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162
.gitignore vendored Normal file
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# ---> Python
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
.pybuilder/
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version
# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock
# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock
# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/#use-with-ide
.pdm.toml
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/
# Celery stuff
celerybeat-schedule
celerybeat.pid
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
# pytype static type analyzer
.pytype/
# Cython debug symbols
cython_debug/
# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/

10
.idea/.gitignore generated vendored
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# Default ignored files
/shelf/
/workspace.xml
# Ignored default folder with query files
/queries/
# Datasource local storage ignored files
/dataSources/
/dataSources.local.xml
# Editor-based HTTP Client requests
/httpRequests/

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1
.idea/misc.xml generated
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<component name="Black"> <component name="Black">
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8
.idea/modules.xml generated
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<?xml version="1.0" encoding="UTF-8"?>
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<module fileurl="file://$PROJECT_DIR$/.idea/PythonProject1.iml" filepath="$PROJECT_DIR$/.idea/PythonProject1.iml" />
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2
.idea/vcs.xml generated
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154
.idea/workspace.xml generated Normal file
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&quot;RunOnceActivity.typescript.service.memoryLimit.init&quot;: &quot;true&quot;,
&quot;ai.playground.ignore.import.keys.banner.in.settings&quot;: &quot;true&quot;,
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&quot;ignore.virus.scanning.warn.message&quot;: &quot;true&quot;,
&quot;nodejs_package_manager_path&quot;: &quot;npm&quot;,
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<component name="RunManager">
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<option name="PARENT_ENVS" value="true" />
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README.md Normal file
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# MyPractice

20
data/sales.csv Normal file
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Ноутбук,Электроника,1200,5,2024-01-15
Мышь,Электроника,25,15,2024-01-20
Клавиатура,Электроника,45,10,2024-02-10
Кофеварка,Техника,150,3,2024-02-15
Футболка,Одежда,20,50,2024-02-20
Джинсы,Одежда,60,20,2024-03-05
Лампа,Дом,35,12,2024-03-12
Чайник,Техника,80,8,2024-03-20
Монитор,Электроника,300,4,2024-04-01
Носки,Одежда,5,100,2024-04-05
Рюкзак,Аксессуары,55,15,2024-04-10
Книга,Хобби,15,30,2024-01-25
Блокнот,Хобби,8,40,2024-02-01
Ручка,Хобби,2,200,2024-02-05
Коврик для йоги,Спорт,25,20,2024-03-15
Гантели,Спорт,40,10,2024-04-12
Наушники,Электроника,90,12,2024-04-18
Сковорода,Дом,45,6,2024-01-30
Подушка,Дом,25,14,2024-02-28
Зеркало,Дом,110,2,2024-03-25
1 Ноутбук Электроника 1200 5 2024-01-15
2 Мышь Электроника 25 15 2024-01-20
3 Клавиатура Электроника 45 10 2024-02-10
4 Кофеварка Техника 150 3 2024-02-15
5 Футболка Одежда 20 50 2024-02-20
6 Джинсы Одежда 60 20 2024-03-05
7 Лампа Дом 35 12 2024-03-12
8 Чайник Техника 80 8 2024-03-20
9 Монитор Электроника 300 4 2024-04-01
10 Носки Одежда 5 100 2024-04-05
11 Рюкзак Аксессуары 55 15 2024-04-10
12 Книга Хобби 15 30 2024-01-25
13 Блокнот Хобби 8 40 2024-02-01
14 Ручка Хобби 2 200 2024-02-05
15 Коврик для йоги Спорт 25 20 2024-03-15
16 Гантели Спорт 40 10 2024-04-12
17 Наушники Электроника 90 12 2024-04-18
18 Сковорода Дом 45 6 2024-01-30
19 Подушка Дом 25 14 2024-02-28
20 Зеркало Дом 110 2 2024-03-25

