1663588980
Top 5 Golang Libraries for Regular Expressions
In today's post we will learn about Top 5 Golang Libraries for Regular Expressions.
What is a Regular Expression?
Regular expressions are specially encoded text strings used as patterns for matching sets of strings. They began to emerge in the 1940s as a way to describe regular languages, but they really began to show up in the programming world during the 1970s. The first place I could find them showing up was in the QED text editor written by Ken Thompson.
“A regular expression is a pattern which specifies a set of strings of characters; it is said to match certain strings.” —Ken Thompson
Regular expressions later became an important part of the tool suite that emerged from the Unix operating system—the ed, sed and vi (vim) editors, grep, AWK, among others. But the ways in which regular expressions were implemented were not always so regular.
Table of contents:
- Genex - Count and expand Regular Expressions into all matching Strings.
- Go-wildcard - Simple and lightweight wildcard pattern matching.
- Goregen - Library for generating random strings from regular expressions.
- Regroup - Match regex expression named groups into go struct using struct tags and automatic parsing.
- Rex - Regular expressions builder.
1 - Genex:
Count and expand Regular Expressions into all matching Strings.
Easy and efficient package to expand any given regex into all the possible strings that it can match.
This is the code that powers namegrep.
Usage
package main
import (
"fmt"
"regexp/syntax"
"github.com/alixaxel/genex"
)
func main() {
charset, _ := syntax.Parse(`[0-9a-z]`, syntax.Perl)
if input, err := syntax.Parse(`(foo|bar|baz){1,2}\d`, syntax.Perl); err == nil {
fmt.Println("Count:", genex.Count(input, charset, 3))
genex.Generate(input, charset, 3, func(output string) {
fmt.Println("[*]", output)
})
}
}Output
Count: 120
[*] foo0
[*] ...
[*] foo9
[*] foofoo0
[*] ...
[*] foofoo9
[*] foobar0
[*] ...
[*] foobar9
[*] foobaz0
[*] ...
[*] foobaz9
[*] bar0
[*] ...
[*] bar9
[*] barfoo0
[*] ...
[*] barfoo9
[*] barbar0
[*] ...
[*] barbar9
[*] barbaz0
[*] ...
[*] barbaz9
[*] baz0
[*] ...
[*] baz9
[*] bazfoo0
[*] ...
[*] bazfoo9
[*] bazbar0
[*] ...
[*] bazbar9
[*] bazbaz0
[*] ...
[*] bazbaz9
Install
go get github.com/alixaxel/genex2 - Go-wildcard:
Simple and lightweight wildcard pattern matching.
Why
This part of Minio project, a very cool, fast and light wildcard pattern matching.
Originally the purpose of this fork is to give access to this "lib" under Apache license, without importing the entire Minio project ...
Two function are available MatchSimple and Match
MatchSimpleonly covert*usage (which is faster thanMatch)Matchsupport full wildcard matching,*and?
I know Regex, but they are much more complex, and slower (even prepared regex) ...
I know Glob, but most of the time, I only need simple wildcard matching.
How to
⚠️ WARNING: Unlike the GNU "libc", this library have no equivalent to "FNM_FILE_NAME". To do this you can use "path/filepath" https://pkg.go.dev/path/filepath#Glob
Using this fork
go get github.com/IGLOU-EU/go-wildcard@latestUsing Official Minio (GNU Affero General Public License 3.0 or later)
From https://github.com/minio/minio/commit/81d5688d5684bd4d93e7bb691af8cf555a20c28c the minio pkg are moved to https://github.com/minio/pkg
go get github.com/minio/pkg/wildcard@latestQuick Example
This example shows a Go file with pattern matching ...
package main
import (
"fmt"
wildcard "github.com/IGLOU-EU/go-wildcard"
)
func main() {
str := "daaadabadmanda"
pattern := "da*da*da*"
result := wildcard.MatchSimple(pattern, str)
fmt.Println(str, pattern, result)
pattern = "?a*da*d?*"
result = wildcard.Match(pattern, str)
fmt.Println(str, pattern, result)
}3 - Goregen:
Library for generating random strings from regular expressions.
Package regen is a library for generating random strings from regular expressions. The generated strings will match the expressions they were generated from. Similar to Ruby's randexp library.
E.g.
regen.Generate("[a-z0-9]{1,64}")
will return a lowercase alphanumeric string between 1 and 64 characters long.
