Forem: Jhohannes

Why Your Applications Need Optimistic Updates

Jhohannes — Sat, 20 Jul 2024 22:57:38 +0000

Introduction

Optimistic update is a key concept in software development, instrumental in enhancing the user experience by making applications feel faster and more efficient. This is where developers tend to be ‘optimistic’ that the server will surely return a success on whatever action the user performs. This strategy involves the application of updates on the client side instantly, without waiting for a server response to confirm the operation’s success. It operates on the assumption that the server-side operation will succeed. This strategy is widely embraced in developing modern web applications, where speed and efficiency are paramount. Despite its advantages, the approach presents unique challenges that must be handled effectively.

Deep Dive into Optimistic Update

Optimistic update is fundamentally based on the principle of optimism. It operates on the assumption that most interactions in an application will succeed. For instance, when a user performs an action such as liking a post or adding a comment, the update is instantly reflected on the user interface, even before the server confirms the operation’s success. This instant feedback gives users a sense of immediate gratification, making the application more responsive and quick. It enhances the user’s perception of the application’s speed and performance, contributing to a positive user experience.

Example: Social Media Likes

Consider whatever social media platform we use daily, be it X, Instagram or Facebook, where users can like posts. When a user clicks the “like” button, the application immediately updates the like count and changes the button’s appearance to indicate that the post has been liked. This happens without waiting for the server to confirm that the like has been recorded. The user sees the change instantly, which makes the application feel fast and responsive. If the server later confirms the like, no further action is needed. If the server reports a failure (e.g., due to a network issue), the application can revert the like count and button appearance to their previous states and notify the user of the failure.

Example: Online Multiplayer Games

In online multiplayer games, players often perform actions that must be reflected immediately on their screens. For instance, when a player moves their character or performs an attack, the game client updates the game state instantly without waiting for the server to confirm the action. This ensures that the game feels smooth and responsive. If the server later detects an issue (e.g., the action is invalid or a network problem), it can send a correction to the client, which then adjusts the game state accordingly.

From a technical perspective, optimistic updating also reduces the server load, as the client doesn’t need to check for updates constantly. This can lead to more efficient use of server resources and potentially reduce the cost and complexity of server-side operations.

The Upsides of Optimistic Update

The implementation of optimistic update brings several benefits to both users and developers. Most notably, it significantly enhances the user experience. It eradicates the lag that typically occurs while waiting for server response, which gives the application a faster, more seamless feel. This immediate feedback is particularly beneficial in applications where real-time feedback is crucial, such as social media platforms and online multiplayer games.

Challenges: Handling Failures in Optimistic Update

Despite its many advantages, optimistic update is not without its challenges. The most significant of these is the handling of failures. Since the application does not wait for server confirmation, there is a risk that the action might fail on the server side. This could lead to inconsistencies between the user’s view of the data and the actual state of the data on the server.

Example: E-commerce Shopping Cart

In an e-commerce application, when a user adds an item to their shopping cart, the application might immediately update the cart’s contents and display the new item. However, if the server later reports that the item is out of stock, the application needs to remove the item from the cart and notify the user. This requires a mechanism to revert the changes on the client side and handle the failure gracefully. The application might display a message informing the user that the item is unavailable and suggest alternative products.

Developers need to implement a robust system to handle such scenarios. This typically involves a mechanism to revert the changes on the client side and notify the user about the failure. These mechanisms must be designed carefully to ensure they do not negatively impact the user experience.

Conclusion

Optimistic update is a powerful technique that can significantly improve the user experience in modern web applications. By assuming success and updating the user interface immediately, applications can feel faster and more responsive. However, it is crucial to handle potential failures effectively to ensure the reliability of the application.

While optimistic updating may not be suitable for all situations, with careful planning and robust error handling, it can be a valuable tool in a developer’s arsenal. It’s a strategy that requires a balance - the benefits of immediate feedback and perceived speed must be weighed against the challenges of handling potential failures. But when done right, the benefits can significantly outweigh the challenges, leading to applications that are not just faster, but also more user-friendly and efficient.

Installing Tensorflow(with GPU support) in linux or WSL

Jhohannes — Tue, 20 Jun 2023 20:07:23 +0000

I was trying to install Tensorflow with GPU support on my Linux machine and WSL, but I was having a terrible time. I spent hours and days🤦‍♂️ scouring the internet looking for solutions, but nothing seemed to work. I felt like I was going in circles, and I was getting more and more frustrated with each passing minute. Eventually, I did manage to figure out a way to install Tensorflow with GPU support, and it was like a weight had been lifted off my shoulders.

I don't want you to go through the same pain and frustration that I experienced, so I'm going to share with you the steps to follow to install Tensorflow with GPU support in Linux or WSL. Trust me, it will save you a lot of time and headaches!😉

Tensorflow is an open-source software library used for dataflow and differentiable programming across various tasks. It is a popular choice for machine learning and deep learning tasks due to its flexibility and scalability. By default, Tensorflow installation does not include GPU support. However, GPU support can significantly speed up the training of deep learning models.

