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complete login system php mysql. Here, i will show you how to build complete login system in php mysql using session.
And as well as how to create login page, user profile page in php with database and validation.
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simple search code in php with demo. Here, i will show you how to create live search in PHP MySQL using jQuery ajax from database.
Use the following simple steps and create ajax live search PHP MySQL from database:
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Despite the Covid-19 threat to the world and economy of every country, Online Grocery Market has recorded a 3X increase since 2019 till now.
“About 1-4th online shoppers are already shopping groceries on the internet in developed countries and 55% are willing to in near future. – Nielson study”
The new store these days are digital stores, Web stores, and Mobile applications where 70% of the customers reach and buy every day.
Take your store where the customers are to generate more revenue by developing e-commerce grocery store/application and Supermarket online store and mobile application.
Online grocery shopping sales in the United States from 2018 to 2023(in billion U.S. dollars)
“As per Statista, The U.S. online grocery market was estimated to generate sales worth about 28.68 billion U.S. dollars in 2019, with sales forecast to reach 59.5 billion U.S. dollars by 2023.”
Online store and mobile applications are helping small grocery business owners reach 70% more customers and generate unbelievable but real 48% more revenue other than the existing one. Check out a few of the businesses listed below:
Want to start an online grocery store? – Here’s what you should know
If you dream of owning your own online store regardless are you setting up a small business for the first time or you’ve been in the game a long time, this guide will help you learn how to start an online store.
Online selling, better known as e-commerce, has truly hit its pace. Fortunately, getting started is easier than you might think provided you have basic information about the business (which we will cover here) and you have a team of ecommerce website store solution experts to get the things implemented.
Accenture estimates, by the end of 2020, the ecommerce industry will get 13.5% of the revenue share. What does it mean for online store owners? It means that out of every 7 dollars spent on retail consumption: eCommerce will get about 1 dollar.
This article was originally published - How to start an online grocery store?
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Are you an Arctic Code Vault Contributor or have seen someone posting about it and don’t know what it is. So let’s take a look at what is an Arctic Code Vault Contributor and who are the ones who gets this batch.
GitHub, the world’s largest open-source platform for software and programs has safely locked the data of huge value and magnitude in a coal mine in Longyearbyen’s Norwegian town in the Arctic region.
Back in November 2019, GitHub Arctic Code Vault was first announced.
The GitHub Arctic Code Vault is a data repository preserved in the Arctic
World Archive (AWA), a very-long-term archival facility 250 meters deep in the permafrost of an Arctic mountain. The archive is located in a decommissioned coal mine in the Svalbard archipelago, closer to the North Pole than the Arctic Circle.
Last year, GitHub said that it plans to capture a snapshot of every active
public repository on 02/02/2020 and preserve that data in the Arctic
The project began on February 2, when the firm took a snapshot of all of
GitHub’s active public repositories to store them in the vault. They initially intended to travel to Norway and personally escort the world’s open-source technology to the Arctic but their plans were derailed by the global pandemic. Then, they had to wait until 8 Julyfor the Arctic Data Vault data to be deposited.
GitHub announced that the code was successfully deposited in the Arctic Code Vault on July 8, 2020. Over the past several months, GitHub worked
with its archive partners Piql to write the 21TB of GitHub repository data to 186 reels of piqlFilm (digital photosensitive archival film).
GitHub’s strategic software director, Julia Metcalf, has written a blog post
on the company’s website notifying the completion of GitHub’s Archive Program on July 8th. Discussing the objective of the Archive Program, Metcalf wrote “Our mission is to preserve open-source software for future generations by storing your code in an archive built to last a thousand years.”
The Arctic Code Vault is only a small part of the wider GitHub Archive
Program, however, which sees the company partner with the Long Now
Foundation, Internet Archive, Software Heritage Foundation, Microsoft
Research and others.
Svalbard has been regulated by the international Svalbard Treaty as a demilitarized zone. Home to the world’s northernmost town, it is one of the most remote and geopolitically stable human habitations on Earth.