Expressions are parsed using the Go standard library's parser: http://golang.org/pkg/regexp/syntax/.
Constraints
"." will generate any character, not necessarily a printable one.
"x{0,}", "x*", and "x+" will generate a random number of x's up to an arbitrary limit. If you care about the maximum number, specify it explicitly in the expression, e.g. "x{0,256}".
Flags ¶
Flags can be passed to the parser by setting them in the GeneratorArgs struct. Newline flags are respected, and newlines won't be generated unless the appropriate flags for matching them are set.
E.g. Generate(".|[^a]") will never generate newlines. To generate newlines, create a generator and pass the flag syntax.MatchNL.
The Perl character class flag is supported, and required if the pattern contains them.
Unicode groups are not supported at this time. Support may be added in the future.
Concurrent Use
A generator can safely be used from multiple goroutines without locking.
A large bottleneck with running generators concurrently is actually the entropy source. Sources returned from rand.NewSource() are slow to seed, and not safe for concurrent use. Instead, the source passed in GeneratorArgs is used to seed an XorShift64 source (algorithm from the paper at http://vigna.di.unimi.it/ftp/papers/xorshift.pdf). This source only uses a single variable internally, and is much faster to seed than the default source. One source is created per call to NewGenerator. If no source is passed in, the default source is used to seed.
The source is not locked and does not use atomic operations, so there is a chance that multiple goroutines using the same source may get the same output. While obviously not cryptographically secure, I think the simplicity and performance benefit outweighs the risk of collisions. If you really care about preventing this, the solution is simple: don't call a single Generator from multiple goroutines.
Benchmarks
Benchmarks are included for creating and running generators for limited-length, complex regexes, and simple, highly-repetitive regexes.
go test -bench .
The complex benchmarks generate fake HTTP messages with the following regex:
POST (/[-a-zA-Z0-9_.]{3,12}){3,6}
Content-Length: [0-9]{2,3}
X-Auth-Token: [a-zA-Z0-9+/]{64}
([A-Za-z0-9+/]{64}
){3,15}[A-Za-z0-9+/]{60}([A-Za-z0-9+/]{2}==|[A-Za-z0-9+/]{3}=)
The repetitive benchmarks use the regex
a{999}
See regen_benchmarks_test.go for more information.
On my mid-2014 MacBook Pro (2.6GHz Intel Core i5, 8GB 1600MHz DDR3), the results of running the benchmarks with minimal load are:
BenchmarkComplexCreation-4 200 8322160 ns/op
BenchmarkComplexGeneration-4 10000 153625 ns/op
BenchmarkLargeRepeatCreateSerial-4 3000 411772 ns/op
BenchmarkLargeRepeatGenerateSerial-4 5000 291416 ns/op4 - Regroup:
Match regex expression named groups into go struct using struct tags and automatic parsing.
Simple library to match regex expression named groups into go struct using struct tags and automatic parsing
Installing
go get github.com/oriser/regroup
Example
Named groups map
package main
import (
"fmt"
"github.com/oriser/regroup"
)
var re = regroup.MustCompile(`(?P<duration>.*?)\s+(?P<num>\d+)\s+(?P<foo>.*)`)
func main() {
matches, err := re.Groups("5s 123 bar")
if err != nil {
panic(err)
}
fmt.Printf("%+v\n", matches)
}Will output: map[duration:5s foo:bar num:123]
Single match
package main
import (
"fmt"
"github.com/oriser/regroup"
"time"
)
var re = regroup.MustCompile(`(?P<duration>.*?)\s+(?P<num>\d+)\s+(?P<foo>.*)`)
type B struct {
Str string `regroup:"foo"`
}
type A struct {
Number int `regroup:"num"`
Dur time.Duration `regroup:"duration"`
AnotherStruct B
}
func main() {
a := &A{}
if err := re.MatchToTarget("5s 123 bar", a); err != nil {
panic(err)
}
fmt.Printf("%+v\n", a)
}Will output: &{Number:123 Dur:5s AnotherStruct:{Str:bar}}
5 - Rex:
Regular expressions builder.
Why?
It makes readability better and helps to construct regular expressions using human-friendly constructions. Also, it allows commenting and reusing blocks, which improves the quality of code. It provides a convenient way to use parameterized patterns. It is easy to implement custom patterns or use a combination of others.
