If you?ve ever needed a quick, reliable way to generate random data, look no further than RandomGenerator.pro. This sleek, user-friendly website is a treasure trove for anyone seeking randomness in a variety of forms, whether for creative projects, testing, or just pure curiosity.
At its core, RandomGenerator.pro offers a range of tools to generate random numbers, letters, colors, and more. The interface is clean and intuitive, making it accessible to users of all levels. Need a random number for a raffle or a unique string for a coding project? The site delivers with just a few clicks. One standout feature is its ability to customize parameters, allowing you to set ranges or specific criteria for your random outputs, which adds a layer of flexibility that?s hard to beat.
What sets RandomGenerator.pro apart is its simplicity paired with utility. There?s no unnecessary clutter?just straightforward tools that work efficiently. It?s perfect for developers, educators, or anyone who needs a dash of randomness in their work or play. Plus, it?s free to use, which is always a bonus.
Whether you?re brainstorming, prototyping, or simply exploring, RandomGenerator.pro is a handy resource worth bookmarking. Give it a spin next time you need a random spark?it?s a small but mighty tool that delivers every time!
Website Description
Find the ultimate set of free random generators intended to inspire, teach, and entertain. Our inclusive platform has more than 30 distinct generators across various categories, ranging from animals and entertainment to food and nature. Whether you are a creative professional needing inspiration, an educator in need of teaching materials, a student completing projects, or merely someone new to discovering interesting things, our random generators offer unlimited means of exploration and creativity.
Random Generator Pro is the web's most extensive and accessible collection of random generators. Every generator has been hand-developed to present precise, high-quality information in each generation. Our website fuses high-performance random generation engines with huge databases to yield first-rate, targeted results for all categories. Ideal for art, education, choices, amusement, and many other applications - absolutely free and fully accessible without joining.
When working with audio in Audacity, achieving consistent loudness is crucial. You'll often encounter two powerful tools: Normalize and Loudness Normalization. While both aim to adjust audio levels, they operate on fundamentally different principles. Understanding their distinctions is key to making the right choice for your audio projects.
Normalize: Peak-Based Adjustment
Normalize works by finding the highest peak (the loudest point) in your selected audio and adjusting the entire waveform proportionally. You specify a target peak level (usually in dBFS - decibels relative to full scale), and Audacity scales the audio so that the highest peak reaches that target.
Peak-Based: Focuses solely on the loudest point.
Simple and Fast: Relatively quick processing.
Ignores Perceived Loudness: Doesn't consider how loud the audio sounds to human ears.
Can Create Inconsistent Perceived Loudness: Peaks may be normalized, but overall loudness may still be inconsistent.
Useful for aligning peak levels of similar audio files or preparing audio for further processing.
Loudness Normalization considers the perceived loudness of the audio, aligning it with how humans hear. It uses algorithms that analyze the audio?s overall loudness over time, rather than just the peaks. It targets a specific Integrated Loudness value, typically measured in LUFS (Loudness Units relative to Full Scale).
Perceived Loudness-Based: Considers the average loudness over time.
More Complex Processing: Takes longer than Normalize.
Creates Consistent Perceived Loudness: Results in a more uniform and balanced listening experience.
Uses LUFS and True Peak values.
Better for broadcast, streaming, and podcasting where consistent loudness is essential.
Follows industry standards like ITU-R BS.1770.
Which One is "Better" for Making Audio Louder?
The answer depends on your goal:
For simply raising the peak level without considering perceived loudness, use Normalize.
For achieving a consistent and balanced listening experience, use Loudness Normalization.
Why Loudness Normalization is Often Preferred:
Human hearing doesn?t perceive loudness linearly. A short, very loud peak might not sound as loud as a sustained, moderately loud sound. Loudness Normalization accounts for this by analyzing the audio?s overall energy over time. This results in audio that sounds more consistent and comfortable to listen to.
Practical Example:
Imagine you have a podcast recording with a few loud coughs and otherwise quiet speech.
Normalize: If you normalize to -1 dBFS, the coughs will reach -1 dBFS, but the speech might still be very quiet. This would result in an inconsistent listening experience.
