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
Self-Supervised Monocular DepthEstimation with Internal Feature Fusion(arXiv), BMVC2021

DIFFNet This repo is for Self-Supervised Monocular Depth Estimation with Internal Feature Fusion(arXiv), BMVC2021 A new backbone for self-supervised d

Hang 94 Dec 25, 2022
Cross-view Transformers for real-time Map-view Semantic Segmentation (CVPR 2022 Oral)

Cross View Transformers This repository contains the source code and data for our paper: Cross-view Transformers for real-time Map-view Semantic Segme

Brady Zhou 363 Dec 25, 2022
Embeddinghub is a database built for machine learning embeddings.

Embeddinghub is a database built for machine learning embeddings.

Featureform 1.2k Jan 01, 2023
Spontaneous Facial Micro Expression Recognition using 3D Spatio-Temporal Convolutional Neural Networks

Spontaneous Facial Micro Expression Recognition using 3D Spatio-Temporal Convolutional Neural Networks Abstract Facial expression recognition in video

Bogireddy Sai Prasanna Teja Reddy 103 Dec 29, 2022
Vit-ImageClassification - Pytorch ViT for Image classification on the CIFAR10 dataset

Vit-ImageClassification Introduction This project uses ViT to perform image clas

Kaicheng Yang 4 Jun 01, 2022
Official PyTorch implementation of "Improving Face Recognition with Large AgeGaps by Learning to Distinguish Children" (BMVC 2021)

Inter-Prototype (BMVC 2021): Official Project Webpage This repository provides the official PyTorch implementation of the following paper: Improving F

Jungsoo Lee 16 Jun 30, 2022
Rule Based Classification Project For Python

Rule-Based-Classification-Project (ENG) Business Problem: A game company wants to create new level-based customer definitions (personas) by using some

Deniz Can OĞUZ 4 Oct 29, 2022
Official implementation of cosformer-attention in cosFormer: Rethinking Softmax in Attention

cosFormer Official implementation of cosformer-attention in cosFormer: Rethinking Softmax in Attention Update log 2022/2/28 Add core code License This

120 Dec 15, 2022
Code for the paper: Sketch Your Own GAN

Sketch Your Own GAN Project | Paper | Youtube Our method takes in one or a few hand-drawn sketches and customizes an off-the-shelf GAN to match the in

677 Dec 28, 2022
[3DV 2020] PeeledHuman: Robust Shape Representation for Textured 3D Human Body Reconstruction

PeeledHuman: Robust Shape Representation for Textured 3D Human Body Reconstruction International Conference on 3D Vision, 2020 Sai Sagar Jinka1, Rohan

Rohan Chacko 39 Oct 12, 2022
Pytorch implementation for "Implicit Semantic Response Alignment for Partial Domain Adaptation"

Implicit-Semantic-Response-Alignment Pytorch implementation for "Implicit Semantic Response Alignment for Partial Domain Adaptation" Prerequisites pyt

4 Dec 19, 2022
Recurrent Scale Approximation (RSA) for Object Detection

Recurrent Scale Approximation (RSA) for Object Detection Codebase for Recurrent Scale Approximation for Object Detection in CNN published at ICCV 2017

Yu Liu (Louis) 239 Dec 28, 2022
Simple keras FCN Encoder/Decoder model for MS-COCO (food subset) segmentation

FCN_MSCOCO_Food_Segmentation Simple keras FCN Encoder/Decoder model for MS-COCO (food subset) segmentation Input data: [http://mscoco.org/dataset/#ove

Alexander Kalinovsky 11 Jan 08, 2019
Rename Images with Auto Generated Neural Image Captions

Recaption Images with Generated Neural Image Caption Example Usage: Commandline: Recaption all images from folder /home/feng/Downloads/images to folde

feng wang 3 May 01, 2022
It helps user to learn Pick-up lines and share if he has a better one

Pick-up-Lines-Generator(Open Source) It helps user to learn Pick-up lines Share and Add one or many to the DataBase Unique SQLite DataBase AI Undercon

knock_nott 0 May 04, 2022
General purpose Slater-Koster tight-binding code for electronic structure calculations

tight-binder Introduction General purpose tight-binding code for electronic structure calculations based on the Slater-Koster approximation. The code

9 Dec 15, 2022
imbalanced-DL: Deep Imbalanced Learning in Python

imbalanced-DL: Deep Imbalanced Learning in Python Overview imbalanced-DL (imported as imbalanceddl) is a Python package designed to make deep imbalanc

NTUCSIE CLLab 19 Dec 28, 2022
Face Detection and Alignment using Multi-task Cascaded Convolutional Networks (MTCNN)

Face-Detection-with-MTCNN Face detection is a computer vision problem that involves finding faces in photos. It is a trivial problem for humans to sol

Chetan Hirapara 3 Oct 07, 2022
Code of 3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces

3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces Installation After cloning the repo open

37 Dec 03, 2022
Snscrape-jsonl-urls-extractor - Extracts urls from jsonl produced by snscrape

snscrape-jsonl-urls-extractor extracts urls from jsonl produced by snscrape Usag

1 Feb 26, 2022