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Search - "data oriented programming"
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NEW 6 Programming Language 2k16
1. Go
Golang Programming Language from Google
Let's start a list of six best new programming language and with Go or also known by the name of Golang, Go is an open source programming language and developed by three employees of Google and the launch in 2009, very cool just 3 people.
Go originated and developed from the popular programming languages such as C and Java, which offers the advantages of compact notation and aims to keep the code simple and easy to read / understand. Go language designers, Robert Griesemer, Rob Pike and Ken Thompson, revealed that the complexity of C ++ into their main motivation.
This simple programming language that we successfully completed the most tasks simply by librariesstandar luggage. Combining the speed of pemrogramandinamis languages such as Python and to handalan of C / C ++, Go be the best tools for building 'High Volume of distributed systems'.
You need to know also know, as expressed by the CTO Tokopedia namely Mas Leon, Tokopedia will switch to GO-lang as the main foundation of his system. Horrified not?
eh not watch? try deh see in the video below:
[Embedyt] http://youtube.com/watch/...]
2. Swift
Swift Programming Language from Apple
Apple launched a programming language Swift ago at WWDC 2014 as a successor to the Objective-C. Designed to be simple as it is, Swift focus on speed and security.
Furthermore, in December 2015, Swift Apple became open source under the Apache license. Since its launch, Swift won eye and the community is growing well and has become one of the programming languages 'hottest' in the world.
Learning Swift make sure you get a brighter future and provide the ability to develop applications for the iOS ecosystem Apple is so vast.
Also Read: What to do to become a full-stack Developer?
3. Rust
Rust Programming Language from Mozilla
Developed by Mozilla in 2014 and then, and in StackOverflow's 2016 survey to the developer, Rust was selected as the most preferred programming language.
Rust was developed as an alternative to C ++ for Mozilla itself, which is referred to as a programming language that focus on "performance, parallelisation, and memory safety".
Rust was created from scratch and implement a modern programming language design. Its own programming language supported very well by many developers out there and libraries.
4. Julia
Julia Programming Language
Julia programming language designed to help mathematicians and data scientist. Called "a complete high-level and dynamic programming solution for technical computing".
Julia is slowly but surely increasing in terms of users and the average growth doubles every nine months. In the future, she will be seen as one of the "most expensive skill" in the finance industry.
5. Hack
Hack Programming Language from Facebook
Hack is another programming language developed by Facebook in 2014.
Social networking giant Facebook Hack develop and gaungkan as the best of their success. Facebook even migrate the entire system developed with PHP to Hack
Facebook also released an open source version of the programming language as part of HHVM runtime platform.
6. Scala
Scala Programming Language
Scala programming termasukbahasa actually relatively long compared to other languages in our list now. While one view of this programming language is relatively difficult to learn, but from the time you invest to learn Scala will not end up sad and disappointing.
The features are so complex gives you the ability to perform better code structure and oriented performance. Based programming language OOP (Object oriented programming) and functional providing the ability to write code that is capable of evolving. Created with the goal to design a "better Java", Scala became one behasa programming that is so needed in large enterprises.3 -
Imagine yourself being a CTO back then.
Brand new Acura NSX. No MacBooks, ThinkPads are hot. Your company has its own skyscraper. CASE tools are just introduced and they’re hotter than blockchain now. You do software architecture in IBM Rational Rose, typing on your Model M and thinking really hard about Java OOP which is very hot right now.
You have Erlang servers at your own data center. You laugh at people writing in COBOL. You excited about aspect-oriented programming.
What a wonderful time.3 -
When I was in college OOP was emerging. A lot of the professors were against teaching it as the core. Some younger professors were adamant about it, and also Java fanatics. So after the bell rang, they'd sometimes teach people that wanted to learn it. I stayed after and the professor said that object oriented programming treated things like reality.
My first thought to this was hold up, modeling reality is hard and complicated, why would you want to add that to your programming that's utter madness.
Then he started with a ball example and how some balls in reality are blue, and they can have a bounce action we can express with a method.
My first thought was that this seems a very niche example. It has very little to do with any problems I have yet solved and I felt thinking about it this way would complicate my programs rather than make them simpler.
I looked around the at remnants of my classmates and saw several sitting forward, their eyes lit up and I felt like I was in a cult meeting where the head is trying to make everyone enamored of their personality. Except he wasn't selling himself, he was selling an idea.
I patiently waited it out, wanting there to be something of value in the after the bell lesson. Something I could use to better my own programming ability. It never came.
This same professor would tell us all to read and buy gang of four it would change our lives. It was an expensive hard cover book with a ribbon attached for a bookmark. It was made to look important. I didn't have much money in college but I gave it a shot I bought the book. I remember wrinkling my nose often, reading at it. Feeling like I was still being sold something. But where was the proof. It was all an argument from authority and I didn't think the argument was very good.
