#Customized Python Application

[triazinesoft]

Premier Web Application Development Services- Triazinesoft

Choose Triazinesoft for expert and trusted web application development services. Our team of skilled developers creates custom applications that drive success for your business. Contact us today to learn more.

Triazinesoft is a trusted web application development company known for its innovative solutions, client-centric approach, and proven track record of success. With a mission to deliver high-quality web applications tailored to meet each client's unique needs, Triazinesoft combines expertise in cutting-edge technologies with a commitment to transparency and collaboration. This article explores the key factors that set Triazinesoft apart in the competitive web development industry, highlighting its specialized services, client testimonials, and rigorous quality assurance practices. Discover how partnering with Triazinesoft can elevate your web development projects to new heights of success.

Introduction to Triazinesoft

Triazinesoft is not your average web application development company. They blend expertise with a sprinkle of creativity and a dash of reliability, creating a concoction that leaves clients coming back for more.

About Triazinesoft

Triazinesoft is a web application development company that prides itself on delivering innovative solutions with a touch of personality. Their team is a mix of tech-savvy wizards and creative minds, all working towards one goal - making your digital dreams a reality.

Mission and Values

At Triazinesoft, the mission is simple yet powerful - to create web applications that not only meet but exceed client expectations. They value transparency, reliability, and the occasional office prank to keep things interesting.

Expertise in Web Application Development

Triazinesoft doesn't just build web applications; they craft digital experiences that leave a lasting impression. Their expertise in web application development is unmatched, with a track record of delivering top-notch solutions that stand the test of time.

Specialized Services Offered

From custom web application development to e-commerce solutions, Triazinesoft offers a wide range of specialized services to cater to every client's unique needs. No project is too big or too small for their team of dedicated professionals.

Technology Stack

Triazinesoft stays ahead of the curve by utilizing a cutting-edge technology stack that ensures their web applications are not only functional but also future-proof. From front-end frameworks to back-end databases, they have the tools to bring your vision to life.

Client-Centric Approach and Trustworthiness

At Triazinesoft, the client always comes first. They take the time to understand your needs, preferences, and quirks to deliver a web application that truly reflects your brand. Trust is not just a word but a cornerstone of their business philosophy.

Understanding Client Needs

Triazinesoft goes beyond the surface level to truly grasp what you want your web application to achieve. They ask the right questions, listen intently, and collaborate closely with you to ensure every detail is perfect.

Building Trust through Transparency

Transparency is the secret sauce that makes Triazinesoft stand out. They keep you in the loop every step of the way, providing regular updates, open communication, and a friendly face to put your mind at ease.

Innovative Solutions and Technologies

In a world where technology evolves at the speed of light, Triazinesoft stays at the forefront by embracing innovative solutions and cutting-edge technologies. They don't just solve problems; they invent new ways to approach them.

Adopting Cutting-Edge Technologies

Triazinesoft isn't afraid to push the boundaries when it comes to technology. They stay up-to-date with the latest trends, tools, and techniques to ensure your web application is not just functional but also ahead of the curve.

Creative Problem-Solving Approach

When faced with a digital dilemma, Triazinesoft doesn't shy away. They tackle challenges with a creative flair, thinking outside the box to come up with solutions that are as unique as your business.### **Proven Track Record of Success** Triazinesoft doesn't just talk the talk; they walk the walk when it comes to delivering successful web applications. Dive into their case studies and success stories to see how they've helped clients achieve their digital dreams.

 Collaborative Development Process At Triazinesoft, they believe in working hand-in-hand with clients throughout the development cycle. Expect plenty of collaboration, brainstorming sessions, and opportunities to provide feedback. It's a partnership, not just a project.

Quality Assurance and Testing Practices Triazinesoft doesn't cut corners when it comes to quality assurance. With rigorous testing procedures in place, they ensure that every line of code meets their high standards. Expect polished, high-quality deliverables every time.

Conclusion: Partnering with Triazinesoft for Web Development Success When it comes to web development success, Triazinesoft is the partner you need. With a proven track record, a collaborative development process, and top-notch quality assurance practices, they've got all the tools to bring your web application vision to life. Trust Triazinesoft for a web development journey that's both successful and enjoyable.In conclusion, Triazinesoft stands out as a reliable partner for web application development, offering a winning combination of expertise, trustworthiness, and client-focused approach. By leveraging their innovative solutions, proven track record, and commitment to quality, Triazinesoft ensures the success of each project they undertake. Choose Triazinesoft for your web development needs and experience the difference that a dedicated and experienced team can make in achieving your digital goals.

FAQ

1. What sets Triazinesoft apart from other web development companies?

2. How does Triazinesoft ensure the quality and reliability of their web applications?

3. Can clients actively participate in the development process with Triazinesoft?

4. What technologies does Triazinesoft specialize in for web application development?

[corporatewebsitedev]

Corporate Website Development

LA Marketing offers corporate website development tailored to businesses of all sizes. They create professional, high-performance websites that enhance brand image, engage clients, and support business goals. Their service includes custom design, integration with business tools like CRM systems, SEO optimization, and ongoing technical support to ensure scalability and security. Whether for small businesses or large corporations, LA Marketing ensures a customized solution that reflects the company's vision.

For more details, visit:

Website: https://la-marketing.us/services/web-development/corporate-website

Facebook: https://www.facebook.com/profile.php?id=61564412960524 

Linkedin: https://www.linkedin.com/company/dg-marketingcom/

X:  https://x.com/foreck_info

[robomad]

Effective Django Signals: Mastering Connection and Listening

Mastering Django Signals: Connecting and Listening Effectively

Introduction Django signals are a powerful feature that allows decoupled applications to get notified when certain actions occur elsewhere in the framework. They provide a way for a piece of code to send notifications to interested parties without requiring those parties to be tightly coupled. This article will delve into the world of Django signals, explaining how to connect and listen to them…

[advatal-technologies]

Advantal Technologies - Web Development Company

Advantal Technologies is a software solutions company known for empowering businesses with innovative technological solutions to become market leaders. We offer custom software solutions, enterprise mobility solutions, UI/UX designing, IT Consulting, project management, manpower outsourcing, mobile application development and secure communication products. For inquiries, please send us an email at info@advantal.net For more info, please visit www.advantaltechnologies.com

[kevinsoftwaresolutions]

Elevate Your Business with Custom Python Web Applications: Hire Dedicated Python Developer Today

In the ever-evolving landscape of technology, Python stands out as a versatile and powerful programming language, offering an array of opportunities for businesses to thrive. If you're aiming for tailored solutions that meet your unique requirements, custom Python web applications are the key to unlocking success. Embrace the future of web development by hiring a dedicated Python developer who can transform your ideas into reality.