It is just a builder, so it returns standart *regexp.Regexp.
The library supports groups, composits, classes, flags, repetitions and if you want you can even use raw regular expressions in any place. Also it contains a set of predefined helpers with patterns for number ranges, phones, emails, etc...
Let's see an example of validating or matching someid[#] using a verbose pattern:
re := rex.New(
rex.Chars.Begin(), // `^`
// ID should begin with lowercased character.
rex.Chars.Lower().Repeat().OneOrMore(), // `[a-z]+`
// ID should contain number inside brackets [#].
rex.Group.NonCaptured( // (?:)
rex.Chars.Single('['), // `[`
rex.Chars.Digits().Repeat().OneOrMore(), // `[0-9]+`
rex.Chars.Single(']'), // `]`
),
rex.Chars.End(), // `$`
).MustCompile()Yes, it requires more code, but it has its advantages.
More, but simpler code, fewer bugs.
You can still use original regular expressions as is in any place. Example of matching numbers between -111.99 and 1111.99 using a combination of patterns and raw regular expression:
re := rex.New(
rex.Common.Raw(`^`),
rex.Helper.NumberRange(-111, 1111),
rex.Common.RawVerbose(`
# RawVerbose is a synonym to Raw,
# but ignores comments, spaces and new lines.
\. # Decimal delimter.
[0-9]{2} # Only two digits.
$ # The end.
`),
).MustCompile()
// Produces:
// ^((?:\x2D(?:0|(?:[1-9])|(?:[1-9][0-9])|(?:10[0-9])|(?:11[0-1])))|(?:0|(?:[1-9])|(?:[1-9][0-9])|(?:[1-9][0-9][0-9])|(?:10[0-9][0-9])|(?:110[0-9])|(?:111[0-1])))\.[0-9]{2}$The style you prefer is up to you
Thank you for following this article.
Related videos:
Regular Expression Basics for Go Programmers
What is GEEK
Buddha Community
1597311542
Top 5 Mobile App Development Companies in New York
New York is the best potential business hub for the technology and IT industry. Thousands of companies are established in New York for the mobile app development or technology industry. So, here quite a confusion is that how to choose the right company for your business amongst all the companies. No need to worry about it, We have found the most reliable and trustworthy mobile app development companies that are the top-tiers in New York. Before we share the companies list you need to know the benefits of mobile app development for your business.
Key Benefits of Mobile App Development:
· Improves Efficiency
· Offers High Scalability
· Secures Your App Data
· Integrates With Existing Software
· Easy to Maintain
· Improves Customer Relationship
· Facilitates New Client Data Retrieval
· Provides Real-time Project Access
Are you looking for top mobile app development companies in New York that help to create a custom mobile app as per your business requirements? Please go through these Top 5 mobile app development companies that provide exceptional development and design services for your business.
Top Mobile App Development Companies in New York:
1. AppCluesInfotech
AppClues Infotech is one of the leading mobile app development company based in New York that builds high-quality mobile apps. Being a versatile mobile app development company, they provide services on various platforms like Android, iOS, Cross-platform, Windows, etc. They are aware of the latest technologies and features of industry. They utilize them to create a user-engaging mobile app. They have the best team of designers and developers who are delivered a mobile app with high-quality and performance.
Founded In: 2014
Employees: 50 to 200 Members
Location: USA
Website: https://www.appcluesinfotech.com/
2. Data EximIT
Data EximIT is one of the leading mobile app development company in New York that provides top-notch and elegant mobile app development services with the latest market trends and functionalities at a competitive price. They have highly experienced mobile app designers and developers team who have the best strength of developing all types of a mobile app. They deliver a feature-rich mobile app for their clients that give the best business ROI.
Founded In: 2004
Employees: 50 to 150 Members
Location: USA & India
Website: https://www.dataeximit.com/
3. WebClues Infotech
WebClues Infotech is the most reliable & superior company that builds custom mobile apps to do things differently. They are the best mobile app development company in New York, USA and as well as globally with high proficiency. They have a highly experienced app developers team that has the best strength of work on multiple platforms like android, Cross-platform, and iOS.
They have successfully delivered 950+ mobile app projects effectively and on-time. Build your Robust, Secure, Scalable & High-performance mobile app with WebClues Infotech with creative & dynamic designs at an affordable price.
