This is an extension for VS Code to improve the search functionality by adding advanced filtering options: project files, text, functions, variables, docs, configs, and comments.
It’s a work in progress, so any feedback and suggestion is welcome!
53 karma · joined April 4, 2024
https://github.com/stefanicjuraj
This is an extension for VS Code to improve the search functionality by adding advanced filtering options: project files, text, functions, variables, docs, configs, and comments.
It’s a work in progress, so any feedback and suggestion is welcome!
As for crowd-sourcing the glossary, that is also planned. I just need to structure the existing entries first, and it's good to go! It will be published as part of the GitHub repository.
I regularly share projects and ideas with family, friends, colleagues, and online communities. Many of them live in different time zones, and I want to ensure my posts reach them to get a timely feedback; not hours before/after they’ve already checked their feeds.
Although I like to practice the "just publish it" initiative, without too much second-guessing, I wanted a more reliable data-driven approach.
Now, instead of guessing, I can check the app and know when to post for better visibility, and so can you.
Average Trend – This is calculated by taking the percentage change between consecutive months and averaging these values. It gives a general sense of how skill mentions increasing or decreasing over time.
Median Trend – The percentage changes between months are sorted, and the median value is taken. This reduces the impact of extreme fluctuations and provides a more stable measure of growth.
CAGR (Compound Annual Growth Rate) Trend – This is calculated by comparing the first and last month's skill mentions count, then applying the CAGR formula to estimate a steady growth rate over the observed period. This measures long-term trends rather than month-to-month volatility.
If there are fewer than three months of data, trends are marked as "N/A" due to insufficient data for meaningful analysis.
I’ll definitely add more context and details to improve clarity in the project. I agree that 1500+ job ads are a starting point rather than a definitive trend analysis. That’s why I plan to continue collecting and analyzing job postings over time to get a more representative dataset.
To answer your questions — the job ads were primarily sourced using search queries tailored to each category. For example, the "Frontend" category included searches for "Frontend Developer" / "Frontend Engineer" / "Frontend Web Developer". Similar criteria was used for other categories too.
The dataset covers multiple countries but is predominantly focused on regions: North America and EU.
After recently graduating from college, I set myself a personal project to develop a simple tool for analyzing job advertisements and extracting the most in-demand skills, technologies, and tools for various IT positions.
By automatically scanning and processing data from more than 1500 job ads, the project identifies key skills and technologies that employers and recruiters are looking for.
You can browse various IT positions to explore the skills needed for each, including Frontend, Backend, DevOps, AI/ML, Data (Engineering/Science), Full Stack, UX/UI, Technical Writing, Quality Assurance, iOS/Android, Management, and Cybersecurity.
The project was already announced via Reddit, receiving over 150,000+ views on the launch post!