Loudness Normalization: If you loudness normalize to -16 LUFS, the overall perceived loudness of the podcast will be consistent. The coughs will be brought down, and the speech will be raised to a more balanced level.
While Normalize has its uses, Loudness Normalization is generally the superior choice for achieving consistent and professional-sounding audio. By understanding the differences between these two tools, you can make informed decisions and elevate the quality of your audio projects. Choose Loudness Normalization when you want to create a listening experience that is both loud and consistent.
Pytest has solidified its position as a go-to testing framework for Python developers due to its simplicity, extensibility, and powerful features. In this blog post, we'll dive deep into using Pytest, specifically focusing on its integration with Playwright for browser automation, and explore how to capture screenshots during fixture teardown for enhanced debugging and result analysis.
Capturing Screenshots in Fixture Teardown
To capture a screenshot before the browser closes, we can modify the page fixture to include a teardown phase. This will help make debugging a bit easier and a chance to look at automation to see if there's any weirdness.
Any code in the Fixture that appears after "yield page" will run at the conclusion of the test.
After running the tests, you'll find screenshots in the screenshots directory. These screenshots will help you understand the state of the browser at the end of each test, especially during failures.
Benefits of Screenshot Capture
Debugging: Quickly identify issues by visually inspecting the browser state. Reporting: Include screenshots in test reports for better documentation. Visual Validation: Verify UI elements and layout.
As QA teams grow and evolve, they often find themselves at a crossroads: Are they focusing on rigid, dogmatic practices, or are they embracing a more fluid, karmic approach that adapts to the moment? Let's dive into this philosophical tug-of-war and explore what it means for your QA team - and your software.
Dogma: The Comfort of the Rulebook
Dogma in QA is the strict adherence to predefined processes, checklists, and methodologies, no matter the context. It's the "we've always done it this way" mindset. Think of the team that insists on running a full regression test suite for every minor bug fix, even when a targeted test would suffice. Or the insistence on manual testing for every feature because automation "can't be trusted."
There's a certain comfort in dogma. It provides structure, predictability, and a clear path forward. For new QA engineers, a dogmatic framework can be a lifeline - a set of rules to follow when the chaos of software development feels overwhelming. And in highly regulated industries like healthcare or finance, dogmatic adherence to standards can be a legal necessity.
But here's the catch: Dogma can calcify into inefficiency. When a team clings to outdated practices - like refusing to adopt modern tools because "the old way works" - they risk missing out on innovation. Worse, they might alienate developers and stakeholders who see the process as a bottleneck rather than a value-add. Dogma, unchecked, turns QA into a gatekeeper rather than a collaborator.
Karma: The Flow of Cause and Effect
On the flip side, a karmic approach to QA is all about adaptability and consequences. It's the belief that good testing practices today lead to better outcomes tomorrow - less technical debt, happier users, and a smoother development cycle. A karmic QA team doesn't blindly follow a script; they assess the situation, weigh the risks, and adjust their strategy accordingly.
Imagine a team facing a tight deadline. Instead of dogmatically running every test in the book, they prioritize high-risk areas based on code changes and user impact. Or consider a team that invests in automation not because it's trendy, but because they've seen how manual repetition burns out testers and delays releases. This is karma in action: thoughtful decisions that ripple outward in positive ways.
The beauty of a karmic approach is its flexibility. It embraces new tools, techniques, and feedback loops. It's less about "the process" and more about the result - delivering quality software that meets real-world needs. But there's a downside: Without some structure, karma can devolve into chaos. Teams might skip critical steps in the name of agility, only to face a flood of bugs post-release. Karma requires discipline and judgment, not just good intentions.
Striking the Balance
So, is your QA team following dogma or karma? The truth is, neither is inherently "right" or "wrong" - it's about finding the sweet spot between the two.
Audit Your Dogma: Take a hard look at your current processes. Are there sacred cows that no one's questioned in years? Maybe that 50-page test plan made sense for a legacy system but not for your new microservices architecture. Challenge the status quo and ditch what doesn't serve the goal of quality.
