#but i switch between sql and python for work

[schumigrace]

where my analyst girlies (gn) at are we python, sql, or R stans out here

[bright-and-burning]

hii i saw you posting about your job and you work with code/data, right?? do you mind explaining a little bit of what you do? i’m a data scientist and i get excited to find fellow computer/data ppl in the wild. (also i’m having a bit of a career crisis and have been wondering what else i could do with my skills lol)

omg hello fellow data person <3 i feel like there’s surprisingly few of us around here (in comparison to the lawyer population of f1blr lol). thinking carefully abt how to explain my job w/o self doxxing akdhskhd. the short answer is i do something different on a monthly (if not weekly) basis basically 😭

(the doing something different all the time is actually kind of wonderful for me personally; when im sick of a project i know ill have like maximum another month of working on it all the time and then im free.)

the long answer is…

i work in the public sector on a research team. we do a LOT of things for only being like. a dozen people. *i* do a lot of things. i work a ton with demographic data, and mobility data, and GIS data (usually all together), to name a few bits and bobs, which is fun. i do a lot of what we call foundational research, which is like. maintaining and improving datasets/databases and tools for quick requests and easy periodic updates for dashboards/reports/etc. i don’t have the subject area expertise/background most of my coworkers have (lots of phds in a field i LOATHED in undergrad lmfao), but i do eat sleep breathe python, so. i ask a lot of silly questions abt acronyms and concepts, and in return they get the analysis they wanted about 10 hours earlier than they expected.

technically speaking i mostly work with python, sql, arcgis, and i guess excel if you wanna count that (although when i have to use excel i get grumpy). i get to write memos w my cute little data visualizations and maps sometimes, and contribute to reports and presentations, but mostly i put out fires, keep the data im responsible for up to date and thriving (i think im at like. four Very Different datasets im in charge of now?? maybe five actually), and fulfill various pull requests

idk what you do rn anon but having had experience in data science in finance… i like this uhhh so much better. i can’t even talk abt the most fun bits of my job bc they’re the most specific LOL but idk in finance i was never gonna be switching between exploring the spatial logic of shifts in employment numbers over time and proving [redacted federal agency’s Very Very Well Known Household Name numbers] wrong to their faces, much less in a two week span.

and at the end of the day i can walk around town and point to physical shit like “oh yeah i helped make this project happen, and i proved the usefulness of This project, and—” (as one mutual who shall not be named knows bc i literally worked on a project that took away their street parking LOL) while also knowing that i’m like. contributing to tangibly helping people (the street parking disappeared for BIKE LANES. OK.)

also the benefits are great. i will shill so hard for government vacation benefits lol. but i also have a lot of friends in data science that do very different things from me, so if you ever wanna slide in the dms i can talk more specifically abt that and more specifically abt what i do. please feel free!!

[priya-joshi]

What It’s Like to Be a Full Stack Developer: A Day in My Life

Have you ever wondered what it’s like to be a full stack developer? The world of full stack development is a thrilling and dynamic one, filled with challenges and opportunities to create end-to-end solutions. In this blog post, I’m going to take you through a day in my life as a full stack developer, sharing the ins and outs of my daily routine, the exciting projects I work on, and the skills that keep me at the forefront of technology.

Morning Ritual: Coffee, Code, and Planning

My day typically begins with a strong cup of coffee and some quiet time for reflection. It’s during this peaceful morning routine that I gather my thoughts, review my task list, and plan the day ahead. Full stack development demands a strategic approach, so having a clear plan is essential.

Once I’m geared up, I dive into code. Mornings are often the most productive time for me, so I use this period to tackle complex tasks that require deep concentration. Whether it’s optimizing database queries or fine-tuning the user interface, the morning is when I make significant progress.

The Balancing Act: Frontend and Backend Work

One of the defining aspects of being a full stack developer is the constant juggling between frontend and backend development. I seamlessly switch between crafting elegant user interfaces and building robust server-side logic.

In the frontend world, I work with HTML, CSS, and JavaScript to create responsive and visually appealing web applications. I make sure that the user experience is smooth, intuitive, and visually appealing. From designing layouts to implementing user interactions, frontend development keeps me creatively engaged.

On the backend, I manage server-side scripting languages like Python and Node.js, ensuring that the data and logic behind the scenes are rock-solid. Databases, both SQL and NoSQL, play a central role in the backend, and I optimize them for performance and scalability. Building APIs, handling authentication, and managing server infrastructure are all part of the backend responsibilities.

Collaboration and Teamwork

Full stack development often involves collaborating with a diverse team of developers, designers, and project managers. Teamwork is a cornerstone of success in our field, and communication is key. I engage in daily stand-up meetings to sync up with the team, share progress, and discuss roadblocks.

Collaborative tools like Git and platforms like GitHub facilitate seamless code collaboration. Code reviews are a regular part of our workflow, ensuring that the codebase remains clean, maintainable, and secure. It’s in these collaborative moments that we learn from each other, refine our skills, and collectively push the boundaries of what’s possible.

Continuous Learning and Staying Updated

Technology evolves at a rapid pace, and staying updated is paramount for a full stack developer. In the afternoon, I set aside time for learning and exploration. Whether it’s delving into a new framework, exploring emerging technologies like serverless computing, or simply catching up on industry news, this dedicated learning time keeps me ahead of the curve. The ACTE Institute offers numerous Full stack developer courses, bootcamps, and communities that can provide you with the necessary resources and support to succeed in this field. Best of luck on your exciting journey!

The Thrill of Problem Solving

As the day progresses, I often find myself tackling unforeseen challenges. Full stack development is, at its core, problem-solving. Debugging issues, optimizing code, and finding efficient solutions are all part of the job. These challenges keep me on my toes and are a source of constant learning.

Evening Reflection: Wrapping Up and Looking Ahead

As the day winds down, I wrap up my work, conduct final code reviews, and prepare for the next day. Full stack development is a fulfilling journey, but it’s important to strike a balance between work and personal life.

Reflecting on the day’s accomplishments and challenges, I’m reminded of the rewarding nature of being a full stack developer. It’s a role that demands versatility, creativity, and adaptability, but it’s also a role that offers endless opportunities for growth and innovation.

Being a full stack developer is not just a job; it’s a way of life. Each day is a new adventure filled with code, collaboration, and the excitement of building end-to-end solutions. While the challenges are real, the satisfaction of creating something meaningful is immeasurable. If you’ve ever wondered what it’s like to be a full stack developer, I hope this glimpse into my daily life has shed some light on the dynamic and rewarding world of full stack development.

[jamiahamdardonline]

Career Change Courses for Transition to Tech & Management Roles

More professionals today are exploring new fields after a decade or more in one job. With evolving industries and rising job dissatisfaction, many feel, "I want to change my career," especially in their 30s and 40s.

Thanks to digital education, making an IT career switch has become more accessible. UGC-approved online degrees in tech and management offer the skills, credentials, and confidence to step into new roles without leaving your job.

Is It Too Late to Switch Careers in Your 30s or 40s?

Not at all. The idea that career change is only for the young is a myth. In fact, many experienced professionals make successful transitions in their mid-life with strategic planning and learning.

Here’s a look at common myths versus reality:

Many believe it’s too late to start over in their 30s or 40s, but in reality, experience often adds significant value in new roles. While learning new tech skills may seem daunting, online platforms today make complex concepts much easier to grasp. It’s also a myth that hiring managers only prefer younger candidates—many companies actively seek professionals with maturity and adaptability. And you don’t need to quit your job to study; most modern courses are designed to fit the schedules of working professionals.

Many professionals considering a career change at 35 or beyond are achieving better income, job satisfaction, and work-life balance. Even those switching careers at a later stage bring a unique combination of maturity and problem-solving, which employers actively seek.

Top Career Change Paths for Mid-Career Professionals

If you're seeking direction, here are promising career change options:

IT and Data Analytics – Enter roles that analyse and interpret digital data for business insights.

Software Development – Build web, mobile, and enterprise applications using modern programming tools.

Digital Business Management – Lead e-commerce, marketing, or tech-driven business models.