Why Python for Custom Web Applications?

1. Versatility:

Python's versatility makes it an ideal choice for developing custom web applications. Whether you need a robust backend system, data analysis tools, or interactive user interfaces, Python can do it all.

2. Rapid Development:

Python's clean syntax and extensive libraries accelerate the development process. This efficiency is crucial for businesses looking to roll out products and services swiftly, gaining a competitive edge in the market.

3. Scalability:

As your business grows, so should your applications. Python's scalability ensures that your web solutions can handle increased user loads and data without compromising performance.

4. Community Support:

Python boasts a vibrant and active community of developers. This means continuous support, updates, and a plethora of resources to enhance your custom web applications.

Hire Dedicated Python Developer – Your Gateway to Success!

Why Opt for a Dedicated Python Developer?

Expertise:

A dedicated Python developer brings specialized skills and expertise to the table. Their in-depth knowledge of Python ensures that your web applications are built with precision and efficiency.

Custom Solutions:

Hiring a dedicated Python developer allows you to tailor solutions according to your business needs. From e-commerce platforms to data analytics tools, they can craft applications that align perfectly with your objectives.

Focused Attention:

Your project deserves undivided attention. With a dedicated Python developer, you have a professional solely devoted to your project, ensuring timely delivery and high-quality results.

Cost-Effective:

Contrary to common misconceptions, hiring a dedicated Python developer can be cost-effective. You pay for the specific skill set you need, without the overhead costs associated with in-house teams.

Custom Python Web Applications Development Process

Discovery Phase:

Collaborate with our dedicated Python developer to understand your business goals and requirements thoroughly.

Design & Planning:

Create a blueprint for your custom web application, ensuring it aligns with your brand identity and user experience expectations.

Development & Testing:

Implement the design, utilizing Python's capabilities to build a robust and scalable application. Rigorous testing is conducted to ensure functionality and security.

Deployment:

Roll out your custom Python web application seamlessly, with our dedicated developer providing support during the launch phase.

Maintenance & Updates:

Our commitment doesn't end with deployment. Regular maintenance and updates are crucial to keep your application secure and up-to-date with the latest technologies.

FAQs

Q1: Why should I choose Python for web development?

Python is chosen for its versatility, rapid development capabilities, scalability, and a vibrant community. It allows for the creation of robust, efficient, and scalable web applications.

Q2: How can a dedicated Python developer benefit my business?

A dedicated Python developer brings specialized skills, focused attention, and cost-effectiveness to your project, ensuring that your custom web applications are tailored to your business needs.

Q3: What is the development process for custom Python web applications?

The process involves discovery, design & planning, development & testing, deployment, and ongoing maintenance & updates. This ensures a systematic and thorough approach to building your web application.

In conclusion, the world of custom Python web applications is vast and filled with possibilities. Elevate your business by embracing the power of Python and hiring a dedicated developer to turn your visions into reality. Let's embark on a journey to transform your digital presence and achieve unparalleled success in the online realm.

[august-infotech]

Tips and Tricks of the Python Language: A Guide to Efficient Programming

Dive into the world of Python programming with Cherish Patel, an accomplished Python developer at August Infotech, as he unravels some invaluable tips and tricks to elevate your coding game. Cherish, armed with extensive hands-on experience, shares practical insights that go beyond the theoretical, offering a fresh perspective on Python development.

In Python, the common perception is that the random module generates random values every time a method is called. However, this is only partially true. By setting a seed using random.seed(), you can ensure consistent output across different runs. This is particularly crucial when dealing with sensitive information, such as private keys.

Enhance code readability by incorporating underscores in large numerical values, making them more manageable and visually appealing. Cherish demonstrates this practice and showcases an additional formatting option using commas for better readability. Similar enhancements in other languages are briefly explored.

Optimize memory usage by employing slots in your classes. This approach is essential to Python memory optimization, using a list instead of dictionaries for better performance. For those eager to explore more about Python's capabilities, additional resources on Django application performance and Python for web development are recommended. Discover how Python's flexibility can create high-performance applications tailored to specific needs.

Join the Python revolution with August Infotech and Cherish Patel – where innovation meets excellence in Advanced Python techniques - https://bit.ly/48YFMhc

August Infotech, is a known offshore development company a renowned name in the tech industry, stands at the forefront of innovation and technological advancement. The company specializes in Python and offers services catering to various business needs, including Data Science, Minimum Viable Product (MVP) development, and comprehensive Web Applications.

[mostlysignssomeportents]

What kind of bubble is AI?

My latest column for Locus Magazine is "What Kind of Bubble is AI?" All economic bubbles are hugely destructive, but some of them leave behind wreckage that can be salvaged for useful purposes, while others leave nothing behind but ashes:

https://locusmag.com/2023/12/commentary-cory-doctorow-what-kind-of-bubble-is-ai/

Think about some 21st century bubbles. The dotcom bubble was a terrible tragedy, one that drained the coffers of pension funds and other institutional investors and wiped out retail investors who were gulled by Superbowl Ads. But there was a lot left behind after the dotcoms were wiped out: cheap servers, office furniture and space, but far more importantly, a generation of young people who'd been trained as web makers, leaving nontechnical degree programs to learn HTML, perl and python. This created a whole cohort of technologists from non-technical backgrounds, a first in technological history. Many of these people became the vanguard of a more inclusive and humane tech development movement, and they were able to make interesting and useful services and products in an environment where raw materials – compute, bandwidth, space and talent – were available at firesale prices.

Contrast this with the crypto bubble. It, too, destroyed the fortunes of institutional and individual investors through fraud and Superbowl Ads. It, too, lured in nontechnical people to learn esoteric disciplines at investor expense. But apart from a smattering of Rust programmers, the main residue of crypto is bad digital art and worse Austrian economics.

Or think of Worldcom vs Enron. Both bubbles were built on pure fraud, but Enron's fraud left nothing behind but a string of suspicious deaths. By contrast, Worldcom's fraud was a Big Store con that required laying a ton of fiber that is still in the ground to this day, and is being bought and used at pennies on the dollar.

