teleren/devto huggingface dataset:
5 Free Tools to Boost Developer Productivity
Tags: webdev, beginners, tutorial, productivity
Published: 2024-05-03 19:09:30

Hey there, devs! Are you tired of feeling like you're not getting enough done in a day? Do you find yourself switching between apps and tools, trying to stay organized and focused? Well, worry no more! We've got you covered with these 5 free tools that'll help you stay productive and get more done in less time.
## [1. Notion - The Ultimate Productivity Hub](https://affiliate.notion.so/qpcf3d97sqqg)
Notion is like the Swiss Army knife of productivity tools. It's an all-in-one workspace where you can take notes, create tasks, and even build databases. With its flexible and customizable layout, you can organize your projects and ideas in a way that makes sense to you. Plus, its collaboration features make it easy to work with others in real-time. Whether you're a solo dev or part of a team, Notion is a game-changer.
## [2. Todoist - Task Management Made Easy](https://todoist.com/)
Todoist is a simple yet powerful task manager that helps you stay on top of your to-do list. With its intuitive interface and features like prioritization, deadlines, and reminders, you'll never miss a deadline again. Plus, its integration with other apps like GitHub and Slack makes it a great addition to your workflow.
## [3. Visual Studio Code - Code Like a Pro](https://code.visualstudio.com/download)
Visual Studio Code (VS Code) is a free code editor that's packed with features to help you code more efficiently. With its syntax highlighting, code completion, and debugging tools, you'll be writing code like a pro in no time. Plus, its extension marketplace has a ton of plugins to help you customize your workflow.
## [4. Clockify - Time Tracking Made Simple](https://clockify.me/)
Clockify is a free time-tracking tool that helps you stay focused and on track. With its simple and intuitive interface, you can easily log your time across multiple projects and clients. Plus, its reporting features give you valuable insights into how you're spending your time, so you can optimize your workflow.
## [5. GitHub - Version Control for Free](https://github.com/)
GitHub is a must-have for any developer, and its free plan is a great place to start. With its version control features, you can collaborate with others and keep track of changes to your code. 
Plus, its community features let you connect with other devs and learn from their experiences.

There you have it, folks! These 5 free tools will help you stay productive, organized, and focused. 

Whether you're a seasoned dev or just starting out, these tools are sure to boost your workflow and help you get more done in less time. Happy coding!
File Input and Output in Ruby
Published: 2024-05-03 18:48:46

As we know that Ruby one of the language for backend technology, so it must have a module to deal with file system in your Operating system. 

Ruby I/O is a way to interact with your system. Data is sent in the form of bytes/characters. IO class is the basis for all input and output in Ruby. It may be duplexed, hence may use more than one native operating system stream.

IO has a subclass as File class which allows reading and writing files in Ruby. The two classes are closely associated. IO object represent readable/writable interactions to keyboards and screens.

## Common modes in I/O port

As it is known in most of  other languages that have file system module, they have modes when dealing with file.

like if you want to append, delete, add, or read and this modes in ruby when  you dealing with files:

- "r": read-only mode is the default mode starts at beginning of file.
- "r+": read-write mode, starts at beginning of file.
- "w": write-only mode, either creates a new file or truncates an existing file for writing.
- "w+": read-write mode, either creates a new file or truncates an existing file for reading and writing.
- "a": write-only mode, if file exists it will append the file otherwise a new file will be created for writing only.
- "a+": read and write mode, if file exists it will append the file otherwise a new file will be created for writing and reading.- "r": read-only mode is the default mode starts at beginning of file.
- "r+": read-write mode, starts at beginning of file.
- "w": write-only mode, either creates a new file or truncates an existing file for writing.
- "w+": read-write mode, either creates a new file or truncates an existing file for reading and writing.
- "a": write-only mode, if file exists it will append the file otherwise a new file will be created for writing only.
- "a+": read and write mode, if file exists it will append the file otherwise a new file will be created for writing and reading.

## Ruby opening a file
A Ruby file can be created using different methods for reading, writing or both.
```ruby
f = File.new("fileName.rb")  
```
or 
```ruby
File.open("fileName.rb", "mode") do |f| 
``` 
* The different between open and new methods that open can take block of code and determine a specific mode.