Project Management and Operations – Manage teams, timelines, and deliverables efficiently.

How Can an Online BCA Help You Start a Career in Tech?

A BCA is ideal for non-technical professionals who want to build a new foundation in IT. If you’ve ever said, “I want to change my career,” this is a great place to start. This course covers programming languages, database management, operating systems, and web technology—key areas for tech careers.

Job roles include Junior Developer, QA Tester, and Support Analyst—making it a practical first step in an IT career switch.

Admission in Online BCA Program

Why MCA Is a Smart Career Switch for Deep Tech Roles?

An MCA is designed for those with basic technical knowledge or a BCA/IT background, looking to level up. You’ll master in-demand skills like Python, cloud computing, and AI/ML—perfect for a deeper dive into tech.

Graduates often become Software Engineers, Data Scientists, or System Analysts—ideal if you're planning a career switch to data science or back-end development.

Admission in an Online MCA Program

Leveraging an Online MBA for Business and Tech Leadership

Professionals aiming to move into leadership roles can benefit immensely from an online MBA. Specialisations in IT Management, Marketing, HR, and Finance open doors to roles like Product Manager, Business Analyst, and Operations Lead.

This is especially powerful for those making a career change in 40s, combining experience with strategic business thinking.

Admission in an Online MBA Program

Career Change to Data Science or Data Analyst Roles

BCA and MCA programs provide the technical base, such as coding, data structures, and software tools that support roles in analytics.

For mid-level professionals, combining an MBA with Excel, SQL, and visualisation skills bridges the gap between business and data, ideal for those who want to switch careers to data analyst roles.

You can further boost your profile with certifications in Python, Excel, and Power BI.

Benefits of Studying at Jamia Hamdard Online

Jamia Hamdard offers fully online degrees that cater to working professionals looking to reinvent themselves.

Recognised by UGC, ensuring academic credibility

Budget-friendly tuition, supporting long-term ROI

Designed for working professionals, with evening/weekend flexibility

Career support, including mentorship, resume guidance, and more

How to Decide Between BCA, MCA, and MBA

Choosing the right program depends on your background, interests, and goals. Here's a quick comparison:

Choosing between BCA, MCA, and MBA depends on your background and career goals. BCA is ideal for students from any stream, including non-tech, who want to build foundational tech skills like programming, databases, and web technologies. MCA is best suited for those with a BCA or some tech background and covers advanced topics like cloud computing, AI/ML, and full-stack development. MBA, on the other hand, welcomes candidates from any stream, especially those with work experience, and focuses on business strategy, finance, marketing, and HR. While BCA leads to roles like support analyst, tester, or developer, MCA opens up opportunities such as software engineer or data scientist. MBA graduates typically move into roles like product manager, business analyst, or HR lead.

Final Thoughts: Taking the Leap to a New Career

A successful career move is built on planning, learning, and positioning.

Start by choosing the right degree and aligning it with your long-term goals. Build a strong resume post-course, showcase your projects, and don’t hesitate to reach out for internships or entry-level roles.

Transitioning to a new field is no longer a gamble – it’s a strategy.

[sruthypm]

Discover the Best Data Science Course in Kerala at Techmindz: Transform Your Career with Real-World Skills

In an era where data drives every decision, Data Science is no longer a niche skill—it's a necessity. From healthcare to finance, from e-commerce to public policy, industries are looking for data-driven minds who can turn raw data into actionable insight. If you're searching for the best data science course in Kerala, Techmindz offers a future-proof pathway to a thriving career in this high-demand field.

🌐 Why Data Science Matters Today

Data is often called the "new oil." But raw data alone means nothing unless it's refined. That’s where data science comes in—transforming information into predictive insights that power everything from business strategies to AI innovations.

With Kerala’s growing IT ecosystem, the need for skilled data scientists has never been greater. Companies in Kochi, Trivandrum, and Calicut are actively hiring professionals who can work with data to solve complex business challenges.

🏫 Techmindz: Your Gateway to the Best Data Science Course in Kerala

Located inside Infopark, Kochi, Techmindz is one of Kerala’s leading IT training institutions, known for industry-aligned programs, expert mentorship, and corporate placements. Our data science program is meticulously designed to bridge the gap between academic learning and real-world application.

🧠 What You’ll Learn at Techmindz

Our Data Science course is structured to cover a wide spectrum of in-demand skills:

Data Analysis & Visualization: Python, Pandas, NumPy, Tableau, Power BI

Statistical Modeling & Machine Learning: Scikit-learn, TensorFlow, Keras

Big Data Technologies: Hadoop, Spark (overview sessions)

SQL & Data Management

Capstone Projects with Real Datasets

🎓 Why Techmindz is the Best Choice

✅ Live Industry Projects Apply what you learn through practical assignments and real-time business problems.

✅ Expert Faculty with Industry Background Learn from experienced data scientists who bring hands-on knowledge to the classroom.

✅ 100% Placement Assistance Resume building, interview preparation, and direct referrals to tech companies across Kerala.

✅ Hybrid Learning Model Attend classes online or on-campus at Infopark based on your convenience.

👤 Who Should Enroll?

Whether you're a:

Graduate aiming to enter IT

Professional upskilling for a career switch

Entrepreneur looking to harness data for business growth

This course is built to accommodate learners from both technical and non-technical backgrounds.

💼 Career Opportunities After Course Completion

Completing the best data science course in Kerala with Techmindz opens doors to roles like:

Data Analyst

Business Intelligence Developer

Machine Learning Engineer

Junior Data Scientist

Data Engineer

With the digital transformation happening across industries in Kerala, certified data professionals are in high demand.

📢 What Our Students Say

“Techmindz gave me the confidence to switch from finance to data science. The teaching was practical, and the project-based approach helped me crack interviews easily.” — Priya K., Data Analyst at a Kochi fintech startup

“I compared many institutes, and Techmindz stood out for its industry-backed curriculum and career guidance. Easily the best data science course in Kerala.” — Arun M., ML Engineer at a healthcare firm

🚀 Ready to Take the First Step?

Your career in data science starts here. Enroll at Techmindz, the training institute that equips you with the skills employers are actively seeking. Book a free counseling session or visit our Infopark campus to learn more.

🧩 Final Word

Don’t settle for average when it comes to your career. Choose Techmindz—where education meets innovation, and learning leads to opportunity. When it comes to the best data science course in Kerala, Techmindz is the name professionals trust and employers recognize.

https://www.techmindz.com/data-science/

[krakenartificer]

Hi Raina! I'd like to appeal to your hard-won wisdom on The Adult World-- do you think it's possible to teach yourself/find online resources to help learn things like data analysis? I want to look at numbers and graphs and spreadsheets for money but don't know what resources are good enough to trick capitalism and bosses into hiring me for it!

Oh, yeah, 100% Source: I pretty much did that. So first the disclaimers: I did have a bachelor's degree in applied mathematics, and I did shell out for an MBA as my happy-divorce-day present to myself. I know that I really don't use either of those things in my day-to-day work, but hiring managers probably are considering them when they look at my resume. I'm also white, a native English speaker, and talk like an educated middle-class suburbian, which I'm sure also play into mangers' willingness to give me the benefit of the doubt. So my exact path may not work for you. That said, data, in particular, has several advantages right now:

1) Demand is large, and supply is small. If my department doubled in size, we could still not quite answer all of the questions the business leaders are asking of us. I don't think there's been a moment that I've worked for this company that we didn't have a least one job slot we were hiring for. In addition to making this a lucrative industry, it also makes it fairly easy to break into, because hiring managers are willing to accept far less perfect candidates if only they can get someone who knows something working on this project.

2) The field is changing very fast. No one knows what languages or software we'll be using a year from now, so it doesn't really matter that much if you don't know the one we happen to be using right now. Supervisors are much more concerned with "When it turns out we have to switch our entire reporting scheme to Scala, will you be able to learn that?" And in that context, it is incredibly encouraging to hear a candidate say that they once had to do a thing in Python but they didn't know Python so they Googled and perused Stack Overflow until they could do the thing. You are very likely to have a question at the interview that's something like "Describe a time you had to learn something quickly" or "What's your approach when you don't know how to do something?", and as an autodidact, you will have lots of examples for those moments.