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data/sales.txt Normal file
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126
main.py
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import math import csv
def lcm(a: int, b: int) -> int: from collections import defaultdict
if a == 0 or b == 0:
return 0
return abs(a * b) // math.gcd(a, b)
if __name__ == "__main__":
num1 = 4
num2 = 6
result = lcm(num1, num2)
print(f"Наибольшее общее кратное двух чисел {num1} и {num2} равно {result}")
def load_data(filepath: str) -> list[dict]:
records = []
with open(filepath, mode='r', encoding='utf-8') as f:
reader = csv.reader(f)
for row in reader:
if not row: continue
name, category, price, quantity, date = row
records.append({
"name": name.strip(),
"category": category.strip(),
"price": float(price),
"quantity": int(quantity),
"date": date.strip()
})
return records
def clean_data(records: list[dict]) -> list[dict]:
cleaned = []
for r in records:
if r['price'] >= 0 and r['quantity'] >= 0:
r['category'] = r['category'].lower()
cleaned.append(r)
return cleaned
def filter_by_category(records: list[dict], category: str) -> list[dict]:
return [r for r in records if r['category'] == category.lower()]
def filter_by_price_range(records: list[dict], min_price: float, max_price: float) -> list[dict]:
return [r for r in records if min_price <= r['price'] <= max_price]
def total_revenue(records: list[dict]) -> float:
return sum(r['price'] * r['quantity'] for r in records)
def category_revenue(records: list[dict]) -> dict[str, float]:
rev_map = defaultdict(float)
for r in records:
rev_map[r['category']] += r['price'] * r['quantity']
return dict(rev_map)
def top_n_items(records: list[dict], n: int) -> list[tuple[str, int]]:
counts = defaultdict(int)
for r in records:
counts[r['name']] += r['quantity']
sorted_items = sorted(counts.items(), key=lambda x: x[1], reverse=True)
return sorted_items[:n]
def monthly_sales(records: list[dict]) -> dict[str, float]:
monthly_rev = defaultdict(float)
for r in records:
month = r['date'][:7] # Извлекает YYYY-MM
monthly_rev[month] += r['price'] * r['quantity']
return dict(sorted(monthly_rev.items()))
def best_selling_category(records: list[dict]) -> str:
cat_rev = category_revenue(records)
if not cat_rev: return ""
return max(cat_rev, key=cat_rev.get)
def export_summary(records: list[dict], output_path: str) -> None:
rev = total_revenue(records)
best_cat = best_selling_category(records)
top3 = top_n_items(records, 3)
monthly = monthly_sales(records)
with open(output_path, 'w', encoding='utf-8') as f:
f.write("СВОДНЫЙ ОТЧЕТ ПО ПРОДАЖАМ\n")
f.write("=" * 30 + "\n")
f.write(f"Общая выручка: {rev:.2f}\n")
f.write(f"Лучшая категория: {best_cat}\n\n")
f.write("Топ-3 товара (по количеству):\n")
for name, qty in top3:
f.write(f"- {name}: {qty} шт.\n")
f.write("\nВыручка по месяцам:\n")
for month, m_rev in monthly.items():
f.write(f"- {month}: {m_rev:.2f}\n")
def main():
#Пометки для себя любимого
#Загрузка
data = load_data("data/sales.csv")
#Очистка
data = clean_data(data)
#Фильтрация
filtered = filter_by_price_range(data, 10, 500)
#Анализ
rev = total_revenue(filtered)
cat_rev = category_revenue(filtered)
best_cat = best_selling_category(filtered)
top3 = top_n_items(filtered, 3)
monthly = monthly_sales(filtered)
#Вывод в консоль
print(f"--- Результаты анализа (фильтр: 10-500 руб) ---")
print(f"Общая выручка: {rev:.2f}")
print(f"Лучшая категория: {best_cat.capitalize()}")
print(f"Топ-3 товара: {top3}")
print(f"Выручка по месяцам: {monthly}")
#Экспорт
export_summary(filtered, "report.txt")
print(f"\nОтчет успешно сохранен в report.txt")
if __name__ == "__main__":
main()

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"C:\Program Files\Python314\python.exe" C:\Users\USER\PycharmProjects\PythonProject1\main.py СВОДНЫЙ ОТЧЕТ ПО ПРОДАЖАМ
Наибольшее общее кратное двух чисел 4 и 6 равно 12 ==============================
Общая выручка: 9830.00
Лучшая категория: электроника
Process finished with exit code 0 Топ-3 товара (по количеству):
- Футболка: 50 шт.
- Книга: 30 шт.
- Джинсы: 20 шт.
Выручка по месяцам:
- 2024-01: 1095.00
- 2024-02: 2250.00
- 2024-03: 2980.00
- 2024-04: 3505.00