HMLLDB is a collection of LLDB commands to assist in the debugging of iOS apps.

Overview

HMLLDB is a collection of LLDB commands to assist in the debugging of iOS apps.
中文介绍

Features

  • Non-intrusive. Your iOS project does not need to be modified
  • All commands support real device and simulator
  • All commands support Objective-C and Swift project
  • Some commands provide interactive UI within the APP

Requirements

  • Xcode 12.3
  • 64-bit simulator or real device, iOS 9.0+
  • Debug configuration (or Optimization Level set [-O0]/[-Onone])

Installation

  1. Download all the files. I recommend cloning the repository.
  2. Open up (or create) ~/.lldbinit file, and append the following lines to the end of the file:
command script import /path/to/HMLLDB.py

For example, the command in my computer:
command script import /Users/pal/Desktop/gitProjects/HMLLDB/commands/HMLLDB.py

  1. Restart Xcode, run your own iOS project, click Pause program execution to enter the LLDB debugging mode, enter the command help, if you see the commands described below, the installation is successful.

Commands

Command Description
deletefile Delete the specified file in the sandbox
pbundlepath Print the path of the main bundle
phomedirectory Print the path of the home directory("~")
fclass Find the class containing the input name(Case insensitive)
fsubclass Find the subclass of the input
fsuperclass Find the superclass of the input
fmethod Find the specified method in the method list, you can also find the method list of the specified class
methods Execute [inputClass _methodDescription] or [inputClass _shortMethodDescription]
properties Execute [inputClass _propertyDescription]
ivars Execute [instance _ivarDescription]
plifecycle Print life cycle of UIViewController
redirect Redirect stdout/stderr
push Find UINavigationController in keyWindow then push a specified UIViewController
showhud Display the debug HUD on the key window, it is showing the memory usage, CPU utilization and FPS of the main thread
sandbox Presenting a sandbox browser that can share and delete files
inspect Inspect UIView
environment Show diagnostic environment.
...

All commands in the table can use help <command> to view the syntax and examples. For example, the output of help fmethod:

(lldb) help fmethod
     Find the method.  Expects 'raw' input (see 'help raw-input'.)

Syntax: fmethod

    Syntax:
        fmethod <methodName>  (Case insensitive.)
        fmethod [--class] <className>

    Options:
        --class/-c; Find all method in the class

    Examples:
        (lldb) fmethod viewdid
        (lldb) fmethod viewDidLayoutSubviews
        (lldb) fmethod -c UITableViewController

    This command is implemented in HMClassInfoCommands.py

Example

Some examples use the demo in the Kingfisher project.
It is recommended to click Pause program execution to enter the LLDB debugging mode to execute commands, instead of executing commands by hitting breakpoints.

deletefile

It is recommended to re-run the project after executing the command, because some data is still in the memory.

# Delete all file in the sandbox
(lldb) deletefile -a

# Delete the "~/Documents" directory
(lldb) deletefile -d

# Delete the "~/Library" directory
(lldb) deletefile -l

# Delete the "~/tmp" directory
(lldb) deletefile -t

# Delete the "~/Library/Caches" directory
(lldb) deletefile -c

# Delete the "~Library/Preferences" directory
(lldb) deletefile -p

# Delete the specified file or directory
(lldb) deletefile -f path/to/fileOrDirectory

pbundlepath & phomedirectory

# Print the path of the main bundle
(lldb) pbundlepath
[HMLLDB] /Users/pal/Library/Developer/CoreSimulator/Devices/D90D74C6-DBDF-4976-8BEF-E7BA549F8A89/data/Containers/Bundle/Application/84AE808C-6703-488D-86A2-C90004434D3A/Kingfisher-Demo.app

# Print the path of the home directory
(lldb) phomedirectory
[HMLLDB] /Users/pal/Library/Developer/CoreSimulator/Devices/D90D74C6-DBDF-4976-8BEF-E7BA549F8A89/data/Containers/Data/Application/3F3DF0CD-7B57-4E69-9F15-EB4CCA7C4DD8

# If it is running on the simulator, you can add the -o option to open path with Finder
(lldb) pbundlepath -o
(lldb) phomedirectory -o

fclass & fsubclass & fsuperclass & fmethod

These commands are optimized for Swift, and the namespace can be omitted when entering the Swift class.

fclass: Find all class names that contain the specified string.