## Ruby reading a file
There are three different methods to read a file.

To return a single line, following syntax is used.
```ruby
while line = gets   
    puts line   
end   
```
To return the whole file after the current position, following syntax is used.

```ruby
f.read  
```
To return file as an array of lines, following syntax is used.

```ruby
f.readlines
```
## Ruby writing a file
```ruby
#!/usr/bin/ruby   
  
aFile = File.new("about.txt", "r+")   
if aFile   
   aFile.syswrite("New content is written in this file.\n")   
end  
```

## Ruby renaming and deleting a file

Ruby files are renamed using rename method and deleted using delete mehtod.

To rename a file, following syntax is used.

```ruby
File.rename("old.txt", "new.txt")   
```

To delete a file, following syntax is used.

```ruby
File.delete("filename.txt")  
```
Episode 24/17: Ionic 8, JsAction
Tags: webdev, javascript, programming, angular
Published: 2024-05-03 18:46:56

Ionic had its version 8 release, and JSAction, a library to catch DOM events until hydration finishes, will become part of Angular.

{% embed https://youtu.be/-2Se9sSgVec %}

## Ionic 8

Ionic is the most popular toolkit for creating cross-platform applications in Angular, including web and mobile apps. Its components change their design depending on the platform, making the apps look like native ones.

Ionic has been available in version 8 since mid-April. According to the release notes, the major changes focused on improving accessibility.

We have a high contrast theme, better integration of light and dark color palettes, and further features.

For more details, consult the official blog.

{% embed https://ionic.io/blog/ionic-8-is-here %}

## JSAction

Towards progressive hydration, we've learned that Angular 18 will include another piece of the puzzle. Currently, there is a period between the display of the static page coming from SSR and when Angular is loaded and adds all its event listeners.

It is not handled if the loading is too slow and the user dispatches a DOM event. In the old version of SSR, namely nguniversal, we had a library called preboot, which was responsible for that.

The new version will use a library called JSAction, which catches and holds the DOM events until Angular is ready. JSAction also runs on Google's search and has proven its quality over many years.

With JSAction in place, it will be possible to run deferred views on the server first and only hydrate them once the user starts to interact with them, i.e., dispatching DOM events.

For more information, head to the article published by Jatin Ramanathan and Tom Wilkinson on the Angular Blog

{% embed https://medium.com/angular-blog/event-dispatch-in-angular-89d868d2351c %}

## DOM Attributes and Properties

Jake Archibald published an article explaining the difference between HTML attributes and properties. It may not be something we require daily, but it is good to hear about these things, and relatively easy to read.

{% embed https://jakearchibald.com/2024/attributes-vs-properties/ %}
XGBoost
Published: 2024-05-03 18:43:00

XGBoost is short for “Extreme Gradient Boosting” and is a popular machine learning algorithm that can be used for both regression and classification problems. XGBoost optimizes the gradient boosting framework and provides a fast, efficient and flexible modeling tool.

Gradient boosting creates a series of models, usually decision trees, and combines these models to obtain a more powerful model. Each new model tries to correct the mistakes of previous models. This process continues until a certain stopping criterion.

Some important features of XGBoost are:


**Regularization**: XGBoost includes L1 (Lasso Regression) and L2 (Ridge Regression) regularization terms to control model complexity. This helps the model avoid overfitting.

**Parallel Processing**: XGBoost performs the training of decision trees in parallel, which makes the algorithm run faster.

**Flexibility**: XGBoost offers the ability to define custom optimization goals and evaluation criteria.

**Handling Missing** Values: XGBoost can handle missing values automatically.

**Tree Pruning**: XGBoost prevents overfitting by stopping tree growth without positive gain.

**Cross-Validation**: XGBoost can cross-validate at each iteration step, making it easy to determine the optimal number of rounds of iteration.

An example code for training the XGBoost model in Python is as follows:

```
import xgboost as xgb
from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split

# Load the dataset
boston = load_boston()
X = boston.data
y = boston.target

# Separate the data into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=123)

# Create the XGBoost model
model = xgb.XGBRegressor(objective ='reg:squarederror', colsample_bytree = 0.3, learning_rate = 0.1,
                 max_depth = 5, alpha = 10, n_estimators = 10)

# Train the model
model.fit(X_train, y_train)

# Make predictions
predictions = model.predict(X_test)
```
In this example, an XGBoost regression model is trained on the Boston home prices dataset. The hyperparameters of the model are determined as objective, colsample_bytree, learning_rate, max_depth, alpha and n_estimators.
May the Source Be With You, 2024!
Tags: puppet, community, maythefourth, hackathon
Published: 2024-05-03 18:37:38

It's Star Wars Day again, and we usually do a hackathon to celebrate. This year it falls on a weekend though, and we're trying to get better at respecting everyone's work-life balance and personal time. 