3) There are lots of places that don't have anything at all. A person who knows how to put conditional formatting on a column in Excel would be an improvement on what some smaller companies are currently doing. If you can make a graph and code a vlookup() function, then you're an Expert!

4) the field is so new, and is changing so fast, we're still working out the distinctions between the assorted sub-fields. Which means you can start as someone who does data visualization, pivot to data science, change your mind and end up in data engineering, and then decide to do database administration instead.

So yeah. My recommendation is to search job boards for things that look like they might be what you want to do, and write down what the minimum qualifications are for each one. If you already meet 70% of the requirements, start applying! If not, make a li'l histogram of requirements they want and you don't have, and start finding ways to get them.

I, for instance, downloaded an SQL syllabus from some university class that had it publicly posted, and learned SQL by just doing the assignments on my own time when things were slow at the retail job I had. I got an office job on the strength of that, buuuuut my first assignment wasn't really doable in SQL, so I did the work in Python (a language that, up until that point, I had made 0 programs in, but I had watched while someone else made a program in it), and then bodged it into Excel for visualization. That made me look enough like a developer that the data science team was willing to talk to me, and so I got to sit in on the Alteryx intro seminar when they did, and then (since Alteryx was brand new and didn't really have any documentation or communities at that point) taught myself how to use it by trial-and-error. That got me enough experience that I subsequently got offered a job paying twice as much, working with BASH, hql, scala, and Jenkins (a list of coding options that -- you'll notice -- I had not yet had any experience in).

Basically, as a rule, hiring managers have no idea what all is going on behind the scenes, nor do they care, as long as they get the intended outcome. So my approach for interviews is to approach it as communication/translation problem for the first half: what exactly are they hoping the person in this position will be doing? "So, for example, {possible project based on my understanding of how they described the job}, would that be the type of thing?" Repeat until you're pretty sure you know what they're looking for. If you can do that thing, then you're justified in saying "I can do that", and you probably have evidence to back it up. So the second half of the interview is using their questions as an opportunity to lay out your evidence. Bonus: asking questions in the interview makes you look both smarter and more engaged!

If you get a technical interview/whiteboarding interview, don't panic! They're looking more at how you approach the problem than they're looking at your actual ability to write solid code / know the exact names for everything (my last interview I had to ask "What's that?" after, like, 3/4 of the questions. Then the interviewer would start describing it, and I'd be like "OH yeah, so then ....". I got the job.) So if you don't know what to do, start writing out outlines, mind-maps, lists ... whatever would help you figure out how to get started. Write down the facts of the situation, and implications of those facts; write down questions you have, and how to get them answered. This is a situation where partial credit is very VERY much a possibility, so get as many possible partial-credit sources on the whiteboard as possible.

So yeah. Coursera, Khan Academy, etc, all great. You can also just find some school that doesn't password-protect their class materials, and if you can mess around enough to solve the problems on the homework assignments, then you know (at least) as much as anyone who's officially taken that class. Alteryx and Tableau offer free online training with a web-portal sample of their software. You could also check for volunteer opportunities: I'm organizing permit applications for Sierra Club, and I bet there's a non-profit near you that would be equally delighted (read: fucking overjoyed) to let you take over all graph/numbers/spreadsheets for their projects. Then you get them to write you a letter of recommendation, and put the reporting work on your resume, and you've got "real world experience" while you're saving the world.

I wish you the best, and feel free to ask more questions as you go farther along your journey! I definitely recommend the data-work life; it's been my favorite career so far.

[capitalism-and-analytics]

Hi! Definitely okay if you don’t want to answer-what does a Financial Data Engineering Manager do?

Also-I work as an accountant and currently working on my masters on Data Analytics, mainly focusing on Python. Any advice for someone who wants to combine their accounting and programming knowledge? Any other languages I should learn?

I like my current job but I see so much room for improvement. I would like to get to a point where I am creating things and making decisions.

Hope that makes sense!

So basically my team serves a subgroup of the broader accounting and data engineering team for implementation and processing of new accounting data requirements for new product solutions to be ingested into the financial ERP system to be leveraged by the rest of the stakeholders of the company that rely on financial data for decision making and reporting purposes. This is also involves maintaining and monitoring that the ETL process of this data is complete, accurate, and valid for auditing purposes between upstream and downstream.

What effectively this means is that the business (i.e. product owners) will come up with a new business offering that requires accounting requirements for capturing the relevant financial data into the appropriate journal entry's and accounts appropriately in the accounting cycle, while fulfilling GAAP requirements of recognition.

This serves as a problem because the product owners' engineering team will capture all the data when they set-up the product upstream in the source systems, but they have no clue in using that data at what business event level various JE's need to get booked or which attributes within those events need to get captured when posting a given JE's. Conversely, the engineering team downstream has no clue of the same treatment of what needs to be pulled from the upstream in calculating those JE's to be pushed at month-end to the ERP system.

To give an example, imagine if the business told you of a new product they were offering like if Bubba's Computer Business started a PC cleaning service and it involved third-party delivery and had the options of both financing and lump sum payment. At what points in the transaction would you book certain JE's and to book those certain JE's, where would you pull the information? It can get very complicated though when you start to consider that at each business event, there are multiple paths; i.e. what happens if payment fails, what happens if the service gets canceled, what happens if the cashier cancels the order after they accept payment, what if Bubba accept multiple payment providers and they provide varying levels of data detail or even different mechanisms of data recognition, etc.

Any advice for someone who wants to combine their accounting and programming knowledge? Any other languages I should learn?

SQL and if your team utilizes MS products regularly (Excel, PPT, or even Word), then VBA

Some companies leverage R and SAS too, so YMMV

As far as advice, I would definitely look into roles categorized under business intelligence or business data engineering. Additionally, make sure to take positions focused on accounting that market towards being data-heavy with a grain of salt, it is very common these days for accounting departments to pretend to care about data analysis skill sets. Furthermore, figure out what interests you, sometimes you're better off switching roles than trying to change your current role.

I would like to get to a point where I am creating things and making decisions.

Probably stick to smaller/mid-size companies, otherwise those will be conflicting responsibilities. To give context to what I mean, generally "creating things" is a responsibility of individual contributors (ICs) and "making decisions" is a responsibility of people managers (PMs) in big businesses. In smaller businesses, this is less common due to lack of segregation of duties and resources, which means you get tasked with more responsibilities.

*When I say "making decisions" I mean significant decisions, not like day-to-day ones.

[cherami-chat]