(lldb) fclass NormalLoadingViewController
[HMLLDB] Waiting...
[HMLLDB] Count: 1 
Kingfisher_Demo.NormalLoadingViewController (0x102148fa8)

# Case insensitive
(lldb) fclass Kingfisher_Demo.im
[HMLLDB] Waiting...
[HMLLDB] Count: 2 
Kingfisher_Demo.ImageDataProviderCollectionViewController (0x102149a18)
Kingfisher_Demo.ImageCollectionViewCell (0x1021498e8)

fsubclass: Find all subclasses of a class.

(lldb) fsubclass UICollectionViewController
[HMLLDB] Waiting...
[HMLLDB] Subclass count: 10 
Kingfisher_Demo.InfinityCollectionViewController
Kingfisher_Demo.HighResolutionCollectionViewController
...

fsuperclass: Find the super class of a class.

(lldb) fsuperclass UIButton
[HMLLDB] UIButton : UIControl : UIView : UIResponder : NSObject

(lldb) fsuperclass KingfisherManager
[HMLLDB] Kingfisher.KingfisherManager : Swift._SwiftObject

fmethod: Find the specified method in the method list, you can also find the method list of the specified class.

# Find the specified method in the method list. Case insensitive.
(lldb) fmethod viewdidload
[HMLLDB] Waiting...
[HMLLDB] Methods count: 158 
(-) playbackControlsViewDidLoad:
	Type encoding:[email protected]:[email protected]
	Class:AVPlaybackControlsController
(-) turboModePlaybackControlsPlaceholderViewDidLoad:
	Type encoding:[email protected]:[email protected]
	Class:AVPlaybackControlsController
(-) viewDidLoad
	Type encoding:[email protected]:8
	Class:AVNewsWidgetPlayerBehaviorContext
...

# Option -c: Find the method list of the specified class. Case sensitive.
(lldb) fmethod -c ImageCache
[HMLLDB] Waiting...
[HMLLDB] Class: Kingfisher.ImageCache (0x10264c6f8)
Instance methods count: 3. Class method count: 0.
(-) cleanExpiredDiskCache
	Type encoding:[email protected]:8
(-) backgroundCleanExpiredDiskCache
	Type encoding:[email protected]:8
(-) clearMemoryCache
	Type encoding:[email protected]:8

methods & properties & ivars

methods: Execute [inputClass _methodDescription] or [inputClass _shortMethodDescription] properties: Execute [inputClass _propertyDescription] ivars: Execute [instance _ivarDescription]

These commands are optimized for Swift, and the namespace can be omitted when entering the Swift class.

# Syntax
methods [--short] <className/classInstance>
properties <className/classInstance>
ivars <Instance>

(lldb) methods NormalLoadingViewController
[HMLLDB] <Kingfisher_Demo.NormalLoadingViewController: 0x10d55ffa8>:
in Kingfisher_Demo.NormalLoadingViewController:
	Instance Methods:
		- (id) collectionView:(id)arg1 cellForItemAtIndexPath:(id)arg2; (0x10d523f30)
		- (long) collectionView:(id)arg1 numberOfItemsInSection:(long)arg2; (0x10d522a20)
		- (void) collectionView:(id)arg1 willDisplayCell:(id)arg2 forItemAtIndexPath:(id)arg3; (0x10d523af0)
		- (void) collectionView:(id)arg1 didEndDisplayingCell:(id)arg2 forItemAtIndexPath:(id)arg3; (0x10d522cb0)
		- (id) initWithCoder:(id)arg1; (0x10d522960)
...

# These commands can only be used for subclasses of NSObject
(lldb) methods KingfisherManager
[HMLLDB] KingfisherManager is not a subclass of NSObject

plifecycle

Used to print the life cycle of UIViewController.
In a non-intrusive way, and Xcode can set the console font color to make it clearer. It has become one of my favorite commands.