Embrace Karmic Wisdom: Encourage your team to think critically about cause and effect. If a process feels like busywork, ask: What's the payoff? If a new tool could save hours, why not try it? Build a culture where decisions are tied to outcomes, not just tradition.
Blend the Best of Both: Use dogma as a foundation - standardized bug reporting, compliance checks, or a core set of tests that never get skipped. Then layer on karmic flexibility - tailoring efforts to the project's unique risks and timelines.
A Real-World Example
I heard of a QA team that swore by their exhaustive manual test suite. Every release, they'd spend two weeks clicking through the UI, even for tiny updates. Dogma ruled. Then a new lead joined, pushing for automation in high-traffic areas. The team resisted - until they saw the karma: faster releases, fewer late-night bug hunts, less late night testing, and happier devs. They didn't abandon manual testing entirely; they just redirected it where human intuition mattered most. The result? A hybrid approach that delivered quality without the grind.
The QA Crossroads
Your QA team's philosophy shapes more than just your testing - it influences your entire product lifecycle. Dogma offers stability but can stifle progress. Karma promises agility but demands discernment. The best teams don't pick a side; they dance between the two, guided by one question: Does this help us build better software? So, take a moment to reflect. Is your QA team stuck in the past, or are they sowing seeds for a better future? The answer might just determine whether your next release is a triumph - or a lesson in what could've been.
The flexibility of remote working is leading to greater employee satisfaction, better performance outcomes and improved engagement, qualities that reinforce all Forbes magazine's observation that the hybrid model is the 'key productivity strategy' for the 2020s workplace. For this accolade to be maintained, hybrid workers need to be able to seamlessly transfer between remote locations and their formal workplace without the change of setting compromising efficiency and security. As a result, the work of hybrid employees is highly dependent on company issued equipment that is not only safely delivered but that also remains compliant, secure and well maintained. By taking practical steps to closely monitor the movement of equipment, upgrade devices as soon as necessary and control risks throughout a product's life cycle, businesses can keep their remote workers safely connected, while at the same time avoid unnecessary downtime caused by IT issues and ensure high levels of productivity are maintained.
Safely Delivering Company-Owned Technology
Most businesses prefer to provide hybrid employees with company-owned equipment as, when it is well supported, it can enhance security and encourage productivity. While ensuring compliance, protecting sensitive data and providing effective IT support is enabled with company supplied equipment, the safe delivery, maintenance and tracking of valuable devices across different locations can prove to be difficult, especially for larger companies with extensive networks of hybrid and remote workers. A robust device management system is essential for the management of company-supplied equipment and can address these issues with clear processes for monitoring devices and providing regular updates on their location. It can also oversee the safe return of equipment when it is no longer needed and, if a device is lost or stolen, allow the remote wiping of data to ensure company-wide cybersecurity.
Replacing Old and Outdated Devices
While managing the safe deployment of equipment, productivity can still suffer if equipment for hybrid workers is not regularly updated. Aging devices are slower to run, cause unnecessary downtime and require more technical support. However, even though older PCs and outdated laptops can have an impact on productivity, at least 40 percent of small and medium-sized businesses are failing to implement or follow a PC refresh policy. Keeping a record of the age and condition of company supplied devices allows managers to see when they are due to be upgraded. Even when IT budgets are stretched, continuing the issue and maintenance of out of date hardware is a false economy. To ensure cybersecurity and compatibility with new software, promptly upgrading devices will improve overall efficiency and worker productivity in the longer term.
Ensuring Secure Remote Access
Now that 38% of US employees are working remotely at least some of the time, finding ways to safely access off prem devices can also be a problem. While many workers are concerned about being monitored when working from home, their employer has the right to track their activity if they are using technology provided by the company. IT support teams also need access to their colleagues' computers in order to reconfigure settings, update files and provide help with technical issues but this open remote access can compromise cybersecurity. Log in systems that use a cloud directory with multi factor authentication can help to safely connect users, while a VPN can be used to securely deploy software to remote equipment. A good time to schedule software updates or the transfer of sensitive data is when hybrid workers are visiting the office. Raising cybersecurity awareness among workers is crucial for any company with hybrid workers, and when robust security protocols are introduced and followed, workflow and productivity remains high as computer updates are seamlessly introduced and system disruptions due to technical issues are minimized.