Dev Blog #2

Courtesy of Thell --

Last week we talked about user accounts and said that this week we’d talk about the new software stack, so let’s do that. On both new and old Cherp, the core technologies are staying roughly the same - we use PHP as the backend language that handles all the server side logic. This interacts with PostgreSQL as our database engine, and Redis acts as a caching layer between the two for information that takes a little while to get but that’s accessed often; things like your unread count, chat status, etc (Coincidentally, this is also the cause of the ghost unread bug - it caches your unread count for 24 hours unless it changes, but grace period and account deletes don’t decrement the counter. More on that in a minute). On the frontend, we currently use React, an abominable monstrosity that we’re glad to be dropping. Let’s talk about PHP first. Cherubplay was originally written in Python, but nobody really knew enough Python to fix that code up when it started breaking. As such, current Cherp uses PHP 7.4. This is about to leave active support meaning it’ll be receiving security updates only, meaning that for this rewrite, we’re switching to PHP 8. Right now, we’re coding with 8.0 in mind, but by the time we release, we’ll be on 8.1. It’s quite likely that we’ll be able to upgrade through all the 8.x versions after this with little issue. On top of PHP, current Cherp uses a microframework called Slim to provide some API routing stuff. For new Cherp, we’re using Laravel, something most PHP developers reading this will be familiar with. Personally, I prefer the older system (albeit with some major code touch ups needed), but that’s because I find MVC as a paradigm overly convoluted for what it does - but given Laravel is extremely widely used, and will make recruiting new devs easier in future, that’s what we’re going with. It gives us a lot of tools to work with, and so far, is making some things easier and some things harder. React is what you use right now to see the site. It’s awful, and we hate it. It’s a Javascript framework created by Facebook. For the new version, Laravel gives us a set of tools called Blade that lets us write the frontend in PHP. On top of this, there’s also a system called Livewire that we’re adding - this uses Blade as a basis, but adds some fancy dynamism on top so that you can have a similar experience to what you already have with dynamic elements. This way there’s a lot less Javascript involved, which means it’ll be easier on your computer and, if you’re one of those users who use mobile, your battery won’t drain as fast either. PostgreSQL (or Postgres, nobody can apparently decide how to refer to it) is the database we use. SQL is widely understood at this point by most techy people, but for those unaware, it stands for Structured Query Language. Ignore the people who tell you it’s pronounced “sequel”, they’re wrong and should be shunned (EDITOR'S NOTE: This opinion is incorrect). The most popular databases of this type are Postgres and MySQL (or MariaDB, a fork of MySQL that has a nicer license and which you should really be using instead). MySQL/MariaDB is a lot more popular than Postgres, but Postgres has a lot of extra flexibility. Most people don’t need this, but current Cherp uses Array datatypes. Arrays are very powerful, but - whether it’s just because of the way PHP forces you to use them and they’re better in other languages, or because the datatype itself kinda sucks - they’re absolutely awful to work with. For the rewrite, we’re keeping Postgres - even without using any of the advanced features, it’s powerful and fast, and if you give me 10 minutes alone in a room with it, I can make it do some impressive things. What we are doing is getting rid of arrays, and moving the stuff we use them for into a separate table. It’s one of those things that’s paradoxically both messier and cleaner, but it’ll reduce the load on PHP when it has to explode or implode the arrays when pulling/pushing to the database. Redis is also staying, though exactly how much use it’ll get right now is

debatable, and can only be answered once we’ve learned a little more about how Laravel handles things. Right now, we use it for login sessions and, as mentioned, caching. For those who don’t know, caching is where you store something that takes a long time to get to a faster place so it can be called faster. For example, let’s say I log in for the first time in a while. When I log in, the top bar needs to show how many unread chats I have, so it asks the database to count how many chats have me as a participant. Then, it filters these to find ones where my chat_status is marked “unread”. Then it gives the count back. Each step of this is slow, and takes time. It’s also something that’s requested on every page load, so rather than do it every time, we put a step in at the beginning and at the end - check Redis first. Redis stores everything in memory using key-value pairs. Redis has up to 16 “databases” - let’s say the unread_counts is database 2. So, it tells Redis to check database 2 for a value with key [whatever my user ID is]. If it’s there - it just spits the number out. If not, it’ll run through the process of asking the database, and when it’s done, it gives the number to Redis. There’s a few other places where this is done, and a few places where the cached number is ignored and forces another database check to refresh it, but broadly speaking, Redis cuts the performance cost of the site to about 20% of what it’d otherwise be. And there we go - a summary of what we’re using, both for the new site and the old one, as well as a little overview of what it does. If you’re in the Cherp Discord server (TT make this a link) (EDITOR'S NOTE: Ok, done), feel free to hop into the coding channel and I’ll answer any more in depth questions you have.

Thank you!

[jjkfire]

update 4/27/21:

I'm working at a startup so it's extremely busy. but I love my job! i am trying to find the time to fit writing in my schedule tho. gonna figure it out someday lol. my stories are not abandoned, don't worry. all the endings and plot points have been planned. i'm just struggling to find the time to write atm. still very grateful for all the kind words and support you guys have given me over the years. hope all of you are out there living your best lives, exploring, learning, and finding joy in all the little things 😊 join my tag list (read the instructions pls) to get notified when I update my fics!

//

previous big update:

hello! i know i’ve been sort of mia but… it’s been an absolutely chaotic time for me. 

the (long) story goes a little something like this:

earlier this year during spring break, i had friends who convinced me to give america a shot and apply for jobs after grad. i really didn’t want to because the visa process is a pain and it costs a lot. also, not a lot of companies want to hire internationals so it’s very demoralizing to receive a million rejections… but my friends are very persuasive people lol. 

so it was super hectic during the last few months I had in the country as i tried to get through the visa process, study, work, beef up my resume, apply for jobs and graduate at the same time. (i understand that a ton of people have to do this too… but it’s hard y’all). anyway, one Medium article, one cold email, and a number of grueling interviews later, i found out i got a job!

now i just had to convince my parents… this was actually in all honesty, the most stressful part. i love them to death but my father really made it feel like i was choosing between my family and a job and ngl i cried myself to sleep on the regular. in the end, he finally gave me the okay to take the job but i know he’s still very upset. that’s honest to god the worst part. (my mum’s been super supportive tho so i guess that’s the silver lining in all of this!)

prior to getting the job though, I was really in limbo. I had returned to my home country because I and by extension, my parents, were not confident that i was going to be able to land a job in the US. I was very confused because I was neither here nor there. I was interviewing with the american company from my home country, trying my best to make sure they’d still be interested in me as a candidate no matter how many hurdles there were. then, to ensure that I had a safety net, I was also doing interviews locally and sending out resumes whenever I could. I was exhausted. and I know everyone goes through the job hunt so it’s equally as exhausting for everyone but yeah it was not a fun time.

anyway so now that I took that job in america i gotta move halfway across the world again, but this time without financial support and i don’t know… maybe this is the first time i’ll be truly independent and ya im seconds away from shittin myself. really gotta put on my big girl pants and try to not be broke yeet yeet.

but uhh that’s the low down on why i haven’t been able to write much at all…….. and yeah! working on it tho… haha always working on it.

to end all of this, I just want to say that I’m super lucky to have all of you. I basically got the job because of that article I wrote. I know I sound like a broken record talking about my article over and over but I dunno I guess all of this is just a little wild to me ahah.

I owe a lot of my confidence in my writing to all of you. I personally think my writing improved bc of this blog and the support you guys give me is… unreal (“: I know it may seem insignificant to some of you to reblog/like and comment on a fic but it really spurs me creatively and makes me feel sort of confident about my writing. all of that is probably why I didn’t think twice about hitting that post button on my article. although it’s a very different type of writing… I don’t know it’s just knowing that my writing is worth something… knowing that my writing is worth taking 5 minutes out of your day to read, is pretty cool and you guys kind of gave me that! (i am in no way saying that my writing is the best thing on earth. far from it. but i think you guys understand what i’m trying to say!)

so in some way, you guys helped me get a job! nice work team hahahah. also, also i just want to say, never give up. I decided I wanted to try my luck at the American job market maybe around the end of March and graduation was in early May. so I had about more or less a month to do something. I knew I needed a way to set myself apart from everyone else because my gpa wasn’t stellar and I hadn’t had any internships in America. not to mention the fact that I was an international student hence it was even harder to get hired. so basically, why would a company pick me over the next person? I thought perhaps knowing how to code was the way to give myself an edge so I learned some basic python and sql but then I realized there wasn’t really an impressive project I could attempt within that short time frame and I also knew far too little to do anything anyway. this meant that I was back at square one.

so, I switched gears instead. I sat down and really thought about what I could do. I concluded that at the very least, I could write. I knew I could write so I needed something that I could use along with my writing and I was like… it’s gotta be data! knowing that, I picked up the basics on how to use Tableau and I also picked up VBA macros in excel (if you don’t know what this is… I think you should Google it. it will literally blow your mind. excel can do a lot more than you can imagine). Then, I picked what I wanted to write my article on, got the data I needed from google trends, used vba macros to make the calculations faster, used tableau to make charts based on the data and photoshop to spice up the charts and etc. I did my research in the meantime as well and had a rough plan on what I was going to write about. after this, it was all systems go and it went a little like this:

wrote the article. attached my charts. linked the links. hit that post button. applied to all the jobs & companies that I thought would see value in what I did and can do. got rejected many times. felt discouraged. did more searching on companies that were willing to hire internationals. decided to send a cold email to a company. ACTUALLY HEARD BACK. went through multiple interviews. ACTUALLY GOT THE JOB.