Luke Skywalker actually only said _May the Force be with you!_ once and it was offscreen. We're going to channel a bit of that energy here and do a low-key "offscreen" self-paced hackathon. Any non-trivial pull request contributed to either the puppetlabs or voxpupuli GitHub namespaces on May 4 will earn you an iconic _**May the Source Be With You**_ sticker.

So what's fair game? Anything, really. Write a [blog post for Vox](https://github.com/voxpupuli/voxpupuli.github.io/tree/master/_posts). Fix a bug for add a feature to a Puppet Supported module. Clean up documentation for r10k to make it more readable. Check out the [issues list](https://github.com/issues?q=is%3Aopen+is%3Aissue+user%3Avoxpupuli+archived%3Afalse+sort%3Acreated-desc) on the [Vox Pupuli homepage](https://voxpupuli.org) and see if there's anything that you'd like to fix.

Just don't flood us with low effort spam. We all remember what happened with Hacktoberfest. If you contribute something, make it more than a whitespace or typo fix.

> **And a very important point to close on! If you want the sticker, you'll need to use [this form](https://forms.office.com/r/Cn55uJmWMH) to share your mailing address.**

You can follow along and see what's been contributed with [this dashboard](https://github.com/pulls?q=is%3Apr+user%3Apuppetlabs+user%3Avoxpupuli+archived%3Afalse+sort%3Acreated-asc+created%3A2024-05-04+). Who will be the first to contribute?

Happy weekend, happy hacking, and we're excited to see what you create. May the source be with you!
3 Steps to Enable Windows Sandbox.
Published: 2024-05-03 18:37:24

**What is Windows Sandox in simple term?**
Windows Sandbox is like a secure, temporary playground for your computer. It lets you open an unknown files or applications in an isolated environment, separate from your main system. This way, if anything goes wrong or the file contains malware, it can't harm your actual computer. Once you're done testing or checking the file, you can close the sandbox, and everything inside it disappears—like it was never there. It's a way to experiment safely without risking your system's safety

**How to Activate Windows Sandbox**

1. Go to your Windows start button, and type 
'Picture 1: Turn Windows features on or off', Click to open. Make sure you're logged in as the system administrator. If not, you'll need the administrator password to proceed.

![Search for Turn on Windows Features](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/l570ej8nprv3211edi3z.png)
2. Check the box next to 'Windows Sandbox'
3. Click 'OK' and restart your computer.
![Picture 2: Checked Windows sandbox ](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/peg1uzbpayu3umavxcc1.png)
Now Windows Sandbox is activated on your computer.To open Sandbox, click Start and search for 'Sandbox'. You'll find it among your available applications." 
Good job. You have now successfully enabled windows Sandbox on your computer.
Lucide Icons for VS Code [Unofficial]
Tags: lucide, icons, vscode, javascript
Published: 2024-05-03 18:32:30

Hey there,

You know that feeling when you're in the flow, coding away, and then you realize you need an icon? Instead of interrupting your rhythm to hunt one down online, now you can just grab it from within VS Code.

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/bywsdzxtytj1fu7j6rjy.jpg)

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/w94njpaztt4gdx8n564x.jpg)

I made this extension because, well, I needed it myself. And I figured, hey, if it helps me, it might just help you too.

So if you're tired of the back-and-forth between your code and your browser, give it a shot. It's free, it's easy, and it's made with a whole lot of love.

Download it now from the Visual Studio Code Marketplace and let's make coding a little smoother, one icon at a time.

And its also open source.

VSCode: https://marketplace.visualstudio.com/items?itemName=Lakshmisankar.vscode-lucide-icons

Repo Link: https://github.com/plsankar/vscode-lucide-icons
Model Selection: GridSearchCV
Published: 2024-05-03 18:32:14

GridSearchCV is a method used to tune model hyperparameters. Hyperparameters are parameters that control the training process of a machine learning model and can affect the overall performance of the model. GridSearchCV finds the best set of hyperparameters by trying all possible combinations on a specified set of hyperparameters.