System Requirements

To install Tensorflow with GPU support, you need the following system requirements:

NVIDIA® GPU card with CUDA®. Check if your GPU has CUDA support here
CUDA® Toolkit 11.0 or higher
cuDNN SDK 8.0.4 or higher
Linux or Windows Subsystem for Linux (WSL) [will be using ubuntu in this blog]

Prerequisite

Python 3.6 - 3.9
Ubuntu 16.x or later

Installation Steps

Follow the below steps for installing Tensorflow with GPU support:

First, install the CUDA® Toolkit. You can download the latest version of CUDA® Toolkit from the NVIDIA® website(ubuntu or linux). Make sure to select the appropriate version of the toolkit according to your GPU card and Linux distribution.

After installing the deb(local) file, you can install this by running this in the terminal.

sudo apt install ./<name_of_file>.deb

NB: Make sure you are in the right directory before running the above command.

Alternatively, you can install the CUDA® toolkit right in your terminal.

sudo apt install nvidia-cuda-toolkit

Run this command to check if installation of the toolkit has been successful.

nvcc -V

output should look like this.

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Thu_Nov_18_09:45:30_PST_2021
Cuda compilation tools, release 11.5, V11.5.119
Build cuda_11.5.r11.5/compiler.30672275_0

After installing the CUDA® Toolkit, download the cuDNN SDK from the NVIDIA® website. Unzip the downloaded file and move the contents to the appropriate directory.

NB: To be sure of the version of the cuDNN to install. Please check the version on the tensorFlow website.

Unzip with this command:
```
tar -xvzf cudnn-linux-x86_64-8.9.2.26_cuda11-archive.tar.xz.tgz
```
After extracting the files, I like to rename to folder because of the next command. In this case I renamed the folder from cudnn-linux-x86_64-8.9.2.26_cuda11-archive to cudnn.

Now let’s copy the extracted files into the cuda dir.

```bash
sudo cp cudnn/include/cudnn.h /usr/lib/cuda/include/
sudo cp cudnn/lib/libcudnn* /usr/lib/cuda/lib64/
```

Set file permissions for cudnn

```bash
sudo chmod a+r /usr/lib/cuda/include/cudnn.h /usr/lib/cuda/lib64/libcudnn*
```

Export CUDA environment variables. To set them, run:

 echo 'export LD_LIBRARY_PATH=/usr/lib/cuda/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
 echo 'export LD_LIBRARY_PATH=/usr/lib/cuda/include:$LD_LIBRARY_PATH' >> ~/.bashrc

Install Tensorflow using pip. To install Tensorflow with GPU support, use the following command:
```
pip install tensorflow-gpu
```
Maybe instead of just installing globally into the python environment, let’s use the conda and create an environment out of it. It is recommended to use a virtual environment for your Tensorflow project to avoid conflicts with other packages and ensure reproducibility. You can create a virtual environment using the following command:

Steps with using miniconda.
1. First download and install Miniconda from their website.
2. Let’s create our environment.
```
conda create --name tf python=3.8
```
1. Activate the environment.
```
conda activate tf
```
1. Create a jupyter support for this environment.
```
conda install nb_conda
```
1. Time to install tensorflow. For CPU support only, use this:
```
conda install -c anaconda tensorflow
```
For both CPU and GPU support, use this:
```
conda install -c anaconda tensorflow-gpu
```
Verify the installation by running a simple Tensorflow program that uses the GPU. If the program executes without any errors, then the installation was successful.

import tensorflow as tf
tf.config.list_physical_devices("GPU")

You will see similar output, [PhysicalDevice(name=’/physical_device:GPU:0′, device_type=’GPU’)]

Conclusion

In conclusion, installing Tensorflow with GPU support can significantly speed up the training of deep learning models. By following the above steps, you can easily install Tensorflow with GPU support in Linux or WSL.

If you encounter any issues during the installation process, you can refer to the Tensorflow documentation for troubleshooting or seek assistance from the Tensorflow community. It is also important to note that the installation steps may vary depending on your system configuration.

By installing Tensorflow with GPU support, you can take advantage of the power of your GPU to accelerate the training of deep learning models and achieve faster results. With the increasing demand for deep learning applications, installing Tensorflow with GPU support is becoming more important than ever.

Adding SSH-key to GitHub🔐🗝️

Jhohannes — Mon, 09 May 2022 10:56:23 +0000

In this blog, I am going to be teaching you exactly how you could add an SSH key to your GitHub which could prevent you from constantly typing in your email and password anytime you want to push to Github.

SSH key which stands for Secure Socket Shell or Secure Shell is just an access credential which resembles a password used to gain access to an encrypted connection between systems and and use that connection to manage a remote system.

Setting it up on your machine

First thing you would need to do is to generate the public and private key which would be used for the connection between your computer and Github. Your private key is meant not to be shared. If something is to be shared here, that should probably be your public key as the name suggests.
And to do this, run this command:

ssh-keygen -t rsa -b 4096 -C 'type your email here'

You would be asked the location to store the file. You can specify where you want it to be stored or press ENTER to store it in the default location.