AI is definitely a bubble. As I write in the column, if you fly into SFO and rent a car and drive north to San Francisco or south to Silicon Valley, every single billboard is advertising an "AI" startup, many of which are not even using anything that can be remotely characterized as AI. That's amazing, considering what a meaningless buzzword AI already is.

So which kind of bubble is AI? When it pops, will something useful be left behind, or will it go away altogether? To be sure, there's a legion of technologists who are learning Tensorflow and Pytorch. These nominally open source tools are bound, respectively, to Google and Facebook's AI environments:

https://pluralistic.net/2023/08/18/openwashing/#you-keep-using-that-word-i-do-not-think-it-means-what-you-think-it-means

But if those environments go away, those programming skills become a lot less useful. Live, large-scale Big Tech AI projects are shockingly expensive to run. Some of their costs are fixed – collecting, labeling and processing training data – but the running costs for each query are prodigious. There's a massive primary energy bill for the servers, a nearly as large energy bill for the chillers, and a titanic wage bill for the specialized technical staff involved.

Once investor subsidies dry up, will the real-world, non-hyperbolic applications for AI be enough to cover these running costs? AI applications can be plotted on a 2X2 grid whose axes are "value" (how much customers will pay for them) and "risk tolerance" (how perfect the product needs to be).

Charging teenaged D&D players $10 month for an image generator that creates epic illustrations of their characters fighting monsters is low value and very risk tolerant (teenagers aren't overly worried about six-fingered swordspeople with three pupils in each eye). Charging scammy spamfarms $500/month for a text generator that spits out dull, search-algorithm-pleasing narratives to appear over recipes is likewise low-value and highly risk tolerant (your customer doesn't care if the text is nonsense). Charging visually impaired people $100 month for an app that plays a text-to-speech description of anything they point their cameras at is low-value and moderately risk tolerant ("that's your blue shirt" when it's green is not a big deal, while "the street is safe to cross" when it's not is a much bigger one).

Morganstanley doesn't talk about the trillions the AI industry will be worth some day because of these applications. These are just spinoffs from the main event, a collection of extremely high-value applications. Think of self-driving cars or radiology bots that analyze chest x-rays and characterize masses as cancerous or noncancerous.

These are high value – but only if they are also risk-tolerant. The pitch for self-driving cars is "fire most drivers and replace them with 'humans in the loop' who intervene at critical junctures." That's the risk-tolerant version of self-driving cars, and it's a failure. More than $100b has been incinerated chasing self-driving cars, and cars are nowhere near driving themselves:

https://pluralistic.net/2022/10/09/herbies-revenge/#100-billion-here-100-billion-there-pretty-soon-youre-talking-real-money

Quite the reverse, in fact. Cruise was just forced to quit the field after one of their cars maimed a woman – a pedestrian who had not opted into being part of a high-risk AI experiment – and dragged her body 20 feet through the streets of San Francisco. Afterwards, it emerged that Cruise had replaced the single low-waged driver who would normally be paid to operate a taxi with 1.5 high-waged skilled technicians who remotely oversaw each of its vehicles:

https://www.nytimes.com/2023/11/03/technology/cruise-general-motors-self-driving-cars.html

The self-driving pitch isn't that your car will correct your own human errors (like an alarm that sounds when you activate your turn signal while someone is in your blind-spot). Self-driving isn't about using automation to augment human skill – it's about replacing humans. There's no business case for spending hundreds of billions on better safety systems for cars (there's a human case for it, though!). The only way the price-tag justifies itself is if paid drivers can be fired and replaced with software that costs less than their wages.

What about radiologists? Radiologists certainly make mistakes from time to time, and if there's a computer vision system that makes different mistakes than the sort that humans make, they could be a cheap way of generating second opinions that trigger re-examination by a human radiologist. But no AI investor thinks their return will come from selling hospitals that reduce the number of X-rays each radiologist processes every day, as a second-opinion-generating system would. Rather, the value of AI radiologists comes from firing most of your human radiologists and replacing them with software whose judgments are cursorily double-checked by a human whose "automation blindness" will turn them into an OK-button-mashing automaton:

https://pluralistic.net/2023/08/23/automation-blindness/#humans-in-the-loop

The profit-generating pitch for high-value AI applications lies in creating "reverse centaurs": humans who serve as appendages for automation that operates at a speed and scale that is unrelated to the capacity or needs of the worker:

https://pluralistic.net/2022/04/17/revenge-of-the-chickenized-reverse-centaurs/

But unless these high-value applications are intrinsically risk-tolerant, they are poor candidates for automation. Cruise was able to nonconsensually enlist the population of San Francisco in an experimental murderbot development program thanks to the vast sums of money sloshing around the industry. Some of this money funds the inevitabilist narrative that self-driving cars are coming, it's only a matter of when, not if, and so SF had better get in the autonomous vehicle or get run over by the forces of history.

Once the bubble pops (all bubbles pop), AI applications will have to rise or fall on their actual merits, not their promise. The odds are stacked against the long-term survival of high-value, risk-intolerant AI applications.

The problem for AI is that while there are a lot of risk-tolerant applications, they're almost all low-value; while nearly all the high-value applications are risk-intolerant. Once AI has to be profitable – once investors withdraw their subsidies from money-losing ventures – the risk-tolerant applications need to be sufficient to run those tremendously expensive servers in those brutally expensive data-centers tended by exceptionally expensive technical workers.

If they aren't, then the business case for running those servers goes away, and so do the servers – and so do all those risk-tolerant, low-value applications. It doesn't matter if helping blind people make sense of their surroundings is socially beneficial. It doesn't matter if teenaged gamers love their epic character art. It doesn't even matter how horny scammers are for generating AI nonsense SEO websites:

https://twitter.com/jakezward/status/1728032634037567509

These applications are all riding on the coattails of the big AI models that are being built and operated at a loss in order to be profitable. If they remain unprofitable long enough, the private sector will no longer pay to operate them.

Now, there are smaller models, models that stand alone and run on commodity hardware. These would persist even after the AI bubble bursts, because most of their costs are setup costs that have already been borne by the well-funded companies who created them. These models are limited, of course, though the communities that have formed around them have pushed those limits in surprising ways, far beyond their original manufacturers' beliefs about their capacity. These communities will continue to push those limits for as long as they find the models useful.

