What if you could see the entire dependency tree of a single team?
You can only debug version conflicts when you understand which packages depend on what. But manually sorting out these connections in a pile of nested dependencies is tedious and time-consuming.
uv tree does this automatically: it displays a complete dependency graph so you can track any package and understand where it came from.
Key features:
✅ Full visualization of dependencies
✅ Highlights dependencies for which updates are available
✅ Shows which packages depend on a specific library
✅ Filters the tree to show only the dependencies of the selected package
Installation
👉 @DataScience4
You can only debug version conflicts when you understand which packages depend on what. But manually sorting out these connections in a pile of nested dependencies is tedious and time-consuming.
uv tree does this automatically: it displays a complete dependency graph so you can track any package and understand where it came from.
Key features:
Installation
uv: pip install uvPlease open Telegram to view this post
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It works like a red team within your system. You describe the task in plain language — then it plans the attack itself, selects tools, and proceeds through the entire process: from reconnaissance to reporting. Without manual fiddling and endless commands.
What it can do in practice:
git clone https://github.com/GH05TCREW/ghostcrew.git
cd ghostcrew
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python main.py
#python #soft #github
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#python #soft #github
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Forwarded from PyData Careers
If you're testing forms, mockups, or just want to play with data, there's Mimesis — a generator of fake data. Names, emails, addresses, and phone numbers. There's a location setting that allows you to select a country, and the data will be generated accordingly.
from typing import Dict
from mimesis.enums import Gender
from mimesis import Person
def generate_fake_user(locale: str = "es", gender: Gender = Gender.MALE) -> Dict[str, str]:
"""
Generates fake user data based on the locale and gender.
:param locale: The locale (for example, 'ru', 'en', 'es')
:param gender: The gender (Gender.MALE or Gender.FEMALE)
:return: A dictionary with the fake user data
"""
person = Person(locale)
user_data = {
"name": person.full_name(gender=gender),
"height": person.height(),
"phone": person.telephone(),
"occupation": person.occupation(),
}
return user_data
if __name__ == "__main__":
fake_user = generate_fake_user(locale="es", gender=Gender.MALE)
print(fake_user)
{
'name': 'Carlos Herrera',
'height': '1.84',
'phone': '912 475 289',
'occupation': 'Arquitecto'
)ru, 🇺🇸 en, 🇪🇸 es, etc.) Save it, it'll come in handy
#python #github #interview
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✨ How to Integrate Local LLMs With Ollama and Python ✨
📖 Learn how to integrate your Python projects with local models (LLMs) using Ollama for enhanced privacy and cost efficiency.
🏷️ #intermediate #ai #tools
📖 Learn how to integrate your Python projects with local models (LLMs) using Ollama for enhanced privacy and cost efficiency.
🏷️ #intermediate #ai #tools
✨ introspection | Python Glossary ✨
📖 The ability of a program to examine the type or properties of an object at runtime.
🏷️ #Python
📖 The ability of a program to examine the type or properties of an object at runtime.
🏷️ #Python
✨ local variable | Python Glossary ✨
📖 A variable that you bind inside a function or method body.
🏷️ #Python
📖 A variable that you bind inside a function or method body.
🏷️ #Python
✨ Quiz: How to Integrate ChatGPT's API With Python Projects ✨
📖 Test your knowledge of the ChatGPT API in Python. Practice sending prompts with openai and handling text and code responses in this quick quiz.
🏷️ #intermediate #ai #api
📖 Test your knowledge of the ChatGPT API in Python. Practice sending prompts with openai and handling text and code responses in this quick quiz.
🏷️ #intermediate #ai #api
How to correctly terminate Python scripts
In production, it's important to clearly signal the result of the program's work. For this,
• 0 — success
• a non-zero value — error
This approach helps CI/CD, Docker or cron to correctly respond to failures. It's mandatory for CLI utilities and automation, so that the execution is predictable
https://t.iss.one/DataScience4
In production, it's important to clearly signal the result of the program's work. For this,
sys.exit(<code>) is used:• 0 — success
• a non-zero value — error
This approach helps CI/CD, Docker or cron to correctly respond to failures. It's mandatory for CLI utilities and automation, so that the execution is predictable
https://t.iss.one/DataScience4
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✨ Anaconda Navigator | Python Tools ✨
📖 A desktop graphical interface included with the Anaconda Distribution.
🏷️ #Python
📖 A desktop graphical interface included with the Anaconda Distribution.
🏷️ #Python
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