I left college thinking the whole thing was silly and would surely go away with time. And then it grew, and grew. It started to be impossible to avoid it. So I'd just use it when I had to and that became more and more often.
I began to doubt myself. Perhaps I was wrong, surely all these people using and loving this paradigm could not be wrong. I took on a 3 year project to dive deep into OOP later in my career. I was already intimately aware of OOP having to have done so much of it. But I caught up on all the latest ideas and practiced them for a the first year. I thought if OOP is so good I should be able to be more productive in years 2 and 3.
It was the most miserable I had ever been as a programmer. Everything took forever to do. There was boilerplate code everywhere. You didn't so much solve problems as stuff abstract ideas that had nothing to do with the problem everywhere and THEN code the actual part of the code that does a task. Even though I was working with an interpreted language they had added a need to compile, for dependency injection. What's next taking the benefit of dynamic typing and forcing typing into it? Oh I see they managed to do that too. At this point why not just use C or C++. It's going to do everything you wanted if you add compiling and typing and do it way faster at run time.
I talked to the client extensively about everything. We both agreed the project was untenable. We moved everything over another 3 years. His business is doing better than ever before now by several metrics. And I can be productive again. My self doubt was over. OOP is a complicated mess that drags down the software industry, little better than snake oil and full of empty promises. Unfortunately it is all some people know.
Now there is a functional movement, a data oriented movement, and things are looking a little brighter. However, no one seems to care for procedural. Functional and procedural are not that different. Functional just tries to put more constraints on the developer. Data oriented is also a lot more sensible, and again pretty close to procedural a lot of the time. It's just odd to me this need to separate from procedural at all. Procedural was very honest. If you're a bad programmer you make bad code. If you're a good programmer you make good code. It seems a lot of this was meant to enforce bad programmers to make good code. I'll tell you what I think though. I think that has never worked. It's just hidden it away in some abstraction and made identifying it harder. Much like the code methodologies themselves do to the code.
Now I'm left with a choice, keep my own business going to work on what I love, shift gears and do what I hate for more money, or pivot careers entirely. I decided after all this to go into data science because what you all are doing to the software industry sickens me. And that's my story. It's one that makes a lot of people defensive or even passive aggressive, to those people I say, try more things. At least then you can be less defensive about your opinion.53 -
python machine learning tutorials:
- import preprocessed dataset in perfect format specially crafted to match the model instead of reading from file like an actual real life would work
- use images data for recurrent neural network and see no problem
- use Conv1D for 2d input data like images
- use two letter variable names that only tutorial creator knows what they mean.
- do 10 data transformation in 1 line with no explanation of what is going on
- just enter these magic words
- okey guys thanks for watching make sure to hit that subscribe button
ehh, the machine learning ecosystem is burning pile of shit let me give you some examples:
- thanks to years of object oriented programming research and most wonderful abstractions we have "loss.backward()" which have no apparent connection to model but it affects the model, good to know
- cannot install the python packages because python must be >= 3.9 and at the same time < 3.9
- runtime error with bullshit cryptic message
- python having no data types but pytorch forces you to specify float32
- lets throw away the module name of a function with these simple tricks:
"import torch.nn.functional as F"
"import torch_geometric.transforms as T"
- tensor.detach().cpu().numpy() ???
- class NeuralNetwork(torch.nn.Module):
def __init__(self):
super(NeuralNetwork, self).__init__() ????
- lets call a function that switches on the tracking of math operations on tensors "model.train()" instead of something more indicative of the function actual effect like "model.set_mode_to_train()"
- what the fuck is ".iloc" ?
- solving environment -/- brings back memories when you could make a breakfast while the computer was turning on
- hey lets choose the slowest, most sloppy and inconsistent language ever created for high performance computing task called "data sCieNcE". but.. but. you can use numpy! I DONT GIVE A SHIT about numpy why don't you motherfuckers create a language that is inherently performant instead of calling some convoluted c++ library that requires 10s of dependencies? Why don't you create a package management system that works without me having to try random bullshit for 3 hours???
- lets set as industry standard a jupyter notebook which is not git compatible and have either 2 second latency of tab completion, no tab completion, no documentation on hover or useless documentation on hover, no way to easily redo the changes, no autosave, no error highlighting and possibility to use variable defined in a cell below in the cell above it
- lets use inconsistent variable names like "read_csv" and "isfile"
- lets pass a boolean variable as a string "true"
- lets contribute to tech enabled authoritarianism and create a face recognition and object detection models that china uses to destroy uyghur minority
- lets create a license plate computer vision system that will help government surveillance everyone, guys what a great idea
I don't want to deal with this bullshit language, bullshit ecosystem and bullshit unethical tech anymore.11 -
The Zen Of Ripping Off Airtable:
(patterned after The Zen Of Python. For all those shamelessly copying airtables basic functionality)
*Columns can be *reordered* for visual priority and ease of use.
