A Python package providing rich and interactive visualizations

vprof is a Python package providing rich and interactive visualizations for various Python program characteristics such as running time and memory usage. It supports Python 3.4+ and distributed under BSD license. The project is in active development and some of its features might not work as expected. Screenshots Contributing All contributions are highly encouraged! You can add new features, report and fix existing bugs and write docs and tutorials. Feel free to open an issue or send a pull request! […]

Read more

A drop-in replacement for Django’s runserver

About A drop in replacement for Django’s built-in runserver command. Features include: An extendable interface for handling things such as real-time logging. Integration with the werkzeug interactive debugger. Threaded (default) and multi-process development servers. Ability to specify a WSGI application as your target environment. Note django-devserver works on Django 1.3 and newer Installation To install the latest stable version: pip install git+git://github.com/dcramer/django-devserver#egg=django-devserver django-devserver has some optional dependancies, which we highly recommend installing. pip install sqlparse — pretty SQL formatting pip […]

Read more

A toolbar overlay for debugging Flask applications

This is a port of the excellent django-debug-toolbar for Flask applications. Installation Installing is simple with pip: $ pip install flask-debugtoolbar Usage Setting up the debug toolbar is simple: from flask import Flask from flask_debugtoolbar import DebugToolbarExtension app = Flask(__name__) # the toolbar is only enabled in debug mode: app.debug = True # set a ‘SECRET_KEY’ to enable the Flask session cookies app.config[‘SECRET_KEY’] = ” toolbar = DebugToolbarExtension(app) The toolbar will automatically be injected into Jinja templates when debug mode […]

Read more

A pure-Python library for parsing and analyzing ELF files and DWARF debugging information

pyelftools is a pure-Python library for parsing and analyzing ELF files and DWARF debugging information. See the User’s guide for more details. Pre-requisites As a user of pyelftools, one only needs Python to run. It works with Python versions 2.7 and 3.x (x >= 5). For hacking on pyelftools the requirements are a bit more strict, please see the hacking guide. Installing pyelftools can be installed from PyPI (Python package index): > pip install pyelftools Alternatively, you can download the […]

Read more

IceCream: Never use print() to debug again

IceCream — Never use print() to debug again Do you ever use print() or log() to debug your code? Of course you do. IceCream, or ic for short, makes print debugging a little sweeter. IceCream is well tested, permissively licensed, and supports Python 2, Python 3, PyPy2, and PyPy3. Inspect Variables Have you ever printed variables or expressions to debug your program? If you’ve ever typed something like or the more thorough print(“foo(‘123’)”, foo(‘123’)) then ic() is here to help. […]

Read more

Caffe: a fast open framework for deep learning

Caffe Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors. Check out the project site for all the details like and step-by-step examples. Custom distributions Community Please join the caffe-users group or gitter chat to ask questions and talk about methods and models. Framework development discussions and thorough bug reports are collected on Issues. Happy brewing! License and […]

Read more

Keras: Deep Learning for Python

Keras Under Construction In the near future, this repository will be used once again for developing the Keras codebase. For the time being, the Keras codebase is being developed at tensorflow/tensorflow, and any PR or issue should be directed there. GitHub https://github.com/keras-team/keras    

Read more

Tensors and Dynamic neural networks in Python with strong GPU acceleration

PyTorch is a Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration Deep neural networks built on a tape-based autograd system You can reuse your favorite Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed. See also the ci.pytorch.org HUD. More About PyTorch At a granular level, PyTorch is a library that consists of the following components: Component Description torch a Tensor library like NumPy, with strong GPU support torch.autograd […]

Read more

A radically simple IT automation platform that makes your applications and systems easier

Ansible Ansible is a radically simple IT automation system. It handles configuration management, application deployment, cloud provisioning, ad-hoc task execution, network automation, and multi-node orchestration. Ansible makes complex changes like zero-downtime rolling updates with load balancers easy. More information on the Ansible website. Design Principles Have a dead-simple setup process with a minimal learning curve. Manage machines very quickly and in parallel. Avoid custom-agents and additional open ports, be agentless by leveraging the existing SSH daemon. Describe infrastructure in a […]

Read more

Simple, Pythonic remote execution and deployment

Welcome to Fabric! Fabric is a high level Python (2.7, 3.4+) library designed to execute shell commands remotely over SSH, yielding useful Python objects in return. It builds on top of Invoke (subprocess command execution and command-line features) and Paramiko (SSH protocol implementation), extending their APIs to complement one another and provide additional functionality. For a high level introduction, including example code, please see our main project website; or for detailed API docs, see the versioned API website. GitHub https://github.com/fabric/fabric […]

Read more
1 520 521 522 523 524 973