The AWA is a joint initiative between Norwegian state-owned mining company Store Norske Spitsbergen Kulkompani (SNSK) and very-long-term digital preservation provider Piql AS. AWA is devoted to archival storage in perpetuity. The film reels will be stored in a steel-walled container inside a sealed chamber within a decommissioned coal mine on the remote archipelago of Svalbard. The AWA already preserves historical and cultural data from Italy, Brazil, Norway, the Vatican, and many others.
The 02/02/2020 snapshot archived in the GitHub Arctic Code Vault will
sweep up every active public GitHub repository, in addition to significant dormant repos.
The snapshot will include every repo with any commits between the announcement at GitHub Universe on November 13th and 02/02/2020,
every repo with at least 1 star and any commits from the year before the snapshot (02/03/2019 – 02/02/2020), and every repo with at least 250 stars.
The snapshot will consist of the HEAD of the default branch of each repository, minus any binaries larger than 100KB in size—depending on available space, repos with more stars may retain binaries. Each repository will be packaged as a single TAR file. For greater data density and integrity, most of the data will be stored QR-encoded and compressed. A human-readable index and guide will itemize the location of each repository and explain how to recover the data.
The company further shared that every reel of the archive includes a copy
of the “Guide to the GitHub Code Vault” in five languages, written with input from GitHub’s community and available at the Archive Program’s own GitHub repository.
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Static code analysis refers to the technique of approximating the runtime behavior of a program. In other words, it is the process of predicting the output of a program without actually executing it.
Lately, however, the term “Static Code Analysis” is more commonly used to refer to one of the applications of this technique rather than the technique itself — program comprehension — understanding the program and detecting issues in it (anything from syntax errors to type mismatches, performance hogs likely bugs, security loopholes, etc.). This is the usage we’d be referring to throughout this post.
“The refinement of techniques for the prompt discovery of error serves as well as any other as a hallmark of what we mean by science.”
We cover a lot of ground in this post. The aim is to build an understanding of static code analysis and to equip you with the basic theory, and the right tools so that you can write analyzers on your own.
We start our journey with laying down the essential parts of the pipeline which a compiler follows to understand what a piece of code does. We learn where to tap points in this pipeline to plug in our analyzers and extract meaningful information. In the latter half, we get our feet wet, and write four such static analyzers, completely from scratch, in Python.
Note that although the ideas here are discussed in light of Python, static code analyzers across all programming languages are carved out along similar lines. We chose Python because of the availability of an easy to use
ast module, and wide adoption of the language itself.
Before a computer can finally “understand” and execute a piece of code, it goes through a series of complicated transformations:
As you can see in the diagram (go ahead, zoom it!), the static analyzers feed on the output of these stages. To be able to better understand the static analysis techniques, let’s look at each of these steps in some more detail:
The first thing that a compiler does when trying to understand a piece of code is to break it down into smaller chunks, also known as tokens. Tokens are akin to what words are in a language.
A token might consist of either a single character, like
(, or literals (like integers, strings, e.g.,
Bob, etc.), or reserved keywords of that language (e.g,
def in Python). Characters which do not contribute towards the semantics of a program, like trailing whitespace, comments, etc. are often discarded by the scanner.
Python provides the
tokenize module in its standard library to let you play around with tokens:
code = b"color = input('Enter your favourite color: ')"
for token in tokenize.tokenize(io.BytesIO(code).readline):
TokenInfo(type=62 (ENCODING), string='utf-8')
TokenInfo(type=1 (NAME), string='color')
TokenInfo(type=54 (OP), string='=')
TokenInfo(type=1 (NAME), string='input')
TokenInfo(type=54 (OP), string='(')
TokenInfo(type=3 (STRING), string="'Enter your favourite color: '")
TokenInfo(type=54 (OP), string=')')
TokenInfo(type=4 (NEWLINE), string='')
TokenInfo(type=0 (ENDMARKER), string='')
(Note that for the sake of readability, I’ve omitted a few columns from the result above — metadata like starting index, ending index, a copy of the line on which a token occurs, etc.)
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