Founded In: 2014
Employees: 50 to 250 Members
Location: USA, INDIA, UAE, UK & CANADA
Website: https://www.webcluesinfotech.com/
4. AppClues Studio
AppClues Studio is a leading mobile app development company in New York, USA. The company is versatile in developing custom mobile app development solutions to its customers across the globe. With an experience of 8+ years in mobile app development, Utility is hyper-focused on Return on Investment (ROI) and building good relationships with partner companies. The company is worked with a start-up to large enterprises.
Founded In: 2014
Employees: 50 to 150 Members
Location: USA & UK
Website: https://appcluesstudio.com/
5. WebClues Global
WebClues Global is a prominent mobile application development company in New York, USA. They are one of the top-tier mobile app developers who deliver high-end Android mobile app solutions to their clients. The company operated with 100+ qualified developers who working in different domains to give the best solution for their development. WebClues Global offers various services including web and mobile design & development, E-Commerce Development, Ui/Ux Development.
Founded In: 2014
Employees: 50 to 150 Members
Location: USA, INDIA, UAE, UK & CANADA
Website: https://www.webcluesglobal.com/
#top 5 mobile app development companies in new york #top 5 mobile app development companies in usa #top mobile app development companies in new york #top mobile app development companies in usa #top 5 mobile app development companies
1663588980
Top 5 Golang Libraries for Regular Expressions
In today's post we will learn about Top 5 Golang Libraries for Regular Expressions.
What is a Regular Expression?
Regular expressions are specially encoded text strings used as patterns for matching sets of strings. They began to emerge in the 1940s as a way to describe regular languages, but they really began to show up in the programming world during the 1970s. The first place I could find them showing up was in the QED text editor written by Ken Thompson.
“A regular expression is a pattern which specifies a set of strings of characters; it is said to match certain strings.” —Ken Thompson
Regular expressions later became an important part of the tool suite that emerged from the Unix operating system—the ed, sed and vi (vim) editors, grep, AWK, among others. But the ways in which regular expressions were implemented were not always so regular.
Table of contents:
- Genex - Count and expand Regular Expressions into all matching Strings.
- Go-wildcard - Simple and lightweight wildcard pattern matching.
- Goregen - Library for generating random strings from regular expressions.
- Regroup - Match regex expression named groups into go struct using struct tags and automatic parsing.
- Rex - Regular expressions builder.
1 - Genex:
Count and expand Regular Expressions into all matching Strings.
Easy and efficient package to expand any given regex into all the possible strings that it can match.
This is the code that powers namegrep.
Usage
package main
import (
"fmt"
"regexp/syntax"
"github.com/alixaxel/genex"
)
func main() {
charset, _ := syntax.Parse(`[0-9a-z]`, syntax.Perl)
if input, err := syntax.Parse(`(foo|bar|baz){1,2}\d`, syntax.Perl); err == nil {
fmt.Println("Count:", genex.Count(input, charset, 3))
genex.Generate(input, charset, 3, func(output string) {
fmt.Println("[*]", output)
})
}
}Output
Count: 120
[*] foo0
[*] ...
[*] foo9
[*] foofoo0
[*] ...
[*] foofoo9
[*] foobar0
[*] ...
[*] foobar9
[*] foobaz0
[*] ...
[*] foobaz9
[*] bar0
[*] ...
[*] bar9
[*] barfoo0
[*] ...
[*] barfoo9
[*] barbar0
[*] ...
[*] barbar9
[*] barbaz0
[*] ...
[*] barbaz9
[*] baz0
[*] ...
[*] baz9
[*] bazfoo0
[*] ...
[*] bazfoo9
[*] bazbar0
[*] ...
[*] bazbar9
[*] bazbaz0
[*] ...
[*] bazbaz9
Install
go get github.com/alixaxel/genex2 - Go-wildcard:
Simple and lightweight wildcard pattern matching.
Why
This part of Minio project, a very cool, fast and light wildcard pattern matching.
Originally the purpose of this fork is to give access to this "lib" under Apache license, without importing the entire Minio project ...
Two function are available MatchSimple and Match
MatchSimpleonly covert*usage (which is faster thanMatch)Matchsupport full wildcard matching,*and?
I know Regex, but they are much more complex, and slower (even prepared regex) ...
I know Glob, but most of the time, I only need simple wildcard matching.