Usage:

  1. Create a Symbolic Breakpoint, and then add the method to be printed in the Symbol line.(e.g. -[UIViewController viewDidAppear:])
  2. Add a Action(Debugger Command), enter the plifecycle command
  3. Check the option: Automatically continue after evaluating actions

I usually use the -i option to ignore some system-generated UIViewController. img1

I often Enable viewDidAppear: and dealloc methods, and the other methods are set to Disable and started on demand, as shown below: img2

Output in Xcode: img3

It should be noted that there are two problems with this command.

  1. Cause UIViewController switching lag.
  2. The following warning may be triggered when starting the APP. You need to click Continue program execution in Xcode to let the APP continue to run.
Warning: hit breakpoint while running function, skipping commands and conditions to prevent recursion.

BTW, the source code provides other ways to use LLDB to print the life cycle.

redirect

Redirect stdout/stder.

# You can redirect the output of Xcode to Terminal if you use the simulator
# Open the terminal, enter the "tty" command, you can get the path: /dev/ttys000
(lldb) redirect both /dev/ttys000
[HMLLDB] redirect stdout successful
[HMLLDB] redirect stderr successful

push

Find UINavigationController in keyWindow then push a specified UIViewController.
Notice: push MyViewController needs to execute [[MyViewController alloc] init] first. If the initializer of the class requires parameters, or the class needs to pass parameters after initialization, this command may cause errors.
The GIF demo didn't use Kingfisher because the UIViewController in the demo depends on the storyboard.
img4

showhud

Display the debug HUD on the keyWindow, it is showing the memory usage, CPU utilization and FPS of the main thread. img5

Tapping the debug HUD will present a new view controller, and its function will be introduced later. img6

sandbox

Presenting a sandbox browser that can share and delete files.
It takes a few seconds to call the command for the first time. img7

inspect

Inspect UIView of the current page.
img8

environment

Show diagnostic environment.
You can see that one of items is [Git commit hash], which is one of the reasons why clone repository is recommended.

(lldb) environment
[HMLLDB] [Python version] 3.8.2 (default, Nov  4 2020, 21:23:28) 
		[Clang 12.0.0 (clang-1200.0.32.28)]
[HMLLDB] [LLDB version] lldb-1200.0.44.2
		Apple Swift version 5.3.2 (swiftlang-1200.0.45 clang-1200.0.32.28)
[HMLLDB] [Target triple] x86_64h-apple-ios-simulator
[HMLLDB] [Git commit hash] 088f654cb158ffb16019b2deca5dce36256837ad
[HMLLDB] [Optimized] False: 28  True: 0
[HMLLDB] [Xcode version] 1230
[HMLLDB] [Xcode build version] 12C33
[HMLLDB] [Model identifier] x86_64
[HMLLDB] [System version] iOS 13.0

If an error occurs

Just-in-time compilation via LLDB is not stable. If an error occurs, please check in order according to the following steps.

  1. pull the latest code. Check the Xcode version, HMLLDB generally only adapts to the latest Xcode version.
  2. Open the ~/.lldbinit file and make sure to import the HMLLDB.py at the end of the file so that its commands are not overwritten.
  3. After launching the APP, click Pause program execution to enter the LLDB debugging mode to execute commands, instead of executing commands by hitting breakpoints. (In general, you can execute commands by hitting breakpoints)
  4. Restart Xcode can solve most problems.
  5. Restart the computer.
  6. After completing the above steps, the command still fails. Please copy the error and post it to Issue, and execute the environment command, its output should also be posted to Issue.

License

HMLLDB is released under the MIT license. See LICENSE for details.

Owner
mao2020
iOS Developer
mao2020
Faster RCNN with PyTorch

Faster RCNN with PyTorch Note: I re-implemented faster rcnn in this project when I started learning PyTorch. Then I use PyTorch in all of my projects.