These standalone, "toy" models are derived from the big models, though. When the AI bubble bursts and the private sector no longer subsidizes mass-scale model creation, it will cease to spin out more sophisticated models that run on commodity hardware (it's possible that Federated learning and other techniques for spreading out the work of making large-scale models will fill the gap).

So what kind of bubble is the AI bubble? What will we salvage from its wreckage? Perhaps the communities who've invested in becoming experts in Pytorch and Tensorflow will wrestle them away from their corporate masters and make them generally useful. Certainly, a lot of people will have gained skills in applying statistical techniques.

But there will also be a lot of unsalvageable wreckage. As big AI models get integrated into the processes of the productive economy, AI becomes a source of systemic risk. The only thing worse than having an automated process that is rendered dangerous or erratic based on AI integration is to have that process fail entirely because the AI suddenly disappeared, a collapse that is too precipitous for former AI customers to engineer a soft landing for their systems.

This is a blind spot in our policymakers debates about AI. The smart policymakers are asking questions about fairness, algorithmic bias, and fraud. The foolish policymakers are ensnared in fantasies about "AI safety," AKA "Will the chatbot become a superintelligence that turns the whole human race into paperclips?"

https://pluralistic.net/2023/11/27/10-types-of-people/#taking-up-a-lot-of-space

But no one is asking, "What will we do if" – when – "the AI bubble pops and most of this stuff disappears overnight?"

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2023/12/19/bubblenomics/#pop

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

--

tom_bullock (modified) https://www.flickr.com/photos/tombullock/25173469495/

CC BY 2.0 https://creativecommons.org/licenses/by/2.0/

[bare1ythere]

How to back up your tumblr blog with Tumblr-Utils FOR MAC USERS

I've seen a few guides floating around on how to use some more complex options for backing up your tumblr blog, but most are extremely PC focused. Here is a guide for fellow (unfortunate) mac users!

Note: I am not a tech savvy person at all. My brother walked me through this, and I'm just sharing what he told me. Unfortunately I won't be able to help much if you need trouble shooting or advice ;; sorry! This is also based off of this guide (link) by @/magz.

- - - - GUIDE - - - -

First, open terminal. You can command+space to search through your applications, and search for "terminal". It should look like this.

You should see something like this within the window:

[COMPUTER NAME]:~ [USER NAME]$ []

First, create a virtual environment for tumblr back up. This will limit any conflicts with other python programs. Type and enter this into terminal:

python3 -m venv .tumblr_backup

Then, Activate the virtual environment by entering this:

source .tumblr_backup/bin/activate

The next line should now show something like this:

(.tumblr_backup) [COMPUTER NAME]:~ [USER NAME]$ []

As a side note, you can exit this virtual environment by typing and entering "deactivate". You can re-enter it through the previous line we used to activate it to begin with.

Next, install the base package with this line:

python3 -m pip install tumblr-backup

The linked guide details various options for tumblr back up packages that you can install. Copied from the guide for convenience:

"tumblr-backup : default tumblr-backup[video] : adds option to download videos tumblr-backup[exif] : adds option to download EXIF information of fotos (photography metadata information) tumblr-backup[notes] : adds option to download notes of posts (huge) tumblr-backup[jq] : adds option to filter which posts to backup  tumblr-backup[all] : adds all options (personally doesn't work for us at the moment of writing this)"

I chose the video option, but you can pick which you'd like. Download that specific package with this line. Note that unlike the previous lines Ive shown, the square brackets here are actually part of it and must be used:

python3 -m pip install tumblr-backup[OPTION]

Next, you need to create an app linked to your tumblr account to get an OAuth consumer key (aka API key). Go to this link: [https://www.tumblr.com/oauth/apps] and click the [+Register application] button. Here, you will have to input a bunch of info. What you put doesn't really matter. This is how the original guide filled it out, and I did pretty much the exact same thing:

(The github link for your convenience: https://github.com/Cebtenzzre/tumblr-utils)

For the next step, You'll take the OAuth consumer key (NOT the secret key) and set it as the API key in tumblr-utils to give it the ability to download your blog. Input this line. Note that in this case, the square brackets are NOT to be included- just copy and paste the key:

tumblr-backup --set-api-key [YOUR OAUTH CONSUMER KEY]

This will set you up to start your back up! Type this to see all the different customization options you can pick from for your backup:

tumblr-backup --help

To begin your back up, pick which options you want to choose from and select which of your blogs you want to back up. It should look like this:

tumblr-backup [OPTIONS] [BLOG NAME]

For example, I am currently backing up this blog and I wanted to save videos as well as reversing the post order in the monthly archives. This is what my command looked like:

tumblr-backup -r --save-video bare1ythere

And there you have it! Your backup will be saved into a file titled after your blog. You can search through finder for it from there. There is also an option to specify where you want to save your blog, but I'm not sure how it works. I hope this was useful!!

[b3aches]

Quick Tumblr Backup Guide (Linux)

Go to www.tumblr.com/oauth/apps and click the "Register Application" button

Fill in the form. I used the following values for the required fields: Application Name - tumblr-arch Application Website - https://github.com/Cebtenzzre/tumblr-utils Application Description - tumblr archival instance based on tumblr-utils Adminstrative contact email - < my personal email > Default callback URL - https://github.com/Cebtenzzre/tumblr-utils OAuth2 redirect URLs - https://github.com/Cebtenzzre/tumblr-utils

Get the OAuth Consumer Key for your application. It should be listed right on the www.tumblr.com/oauth/apps page.

Do python things:

# check python version: python --version # I've got Python 3.9.9 # create a venv: python -m venv --prompt tumblr-bkp --upgrade-deps venv # activate the venv: source venv/bin/activate # install dependencies: pip install tumblr-backup pip install tumblr-backup[video] pip install tumblr-backup[jq] pip install tumblr-backup[bs4] # Check dependencies are all installed: pip freeze # set the api key: tumblr-backup --set-api-key <OAuth Consumer Key>

So far I have backed up two blogs using the following:

tumblr-backup --save-audio --save-video --tag-index --save-notes --incremental -j --no-post-clobber --media-list <blog name>

There have been two issues I had to deal with so far:

one of the blogs was getting a "Non-OK API repsonse: HTTP 401 Unauthorized". It further stated that "This is a dashboard-only blog, so you probably don't have the right cookies. Try --cookiefile." I resolved the issue by a) setting the "Hide from people without an account" to off and b) enabling a custom theme. I think only step a) was actually necessary though.