Establish your passphrase which is nothing different from password. It adds to the security of your connection so it is good you set it up.

Press Enter after confirming your passphrase and you should see something like this.

We need to add a key-manager which would hold our private keys for public keys authentication and would also save us some time typing our passphrase over and over again.

eval $(ssh-agent -s)

Now, we need to add the key-pair to the SSH.

ssh-add ~/.ssh/id_rsa

Hit enter and enter the passphrase.

If you change your directory, you would need to specify that dir here also

Copy the public key to use in Github

clip < ~/.ssh/id_rsa.pub

If you couldn’t copy the key with your terminal, you can simply go the .pub file via the dir you saved the keys to. With what we have here, I will navigate to root dir and show all hidden files and dir. Go into the .ssh folder and open and copy the key in **id_rsa.pub**

How to add the keys to Github.

Open your Github and go to settings. (Top right corner by clicking on your avatar | image)

On your left pane, you would find SSH and GPG key. Click on thin

Add new SSH key

Fill in the title and paste the copied ssh key from your clipboard.

The title could be anything of your choice but should be a name that would easily identified.

You would be redirect to confirm the operation by entering your Github password.

CONCLUSION

You have now set up a secure and encrypted connection for data transfer between your computer and Github.

Wireplumber and pipewire in conflict (Arch linux)

Jhohannes — Fri, 29 Oct 2021 09:07:58 +0000

If you ever try an update and run into this error in your terminal that

This is all you have to do.
In your terminal,
type sudo pacman -S pipewire-media-session

then after that
run sudo pacman -Syyu and try updating.

If questions are being asked, just be careful if you have to delete or replace any file.

You're welcome

Printing emojis😏🎉😛😛😝 in python 🐍🐍

Jhohannes — Sun, 24 Oct 2021 11:03:31 +0000

Have you ever thought of inserting emojis into your python program? Well, if you haven't, you should start thinking of inserting one into some of your mini projects to make it fun😜.
Emojis are now everywhere, even in programming now.
In python now, there are three ways you could insert an emoji.

You could use unicodes
The Common Locale Data Repository(CLDR) names
The emoji module

Using the unicodes

Every emoji we use when chatting all have unicodes and we can use these unicodes in python to output these same emoji.
Codes

# face with tears of joy
print("\U0001f602")

# face with tongue
print("\U0001f61b")

Output
😂
😛

For the full emoji list, visit Link
Replace the "+" with "000". So "U+1F602" becomes "U0001F602".

Using CLDR names

Emojis also have CLDR short names. All the short names are provided in the link above.

Code

# face with tears of joy
print("\N{face with tears of joy}")

# face with tongue
print("\N{face with tongue}")

Output
😂
😛

Using the emoji module

To install the module, run pip install emoji in your terminal.
We will use the CLDR short names here by using the emojize() function. All spaces the the CLDR short names would be replaced by an underscore.
Code

# Import the module
import emoji

print(emoji.emojize("Python is :thumbs_up:")
print(emoji.emojize("I :red_heart: python")

Output
Python is 👍
I ❤️ python

Arch linux with Realtek rtl8821ce kernel freezing when WIFI is connected

Jhohannes — Mon, 20 Sep 2021 20:58:22 +0000

If you have recently installed linux and you are facing any freezing problem when connected to the WIFI, chill up buddy. I am here for you.

Do not panic. There is nothing wrong with the distro nor your device. Just the kernel using the default wifi driver it came with.

I would recommend you run a system update first.

sudo pacman -Syyu

If problem still persists, then follow the next instructions.

How I Solved Mine.

I tried installing the drivers manually. https://tutorialforlinux.com/2020/01/12/step-by-step-arch-linux-realtek-rtl8821ce-driver-installation-guide/

The link above should help.
For garuda linux users, you can visit the add/Remove Software to download the drivers.

I went into the /etc/modprobe.d/ folder and created a file blacklist.conf. You might have to root the folder before you can create the file.
Inside the file I only wrote:
I then went to /etc/default/grub and added pci=noaer to the kernel parameters.
Open terminal and run

sudo update-grub

then

sudo reboot

Problem solved!!! Screen freezes no more.
I hope it solves yours.

Forem: Jhohannes

Why Your Applications Need Optimistic Updates

Introduction

Deep Dive into Optimistic Update

Example: Social Media Likes

Example: Online Multiplayer Games

The Upsides of Optimistic Update

Challenges: Handling Failures in Optimistic Update

Example: E-commerce Shopping Cart

Conclusion

Installing Tensorflow(with GPU support) in linux or WSL

System Requirements

Prerequisite

Installation Steps

Steps with using miniconda.

Conclusion

Adding SSH-key to GitHub🔐🗝️

Setting it up on your machine

How to add the keys to Github.

CONCLUSION

Wireplumber and pipewire in conflict (Arch linux)

Printing emojis😏🎉😛😛😝 in python 🐍🐍

Using the unicodes

Using CLDR names

Using the emoji module

Arch linux with Realtek rtl8821ce kernel freezing when WIFI is connected

How I Solved Mine.