Long Chen 1.6k Dec 23, 2022
Animate molecular orbital transitions using Psi4 and Blender

Molecular Orbital Transitions (MOT) Animate molecular orbital transitions using Psi4 and Blender Author: Maximilian Paradiz Dominguez, University of A

3 Feb 01, 2022
Code for "CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds" @ICRA2021

CloudAAE This is an tensorflow implementation of "CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds" Files log:

Gee 35 Nov 14, 2022
Convert BART models to ONNX with quantization. 3X reduction in size, and upto 3X boost in inference speed

fast-Bart Reduction of BART model size by 3X, and boost in inference speed up to 3X BART implementation of the fastT5 library (https://github.com/Ki6a

Siddharth Sharma 19 Dec 09, 2022
Classic Papers for Beginners and Impact Scope for Authors.

There have been billions of academic papers around the world. However, maybe only 0.0...01% among them are valuable or are worth reading. Since our limited life has never been forever, TopPaper provi

Qiulin Zhang 228 Dec 18, 2022
A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Segnet is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This is implementation of http://arxiv.org/pdf/15

Pradyumna Reddy Chinthala 190 Dec 15, 2022
Probabilistic Tensor Decomposition of Neural Population Spiking Activity

Probabilistic Tensor Decomposition of Neural Population Spiking Activity Matlab (recommended) and Python (in developement) implementations of Soulat e

Hugo Soulat 6 Nov 30, 2022
Evaluation framework for testing segmentation networks in PyTorch

Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!

Eugene Khvedchenya 37 Apr 27, 2022
Implementation of Nyström Self-attention, from the paper Nyströmformer

Nyström Attention Implementation of Nyström Self-attention, from the paper Nyströmformer. Yannic Kilcher video Install $ pip install nystrom-attention

Phil Wang 95 Jan 02, 2023
Torchyolo - Yolov3 ve Yolov4 modellerin Pytorch uygulamasıdır

TORCHYOLO : Yolo Modellerin Pytorch Uygulaması Yapılacaklar: Yolov3 model.py ve

Kadir Nar 3 Aug 22, 2022
LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image.

This project is based on ultralytics/yolov3. LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image. Download $ git clone http

26 Dec 13, 2022
Clean Machine Learning, a Coding Kata

Kata: Clean Machine Learning From Dirty Code First, open the Kata in Google Colab (or else download it) You can clone this project and launch jupyter-

Neuraxio 13 Nov 03, 2022
Spatial Action Maps for Mobile Manipulation (RSS 2020)

spatial-action-maps Update: Please see our new spatial-intention-maps repository, which extends this work to multi-agent settings. It contains many ne

Jimmy Wu 27 Nov 30, 2022
RTSeg: Real-time Semantic Segmentation Comparative Study

Real-time Semantic Segmentation Comparative Study The repository contains the official TensorFlow code used in our papers: RTSEG: REAL-TIME SEMANTIC S

Mennatullah Siam 592 Nov 18, 2022
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22)

Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22) Ok-Topk is a scheme for distributed training with sparse gradients

Shigang Li 9 Oct 29, 2022
Lama-cleaner: Image inpainting tool powered by LaMa

Lama-cleaner: Image inpainting tool powered by LaMa

Qing 5.8k Jan 05, 2023
General Assembly Capstone: NBA Game Predictor

Project 6: Predicting NBA Games Problem Statement Can I predict the results of NBA games from the back-half of a season from the opening half of the s

Adam Muhammad Klesc 1 Jan 14, 2022
Object Detection Projekt in GKI WS2021/22

tfObjectDetection Object Detection Projekt with tensorflow in GKI WS2021/22 Docker Container: docker run -it --name --gpus all -v path/to/project:p

Tim Eggers 1 Jul 18, 2022
Tutorial materials for Part of NSU Intro to Deep Learning with PyTorch.

Intro to Deep Learning Materials are part of North South University (NSU) Intro to Deep Learning with PyTorch workshop series. (Slides) Related materi

Hasib Zunair 9 Jun 08, 2022
Short and long time series classification using convolutional neural networks

time-series-classification Short and long time series classification via convolutional neural networks In this project, we present a novel framework f

35 Oct 22, 2022