As hybrid working remains a popular choice for many employees, ensuring they are able to work efficiently and safely off prem is a growing concern for many businesses. By carefully managing the deployment and return of devices, upgrading equipment when necessary and implementing company-wide cybersecurity protocols, businesses can keep their hybrid workers connected and well supported. This in turn increases employee satisfaction and productivity levels, even when workers are located remotely.
If you do any work with PDFs, the site ilovepdf.com is for you!
This is your one stop source for anything you could ever want to do with PDFs:
Merge PDF - Combine PDFs in the order you want with the easiest PDF merger available.
Split PDF- Separate one page or a whole set for easy conversion into independent PDF files.
Compress PDF - Reduce file size while optimizing for maximal PDF quality.
PDF to Word - Easily convert your PDF files into easy to edit DOC and DOCX documents. The converted WORD document is almost 100% accurate.
PDF to PowerPoint - Turn your PDF files into easy to edit PPT and PPTX slideshows.
PDF to Excel - Pull data straight from PDFs into Excel spreadsheets in a few short seconds.
Word to PDF - Make DOC and DOCX files easy to read by converting them to PDF.
PowerPoint to PDF - Make PPT and PPTX slideshows easy to view by converting them to PDF.
Excel to PDF - Make EXCEL spreadsheets easy to read by converting them to PDF.
Edit PDF - Add text, images, shapes or freehand annotations to a PDF document. Edit the size, font, and color of the added content.
PDF to JPG - Convert each PDF page into a JPG or extract all images contained in a PDF.
JPG to PDF - Convert JPG images to PDF in seconds. Easily adjust orientation and margins.
and 14 more tools!
Website Description
Every tool you need to use PDFs, at your fingertips. All are 100% FREE and easy to use! Merge, split, compress, convert, rotate, unlock and watermark PDFs with just a few clicks.
In 2019, I purchased a new iMac. The computer is now six years old. I was thinking if I got a new MacBook pro would there be a significant difference?
I put the question to the test to Grok3, and was surprised to find out that I would notice a big difference. Basically I should see a significant difference. The only downside would be missing the larger screen.
This information is useful for anyone that purchased a computer in the pre-Apple chip days.
2019 iMac
The 2019 iMac came in 21.5-inch and 27-inch variants with Intel processors. For a balanced comparison, let's take a mid-to-high-end model: the 27-inch iMac with a 3.7 GHz 6-core Intel Core i5 (9th-gen Coffee Lake, Turbo Boost up to 4.6 GHz). It typically shipped with 8 GB of DDR4 RAM (upgradable to 64 GB), a Radeon Pro 580X GPU with 8 GB VRAM, and a 1 TB Fusion Drive or optional SSD. Geekbench 5 scores for this model are roughly 1,100?1,200 single-core and 5,500?6,000 multi-core, based on historical data for similar 9th-gen Intel chips. Storage speeds for the Fusion Drive were around 50?100 MB/s for the HDD component and up to 500 MB/s for the SSD portion, while a full SSD option hit ~1,500 MB/s read/write.
Today's MacBook (2025)
As of March 8, 2025, current MacBooks include the MacBook Air (M4) and MacBook Pro (M4, M4 Pro, M4 Max). For a fair comparison, let's use the base MacBook Air M4: a 10-core CPU (4 performance, 6 efficiency cores), 10-core GPU, 16 GB unified memory, and a 256 GB SSD with read/write speeds of ~3,000?5,000 MB/s. Geekbench 6 scores for the M4 are approximately 3,200 single-core and 12,500 multi-core, reflecting Apple's claims of incremental gains over the M3 and real-world tests of early M4 models. The unified memory architecture provides 120 GB/s bandwidth, far outpacing traditional RAM setups.