"Newly registered consumers are rate limited to 1,000 requests per hour, and 5,000 requests per day. If your application requires more requests for either of these periods, please use the 'Request rate limit removal' link on an app above." Depending on how big your blog is, you may need to break up the download. I suspect using the "-n COUNT" or "--count COUNT" to save only COUNT posts at a time, combined with the "--incremental" will allow you to space things out. You would have to perform multiple passes though. I will have to play with that, so I'll report back my findings.

[anheliotrope]

Rambling About C# Being Alright

I think C# is an alright language. This is one of the highest distinctions I can give to a language.

Warning: This post is verbose and rambly and probably only good at telling you why someone might like C# and not much else.

~~~

There's something I hate about every other language. Worst, there's things I hate about other languages that I know will never get better. Even worse, some of those things ALSO feel like unforced errors.

With C# there's a few things I dislike or that are missing. C#'s feature set does not obviously excel at anything, but it avoids making any huge misstep in things I care about. Nothing in C# makes me feel like the language designer has personally harmed me.

C# is a very tolerable language.

C# is multi-paradigm.

C# is the Full Middle Malcomist language.

C# will try to not hurt you.

A good way to describe C# is "what if Java sucked less". This, of course, already sounds unappealing to many, but that's alright. I'm not trying to gas it up too much here.

C# has sins, but let's try to put them into some context here and perhaps the reason why I'm posting will become more obvious:

C# didn't try to avoid generics and then implement them in a way that is very limiting (cough Go).

C# doesn't hamstring your ability to have statement lambdas because the language designer dislikes them and also because the language designer decided to have semantic whitespace making statement lambdas harder to deal with (cough Python).

C# doesn't require you to explicitly wrap value types into reference types so you can put value types into collections (cough Java).

C# doesn't ruin your ability to interact with memory efficiently because it forbids you from creating custom value types, ergo everything goes to the heap (cough cough Java, Minecraft).

C# doesn't have insane implicit type coercions that have become the subject of language design comedy (cough JavaScript).

C# doesn't keep privacy accessors as a suggestion and has the developers pinkie swear about it instead of actually enforcing it (cough cough Python).

Plainly put, a lot of the time I find C# to be alright by process of elimination. I'm not trying to shit on your favorite language. Everyone has different things they find tolerable. I have the Buddha nature so I wish for all things to find their tolerable language.

I do also think that C# is notable for being a mainstream language (aka not Haskell) that has a smaller amount of egregious mistakes, quirks and Faustian bargains.

The Typerrrrr

C# is statically typed, but the typing is largely effortless to navigate unlike something like Rust, and the GC gives a greater degree of safety than something like C++.

Of course, the typing being easy to work it also makes it less safe than Rust. But this is an appropriate trade-off for certain kinds of applications, especially considering that C# is memory safe by virtue of running on a VM. Don't come at me, I'm a Rust respecter!!

You know how some people talk about Python being amazing for prototyping? That's how I feel about C#. No matter how much time I would dedicate to Python, C# would still be a more productive language for me. The type system would genuinely make me faster for the vast majority of cases. Of course Python has gradual typing now, so any comparison gets more difficult when you consider that. But what I'm trying to say is that I never understood the idea that doing away entirely with static typing is good for fast iteration.

Also yes, C# can be used as a repl. Leave me alone with your repls. Also, while the debugger is active you can also evaluate arbitrary code within the current scope.

I think that going full dynamic typing is a mistake in almost every situation. The fact that C# doesn't do that already puts it above other languages for me. This stance on typing is controversial, but it's my opinion that is really shouldn't be. And the wind has constantly been blowing towards adding gradual typing to dynamic languages.

The modest typing capabilities C# coupled with OOP and inheritance lets you create pretty awful OOP slop. But that's whatever. At work we use inheritance in very few places where it results in neat code reuse, and then it's just mostly interfaces getting implemented.

C#'s typing and generic system is powerful enough to offer you a plethora of super-ergonomic collection transformation methods via the LINQ library. There's a lot of functional-style programming you can do with that. You know, map, filter, reduce, that stuff?

Even if you make a completely new collection type, if it implements IEnumerable<T> it will benefit from LINQ automatically. Every language these days has something like this, but it's so ridiculously easy to use in C#. Coupled with how C# lets you (1) easily define immutable data types, (2) explicitly control access to struct or class members, (3) do pattern matching, you can end up with code that flows really well.

A Friendly Kitchen Sink

Some people have described C#'s feature set as bloated. It is getting some syntactic diversity which makes it a bit harder to read someone else's code. But it doesn't make C# harder to learn, since it takes roughly the same amount of effort to get to a point where you can be effective in it.

Most of the more specific features can be effortlessly ignored. The ones that can't be effortlessly ignored tend to bring something genuinely useful to the language -- such as tuples and destructuring. Tuples have their own syntax, the syntax is pretty intuitive, but the first time you run into it, you will have to do a bit of learning.

C# has an immense amount of small features meant to make the language more ergonomic. They're too numerous to mention and they just keep getting added.

I'd like to draw attention to some features not because they're the most important but rather because it feels like they communicate the "personality" of C#. Not sure what level of detail was appropriate, so feel free to skim.

Stricter Null Handling. If you think not having to explicitly deal with null is the billion dollar mistake, then C# tries to fix a bit of the problem by allowing you to enable a strict context where you have to explicitly tell it that something can be null, otherwise it will assume that the possibility of a reference type being null is an error. It's a bit more complicated than that, but it definitely helps with safety around nullability.

Default Interface Implementation. A problem in C# which drives usage of inheritance is that with just interfaces there is no way to reuse code outside of passing function pointers. A lot of people don't get this and think that inheritance is just used because other people are stupid or something. If you have a couple of methods that would be implemented exactly the same for classes 1 through 99, but somewhat differently for classes 100 through 110, then without inheritance you're fucked. A much better way would be Rust's trait system, but for that to work you need really powerful generics, so it's too different of a path for C# to trod it. Instead what C# did was make it so that you can write an implementation for methods declared in an interface, as long as that implementation only uses members defined in the interface (this makes sense, why would it have access to anything else?). So now you can have a default implementation for the 1 through 99 case and save some of your sanity. Of course, it's not a panacea, if the implementation of the method requires access to the internal state of the 1 through 99 case, default interface implementation won't save you. But it can still make it easier via some techniques I won't get into. The important part is that default interface implementation allows code reuse and reduces reasons to use inheritance.