so guys, never give up. recognize your strengths and build around that. if you think you don’t have any strengths, look harder. if you still feel you don’t have any, make the effort to learn something. it’s never too late for anything. I did all of that in one month and 10 days (the learning stuff and writing the article thing I mean). always be open to learning. I say this so much irl that my friends are sick of it but in this day and age with the internet, you can literally learn anything. so please, learn. learn for fun, learn for whatever reason. learn anything. you’ll never know when it’ll come in handy. like my basic Photoshop that I learned just so I could make a header for my blog… literally used that skill for the graphics in my article lol.

anyway, you can achieve a lot more than you think you can. you just gotta throw caution to the wind and do your own thing. be determined, be proactive. if things aren’t going the way you think it should be, do something to change that. you are all amazing and capable of great things! I hope you all know that. my mum always said if you never try, you’ll never know. don’t be afraid, don’t stop to think about what other people will think of you. keep doing you. people doubt you enough so don’t add to that. keep your head held high and keep moving forward.

once again I want to thank you guys for being sort of a support system for me! every comment, nice ask and sweet message has brought me this far. i really mean it (’: always be nice and supportive my sweet dumplings. your words truly have impact!

[mahiworld-blog1]

Important libraries for data science and Machine learning.

Python has more than 137,000 libraries which is help in various ways.In the data age where data is looks like the oil or electricity .In coming days companies are requires more skilled full data scientist , Machine Learning engineer, deep learning engineer, to avail insights by processing massive data sets.

Python libraries for different data science task:

Python Libraries for Data Collection

Beautiful Soup

Scrapy

Selenium

Python Libraries for Data Cleaning and Manipulation

Pandas

PyOD

NumPy

Spacy

Python Libraries for Data Visualization

Matplotlib

Seaborn

Bokeh

Python Libraries for Modeling

Scikit-learn

TensorFlow

PyTorch

Python Libraries for Model Interpretability

Lime

H2O

Python Libraries for Audio Processing

Librosa

Madmom

pyAudioAnalysis

Python Libraries for Image Processing

OpenCV-Python

Scikit-image

Pillow

Python Libraries for Database

Psycopg

SQLAlchemy

Python Libraries for Deployment

Flask

Django

Best Framework for Machine Learning:

1. Tensorflow :

If you are working or interested about Machine Learning, then you might have heard about this famous Open Source library known as Tensorflow. It was developed at Google by Brain Team. Almost all Google’s Applications use Tensorflow for Machine Learning. If you are using Google photos or Google voice search then indirectly you are using the models built using Tensorflow.

Tensorflow is just a computational framework for expressing algorithms involving large number of Tensor operations, since Neural networks can be expressed as computational graphs they can be implemented using Tensorflow as a series of operations on Tensors. Tensors are N-dimensional matrices which represents our Data.



2. Keras :

Keras is one of the coolest Machine learning library. If you are a beginner in Machine Learning then I suggest you to use Keras. It provides a easier way to express Neural networks. It also provides some of the utilities for processing datasets, compiling models, evaluating results, visualization of graphs and many more.

Keras internally uses either Tensorflow or Theano as backend. Some other pouplar neural network frameworks like CNTK can also be used. If you are using Tensorflow as backend then you can refer to the Tensorflow architecture diagram shown in Tensorflow section of this article. Keras is slow when compared to other libraries because it constructs a computational graph using the backend infrastructure and then uses it to perform operations. Keras models are portable (HDF5 models) and Keras provides many preprocessed datasets and pretrained models like Inception, SqueezeNet, Mnist, VGG, ResNet etc

3.Theano :

Theano is a computational framework for computing multidimensional arrays. Theano is similar to Tensorflow , but Theano is not as efficient as Tensorflow because of it’s inability to suit into production environments. Theano can be used on a prallel or distributed environments just like Tensorflow.

4.APACHE SPARK:

Spark is an open source cluster-computing framework originally developed at Berkeley’s lab and was initially released on 26th of May 2014, It is majorly written in Scala, Java, Python and R. though produced in Berkery’s lab at University of California it was later donated to Apache Software Foundation.

Spark core is basically the foundation for this project, This is complicated too, but instead of worrying about Numpy arrays it lets you work with its own Spark RDD data structures, which anyone in knowledge with big data would understand its uses. As a user, we could also work with Spark SQL data frames. With all these features it creates dense and sparks feature label vectors for you thus carrying away much complexity to feed to ML algorithms.

5. CAFFE:

Caffe is an open source framework under a BSD license. CAFFE(Convolutional Architecture for Fast Feature Embedding) is a deep learning tool which was developed by UC Berkeley, this framework is mainly written in CPP. It supports many different types of architectures for deep learning focusing mainly on image classification and segmentation. It supports almost all major schemes and is fully connected neural network designs, it offers GPU as well as CPU based acceleration as well like TensorFlow.

CAFFE is mainly used in the academic research projects and to design startups Prototypes. Even Yahoo has integrated caffe with Apache Spark to create CaffeOnSpark, another great deep learning framework.

6.PyTorch.

Torch is also a machine learning open source library, a proper scientific computing framework. Its makers brag it as easiest ML framework, though its complexity is relatively simple which comes from its scripting language interface from Lua programming language interface. There are just numbers(no int, short or double) in it which are not categorized further like in any other language. So its ease many operations and functions. Torch is used by Facebook AI Research Group, IBM, Yandex and the Idiap Research Institute, it has recently extended its use for Android and iOS.

7.Scikit-learn

Scikit-Learn is a very powerful free to use Python library for ML that is widely used in Building models. It is founded and built on foundations of many other libraries namely SciPy, Numpy and matplotlib, it is also one of the most efficient tool for statistical modeling techniques namely classification, regression, clustering.

Scikit-Learn comes with features like supervised & unsupervised learning algorithms and even cross-validation. Scikit-learn is largely written in Python, with some core algorithms written in Cython to achieve performance. Support vector machines are implemented by a Cython wrapper around LIBSVM.

Below is a list of frameworks for machine learning engineers:

Apache Singa is a general distributed deep learning platform for training big deep learning models over large datasets. It is designed with an intuitive programming model based on the layer abstraction. A variety of popular deep learning models are supported, namely feed-forward models including convolutional neural networks (CNN), energy models like restricted Boltzmann machine (RBM), and recurrent neural networks (RNN). Many built-in layers are provided for users.

Amazon Machine Learning  is a service that makes it easy for developers of all skill levels to use machine learning technology. Amazon Machine Learning provides visualization tools and wizards that guide you through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology.  It connects to data stored in Amazon S3, Redshift, or RDS, and can run binary classification, multiclass categorization, or regression on said data to create a model.

Azure ML Studio allows Microsoft Azure users to create and train models, then turn them into APIs that can be consumed by other services. Users get up to 10GB of storage per account for model data, although you can also connect your own Azure storage to the service for larger models. A wide range of algorithms are available, courtesy of both Microsoft and third parties. You don’t even need an account to try out the service; you can log in anonymously and use Azure ML Studio for up to eight hours.

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license.  Models and optimization are defined by configuration without hard-coding & user can switch between CPU and GPU. Speed makes Caffe perfect for research experiments and industry deployment. Caffe can process over 60M images per day with a single NVIDIA K40 GPU.

H2O makes it possible for anyone to easily apply math and predictive analytics to solve today’s most challenging business problems. It intelligently combines unique features not currently found in other machine learning platforms including: Best of Breed Open Source Technology, Easy-to-use WebUI and Familiar Interfaces, Data Agnostic Support for all Common Database and File Types. With H2O, you can work with your existing languages and tools. Further, you can extend the platform seamlessly into your Hadoop environments.

Massive Online Analysis (MOA) is the most popular open source framework for data stream mining, with a very active growing community. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation. Related to the WEKA project, MOA is also written in Java, while scaling to more demanding problems.

