GEP (GDB Enhanced Prompt) - a GDB plug-in for GDB command prompt with fzf history search, fish-like autosuggestions, auto-completion with floating window, partial string matching in history, and more!

Overview

GEP (GDB Enhanced Prompt)

asciicast

GEP (GDB Enhanced Prompt) is a GDB plug-in which make your GDB command prompt more convenient and flexibility.

Why I need this plug-in?

GDB's original prompt is using hardcoded built-in GNU readline library, we can't add our custom function and key binding easily. The old way to implement them is by patching the GDB's C source code and compiling it again.

But now, you can write your function in Python and use arbitrary key binding easily with GEP without any patching!

And also, GEP has some awesome features already, you can directly use it!

Features

  • Ctrl+R for fzf history reverse search
  • up-arrow for partial string matching in history
  • TAB for auto-completion with floating window
  • fish-like autosuggestions
  • has the ability to build custom key binding and its callback function by modifying geprc.py

How to install it?

Make sure you have GDB 8.0 or higher compiled with Python3.6+ bindings, then:

  1. Install fzf: Installation

  2. Download this plug-in and install it:

git clone https://github.com/lebr0nli/GEP.git && \
cd GEP && \
sh install.sh

Note: This plug-in is using prompt-toolkit 2.0.10 (because IDK why prompt-toolkit 3 is not working with GDB Python API), so the install.sh will download prompt_toolkit==2.0.10 to ~/GEP/. Maybe we can build our prompt toolkit just for this plug-in in the future.

  1. Add source ~/GEP/.gdbinit-gep to the last line of your ~/.gdbinit

You can run:

echo 'source ~/GEP/.gdbinit-gep' >> ~/.gdbinit
  1. Enjoy!

For more configuration

You can modify configuration about history and auto-completion in ~/GEP/.gdbinit-gep.

You can also add your custom key bindings by modifying ~/GEP/geprc.py.

The trade-offs

Since GDB doesn't have a good Python API to fully control and emulate its prompt, this plug-in has some side effects.

However, the side effects are avoidable, here are the guides to avoid them:

gdb.event.before_prompt

The GDB Python API event: gdb.event.before_prompt may be called only once.

So if you are using a GDB plug-in that is listening on this event, this plug-in will cause some bugs.

As far as I know, pwndbg and gef won't be bothered by this side effect now.

To avoid this, you can change the callback function by adding them to gdb.prompt_hook, gdb.prompt_hook has almost the same effects with event.before_prompt, but gdb.prompt_hook can be directed invoke, so this plug-in still can emulate that callback for you!

dont-repeat

When your input is empty and directly press ENTER, GDB will execute the previous command from history if that command doesn't have the property: dont-repeat.

As far as I know, there is no GDB API for checking a command's property.

So, I added some commonly used commands (for original GDB API and GEF) which have that property in a list to avoid repeatedly executing them.

If you have some user-defined function that has dont-repeat property, add your command into the list manually, too.

Note: The list is in .gdbinit-gep.py and the variable name is DONT_REPEAT.

If you found some commands which should or shouldn't be added in that list, let me know on the issue page, thanks!

Bugs, suggestions, and ideas

If you found any bug, or you have any suggestions/ideas about this plug-in, feel free to leave your feedback on the GitHub issue page or send me a pull request!

Thanks!

Owner
Alan Li
Stay hungry, stay foolish. Keep hacking!
Alan Li
Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR

Codebase for "INVASE: Instance-wise Variable Selection" Authors: Jinsung Yoon, James Jordon, Mihaela van der Schaar Paper: Jinsung Yoon, James Jordon,

Jinsung Yoon 50 Nov 11, 2022
Official implementation of the paper 'Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution'

DASR Paper Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution Jie Liang, Hui Zeng, and Lei Zhang. In arxiv preprint. Abs

81 Dec 28, 2022
A 2D Visual Localization Framework based on Essential Matrices [ICRA2020]

A 2D Visual Localization Framework based on Essential Matrices This repository provides implementation of our paper accepted at ICRA: To Learn or Not

Qunjie Zhou 27 Nov 07, 2022
Towhee is a flexible machine learning framework currently focused on computing deep learning embeddings over unstructured data.