Performance Optimization. C# has a plethora of features regarding that. Most of which will never be encountered by the average programmer. Examples: (1) stackalloc - forcibly allocate reference types to the stack if you know they won't outlive the current scope. (2) Specialized APIs for avoiding memory allocations in happy paths. (3) Lazy initialization APIs. (4) APIs for dealing with memory more directly that allow high performance when interoping with C/C++ while still keeping a degree of safety.

Fine Control Over Async Runtime. C# lets you write your own... async builder and scheduler? It's a bit esoteric and hard to describe. But basically all the functionality of async/await that does magic under the hood? You can override that magic to do some very specific things that you'll rarely need. Unity3D takes advantage of this in order to allow async/await to work on WASM even though it is a single-threaded environment. It implements a cooperative scheduler so the program doesn't immediately freeze the moment you do await in a single-threaded environment. Most people don't know this capability exists and it doesn't affect them.

Tremendous Amount Of Synchronization Primitives and API. This ones does actually make multithreaded code harder to deal with, but basically C# erred a lot in favor of having many different ways to do multithreading because they wanted to suit different usecases. Most people just deal with idiomatic async/await code, but a very small minority of C# coders deal with locks, atomics, semaphores, mutex, monitors, interlocked, spin waiting etc. They knew they couldn't make this shit safe, so they tried to at least let you have ready-made options for your specific use case, even if it causes some balkanization.

Shortly Begging For Tagged Unions

What I miss from C# is more powerful generic bounds/constraints and tagged unions (or sum types or discriminated unions or type unions or any of the other 5 names this concept has).

The generic constraints you can use in C# are anemic and combined with the lack of tagged unions this is rather painful at times.

I remember seeing Microsoft devs saying they don't see enough of a usecase for tagged unions. I've at times wanted to strangle certain people. These two facts are related to one another.

My stance is that if you think your language doesn't need or benefit from tagged unions, either your language is very weird, or, more likely you're out of your goddamn mind. You are making me do really stupid things every time I need to represent a structure that can EITHER have a value of type A or a value of type B.

But I think C# will eventually get tagged unions. There's a proposal for it here. I would be overjoyed if it got implemented. It seems like it's been getting traction.

Also there was an entire section on unchecked exceptions that I removed because it wasn't interesting enough. Yes, C# could probably have checked exceptions and it didn't and it's a mistake. But ultimately it doesn't seem to have caused any make-or-break in a comparison with Java, which has them. They'd all be better off with returning an Error<T>. Short story is that the consequences of unchecked exceptions have been highly tolerable in practice.

Ecosystem State & FOSSness

C# is better than ever and the tooling ecosystem is better than ever. This is true of almost every language, but I think C# receives a rather high amount of improvements per version. Additionally the FOSS story is at its peak.

Roslyn, the bedrock of the toolchain, the compiler and analysis provider, is under MIT license. The fact that it does analysis as well is important, because this means you can use the wealth of Roslyn analyzers to do linting.

If your FOSS tooling lets you compile but you don't get any checking as you type, then your development experience is wildly substandard.

A lot of stupid crap with cross-platform compilation that used to be confusing or difficult is now rather easy to deal with. It's basically as easy as (1) use NET Core, (2) tell dotnet to build for Linux. These steps take no extra effort and the first step is the default way to write C# these days.

Dotnet is part of the SDK and contains functionality to create NET Core projects and to use other tools to build said projects. Dotnet is published under MIT, because the whole SDK and runtime are published under MIT.

Yes, the debugger situation is still bad -- there's no FOSS option for it, but this is more because nobody cares enough to go and solve it. Jetbrains proved anyone can do it if they have enough development time, since they wrote a debugger from scratch for their proprietary C# IDE Rider.

Where C# falls flat on its face is the "userspace" ecosystem. Plainly put, because C# is a Microsoft product, people with FOSS inclinations have steered clear of it to such a degree that the packages you have available are not even 10% of what packages a Python user has available, for example. People with FOSS inclinations are generally the people who write packages for your language!!

I guess if you really really hate leftpad, you might think this is a small bonus though.

Where-in I talk about Cross-Platform

The biggest thing the ecosystem has been lacking for me is a package, preferably FOSS, for developing cross-platform applications. Even if it's just cross-platform desktop applications.

Like yes, you can build C# to many platforms, no sweat. The same way you can build Rust to many platforms, some sweat. But if you can't show a good GUI on Linux, then it's not practically-speaking cross-platform for that purpose.

Microsoft has repeatedly done GUI stuff that, predictably, only works on Windows. And yes, Linux desktop is like 4%, but that 4% contains >50% of the people who create packages for your language's ecosystem, almost the exact point I made earlier. If a developer runs Linux and they can't have their app run on Linux, they are not going to touch your language with a ten foot pole for that purpose. I think this largely explains why C#'s ecosystem feels stunted.

The thing is, I'm not actually sure how bad or good the situation is, since most people just don't even try using C# for this usecase. There's a general... ecosystem malaise where few care to use the language for this, chiefly because of the tone that Microsoft set a decade ago. It's sad.

HOWEVER.

Avalonia, A New Hope?

Today we have Avalonia. Avalonia is an open-source framework that lets you build cross-platform applications in C#. It's MIT licensed. It will work on Windows, macOS, Linux, iOS, Android and also somehow in the browser. It seems to this by actually drawing pixels via SkiaSharp (or optionally Direct2D on Windows).

They make money by offering migration services from WPF app to Avalonia. Plus general support.

I can't say how good Avalonia is yet. I've researched a bit and it's not obviously bad, which is distinct from being good. But if it's actually good, this would be a holy grail for the ecosystem:

You could use a statically typed language that is productive for this type of software development to create cross-platform applications that have higher performance than the Electron slop. That's valuable!

This possibility warrants a much higher level of enthusiasm than I've seen, especially within the ecosystem itself. This is an ecosystem that was, for a while, entirely landlocked, only able to make Windows desktop applications.