MLlib (Spark) is Apache Spark’s machine learning library. Its goal is to make practical machine learning scalable and easy. It consists of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as lower-level optimization primitives and higher-level pipeline APIs.

mlpack, a C++-based machine learning library originally rolled out in 2011 and designed for “scalability, speed, and ease-of-use,” according to the library’s creators. Implementing mlpack can be done through a cache of command-line executables for quick-and-dirty, “black box” operations, or with a C++ API for more sophisticated work. Mlpack provides these algorithms as simple command-line programs and C++ classes which can then be integrated into larger-scale machine learning solutions.

Pattern is a web mining module for the Python programming language. It has tools for data mining (Google, Twitter and Wikipedia API, a web crawler, a HTML DOM parser), natural language processing (part-of-speech taggers, n-gram search, sentiment analysis, WordNet), machine learning (vector space model, clustering, SVM), network analysis and  visualization.

Scikit-Learn leverages Python’s breadth by building on top of several existing Python packages — NumPy, SciPy, and matplotlib — for math and science work. The resulting libraries can be used either for interactive “workbench” applications or be embedded into other software and reused. The kit is available under a BSD license, so it’s fully open and reusable. Scikit-learn includes tools for many of the standard machine-learning tasks (such as clustering, classification, regression, etc.). And since scikit-learn is developed by a large community of developers and machine-learning experts, promising new techniques tend to be included in fairly short order.

Shogun is among the oldest, most venerable of machine learning libraries, Shogun was created in 1999 and written in C++, but isn’t limited to working in C++. Thanks to the SWIG library, Shogun can be used transparently in such languages and environments: as Java, Python, C#, Ruby, R, Lua, Octave, and Matlab. Shogun is designed for unified large-scale learning for a broad range of feature types and learning settings, like classification, regression, or explorative data analysis.

TensorFlow is an open source software library for numerical computation using data flow graphs. TensorFlow implements what are called data flow graphs, where batches of data (“tensors”) can be processed by a series of algorithms described by a graph. The movements of the data through the system are called “flows” — hence, the name. Graphs can be assembled with C++ or Python and can be processed on CPUs or GPUs.

Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray). Using Theano it is possible to attain speeds rivaling hand-crafted C implementations for problems involving large amounts of data. It was written at the LISA lab to support rapid development of efficient machine learning algorithms. Theano is named after the Greek mathematician, who may have been Pythagoras’ wife. Theano is released under a BSD license.

Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. The goal of Torch is to have maximum flexibility and speed in building your scientific algorithms while making the process extremely simple. Torch comes with a large ecosystem of community-driven packages in machine learning, computer vision, signal processing, parallel processing, image, video, audio and networking among others, and builds on top of the Lua community.

Veles is a distributed platform for deep-learning applications, and it’s written in C++, although it uses Python to perform automation and coordination between nodes. Datasets can be analyzed and automatically normalized before being fed to the cluster, and a REST API allows the trained model to be used in production immediately. It focuses on performance and flexibility. It has little hard-coded entities and enables training of all the widely recognized topologies, such as fully connected nets, convolutional nets, recurent nets etc.

[bananafield]

Button text html

Button text html how to#

Button text html pdf#

Button text html generator#

Button text html code#

Button text html Pc#

How Base64 encoding and decoding is done in node.The problem occurs if you try to change the text of a button more than once in the same session (using innerHTML).

Button text html Pc#

Note: The innerHTML method has a problem when run on Netscape 6.2 and 7.02 on the PC (and possibly other versions).

Node.js Image Upload, Processing and Resizing using Sharp package Changing html content using JavaScript and CSS.

Actions must be added to buttons using JavaScript or by associating the button with a form. No action takes place by default when a button is clicked. Any text appearing between the opening and closing tags will appear as text on the button. • Upload and Retrieve Image on MongoDB using Mongoose The element is used to create an HTML button.

Button text html how to#

How to Upload File using formidable module in Node.js ?.

Button text html pdf#

How to display a PDF as an image in React app using URL?.

How React Native Make Mobile App Development Simpler?.

Getting started with React Native? Read this first !.

How to change the text and image by just clicking a button in JavaScript ?.

How to change an input button image using CSS?.

It specifies a link on the web page or a place on the same page where the user navigates after clicking on the link. A href attribute is the required attribute of the tag.

ISRO CS Syllabus for Scientist/Engineer Exam Add a link styled as a button with CSS properties. W3Schools offers free online tutorials, references and exercises in all the major languages of the web.This input can be converted to a toggle button. In web development, an HTML radio (or checkbox) input is used to get true and false value on checked and unchecked events respectively. Basic button and input style The height and vertical alignment of buttons and inputs is determined by the combination of borders, padding, font-size, and line-height. ISRO CS Original Papers and Official Keys A toggle button is a visual element of the user interface that is used to switch between two (true/false) state.GATE CS Original Papers and Official Keys.

Button text html code#

And finally, if you override one of these class names by including the generated css code on your website, everything should work fine as expected. the complete page is loaded, then the anonymous function denoted by function HTML Tutorial » HTML Button onClick. (Perfect for horizontal navigation menus) w3-block. A horizontal bar that can be used to group buttons together. Default color is inherited from parent element in version 4. Default color is light-gray in W3.CSS version 3. Let's say if you enter "btn-primary", the code will generate the css code with this class name. A rectangular button with a gray hover effect. As you know a bootstrap button has css class names like btn-primary, btn-secondary etc. In order to include a button on a Bootstrap website, you just need to enter one of the class names listed on the Bootstrap documentation to the "class name" field under the text settings. Can I use these buttons on Twitter bootstrap? This kind of tasks are out of the button generator's scope. On the other hand, if your button needs to perform an action, let's say an ajax request, then you have to write that piece of code. You only need to include generated CSS and HTML codes to render the button. Do I need to include any javascript or jQuery code on my website?Ībsolutely no. All modern browsers should render your css button properly. To do this, just uncheck the "prefix" checkbox above the generated css code. Covering popular subjects like HTML, CSS, JavaScript, Python, SQL, Java, and many, many more. You can also disable vendor prefixes to get a cleaner code. W3Schools offers free online tutorials, references and exercises in all the major languages of the web. The generated code will include vendor prefixes for following browsers Google Chrome, Firefox, Safari, Opera, Internet Explorer and Edge. In addition to this properties, you can also change button's text and class name. Which CSS properties are available for editing? After completing your css button, click on the button preview or "Get Code" button to view generated CSS and HTML codes. Just select a css button from the library and play its css styles.

Button text html generator#

This css button generator is a free online tool that allows you to create cross browser css button styles in seconds.

[preemploymenttest]

How to Hire a Software Developer

Hiring a software developer is no easy task. There are thousands of talented developers out there looking for jobs. How do you choose from them? Software development has become an integral part of our lives. From mobile apps to web applications, almost every aspect of our daily life involves some sort of software. The demand for skilled software engineers is growing at a rapid pace. Learn more: https://blog.hirenest.com/a-guide-on-how-to-hire-a-software-developer/

It takes time and effort to hire a good software engineer. If you don’t get it wrong, hiring a great developer can be rewarding. In order to ensure you hire the right person, follow these steps.

Step 1: Understand what skills and traits you want in a candidate. This will help you narrow down your search and focus on those candidates who match your requirements.

Step 2: Find a job board where you can post your job ad. Posting a job ad on a job board allows potential applicants to find your job opening.

A career in software engineering requires a bachelor's degree in computer science or information systems. Most employers prefer candidates with experience in programming languages like Java, C#, Python, Ruby, PHP, JavaScript, etc.

What is a Software Developer?

A software developer creates applications using computer languages like Java, C#, Python, PHP, etc. They work closely with business analysts, project managers, database administrators, and others to develop solutions that solve problems. You can find out more in our article: https://blog.hirenest.com/a-guide-on-how-to-hire-a-software-developer/

The job outlook for software developers is expected to grow by 20% between 2014 and 2024. This growth is due to increased demand from companies looking to innovate new products and services. Companies are increasingly turning to mobile apps and cloud computing to improve productivity and increase customer satisfaction.

What are the types of software developers?

