_fallback(names_and_titles, seen_pairs, excluded_pairs):
excluded_set = set(excluded_pairs) | set((pair[1], pair[0]) for pair in excluded_pairs) # Include reverse pairs
max_retries = 10000 # Increase the number of retries to improve pairing chances
retries = 0

while retries < max_retries:
random.shuffle(names_and_titles)
pairs = []
used_names = set() # Track names already paired in this run
skipped = [] # Track skipped individuals for debugging

for i in range(0, len(names_and_titles) - 1, 2):
person1, person2 = names_and_titles, names_and_titles[i + 1]
roles1 = set(person1[2:]) if len(person1) > 2 else set() # Handle blank roles
roles2 = set(person2[2:]) if len(person2) > 2 else set() # Handle blank roles
pair = (person1[0], person2[0])
reverse_pair = (person2[0], person1[0])

# Debugging: Log why pairs are skipped
if pair in excluded_set or reverse_pair in excluded_set:
print(f"Skipping pair due to exclusion: {person1[0]} - {person2[0]}")
continue
if pair in seen_pairs or reverse_pair in seen_pairs:
print(f"Skipping pair due to seen pair: {person1[0]} - {person2[0]}")
continue
if roles1 & roles2: # Skip if roles overlap
print(f"Skipping pair due to role overlap: {person1[0]} ({roles1}) - {person2[0]} ({roles2})")
continue
if person1[0] in used_names or person2[0] in used_names: # Avoid duplicate pairings in this run
print(f"Skipping pair due to duplicate usage: {person1[0]} - {person2[0]}")
continue

pairs.append((person1, person2))
used_names.update([person1[0], person2[0]]) # Mark names as used

# Add skipped individuals to the next round
skipped = [person for person in names_and_titles if person[0] not in used_names]
if not skipped: # If no one is skipped, pairing is complete
pairs_set = set((pair[0][0], pair[1][0]) for pair in pairs)
if not any((pair in seen_pairs or (pair[1], pair[0]) in seen_pairs) for pair in pairs_set):
seen_pairs.update(pairs_set)
return pairs

retries += 1

# If retries are exhausted, raise an error with debugging information
print("Unable to generate unique pairs with the given restrictions.")
print(f"Skipped individuals: {[person[0] for person in skipped]}")
raise ValueError("Unable to generate unique pairs with the given restrictions.")

# Generate unique pairs with debugging and fallback logic
unique_pairs = create_unique_pairs_with_debugging_and_fallback(names_and_titles, seen_pairs, excluded_pairs)

# Print the unique pairs with names only
for pair in unique_pairs:
print(f"{pair[0][0]} - {pair[1][0]}")
print("-----")

# Print the total number of pairs
print(f"Total pairs: {len(unique_pairs)}")

# Save the unique pairs to the CSV file
save_pairs_to_csv(csv_file_path, [(pair[0][0], pair[1][0]) for pair in unique_pairs])
< /code>
Я ожидал, что мне предоставлены список пар, которые являются уникальными и не разделяют ту же роль. Однако я генерирую список пар, в которых несколько пар имеют одну и ту же роль.name1,name2
Ava Thompson,Noah Bennett
Liam Carter,Zara Mahmood
Maya Chen,Oliver Grant
Nina Kowalski,Tomás Rivera
Rajiv Mehta,Grace O'Connor
Daniel Okoro,Isla McKenzie


Подробнее здесь: https://stackoverflow.com/questions/797 ... sions-in-p