Speed Comparison
CPU Performance:
Single-Core: 2019 iMac (~1,150 Geekbench 5) vs.?MacBook Air M4 (~3,200 Geekbench 6). Adjusting for benchmark differences (Geekbench 6 scores are ~10?15% higher than Geekbench 5 for the same hardware), the M4 is roughly 2.5?3x faster in single-threaded tasks. This reflects better architecture (ARM vs.?x86) and higher efficiency.
Multi-Core: 2019 iMac (~5,750 Geekbench 5) vs.?MacBook Air M4 (~12,500 Geekbench 6). The M4 is ~2?2.5x faster, thanks to its 10 cores (vs.?6) and optimized design for parallel workloads.
Memory:
2019 iMac: 8 GB DDR4 at ~2,666 MHz (~20?30 GB/s bandwidth), upgradable but still separate from the CPU/GPU.
MacBook Air M4: 16 GB unified memory at 120 GB/s. The M4's memory is ~4?6x faster in bandwidth and integrated, reducing latency. Even with a maxed-out 64 GB iMac config, bandwidth wouldn't approach the M4's.
Storage:
2019 iMac: Fusion Drive (~50?500 MB/s) or SSD (~1,500 MB/s).
MacBook Air M4: SSD (~3,000?5,000 MB/s). The M4's storage is 2?10x faster, depending on the iMac's config, slashing load times and improving file transfers.
Graphics:
2019 iMac: Radeon Pro 580X (~1,200?1,500 GFLOPS, good for 2019 gaming/editing).
MacBook Air M4: 10-core GPU (~4?5 TFLOPS, estimated from M3's ~3 TFLOPS and Apple's claims). The M4's GPU is ~3?4x faster, with hardware ray tracing and better power efficiency, excelling in modern creative workloads.
Real-World Impact:
Boot/App Launch: The iMac took ~20?30 seconds to boot macOS Mojave; the M4 MacBook boots macOS in <10 seconds. Apps like Photoshop might open in 5?10 seconds on the iMac vs.?<2 seconds on the M4.
Workloads: Video encoding (e.g., 4K H.264) could take 2x longer on the iMac. The M4's Neural Engine and media accelerators further widen the gap for AI/ML tasks or ProRes editing - tasks the iMac struggles with.
Conclusion
The MacBook Air M4 (2025) is dramatically faster than a 2019 iMac - 2?3x in CPU performance, 3?4x in graphics, and up to 10x in storage speed. The gap widens with higher-end MacBook Pro M4 models (e.g., M4 Max with 40 GPU cores and 400 GB/s bandwidth). The 2019 iMac's Intel architecture and older components can't compete with Apple Silicon's efficiency and integration. For everyday tasks, creative work, or even heavy lifting, today's MacBook leaves the 2019 iMac in the dust - think minutes vs.?seconds for complex jobs.
Yesterday, I showed how to use Parametrization in Pytest. Here's an example of how you would run that same code in PlayWright with TypeScript:
This code checks to make sure the four websites are up and running. This is just a quick sanity test, it doesn't do any critical path testing.
import{ test, expect }from'@playwright/test';// List of websites to test
const WEBSITES =["https://www.company.com","https://qa1.company.com","https://qa2.company.com","https://stage.company.com",];// Configure Playwright to run in headless mode globally
test.use({ headless: true });
test(`Check Websites Status`,async({ page })=>{// Iterate over websites to create a test for each
for(const website of WEBSITES){
test(`Check if ${website}is up and running`,async({ page })=>{try{// Attempt to load the website
await page.goto(website,{ waitUntil:'domcontentloaded'});// Check if page title exists andisnot empty
const title =await page.title();
expect(title).not.toBe('');// Check if body element exists
const body = page.locator('body');await expect(body).toBeVisible();// Log success
console.log(`? ${website}is up and running (Title: ${title})`);} catch (error){// Oh the Horror: Fail the test with a detailed message
throw new Error(`Website ${website} failed: ${error.message}`);}});}})
Welcome to cryan.com's main blog page! Here you'll find a diverse collection of informative posts covering topics ranging from technology and lifestyle to career advice. There's something here for everyone.
We are committed to delivering the highest quality content, ensuring you have access to the most current and reliable information.