The most common type of developer is the front end developer who creates user interfaces (UIs) and web pages. A back end developer writes code behind those UIs and web pages. They may write server side scripts or they may work directly with databases.

Front end development requires skills like HTML5, CSS3, JavaScript, and jQuery. Back end development requires skills like PHP, Python, Ruby, Java, C#, and SQL.

Software engineers build applications using programming languages. Some of the most popular programming languages include:

Javascript, Python, Java, C++, C#, Objective-C, Swift, Go, Perl, PHP, Ruby, Haskell, Scala, Clojure, F#, Erlang, Lisp, Prolog, Visual Basic.NET, Delphi, Pascal, Ada, COBOL, Fortran, Assembly Language, BASIC, Cobol, PL/1, Tcl, VHDL, Batch Scripting, Shell Scripting, Bash, and many others.

In addition to being able to program in one language, it's important to know at least two different ones so you can switch between them easily. This will help you become familiar with new technologies and keep yourself from getting stuck in a rut.

Why Hire Top Developers?

The best developers will not only understand what you want but they will know how to build it. They will have experience working with different technologies and languages, and will be able to quickly adapt to new challenges.

The first step is to find out if any of your current team members are capable of building this feature. If so, great! But if not, then you should start looking outside of your company. There are many freelance web development agencies who specialize in custom software development. These companies typically offer hourly rates and charge by project. Some of them may even work on retainer contracts where they provide ongoing maintenance services.

Why hiring a good developer is challenging?

The most common reasons why developers fail at building software are lack of experience, poor communication skills, and not having enough resources.

I am sure you know what it means to hire a developer but still, here we will discuss some points which may help you to find the best one.

There are many ways to develop software. It depends upon the type of project and requirements. In this article, we will discuss three different approaches to build software. They are Agile, Waterfall and Spiral Development.

Software development life cycle (SDLC) is the process of developing a product from its inception through delivery. SDLC consists of four phases: Requirements Gathering, Analysis & Design, Implementation and Testing. Each phase has its own set of activities and deliverables. These activities are performed by various groups within the company like Product Owner, Developers, Testers etc.

A software development team usually comprises of several people who work together to complete a particular task. This team includes a Project Manager, Team Lead, Scrum Master, Programmer, QA Analyst, UI Designer, UX Designer, Business Analyst, Customer Support Engineer, Technical Writer, Content Developer, and so on. 

Conclusion

The first thing to consider when hiring a software developer is whether he or she has experience with your industry. If you're looking for someone to build a website, then you want someone who's familiar with web development. If you need help building mobile apps, look for someone who knows about app development.

A good programmer will not only know the basics of programming languages but also understand what makes them tick. They should be able to explain why certain code works the way it does, and they'll be able to tell you if something isn't working correctly. This means being able to read through code and figure out where things might go wrong.

The best programmers are those who are passionate about coding and enjoy solving problems. If you're looking for someone who's going to spend all day every day writing code, then this job probably isn't for you. But if you want someone who enjoys coming up with new ideas and solutions to complex challenges, then software development may be perfect for you. If you want to know more about A Guide on How to Hire a Software Developer, read this article: https://blog.hirenest.com/a-guide-on-how-to-hire-a-software-developer/

[codeadventure1997]

Dawn of the final week.

I've been a part of the flatiron school fullstack software engineering program since early february. It's hard to believe how far I've come, from barely knowing how to program a calculator that works in the console with python to writing fullstack applications in react and rails with full crud functionality and front to backend communication.

As I work on my final project, I'd like to reminisce on the program as a whole and give my thoughts on each phase.

Phase 1, we were learning vanilla javascript and would simulate a backend with JSON server. This phase was me putting my feet in the water and learning what I would have to later in the program. This was the only phase I had to retake the coding challenge, and at the time it was almost overwhelming. The constant cycle of learn, code, learn, code, was very new to me. I passed the retake of the code challenge and completed my first project. This phase was probably the second hardest, because I was acclimating to the program and needed time to get used to the fast and constant pace of it.

Phase 2, we had finished with vanilla JS and immediately threw ourselves headfirst into react JS. Although it was just as fast paced as phase 1, I found that react was a lot easier to grasp than vanilla JS because of how much more efficient and organized it was. The second code challenge was by far the easiest, I had felt unstoppable. My project had been developed with no major hitches, in my head I had crushed react and would continue to crush the rest of the program. Little did I knew i was due for a humbling in phase 3.

Phase 3 had us switch gears completely. We were no longer working on the frontend, we were learning Ruby, SQL, and Sinatra. Pivoting from the now familiar land of javascript and frontend to the completely new backend world with new languages was the hardest transition by far. Up until the code challenge I had to continue studying. I remember the panic attacks from the stress I was putting myself under. I was worried I wouldn't do well on the code challenge and that I would waste the money I spent getting into the program. Literally the night before the code challenge, something clicked in my head. It all started to make sense and I ended up doing great on the code challenge. The project went well too, I got even more experience with the way the backend and the frontend communicate. I worked on the backend as much as I could on that project because I knew how much it would help me in phase 4.

Phase 4, we piggy-backed off of sinatra into Rails. As far as the learning and code challenge went, This was a close #2 for the easiest of the phases. Rails just makes a backend so simple yet it is so robust, I don't feel like I am trading simplicity with configuration control at all with it, sort of a best of both worlds relationship with Rails. As I said, this phase would have been the easiest if not for, the project. During this project I ended up having to do a lot of troubleshooting between the front and backend. While it was stressful at the time, it was a great learning experience. All of that troubleshooting helped tremendously in phase 5.

Phase 5 is just 3 weeks of project basically. Working on my first project completely on my own has been an absolute treat. I feel like all the stress I've been through has well prepared me for this. I've been experimenting with new things in this project, and I feel comfortable enough with the frontend and the backend to do so confidently. My troubleshooting skills have gotten much better now, I'm not scared to write code anymore. I am still working on my final project but I am super proud of what I've done. I've gone from a man who couldn't do more than basic math and console logs to a man that I feel would be a genuine asset to a team.

As I complete my final project I have been looking forward to the opportunities I've worked to get. I can't wait to see my hard work pay off and I'll be sure to keep yall in the loop!

Till next time,

A software engineer

[mobappdevelopmentcompany]

Trending technology stacks of 2020!

The software market is flooded with myriad outstanding technology stacks. However, businesses, particularly those with lesser experience, find it quite challenging to decide on the right technology stack that would prove profitable for them. Typically these businesses are unable to keep up with the pace of technology updates as the older technology stacks that were once ruling the roost are being constantly replaced by emerging new technologies. So, before jump-starting the mobile app development process, it is very important that companies understand the trending technologies that are available in the market, get a thorough knowledge about them and then take the informed decision on which technology to go for.

My write up provides handy insights on the offerings of the trending technology stacks of 2020. Reading this article would prove immensely beneficial to a mobile app development company, mobile app developers, and entrepreneurs planning to develop trendy applications.

The offerings of Trending technology stacks of 2020 

MEAN stack

MEAN stack is free and one of the most popular stack. This stack uses a single JavaScript language end-to-end. It follows a modern approach to crafting robust and speedy apps. MEAN comprises MongoDB (NoSQL database), Express.js backend web framework, Angular.js frontend framework, and Node.js cross-platform server. It supports MVC pattern and owing to Angular JS it is also mobile-friendly. MEAN proves particularly beneficial for use in calendars, news aggregation sites, mapping, and location-finding, etc.

Advantages

MEAN, being an end-to-end JavaScript stack enables Mobile app developers to use a single language throughout the stack. Hence the code can be reused across the whole app, thereby reducing the chances of unnecessary rework.

It is an ideal option for creating scalable, flexible, and agile apps on account of the JS module library of Node.js and NoSQL, hence ideal for cloud hosting.

It provides developers flexibility in structuring data. This enables effortless switching between the document-based NoSQL and SQL.

Deployment of this technology stack becomes easy as it uses its own web server.

A mobile app development Company using MEAN can manage by hiring a sole team of JavaScript developers who are capable of working adaptively.

