As we all know Java is the best language in the world, except there is Go. Go is just so much more, isn’t it? The syntax is so concise and meaningful, the compiler is so much more helpful and the rules are all over it.
We will uncovering the bitter truth, the 5 reasons, that every Java developer should know about Go. We’ll present why Go is just the better programming language and why the hype around Go is all real.
Let your eyes be to opened and your brain to explode. Sarcasm included.
Constructs and techniques and their implementation in different languagesOliverYoung22
Here you will be learning about the following relating to python:
- File handling
- Logic operators
- Variables, local and global variables, constants
- Command words
- Statements
- Sequences
- Subroutines, procedures, functions
- Arrays(list), 2 dimensional arrays
- File handling, read, write, close and database
- Data structures
Constructs and techniques and their implementation in different languagesOliverYoung22
Here you will be learning about the following relating to python:
- File handling
- Logic operators
- Variables, local and global variables, constants
- Command words
- Statements
- Sequences
- Subroutines, procedures, functions
- Arrays(list), 2 dimensional arrays
- File handling, read, write, close and database
- Data structures
Crunching data with go: Tips, tricks, use-casesSergii Khomenko
Talk for the first meetup of Munich Golang User Group. Described use-cases from real Go development, covered fetching data from sql database, connecting to Google services like Google Analytics, Google BigQuery, other aspect of building a geolocation application.
Gary Bernhardt’s famous WAT talk pokes fun at the weird things in Ruby and JavaScript due to weak typing and operator overloading. But Go can be strange, too. It has its own odd behaviors, some of which we run into every day. Learning about Go’s corner cases teaches us how Go works under the covers.
This is the third presentation in pySIG 2015 @ BMS College of Engineering, Bangalore. The code and assignments can be found at https://github.com/pranavsb
Ever wonder what this "new" Kotlin thing is? Curious what the syntax looks like? Unsure how to implement this at your own company? Or do you just want to know what Nick and Cody's favorite things are about this language?
All that and (maybe) more are revealed in Privet Kotlin.
For the last two decades, the amount of data we store, process, and analyze is ever growing. The last decade shows a higher focus on immediate feedback loop data pipeline, using technologies such as Complex Event Processing (CEP), Stream Processing, and Change Data Capture (CDC). Services such as Kafka or NATS are to be found in almost every new system (at least to some extent).
To build a data pipeline, the number of technologies, frameworks, and platforms are endless. Getting the initial grasp of it all is much harder than expected, but together we can tackle it!
Messages sind heutzutage überall. Egal ob JavaScript Frontends in Form von Events, oder Backends mit Kafka oder NATS Message Queues, wir wollen zwei Ziele erreichen, Separation of Concerns (unabhängige Einheiten) und Skalierbarkeit (oder in Frontends Freigabe von Resourcen).
Da heute alles Responsive sein muss, brauchen wir Event-basierte Systeme. Also lasst uns gemeinsam die darunterliegenden Systeme erforschen, verstehen und Einsatzbereiche erarbeiten.
Crunching data with go: Tips, tricks, use-casesSergii Khomenko
Talk for the first meetup of Munich Golang User Group. Described use-cases from real Go development, covered fetching data from sql database, connecting to Google services like Google Analytics, Google BigQuery, other aspect of building a geolocation application.
Gary Bernhardt’s famous WAT talk pokes fun at the weird things in Ruby and JavaScript due to weak typing and operator overloading. But Go can be strange, too. It has its own odd behaviors, some of which we run into every day. Learning about Go’s corner cases teaches us how Go works under the covers.
This is the third presentation in pySIG 2015 @ BMS College of Engineering, Bangalore. The code and assignments can be found at https://github.com/pranavsb
Ever wonder what this "new" Kotlin thing is? Curious what the syntax looks like? Unsure how to implement this at your own company? Or do you just want to know what Nick and Cody's favorite things are about this language?
All that and (maybe) more are revealed in Privet Kotlin.
For the last two decades, the amount of data we store, process, and analyze is ever growing. The last decade shows a higher focus on immediate feedback loop data pipeline, using technologies such as Complex Event Processing (CEP), Stream Processing, and Change Data Capture (CDC). Services such as Kafka or NATS are to be found in almost every new system (at least to some extent).
To build a data pipeline, the number of technologies, frameworks, and platforms are endless. Getting the initial grasp of it all is much harder than expected, but together we can tackle it!
Messages sind heutzutage überall. Egal ob JavaScript Frontends in Form von Events, oder Backends mit Kafka oder NATS Message Queues, wir wollen zwei Ziele erreichen, Separation of Concerns (unabhängige Einheiten) und Skalierbarkeit (oder in Frontends Freigabe von Resourcen).
Da heute alles Responsive sein muss, brauchen wir Event-basierte Systeme. Also lasst uns gemeinsam die darunterliegenden Systeme erforschen, verstehen und Einsatzbereiche erarbeiten.
Farms are simple. A farm, a building or two, maybe a barn. Done. You’d wish.
Monitoring farms and barns is a tedious task. No farm looks like the other and water distribution, next to other elements, has grown generically. A little bit like the good old legacy systems we all love. With the additional complication of keeping track of topology changes, typical building automation systems are out of the scope.
See how clevabit integrated neo4j, PostgreSQL and TimescaleDB to bring observability to farms and what I learned along the way. And there were a lot of “this time it works” moments.
What I learned about IoT Security ... and why it's so hard!Christoph Engelbert
Smart devices taking over our living rooms, our bed rooms, and, in general, our life. It has never been more important to build secure devices, but most companies seem to fail, and they fail hard. We (only) build systems for farms and barns, and still, I wanted security for Cow-stumers.
