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Django GDPR Cookie Consent is a cost-effective, ready-to-use Django app ensuring GDPR cookie compliance, offering easy setup, customizable design, and comprehensive functionality without recurring costs or domain limitations. It saves developers time and money compared to building a solution in-house or using expensive third-party services.
Django Paddle Subscriptions is a Django app streamlining SaaS subscription management, simplifying international tax compliance and billing through Paddle's platform. This €400 solution saves developers significant time and effort compared to building a system from scratch, offering a customizable and secure platform for scaling global SaaS businesses.
Kaggle is a leading platform for data science competitions, where users tackle real-world challenges, share datasets, and build predictive models in a collaborative environment. Now under Google, Kaggle offers a rich progression system and resources that connect and support millions of data scientists worldwide.
The Python 3 documentation provides comprehensive guidance on Python’s syntax, features, and standard library, helping users of all levels navigate the language. It includes sections like tutorials, library references, FAQs, and in-depth guides for both beginners and advanced developers.
Some folks naturally think in SQL. This book leverages the SQL design patterns to create Python code without the overheads of a database.
"The Hitchhiker’s Guide to Python!" is a comprehensive resource for intermediate to advanced Python developers, covering best practices for writing, structuring, and deploying Python code. It provides practical guidance on web development, automation, data science, and more, making it ideal for those looking to improve their skills and grow professionally.
- Ansible
- Blueprint
- Boost.Python
- Buildbot
- Buildout
- C++
- Camelot
- Cement
- Chef
- Click
- Cliff
- Cocoa
- cryptography
- ctypes
- DB-API
- Django ORM
- docopt
- Fabric
- gevent
- GTk
- Jenkins
- JSON
- Kivy
- lxml
- OpenCV
- peewee
- Pillow
- Plac
- PonyORM
- Psutil
- PugSQL
- Puppet
- PyGObject
- Pyjs Desktop
- PyObjC
- PyQt
- PySide
- PySimpleGUI
- Python
- Python Fire
- PyZMQ
- Qt
- Records
- requests
- Salt
- Scikit-learn
- SciPy
- SQLAlchemy
- SQLObject
- SWIG
- Tk
- Toga
- tox
- Travis-CI
- Twisted
- WSGI
- wxPython
- XML
Jupyter Notebook is an open-source web application that enables users to create and share documents containing live code, equations, and visualizations, supporting over 40 programming languages. Its advanced version, JupyterLab, provides a more flexible environment, making both tools ideal for data science, machine learning, and scientific computing tasks across various industries and research fields.
uv is a lightning-fast Python package and project manager, written in Rust, that replaces tools like pip and poetry while offering 10-100x speed improvements. It supports multiple Python versions and advanced project management, providing a flexible, high-performance solution for developers.
Flask's documentation provides a comprehensive guide for building web applications, starting from installation and quick setup to more advanced topics like blueprints, testing, and deployment. It covers key components such as routing, templates, and session management, while offering detailed API references and guidance on extending Flask with community-maintained extensions.
Ansible is an open-source automation tool that simplifies IT infrastructure management and application deployment through its agentless architecture and human-readable playbooks. By automating tasks like resource provisioning, configuration management, and continuous delivery, Ansible empowers DevOps teams to streamline their operations and improve efficiency.
tox is an automation tool designed for Python projects that standardizes and simplifies the testing process by running tests in isolated virtual environments across multiple Python versions and configurations. With features like dependency management and CI integration, tox ensures consistent, reproducible test results, making it an essential resource for developers aiming to maintain code quality.
Pandas is a fast and flexible Python library designed for efficient data manipulation, offering powerful tools like the DataFrame for handling structured data, reshaping, and handling missing values. It supports various data formats and excels in performance, making it widely used across industries for real-world data analysis.
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