Pandas might be a bit more popular than Python Poetry. We know about 219 links to it since March 2021 and only 162 links to Python Poetry. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Libraries for data science and deep learning that are always changing. - Source: dev.to / 5 days ago
# Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / 21 days ago
As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / 25 days ago
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 8 months ago
If you’ve been managing Python projects long enough, you’ve probably dealt with a mess of tools: pip, pip-tools, poetry, virtualenv, conda, maybe even pdm. - Source: dev.to / 17 days ago
First, there was pip. Combined with a requirements.txt, it seemed like a great idea – a straightforward method to declare dependencies explicitly. Luckily, we quickly realized this method tends to spiral into chaos, particularly when developers use "tricks" like pip freeze to lock dependencies rigidly. Fortunately, the Python ecosystem has evolved, introducing modern solutions like Poetry and now uv, offering... - Source: dev.to / about 1 month ago
Anyway, enough reminiscing about the past, this is not intended to be the ultimate guide on asynchronous programming, but a more pragmatic quick-start guide I wish I had back then. Assuming we are in a properly managed project (either through tools like poetry or uv), let’s start with a new module telegram.py for our telegram bot. Remember to add python-telegram-bot dependency to the project. - Source: dev.to / 2 months ago
Managing dependencies in Python projects can often become cumbersome, especially as projects grow in complexity. Poetry is a modern dependency management and packaging tool that simplifies this process, offering a streamlined way to create, manage, and distribute Python projects. - Source: dev.to / 3 months ago
Learn more about poetry here . It’s a great tool. - Source: dev.to / 3 months ago
NumPy - NumPy is the fundamental package for scientific computing with Python
Conda - Binary package manager with support for environments.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
pip - The PyPA recommended tool for installing Python packages.
OpenCV - OpenCV is the world's biggest computer vision library
pre-commit by Yelp - A framework for managing and maintaining multi-language pre-commit hooks