Here's how GridSearchCV works:

First of all, the hyperparameters to be searched and their values are determined as a "grid".
GridSearchCV trains the model for each combination of hyperparameters in the grid and evaluates the performance of the model using cross-validation.
The hyperparameter set that gives the best performance is selected.
Below is a Python example showing how GridSearchCV can be implemented using the scikit-learn library:
```
from sklearn.model_selection import GridSearchCV
from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier

# Load iris dataset
data = load_iris()
X = data.data
y = data.target

# Create your model
model = RandomForestClassifier()

# Determine the grid of hyperparameters to search
param_grid = {
     'n_estimators': [50, 100, 200],
     'max_depth': [None, 10, 20, 30],
}

# Create GridSearchCV
grid_search = GridSearchCV(model, param_grid, cv=5)

# Fit GridSearchCV
grid_search.fit(X, y)

# Print the best hyperparameters and the best score
print("Best parameters: ", grid_search.best_params_)
print("Best score: ", grid_search.best_score_)
```
In this example, GridSearchCV is used to set the 'n_estimators' and 'max_depth' hyperparameters of the RandomForestClassifier model. GridSearchCV evaluates the performance of each hyperparameter combination using 5-fold cross-validation and selects the hyperparameter set that gives the best performance.
How to install Ant Media Server on Ubuntu
Published: 2024-05-03 18:32:03


![Image description](https://www.tkqlhce.com/click-100701360-12454592)(https://dev-to-uploads.s3.amazonaws.com/uploads/articles/v31mk063w17h7r5d8d8u.png)

Ant Media is a streaming server that can be installed on a Linus server for webRTC, HLS & DASH streaming. Here is how to set it up:
Php features: parameter changes
Tags: php
Published: 2024-05-03 18:23:39

- [Attributes](https://dev.to/xwero/php-features-attributes-32p6)
- [First class callable syntax](https://dev.to/xwero/php-features-first-class-callable-syntax-5ab1)
- [Constructor changes](https://dev.to/xwero/php-features-constructor-changes-3ei5)

As promised in my last post this one is about parameters

## Theory

The biggest change is [named parameters](https://wiki.php.net/rfc/named_params) in php 8.0. This makes functions and class methods easier to use, less error prone and makes calling them self documenting.

A little change in php 8.0 is that you can [add a comma](https://wiki.php.net/rfc/trailing_comma_in_parameter_list) after the last parameter. This is made because then you can follow the convention that is used for multi-line arrays.

## Code

```php
function a($b, $c = 1, $d = false,) {
  var_dump($b, $c, $d);
}
```

Since php 5.6 you can do `a(...['b'])`, but now you can do `a(...['b' => 'b'])`. 
You can write it shorter, `a(b: 'b')`. For the really lazy typers `a('b')` is still working.


The best usage is that you can skip parameters that have a default value. So you can do `a(b: 'b', d: true)` or `a('b', d: true)`.

When you use the name there are several safeguards:

- the name must exist. `a(e: 'error')` 
- you can't use a name multiple times. `a(b: 'b', b: 'error')`
- named parameters must be after unnamed parameters `a(d: true, 'b')`. 

If you use all the parameters named the order doesn't matter, `a(d: true, b: 'b')`.

## Conclusion

Named parameters make the code easier to write and read. Because it is php 8.0 this also helps attributes. 

Were you aware of the side effects of this change?
42. Trapping Rain Water
Tags: php, leetcode, algorithms, programming
Published: 2024-05-03 18:21:07

42\. Trapping Rain Water

Hard

Given `n` non-negative integers representing an elevation map where the width of each bar is `1`, compute how much water it can trap after raining.

**Example 1:**

![rainwatertrap](https://assets.leetcode.com/uploads/2018/10/22/rainwatertrap.png)

**Input:** height = [0,1,0,2,1,0,1,3,2,1,2,1]

**Output:** 6

**Explanation:** The above elevation map (black section) is represented by array [0,1,0,2,1,0,1,3,2,1,2,1]. In this case, 6 units of rain water (blue section) are being trapped.