MEAN enjoys the support of a vibrant and active community that helps developers with issues and queries.

MERN stack

The MERN stack is similar to MEAN with the difference that React is used in place of Angular.js. React is a powerful library that creates SPAs and high-end applications having interactive interfaces. Moreover, MERN offers full-stack development and is capable of using codes on servers and browsers simultaneously. However, the React eco-system offers limited core features and so developers have to utilize third-party services.

MEVN stack

MEVN stack is another version of the MEAN stack wherein Vue.js is used as the front-end framework in place of Angular JS. Vue.js combines the best functionalities of React and Angular; and is has garnered popularity in recent years. Its key offerings are:

A rich set of tools

An easy learning curve

A clear programming style

Creation of highly performing web apps.

LAMP stack

LAMP stack happens to be one of the earliest open-source software stacks for building web apps that had stood the test of times and is used extensively even today. Drupal and WordPress are examples of Content Management System Platforms using LAMP.

LAMP comprises Linux, Apache, MySQL, and PHP.

Key highlights

Open-source and non-proprietary platform.

Components can be chosen as per specific business needs.

An apt platform for building customized web applications owing to its simplicity, stability, and proficiency.

Efficient handling of dynamic pages in which the content gets changed each time the page is loaded.

Linux can be replaced with (1) Microsoft Windows as the OS to form a WAMP stack or (2) MAC as the OS to form the MAMP stack.

PHP can be replaced by Perl or the newbie Python.

Ruby on Rails stack

Ruby on Rails stack is a rich archive of open source tools and library integrations that boost the app development speed. RoR enables you to architect complete web apps by integrating JavaScript, CSS, HTML, AND Ruby. Writing the code and debugging it becomes simpler and quicker with RoR. Check here for the role of RoR in web app development.  The frameworks and tools used in the Ruby on Rails stack are JavaScript, CoffeeScript, Bootstrap, jQuery, HTML, CSS, Redis, Node.js, Middleware, MongoDB, and JVM. One of the most popular app Airbnb has been developed using this stack.

Serverless stack

Going serverless ie. building apps on the cloud infrastructure is the latest mantra. The services and tools offered by Serverless computing platforms ease-out infrastructure management and scaling. AWS Lambda is an example of one of the earliest serverless platforms. Google Cloud is another popular provider of cloud computing.

Flutter for Web

Flutter for Web is a revolutionary cross-platform framework, that employs the same business logic and UI on every platform. Usage of Flutter allows one to add new functionalities, create interfaces, and fix bugs without spending time on deployment. Check here to know more about Flutter for the web.

.Net stack

.Net stack facilitates the creation of a bug-free framework decked up with rich features that lead to the creation of interactive and robust web apps. It is interoperable, language-independent, speedy, secure, and portable. However, this tech stack lacks multi-platform support, easy migration, and efficient code management. 

Final Verdict

I hope this article has provided you comprehensive knowledge about these prevalent technology stacks and will help you to choose the right one for your up-coming project. We will give more insights into other technology stacks in the next version of our article.

For expert guidance and technical assistance reach out to Biz4Solutions, a prominent mobile app development company at sales.enquiry@biz4solutions.com.

To know more about our other technologies, refer to the links below:

React Native App Development Company

Angular App Development Company

Ionic App Development Company

[suzanneshannon]

CoreBoy is a cross platform GameBoy Emulator written in C# that even does ASCII

.NET and C# are great languages for programming emulators. Specifically retrogaming and retroarcade emulators. In fact, there's a long history of emulators written in C#. Here's just a few.

Emulating a PlayStation 1 (PSX) entirely with C# and .NET

Virtu, an Apple Emulator in C# for Silverlight, WPF and XNA

A multi-player server-side GameBoy Emulator written in .NET Core and Angular

Commodore 64 Emulator

Today, David Whitney is deep into writing CoreBoy, a GameBoy Emulator written in C# and .NET Core, using WinForms, and I also spy the Avalonia cross-platform open source WPF-like framework. Head over to https://github.com/davidwhitney/CoreBoy and give the gent a STAR. It even has a headless mode and you could use it as a Library in your own software. Who doesn't want a GameBoy library in their app?

I cloned and built it with http://dot.net Core in just a few minutes. Lovely. I enjoy a clean codebase. Assuming you have a backup of one of the many physical GameBoy games you own like me, you can load a binary dump in CoreBoy as a *.gb or *.gbc file and you'll get something this:

Sweet! Sure it's a little buggy and slow but figuring these things out is the fun of it all! I love that David Whitney is taking us on this journey with him.

There's even already a MonoGame-based graphics surface using DesktopGL and "nilllzz" has it running on Ubuntu!

Emulators are always fun projects to read and learn from. Here, David has a clear separation of concerns between the emulator (handling the CPU, loading instructions, etc.) and the graphics surface that is ultimately responsible for putting pixels on screen.

It looks like he hasn't got it working yet (some issues with command line parsing), but in a few minutes with a little hard-coding I was able to switch to ASCII mode with David's SillyAsciiArtCreator that takes a Pixel and RGB value and maps it to ASCII art that looks awesome in the Windows Terminal.

Which is kind of awesome. Why would you do this? BECAUSE YOU CAN

I look forward to seeing what comes of this cool new emulator and I'll be reading its code in more detail in the weeks to come! Great stuff, David!

Sponsor: Couchbase gives developers the power of SQL with the flexibility of JSON. Start using it today for free with technologies including Kubernetes, Java, .NET, JavaScript, Go, and Python.

© 2020 Scott Hanselman. All rights reserved.

      CoreBoy is a cross platform GameBoy Emulator written in C# that even does ASCII published first on https://deskbysnafu.tumblr.com/

[philipholt]

CoreBoy is a cross platform GameBoy Emulator written in C# that even does ASCII

.NET and C# are great languages for programming emulators. Specifically retrogaming and retroarcade emulators. In fact, there's a long history of emulators written in C#. Here's just a few.

Emulating a PlayStation 1 (PSX) entirely with C# and .NET

Virtu, an Apple Emulator in C# for Silverlight, WPF and XNA

A multi-player server-side GameBoy Emulator written in .NET Core and Angular

Commodore 64 Emulator

Today, David Whitney is deep into writing CoreBoy, a GameBoy Emulator written in C# and .NET Core, using WinForms, and I also spy the Avalonia cross-platform open source WPF-like framework. Head over to https://github.com/davidwhitney/CoreBoy and give the gent a STAR. It even has a headless mode and you could use it as a Library in your own software. Who doesn't want a GameBoy library in their app?

I cloned and built it with http://dot.net Core in just a few minutes. Lovely. I enjoy a clean codebase. Assuming you have a backup of one of the many physical GameBoy games you own like me, you can load a binary dump in CoreBoy as a *.gb or *.gbc file and you'll get something this:

Sweet! Sure it's a little buggy and slow but figuring these things out is the fun of it all! I love that David Whitney is taking us on this journey with him.

There's even already a MonoGame-based graphics surface using DesktopGL and "nilllzz" has it running on Ubuntu!

Emulators are always fun projects to read and learn from. Here, David has a clear separation of concerns between the emulator (handling the CPU, loading instructions, etc.) and the graphics surface that is ultimately responsible for putting pixels on screen.

It looks like he hasn't got it working yet (some issues with command line parsing), but in a few minutes with a little hard-coding I was able to switch to ASCII mode with David's SillyAsciiArtCreator that takes a Pixel and RGB value and maps it to ASCII art that looks awesome in the Windows Terminal.

Which is kind of awesome. Why would you do this? BECAUSE YOU CAN

I look forward to seeing what comes of this cool new emulator and I'll be reading its code in more detail in the weeks to come! Great stuff, David!

Sponsor: Couchbase gives developers the power of SQL with the flexibility of JSON. Start using it today for free with technologies including Kubernetes, Java, .NET, JavaScript, Go, and Python.

© 2020 Scott Hanselman. All rights reserved.

      CoreBoy is a cross platform GameBoy Emulator written in C# that even does ASCII published first on http://7elementswd.tumblr.com/