How to
⚠️ WARNING: Unlike the GNU "libc", this library have no equivalent to "FNM_FILE_NAME". To do this you can use "path/filepath" https://pkg.go.dev/path/filepath#Glob
Using this fork
go get github.com/IGLOU-EU/go-wildcard@latestUsing Official Minio (GNU Affero General Public License 3.0 or later)
From https://github.com/minio/minio/commit/81d5688d5684bd4d93e7bb691af8cf555a20c28c the minio pkg are moved to https://github.com/minio/pkg
go get github.com/minio/pkg/wildcard@latestQuick Example
This example shows a Go file with pattern matching ...
package main
import (
"fmt"
wildcard "github.com/IGLOU-EU/go-wildcard"
)
func main() {
str := "daaadabadmanda"
pattern := "da*da*da*"
result := wildcard.MatchSimple(pattern, str)
fmt.Println(str, pattern, result)
pattern = "?a*da*d?*"
result = wildcard.Match(pattern, str)
fmt.Println(str, pattern, result)
}3 - Goregen:
Library for generating random strings from regular expressions.
Package regen is a library for generating random strings from regular expressions. The generated strings will match the expressions they were generated from. Similar to Ruby's randexp library.
E.g.
regen.Generate("[a-z0-9]{1,64}")
will return a lowercase alphanumeric string between 1 and 64 characters long.
Expressions are parsed using the Go standard library's parser: http://golang.org/pkg/regexp/syntax/.
Constraints
"." will generate any character, not necessarily a printable one.
"x{0,}", "x*", and "x+" will generate a random number of x's up to an arbitrary limit. If you care about the maximum number, specify it explicitly in the expression, e.g. "x{0,256}".
Flags ¶
Flags can be passed to the parser by setting them in the GeneratorArgs struct. Newline flags are respected, and newlines won't be generated unless the appropriate flags for matching them are set.
E.g. Generate(".|[^a]") will never generate newlines. To generate newlines, create a generator and pass the flag syntax.MatchNL.
The Perl character class flag is supported, and required if the pattern contains them.
Unicode groups are not supported at this time. Support may be added in the future.
Concurrent Use
A generator can safely be used from multiple goroutines without locking.
A large bottleneck with running generators concurrently is actually the entropy source. Sources returned from rand.NewSource() are slow to seed, and not safe for concurrent use. Instead, the source passed in GeneratorArgs is used to seed an XorShift64 source (algorithm from the paper at http://vigna.di.unimi.it/ftp/papers/xorshift.pdf). This source only uses a single variable internally, and is much faster to seed than the default source. One source is created per call to NewGenerator. If no source is passed in, the default source is used to seed.
The source is not locked and does not use atomic operations, so there is a chance that multiple goroutines using the same source may get the same output. While obviously not cryptographically secure, I think the simplicity and performance benefit outweighs the risk of collisions. If you really care about preventing this, the solution is simple: don't call a single Generator from multiple goroutines.
Benchmarks
Benchmarks are included for creating and running generators for limited-length, complex regexes, and simple, highly-repetitive regexes.
go test -bench .
The complex benchmarks generate fake HTTP messages with the following regex:
POST (/[-a-zA-Z0-9_.]{3,12}){3,6}
Content-Length: [0-9]{2,3}
X-Auth-Token: [a-zA-Z0-9+/]{64}
([A-Za-z0-9+/]{64}
){3,15}[A-Za-z0-9+/]{60}([A-Za-z0-9+/]{2}==|[A-Za-z0-9+/]{3}=)
The repetitive benchmarks use the regex
a{999}
See regen_benchmarks_test.go for more information.
On my mid-2014 MacBook Pro (2.6GHz Intel Core i5, 8GB 1600MHz DDR3), the results of running the benchmarks with minimal load are:
BenchmarkComplexCreation-4 200 8322160 ns/op
BenchmarkComplexGeneration-4 10000 153625 ns/op
BenchmarkLargeRepeatCreateSerial-4 3000 411772 ns/op
BenchmarkLargeRepeatGenerateSerial-4 5000 291416 ns/op4 - Regroup:
Match regex expression named groups into go struct using struct tags and automatic parsing.