**Example 2:**

**Input:** height = [4,2,0,3,2,5]

**Output:** 9

**Constraints:**

*   `n == height.length`
*   <code>1 <= n <= 2 * 10<sup>4</sup></code>
*   <code>0 <= height[i] <= 10<sup>5</sup></code>

**Solution:**

```
class Solution {

    /**
     * @param Integer[] $height
     * @return Integer
     */
    function trap($height) {
        $result = 0;
        $leftIndex = 0;
        $rightIndex = count($height) - 1;
        $maxLeft = 0;
        $maxRight = 0;
        while ($leftIndex < $rightIndex) {
            if ($height[$leftIndex] < $height[$rightIndex]) {
                $maxLeft = max($maxLeft, $height[$leftIndex]);
                $result += $maxLeft - $height[$leftIndex];
                $leftIndex++;
            } else {
                $maxRight = max($maxRight, $height[$rightIndex]);
                $result += $maxRight - $height[$rightIndex];
                $rightIndex--;
            }
        }
        return $result;
    }
}
```


**Contact Links**

- **[LinkedIn](https://www.linkedin.com/in/arifulhaque/)**
- **[GitHub](https://github.com/mah-shamim)**
402. Remove K Digits
Tags: php, leetcode, algorithms, programming
Published: 2024-05-03 18:21:01

402\. Remove K Digits

Medium

Given string num representing a non-negative integer `num`, and an integer `k`, return <i>the smallest possible integer after removing</i> `k` <i>digits from</i> `num`.



**Example 1:**

- **Input:** <code>**num = "1432219", k = 3**</code>
- **Output:** <code>**"1219"**</code>
- **Explanation:** <code>**Remove the three digits 4, 3, and 2 to form the new number 1219 which is the smallest.**</code>

**Example 2:**

- **Input:** <code>**num = "10200", k = 1**</code>
- **Output:** <code>**"200"**</code>
- **Explanation:** <code>**Remove the leading 1 and the number is 200. Note that the output must not contain leading zeroes.**</code>

**Example 3:**

- **Input:** <code>**num = "10", k = 2**</code>
- **Output:** <code>**"0"**</code>
- **Explanation:** <code>**Remove all the digits from the number, and it is left with nothing which is 0.**</code>



**Constraints:**

- <code>1 <= k <= num.length <= 10<sup>5</sup></code>
- `num` consists of only digits.
- `num` does not have any leading zeros except for the zero itself.

**Solution:**

```
class Solution {

    /**
     * @param String $num
     * @param Integer $k
     * @return String
     */
    function removeKdigits($num, $k) {
        if (strlen($num) == $k) {
            return '0';
        }

        $ans = [];
        $stack = [];

        for ($i = 0; $i < strlen($num); $i++) {
            $digit = $num[$i];
            while ($k > 0 && !empty($stack) && $stack[count($stack) - 1] > $digit) {
                array_pop($stack);
                $k -= 1;
            }
            array_push($stack, $digit);
        }

        for ($j = 0; $j < $k; $j++) {
            array_pop($stack);
        }

        foreach ($stack as $c) {
            if ($c == '0' && empty($ans)) {
                continue;
            }
            array_push($ans, $c);
        }

        return implode($ans) ? implode($ans) : '0';
    }
}
```


**Contact Links**

- **[LinkedIn](https://www.linkedin.com/in/arifulhaque/)**
- **[GitHub](https://github.com/mah-shamim)**
K-Fold Cross Validation
Published: 2024-05-03 18:14:18


![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/qkafxzu90f5zab19kegc.png)

K-fold cross-validation is a model evaluation technique. This technique divides the data set into 'k' equally sized subsets (or 'folds'). The model is then trained 'k' times and each time a different fold is used as the test set while the remaining folds are used as the training set.

In each iteration, the performance of the model is evaluated and eventually 'k' different performance measurements are obtained. The average of these measurements is often used to determine overall model performance.

The advantage of k-fold cross-validation is that the entire data set can be used for both training and testing. This allows a more accurate estimate of the model's generalization ability because each data point appears in the test set at least once.

Below is an example of how k-fold cross-validation can be implemented in Python:

```
from sklearn.model_selection import cross_val_score
from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier

# Load iris dataset
data = load_iris()
X = data.data
y = data.target

# Create your model
model = RandomForestClassifier()

# Apply K-fold cross-validation
scores = cross_val_score(model, X, y, cv=5)

# Print performance scores
print("Cross-validation scores: ", scores)
print("Average cross-validation score: ", scores.mean())
```

In this example, 5-fold cross-validation is used (i.e. cv=5). This means that the data set is divided into five equal parts and the model is trained and tested five times. As a result, we obtain five different performance scores and estimate the overall model performance by averaging them.