Building a mostly secure system is fairly simple. There is a good set of low-hanging fruits. Building a really locked down system is tough, though. Much harder than expected. Here is what I learned.
Time-series data, or data being associated with its respective time of occurrence, is everywhere. From the obvious cases, such as metrics, observability, IoT data, all the way to logs, invoicing, or payment records. While storing some of these in relational databases is standard practice, people often reach for specific time-series databases when volume gets high. But imagine if you could have all of them in the same database: PostgreSQL.
With Instana the "Classic" Observability is not the end of the line. Find out what Observability means and how it can help DevOps, Developers, SREs day-by-day.
Building, deploying and operating application systems for high scale and failure tolerance is the supreme field of software engineering. While Continuous Integration (CI) and oftentimes also Continuous Delivery (CD) have become a part of commonly used build pipelines, monitoring and observability is still often an afterthought or manually configured. To keep up with containers being started and stopped for version upgrades, scaling up and down or to mitigate failure situations, monitoring needs to automate all the tasks to react to infrastructure changes and find issues before users being impacted. People today expect “Oops-Less Operation”, or do you want your bank to be offline?
Continuous Integration, Continuous Delivery, Continuous Monitoring!
These days CI and CD are commonly used mechanics to achieve fast turn-around times for high-demand applications. Microservices architectures and highly dynamic envrionments (based on Kubernetes, Docker, …), however, come with a whole different set of problems.
Systems, that not only appear and disappear dynamically (e.g. autoscaling), but most commonly tend to be written using multiple different programming languages, are hard to monitor from the point of view that matters: User Requests and User Experience. but the answer is simple; Continuous Monitoring (CM).
Let's build a polyglot microservices infrastructure. A way to monitor and trace multi-service requests will be demonstrated using Instana’s automatic discovery system.
Everyone knows there isn't just one way of doing things. This is also true for web-administrated Embedded Devices and a lot of different ways to attack the implementation were taken before the combination of Golang and Typescript manifested. Plenty of the tries started by missing knowledge, inability, the hate of some programming languages or just plainly on size requirements. Over Java and C/C++ to Go+Lua, Go+JavaScript and the final decision on Go and Typescript, we follow the adventure of an embedded framework and the arising problems. Pros and Cons but also the feeling for a Java developer and new horizons are given.
JSON, by now, became a regular part of most applications and services. Do we, how ever, really want to transfer human readable information or are we looking for a binary protocol to be as debuggable as JSON? CBOR the Concise Binary Object Representation offers the best of JSON + an extremely efficient, binary representation.
http://www.cbor.io
The days of JNI is counted, Project Panama is on the rise to tear down the walls between Java and C/C++ forever. FFI (Foreign Function Interface) technology finally arrives into the Java world.
The way from monolithic to micro service architectures can hard. Overall micro services are not the all holy grail to just solve all your issues. You need to be aware that you need the right developers and the right toolset. Oh and not to forget, moving state to authorization systems doesn't mean your application is really stateless :)
Anyhow micro services are a great architecture and this deck is a short introduction on why we need to change our application architectures and what pitfalls you you have when introducing the idea of micro services.
The future of Java is insight with Java 9 around the corner. Last year's discussions around the removal from sun.misc.Unsafe and the eventually presented compromise is history. Time to start looking forward to some details from what's coming, especially in terms of the Unsafe API replacement.
Reaching critical masses with your application systems becomes harder every day. Caching helps to provide low latency and high availability over slow calculation, networks, databases and any other kind of external resource.
In-Memory Computing - Distributed Systems - Devoxx UK 2015Christoph Engelbert
Today’s amounts of collected data are showing a nearly exponential growth. More than 75% of all the data have been collected in the past 5 years. To store this data and process it in an appropriate time you need to partition the data and parallelize the processing of reports and analytics. This talk will demonstrate how to parallelize data processing using Hazelcast and it’s underlying distributed data structures. With a quick introduction into the different terms and some short live coding examples we will make the journey into the distributed computing.
JCache - Caching Introduction - What is the idea, where are we coming from and where we want to go in the future. Why we need caching and why do we want to cache?
Nowadays collected amounts of data growing exponentially. More than 75% of all stored data were collected in the last 5 to 6 years. To store and analyze those always fast growing pile of data we have to go new ways. The Scale-Up approach starts to break apart. Partitioning data and parallelize processing and analyzing are the new way.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
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Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
13. @noctarius2k
What Is Go?
Go: The Good Parts
1. It’s opinionated
https://www.pexels.com/photo/blank-paper-with-pen-and-coffee-cup-on-wood-table-6357/
42. @noctarius2k
Clone Or Not Clone, That Is The Question!
func main() {
var var1 int = 1
var var2 handle = 2
types(var1)
types(var2)
}
type handle int
func types(val interface{}) {
switch v := val.(type) {
case int:
fmt.Println(fmt.Sprintf("I am an int: %d", v))
}
switch v := val.(type) {
case handle:
fmt.Println(fmt.Sprintf("I am an handle: %d", v))
}
}
43. @noctarius2k
Clone Or Not Clone, That Is The Question!
func main() {
var var1 int = 1
var var2 handle = 2
types(var1)
types(var2)
}
type handle = int
func types(val interface{}) {
switch v := val.(type) {
case int:
fmt.Println(fmt.Sprintf("I am an int: %d", v))
}
switch v := val.(type) {
case handle:
fmt.Println(fmt.Sprintf("I am an handle: %d", v))
}
}