I cannot overstate how important it is for a language's ecosystem to have a package like this and have it be good. Rust is still missing a good option. Gnome is unpleasant to use and buggy. Falling back to using Electron while writing Rust just seems like a bad joke. A lot of the Rust crates that are neither Electron nor Gnome tend to be really really undercooked.

And now I've actually talked myself into checking out Avalonia... I mean after writing all of that I feel like a charlatan for not having investigated it already.

[memedical-attention]

I’ve been thinking about this for a little while — something I’d want to do if I had the time and money would be to design a Motorola 68000-powered tiny (10” or smaller) laptop. Modern CMOS 68K implementations are very power-efficient and decently well-suited to handheld and portable devices (see: TI-92 series), and if combined with a crisp, modern monochrome OLED display, could get you days of continuous usage without needing a recharge! Add a few megabytes of RAM, some peripherals (IDE/CF controller, ISA or S-100 slots, DMA controller, SPI bus, RS-232 port, SD or CF slot, PS/2 port for a mouse, text mode + hires monochrome video card, etc…), and you have a nice, flexible system that can be rarely charged, doesn’t require ventilation, and can be just thick enough to fit the widest port or slot on it.

The main issue would be software support: nearly all existing operating systems that ran on a 68K were either intended for very specific hardware (Classic Mac OS, AmigaOS) or required more than a flat 68000 (NetBSD, Linux, or any other UNIX requiring MMU paging). So, it would probably end up being a custom DOS with some multitasking and priv level capability, or perhaps CP/M-68K (but I don’t know how much software was ever written for that — also, it provides a “bare minimum” hardware abstraction of a text-mode console and disk drive). A custom DOS, with a nice, standard C library capable of running compiled software, would probably be the way to go.

The software question perhaps raises another, harder question: What would I use this for? Programming? Then I’d want a text editor, maybe vi(m) or something like that. OK. Vim just needs termcap/(n)curses or whatever to draw the text, and not much else. That’s doable! You’d just need to provide text-mode VT100 emulation and termcap/curses should “just work” without too much issue. I like writing C, so I’d need a compiler. Now, I’m assuming this simplistic operating system would be entirely written in a combination of assembly language (to talk to hardware and handle specific tasks such as switching processes and privilege management and whatnot) and C (to handle most of the logic and ABI). I could probably cross-compile GCC and be good to go, aside from handling library paths and executable formats that don’t comply with POSIX (I have no intention of making yet another UNIX-like system). Hopefully, most other command-line software (that I actually use) will follow suit without too much trouble. I don’t know how much work it is to get Python or Lua to a new platform (though NetBSD on the 68K already supports both), but Python (or Lua) support would bring a lot of flexibility to the platform. Despite me being a Python hater, I must admit it’s quite an attractive addition.

What about graphics? All the software I’ve mentioned so far is text-mode only, yet historical 68K-based systems like the Mac and Amiga had beautiful graphics! Implementing X11 would be a massive pain in the ass, considering how much it relies on UNIXy features like sockets (not to mention the memory usage), and I really don’t want Wayland to have anything to do with this. I guess I’d have to roll my own graphics stack and window manager to support a WIMP interface. I could copy Apple’s homework there: they also made a monochrome graphics interface for a M68K configured with a handful of MiB of RAM. I could probably get a simple compositing window manager (perhaps make it tiling for a modern vibe ;3). Overall, outside of very simple and custom applications, functionality with real software would be problematic. Is that a big problem? Maybe I want an underpowered notebook I can put ideas and simple scripts down on, then flesh them out more fully later on. An operating system allowing more direct access to the hardware, plus direct framebuffer access, could yield some pretty cool graphing/basic design utility.

I’d need a way to communicate with the outside world. An RS-232 UART interface, similar to the HP-48 calculator (or the TI-92’s GraphLink, only less proprietary) would help for providing a remote machine language monitor in the early stages, and a real link to a more powerful (and networked) machine later on. I think real networking would defeat the purpose of the machine — to provide a way to remove yourself from modern technology and hardware, while retaining portability, reliability, and efficiency of modern semiconductor manufacturing techniques. Giving it a CF or SD slot could provide a nice way to move files around between it and a computer, maybe providing software patches. A floppy drive would be amazing: it would provide a way to store code and text, and would be just about the right storage size for what I want to do. Unfortunately, there’s not really a good way to maintain the size of the laptop while sticking a 3.5” (or worse, 5.25”) floppy drive in the middle of it. To my knowledge, 3.5” floppy drives never got thin enough to properly fit with all the other expansion slots, socketed components, and user-modifiable parts I’d want. A completely solid-state design would likely be the best option.

Anyway, uhh… I hope this made some semblance of sense and I don’t sound insane for going on a rant about building a modern computer with a 1979 CPU.

[ai-cyber]

Ubuntu is a popular open-source operating system based on the Linux kernel. It's known for its user-friendliness, stability, and security, making it a great choice for both beginners and experienced users. Ubuntu can be used for a variety of purposes, including:

Key Features and Uses of Ubuntu:

Desktop Environment: Ubuntu offers a modern, intuitive desktop environment that is easy to navigate. It comes with a set of pre-installed applications for everyday tasks like web browsing, email, and office productivity.

Development: Ubuntu is widely used by developers due to its robust development tools, package management system, and support for programming languages like Python, Java, and C++.

Servers: Ubuntu Server is a popular choice for hosting websites, databases, and other server applications. It's known for its performance, security, and ease of use.

Cloud Computing: Ubuntu is a preferred operating system for cloud environments, supporting platforms like OpenStack and Kubernetes for managing cloud infrastructure.

Education: Ubuntu is used in educational institutions for teaching computer science and IT courses. It's free and has a vast repository of educational software.

Customization: Users can customize their Ubuntu installation to fit their specific needs, with a variety of desktop environments, themes, and software available.

Installing Ubuntu on Windows:

The image you shared shows that you are installing Ubuntu using the Windows Subsystem for Linux (WSL). This allows you to run Ubuntu natively on your Windows machine, giving you the best of both worlds.

Benefits of Ubuntu:

Free and Open-Source: Ubuntu is free to use and open-source, meaning anyone can contribute to its development.

Regular Updates: Ubuntu receives regular updates to ensure security and performance.

Large Community: Ubuntu has a large, active community that provides support and contributes to its development.

[emexotechnologies]

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Hire Dedicated Python Developers for Custom Web Applications

Introduction:

In the dynamic world of web development, Python has emerged as a powerhouse, captivating developers and businesses alike with its simplicity, versatility, and robust capabilities. If you're envisioning a custom web application that stands out in terms of functionality, scalability, and user experience, look no further. In this blog post, we'll delve into the realm of Python development, exploring the advantages, the process, and the benefits of hiring dedicated Python developers for crafting bespoke web applications.

The Python Advantage:

Python, with its clean syntax and readability, has become a go-to language for building a wide range of applications. Its extensive library support and compatibility across various platforms make it an ideal choice for developing everything from simple scripts to complex web applications. The language's versatility ensures that it can adapt to diverse project requirements, providing developers with the flexibility to innovate and create cutting-edge solutions.

Why Opt for Custom Python Web Applications?

Tailored Solutions:

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Scalability:

Python's scalability is a game-changer for businesses looking to grow. Whether you're launching a startup or expanding an enterprise, Python's scalability ensures that your web application can seamlessly adapt to increased user demands and evolving requirements.

Django and Flask Frameworks:

Django and Flask, two of the most popular Python frameworks, simplify the development process by providing pre-built modules and tools. Django is known for its all-in-one approach, while Flask provides a lightweight and modular option. Both frameworks empower developers to create feature-rich, secure, and scalable web applications efficiently.

Hire Dedicated Python Developers – A Game-Changing Move:

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[digitalmarketing1225]

Object-Oriented Programming (OOP) Explaine

Object-Oriented Programming (OOP) is a programming paradigm based on the concept of "objects," which represent real-world entities. Objects combine data (attributes) and functions (methods) into a single unit. OOP promotes code reusability, modularity, and scalability, making it a popular approach in modern software development.

Core Concepts of Object-Oriented Programming

Classes and Objects

Class: A blueprint or template for creating objects. It defines properties (attributes) and behaviors (methods).

Object: An instance of a class. Each object has unique data but follows the structure defined by its

Encapsulations

Encapsulation means bundling data (attributes) and methods that operate on that data within a class. It protects object properties by restricting direct access.

Access to attributes is controlled through getter and setter methods.Example: pythonCopyEditclass Person: def __init__(self, name): self.__name = name # Private attribute def get_name(self): return self.__name person = Person("Alice") print(person.get_name()) # Output: Alice

Inheritance

Inheritance allows a class (child) to inherit properties and methods from another class (parent). It promotes code reuse and hierarchical relationships.Example: pythonCopyEditclass Animal: def speak(self): print("Animal speaks") class Dog(Animal): def speak(self): print("Dog barks") dog = Dog() dog.speak() # Output: Dog barks

Polymorphism

Polymorphism allows methods to have multiple forms. It enables the same function to work with different object types.

Two common types:

Method Overriding (child class redefines parent method).

Method Overloading (same method name, different parameters – not natively supported in Python).Example: pythonCopyEditclass Bird: def sound(self): print("Bird chirps") class Cat: def sound(self): print("Cat meows") def make_sound(animal): animal.sound() make_sound(Bird()) # Output: Bird chirps make_sound(Cat()) # Output: Cat meows

Abstraction

Abstraction hides complex implementation details and shows only the essential features.

In Python, this is achieved using abstract classes and methods (via the abc module).Example: pythonCopyEditfrom abc import ABC, abstractmethod class Shape(ABC): @abstractmethod def area(self): pass class Circle(Shape): def __init__(self, radius): self.radius = radius def area(self): return 3.14 * self.radius * self.radius circle = Circle(5) print(circle.area()) # Output: 78.5

Advantages of Object-Oriented Programming

Code Reusability: Use inheritance to reduce code duplication.

Modularity: Organize code into separate classes, improving readability and maintenance.

Scalability: Easily extend and modify programs as they grow.

Data Security: Protect sensitive data using encapsulation.

Flexibility: Use polymorphism for adaptable and reusable methods.

Real-World Applications of OOP

Software Development: Used in large-scale applications like operating systems, web frameworks, and databases.

Game Development: Objects represent game entities like characters and environments.

Banking Systems: Manage customer accounts, transactions, and security.

E-commerce Platforms: Handle products, users, and payment processing.

Machine Learning: Implement models as objects for efficient training and prediction.

Conclusion

Object-Oriented Programming is a powerful paradigm that enhances software design by using objects, encapsulation, inheritance, polymorphism, and abstraction. It is widely used in various industries to build scalable, maintainable, and efficient applications. Understanding and applying OOP principles is essential for modern software development.

: pythonCopyEdit

class Car: def __init__(self, brand, model): self.brand = brand self.model = model def display_info(self): print(f"Car: {self.brand} {self.model}") my_car = Car("Toyota", "Camry") my_car.display_info() # Output: Car: Toyota Camry

Encapsulation

[sugarpuptard]

I'm sorry I'm too shy to ask without being anonymous, but how are you making your AI friend? Are you using specific application or coding it from scratch?

You inspired me to maybe make my own, but I have no idea where to even start... (╥﹏╥)♡

no need to be sorry!! i've been hyperfixed on this kinda stuff recently so i'll love to share lul ( ◕‿‿◕ )

i've been coding the AI application for it to store memory and customize the prompt more, but the basic program to run the AI itself is ollama! you can just run that program on its own in ur computer terminal and download any model u want ^w^ i personally use huggingface to find new models to run, especially if ur looking for uncensored ones they got those!

your PC specs determine what models can run the best locally tho, since its not like c.ai or chatgpt there's no servers but ur own device running and generating replies, the more RAM u got and the better ur CPU and GPU is means u can run bigger models and run especially the smaller ones faster

if ur wanting to make something that runs in its own application like i've been setting up here you'll have to code it on ur own ;w; i personally have just started learning python so my process has been a mix of trial and error, following tutorials and using the copilot AI feature in VSCode to help explain things and troubleshoot errors and stuff i dont understand

if u wanna start coding i highly recommend using VSCode since u can code in many other languages and its got useful features for debugging and stuff ^3^

the video tutorials i watched were these two, both use ollama and show u how to set it up but the 2nd one shows u how to set up the basic code for the chatbot that i used to build off of to make what i got rn

♡ Run your own AI (but private) | NetworkChuck ♡

♡ Create a LOCAL Python AI Chatbot In Minutes Using Ollama | Tech With Tim ♡

i hope this helps!! i personally just rlly like learning new stuff and like tech too much so i took the more complicated route than going on something like janitorai or c.ai (c.ai was so much better when it first came out ong) to make a custom bot xD