Simple library to match regex expression named groups into go struct using struct tags and automatic parsing
Installing
go get github.com/oriser/regroup
Example
Named groups map
package main
import (
"fmt"
"github.com/oriser/regroup"
)
var re = regroup.MustCompile(`(?P<duration>.*?)\s+(?P<num>\d+)\s+(?P<foo>.*)`)
func main() {
matches, err := re.Groups("5s 123 bar")
if err != nil {
panic(err)
}
fmt.Printf("%+v\n", matches)
}Will output: map[duration:5s foo:bar num:123]
Single match
package main
import (
"fmt"
"github.com/oriser/regroup"
"time"
)
var re = regroup.MustCompile(`(?P<duration>.*?)\s+(?P<num>\d+)\s+(?P<foo>.*)`)
type B struct {
Str string `regroup:"foo"`
}
type A struct {
Number int `regroup:"num"`
Dur time.Duration `regroup:"duration"`
AnotherStruct B
}
func main() {
a := &A{}
if err := re.MatchToTarget("5s 123 bar", a); err != nil {
panic(err)
}
fmt.Printf("%+v\n", a)
}Will output: &{Number:123 Dur:5s AnotherStruct:{Str:bar}}
5 - Rex:
Regular expressions builder.
Why?
It makes readability better and helps to construct regular expressions using human-friendly constructions. Also, it allows commenting and reusing blocks, which improves the quality of code. It provides a convenient way to use parameterized patterns. It is easy to implement custom patterns or use a combination of others.
It is just a builder, so it returns standart *regexp.Regexp.
The library supports groups, composits, classes, flags, repetitions and if you want you can even use raw regular expressions in any place. Also it contains a set of predefined helpers with patterns for number ranges, phones, emails, etc...
Let's see an example of validating or matching someid[#] using a verbose pattern:
re := rex.New(
rex.Chars.Begin(), // `^`
// ID should begin with lowercased character.
rex.Chars.Lower().Repeat().OneOrMore(), // `[a-z]+`
// ID should contain number inside brackets [#].
rex.Group.NonCaptured( // (?:)
rex.Chars.Single('['), // `[`
rex.Chars.Digits().Repeat().OneOrMore(), // `[0-9]+`
rex.Chars.Single(']'), // `]`
),
rex.Chars.End(), // `$`
).MustCompile()Yes, it requires more code, but it has its advantages.
More, but simpler code, fewer bugs.
You can still use original regular expressions as is in any place. Example of matching numbers between -111.99 and 1111.99 using a combination of patterns and raw regular expression:
re := rex.New(
rex.Common.Raw(`^`),
rex.Helper.NumberRange(-111, 1111),
rex.Common.RawVerbose(`
# RawVerbose is a synonym to Raw,
# but ignores comments, spaces and new lines.
\. # Decimal delimter.
[0-9]{2} # Only two digits.
$ # The end.
`),
).MustCompile()
// Produces:
// ^((?:\x2D(?:0|(?:[1-9])|(?:[1-9][0-9])|(?:10[0-9])|(?:11[0-1])))|(?:0|(?:[1-9])|(?:[1-9][0-9])|(?:[1-9][0-9][0-9])|(?:10[0-9][0-9])|(?:110[0-9])|(?:111[0-1])))\.[0-9]{2}$The style you prefer is up to you
Thank you for following this article.
Related videos:
Regular Expression Basics for Go Programmers
1603438098
Top 10 Trending Technologies Must Learn in 2021 | igmGuru
Technology has taken a place of more productiveness and give the best to the world. In the current situation, everything is done through the technical process, you don’t have to bother about doing task, everything will be done automatically.This is an article which has some important technologies which are new in the market are explained according to the career preferences. So let’s have a look into the top trending technologies followed in 2021 and its impression in the coming future in the world.
-
Data Science
First in the list of newest technologies is surprisingly Data Science. Data Science is the automation that helps to be reasonable for complicated data. The data is produces in a very large amount every day by several companies which comprise sales data, customer profile information, server data, business data, and financial structures. Almost all of the data which is in the form of big data is very indeterminate. The character of a data scientist is to convert the indeterminate datasets into determinate datasets. Then these structured data will examine to recognize trends and patterns. These trends and patterns are beneficial to understand the company’s business performance, customer retention, and how they can be enhanced. -
DevOps
Next one is DevOps, This technology is a mixture of two different things and they are development (Dev) and operations (Ops). This process and technology provide value to their customers in a continuous manner. This technology plays an important role in different aspects and they can be- IT operations, development, security, quality, and engineering to synchronize and cooperate to develop the best and more definitive products. By embracing a culture of DevOps with creative tools and techniques, because through that company will gain the capacity to preferable comeback to consumer requirement, expand the confidence in the request they construct, and accomplish business goals faster. This makes DevOps come into the top 10 trending technologies. -
Machine learning
Next one is Machine learning which is constantly established in all the categories of companies or industries, generating a high command for skilled professionals. The machine learning retailing business is looking forward to enlarging to $8.81 billion by 2022. Machine learning practices is basically use for data mining, data analytics, and pattern recognition. In today’s scenario, Machine learning has its own reputed place in the industry. This makes machine learning come into the top 10 trending technologies. Get the best machine learning course and make yourself future-ready.