Towhee is a flexible machine learning framework currently focused on computing deep learning embeddings over unstructured data.

1.7k Jan 08, 2023
Deep Probabilistic Programming Course @ DIKU

Deep Probabilistic Programming Course @ DIKU

52 May 14, 2022
Realtime_Multi-Person_Pose_Estimation

Introduction Multi Person PoseEstimation By PyTorch Results Require Pytorch Installation git submodule init && git submodule update Demo Download conv

tensorboy 1.3k Jan 05, 2023
Code for the ICASSP-2021 paper: Continuous Speech Separation with Conformer.

Continuous Speech Separation with Conformer Introduction We examine the use of the Conformer architecture for continuous speech separation. Conformer

Sanyuan Chen (陈三元) 81 Nov 28, 2022
A solution to the 2D Ising model of ferromagnetism, implemented using the Metropolis algorithm

Solving the Ising model on a 2D lattice using the Metropolis Algorithm Introduction The Ising model is a simplified model of ferromagnetism, the pheno

Rohit Prabhu 5 Nov 13, 2022
计算机视觉中用到的注意力模块和其他即插即用模块PyTorch Implementation Collection of Attention Module and Plug&Play Module

PyTorch实现多种计算机视觉中网络设计中用到的Attention机制,还收集了一些即插即用模块。由于能力有限精力有限,可能很多模块并没有包括进来,有任何的建议或者改进,可以提交issue或者进行PR。

PJDong 599 Dec 23, 2022
Official implementation of "Robust channel-wise illumination estimation"

This repository provides the official implementation of "Robust channel-wise illumination estimation." accepted in BMVC (2021).

Firas Laakom 4 Nov 08, 2022
Adversarial Attacks are Reversible via Natural Supervision

Adversarial Attacks are Reversible via Natural Supervision ICCV2021 Citation @InProceedings{Mao_2021_ICCV, author = {Mao, Chengzhi and Chiquier

Computer Vision Lab at Columbia University 20 May 22, 2022
This repo contains research materials released by members of the Google Brain team in Tokyo.

Brain Tokyo Workshop 🧠 🗼 This repo contains research materials released by members of the Google Brain team in Tokyo. Past Projects Weight Agnostic

Google 1.2k Jan 02, 2023
Repository for the paper titled: "When is BERT Multilingual? Isolating Crucial Ingredients for Cross-lingual Transfer"

When is BERT Multilingual? Isolating Crucial Ingredients for Cross-lingual Transfer This repository contains code for our paper titled "When is BERT M

Princeton Natural Language Processing 9 Dec 23, 2022
Estimation of human density in a closed space using deep learning.

Siemens HOLLZOF challenge - Human Density Estimation Add project description here. Installing Dependencies: Install Python3 either system-wide, user-w

3 Aug 08, 2021
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.

CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we

Meta Research 283 Dec 30, 2022
An experimental technique for efficiently exploring neural architectures.

SMASH: One-Shot Model Architecture Search through HyperNetworks An experimental technique for efficiently exploring neural architectures. This reposit

Andy Brock 478 Aug 04, 2022
Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks

SSTNet Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks(ICCV2021) by Zhihao Liang, Zhihao Li, Songcen Xu, Mingkui Tan, Kui J

83 Nov 29, 2022
Chainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)

fcn - Fully Convolutional Networks Chainer implementation of Fully Convolutional Networks. Installation pip install fcn Inference Inference is done as

Kentaro Wada 218 Oct 27, 2022
VISNOTATE: An Opensource tool for Gaze-based Annotation of WSI Data

VISNOTATE: An Opensource tool for Gaze-based Annotation of WSI Data Introduction Requirements Installation and Setup Supported Hardware and Software R

SigmaLab 1 Jun 14, 2022
Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)

Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

Hongje Seong 72 Dec 14, 2022