1657018800
Astro is a website build tool for the modern web —
powerful developer experience meets lightweight output.
# Recommended!
npm create astro@latest
# Manual:
npm install --save-dev astro
Looking for help? Start with our Getting Started guide.
Looking for quick examples? Open a starter project right in your browser.
Visit our offical documentation.
Having trouble? Get help in the official Astro Discord.
New contributors welcome! Check out our Contributors Guide for help getting started.
Join us on Discord to meet other maintainers. We'll help you get your first contribution in no time!
Several official projects are maintained outside of this repo:
Astro is generously supported by Netlify, Vercel, and several other amazing organizations.
![]() |
Author: withastro
Source Code: https://github.com/withastro/astro
License: View license
#vite #Astro #typescript #javascript
1657018800
Astro is a website build tool for the modern web —
powerful developer experience meets lightweight output.
# Recommended!
npm create astro@latest
# Manual:
npm install --save-dev astro
Looking for help? Start with our Getting Started guide.
Looking for quick examples? Open a starter project right in your browser.
Visit our offical documentation.
Having trouble? Get help in the official Astro Discord.
New contributors welcome! Check out our Contributors Guide for help getting started.
Join us on Discord to meet other maintainers. We'll help you get your first contribution in no time!
Several official projects are maintained outside of this repo:
Astro is generously supported by Netlify, Vercel, and several other amazing organizations.
![]() |
Author: withastro
Source Code: https://github.com/withastro/astro
License: View license
#vite #Astro #typescript #javascript
1604008800
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., 7
, 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:
Python
1
import io
2
import tokenize
3
4
code = b"color = input('Enter your favourite color: ')"
5
6
for token in tokenize.tokenize(io.BytesIO(code).readline):
7
print(token)
Python
1
TokenInfo(type=62 (ENCODING), string='utf-8')
2
TokenInfo(type=1 (NAME), string='color')
3
TokenInfo(type=54 (OP), string='=')
4
TokenInfo(type=1 (NAME), string='input')
5
TokenInfo(type=54 (OP), string='(')
6
TokenInfo(type=3 (STRING), string="'Enter your favourite color: '")
7
TokenInfo(type=54 (OP), string=')')
8
TokenInfo(type=4 (NEWLINE), string='')
9
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.)
#code quality #code review #static analysis #static code analysis #code analysis #static analysis tools #code review tips #static code analyzer #static code analysis tool #static analyzer
1623192840
On this episode, we will discuss how you can verify that your site works and continues to work. We’re digging into automated testing and how to write tests for your Django apps.
Full show notes are available at https://www.mattlayman.com/django-riffs/13.
Full show notes are available at https://www.mattlayman.com/django-riffs/13.
#does my site work? #your site is #episode summary #episode notes #the site. #my site work
1605177550
#hugo #static #site #generator #markup #static site generator
1625918858
[https://wizzardreview.com/smartybuilderreview/]
Smarty Builder is the brand new software that creates you wildly profitable Ecom sites and floods them with free buyer traffic.
#smarty builder review #smarty builder #ecomtech #ecommercesites #ecom site builder