* Rows are purely presentational, and mostly for grouping and formatting.
* Data cells are objects in their own right, so they can control their own rendering, and formatting.
* Columns (as objects) are where linkages and other column specific data are stored.
* Rows (as objects) are where row specific data (full-row formatting) are stored.
* Rows are views or references *into* columns which hold references to the actual data cells
* Tables are meant for managing and structuring *small* amounts of data (less than 10k rows) per table.
* Just as you might do "=A1:A5" to reference a cell range in google or excel, you might do "opt(table1:columnN)" in a column header to create a 'type' for the cells in that column.
* An enumeration is a table with a single column, useful for doing the equivalent of airtables options and tags. You will never be able to decide if it should be stored on a specific column, on a specific table for ease of reuse, or separately where it and its brothers will visually clutter your list of tables. Take a shot if you are here.
* Typing or linking a column should be accomplishable first through a command-driven type language, held in column headers and cells as text.
* Take a shot if you somehow ended up creating any of the following: an FSM, a custom regex parser, a new programming language.
* A good structuring system gives us options or tags (multiple select), selections (single select), and many other datatypes and should be first, programmatically available through a simple command-driven language like how commands are done in datacells in excel or google sheets.
* Columns are a means to organize data cells, and set constraints and formatting on an entire range.
* Row height, can be overridden by the settings of a cell. If a cell overrides the row and column render/graphics settings, then it must be drawn last--drawing over the default grid.
* The header of a column is itself a datacell.
* Columns have no order among themselves. Order is purely presentational, and stored on the table itself.
* The last statement is because this allows us to pluck individual columns out of tables for specialized views.
*Very* fast scrolling on large datasets, with row and cell height variability is complicated. Thinking about it makes me want to drink. You should drink too before you embark on implementing it.
* Wherever possible, don't use a database.
If you're thinking about using a database, see the previous koan.
* If you use a database, expect to pick and choose among column-oriented stores, and json, while factoring for platform support, api support, whether you want your front-end users to be forced to install and setup a full database,
and if not, what file-based .so or .dll database engine is out there that also supports video, audio, images, and custom types.
* For each time you ignore one of these nuggets of wisdom, take a shot, question your sanity, quit halfway, and then write another koan about what you learned.
* If you do not have liquor on hand, for each time you would take a shot, spank yourself on the ass. For those who think this is a reward, for each time you would spank yourself on the ass, instead *don't* spank yourself on the ass.
* Take a sip if you *definitely* wildly misused terms from OOP, MVP, and spreadsheets.5 -
CIA – Computer Industry Acronyms
CD-ROM: Consumer Device, Rendered Obsolete in Months
PCMCIA: People Can’t Memorize Computer Industry Acronyms
ISDN: It Still Does Nothing
SCSI: System Can’t See It
MIPS: Meaningless Indication of Processor Speed
DOS: Defunct Operating System
WINDOWS: Will Install Needless Data On Whole System
OS/2: Obsolete Soon, Too
PnP: Plug and Pray
APPLE: Arrogance Produces Profit-Losing Entity
IBM: I Blame Microsoft
MICROSOFT: Most Intelligent Customers Realize Our Software Only Fools Teenagers
COBOL: Completely Obsolete Business Oriented Language
LISP: Lots of Insipid and Stupid Parentheses
MACINTOSH: Most Applications Crash; If Not, The Operating System Hangs
AAAAA: American Association Against Acronym Abuse.
WYSIWYMGIYRRLAAGW: What You See Is What You Might Get If You’re Really Really Lucky And All Goes Well.
Credit to: http://devtopics.com/best-programmi... -
Am I the only one that doesn't think purely data-oriented programming is a particularly good idea?
I mean we're throwing out all the principles that have been established over the last 20 years of OOP like encapsulation and implementation hiding. And you can say what you want about OOP and yes it's not perfect, but there are things that work quite well. Implementation hiding is a perfect example of something that I don't think I just want to give up.
DOP feels like going back to programming C in the 80's with fully procedural functions and completely open structs.
Am I just going mad?6 -
FP features in OO/Imperative languages are more Data Oriented Programming (DOP) features than FP. Clojure popularised the term and now every FP language is trying to say “oooh FP is mainstream now”.
No its not. Nobody really cares if you managed to create this beautiful effect system that can emulate what OOP does for decades now. What people care is making data transformations simple and flat.3