To want to know more click on Top 10 Trending Technologies in 2021
You may also read more blogs mentioned below
How to Become a Salesforce Developer
The Scope of Hadoop and Big Data in 2021
#top trending technologies #top 10 trending technologies #top 10 trending technologies in 2021 #top trending technologies in 2021 #top 5 trending technologies in 2021 #top 5 trending technologies
1623050167
Mad Libs: Using regular expressions
From Tiny Python Projects by Ken Youens-Clark
Everyone loves Mad Libs! And everyone loves Python. This article shows you how to have fun with both and learn some programming skills along the way.
Take 40% off Tiny Python Projects by entering fccclark into the discount code box at checkout at manning.com.
When I was a wee lad, we used to play at Mad Libs for hours and hours. This was before computers, mind you, before televisions or radio or even paper! No, scratch that, we had paper. Anyway, the point is we only had Mad Libs to play, and we loved it! And now you must play!
We’ll write a program called mad.py which reads a file given as a positional argument and finds all the placeholders noted in angle brackets like <verb> or <adjective> . For each placeholder, we’ll prompt the user for the part of speech being requested like “Give me a verb” and “Give me an adjective.” (Notice that you’ll need to use the correct article.) Each value from the user replaces the placeholder in the text, and if the user says “drive” for “verb,” then <verb> in the text replaces with drive . When all the placeholders have been replaced with inputs from the user, print out the new text.
#python #regular-expressions #python-programming #python3 #mad libs: using regular expressions #using regular expressions
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Top 5 UI/UX Designing Companies in USA
UI & UX designs are two of the common usually confused and conflated terms in a website and mobile app design.
Why Important UI/UX Design?
The UX/UI Design of the mobile app improves the user experience & customer satisfaction that ultimately helps improve the number of users of the specific application. The UI & UX Design helps to win the consumers’ confidence and make them use your application or website providing them what they are looking for.
The USA is the most extensive market of UI/UX Design. Have a look at the top 5 companies in the USA for UI/UX design.
1. AppClues Infotech
AppClues Infotech is one of the leading UI/UX design company in the USA that offers the best creative designing service. Their dedicated & creative designer uses powerful tools and elements that will help you to redesign your old stuff like Pro. As one of the top app design and development company in the US, they blend their knowledge and skill to deliver top-notch app design and development services.
2. WebClues Infotech
WebClues Infotech is a full-service UI/UX design and development company in the USA. The team of WebClues Infotech is most experienced in dynamic & creative designs. Their creative app design help in engaging customers in an effective way leading to higher ROI and exponential growth of your business.
3. AppClues Studio
AppClues Studio is the best UI/UX designing company with a highly experienced and creative design team. Their highly skilled designer creates a beautiful and interactive design that converts your visitor into repetitive customers by serving an enhanced user experience like never before.
4. WebClues Global
WebClues Global is a team of innovators, creators, and makers. They are masters of their fields who give visually interactive UI/UX designs with precise layout by using different technologies. They create beautiful experiences that transform the world around them by using design & technology.
5. Data Exim IT
Data Exim IT is an excellent company offering the best UI/UX Designing service. They have their strong in-house professional team who are experts in the field of UI/UX. They create simple, clean, and attractive mobile app designs for businesses.
Get in touch with above mentioned top UI/UX designing companies to make dynamic, creative and user-engaging mobile app designs.
Source Link - https://www.quora.com/Top-5-UI-UX-designing-Companies-in-The-USA/answer/Joseph-Petron-2?prompt_topic_bio=1
#top 5 ui/ux design agencies #top ux designers in the united states #top 5 best ux/ui design companies #mobile app development companies in usa #ui/ux designing companies in usa #top mobile app design companies in usa