Developer Tools
Color converters, timestamp tools, and file size calculators for development workflows.
You're debugging a CSS color mismatch: the design mockup shows '#FF6B6B' in hex, but your backend API returns RGB values. Your application logs show timestamps as Unix epoch (1716000000), but you need to know the actual date and time. You're calculating API response times and storage requirements in bytes, but thinking in megabytes. You need tools to translate between these developer-specific formats instantly.
View full converter + formula + examples →1 Megabyte = 0.001 Gigabyte
Context
Software development works in specialized units and formats that don't map to real-world measurements. Color is represented in hexadecimal (#FF6B6B), RGB (255, 107, 107), or HSL (0°, 100%, 71%)—each useful for different contexts but requiring conversion between formats. Time is stored as Unix timestamps (seconds since January 1, 1970) for efficiency but is unreadable without conversion to human dates. File sizes in APIs are in bytes, but developers think in kilobytes, megabytes, or gigabytes.
These conversions aren't optional—they're constant friction in development. A color format mismatch breaks designs. A timestamp misunderstanding causes time-zone bugs. Storage miscalculations lead to database errors or SLA violations. Modern development stacks mix formats constantly: frontends work in hex and RGB, databases store timestamps as Unix epochs, APIs return file sizes in bytes. Having quick, accurate converters for these developer-specific units reduces debugging time and prevents format-related bugs from reaching production.
All Developer Tools Conversions
Why this matters
Converting between color formats in design and code
A designer hands you a hex color (#FF6B6B), but your CSS-in-JS library expects RGB (255, 107, 107). You need to convert quickly without opening Photoshop.
Decoding timestamps in application logs
Your server logs show 'timestamp: 1715884800'. You need to convert that Unix epoch to a human-readable date to correlate with user reports.
Calculating storage and bandwidth for API responses
An API endpoint returns 2.5 MB of JSON per request. You need to calculate how much disk space 100,000 requests would consume, and how long it takes to download on a 10 Mbps connection.
Debugging browser color rendering
An HSL color works in the browser, but when rendered to PNG, it looks wrong. You convert to RGB to verify the actual color values match your intent.
Frequently asked
My design mockup has a hex color #FF6B6B, but my API returns RGB values. How do I convert? →
Use [Hex to RGB Color Converter](/developer-tools/hex-to-rgb/) to instantly convert between formats. Hex #FF6B6B is RGB(255, 107, 107). Remember: hex is pairs of digits (red, green, blue), each 00–FF (0–255 in decimal).
My application logs show timestamp 1716000000. What date and time is that? →
Use [Unix Timestamp Converter](/developer-tools/unix-timestamp/) to decode the epoch. Timestamp 1716000000 is May 17, 2024 at 8:00 PM UTC. Always check your server's timezone—the same epoch represents different local times in different zones.
An API returns a file size of 2,621,440 bytes. How many megabytes is that? →
2,621,440 bytes is exactly 2.5 MB (or 2.5 MiB technically). Use [Bytes to Megabytes](/data/bytes-to-megabytes/) for quick conversions. For storage and bandwidth calculations, remember: 1 KB = 1,024 bytes, 1 MB = 1,024 KB, 1 GB = 1,024 MB.
I need an HSL color that looks like the RGB (100, 150, 200) in my design. How do I convert? →
Use [Hex to RGB/HSL Color Converter](/developer-tools/hex-to-rgb/) to convert RGB to HSL. RGB(100, 150, 200) is approximately HSL(210°, 50%, 59%). HSL is useful for CSS and understanding hue/saturation/lightness independently.
My download is 45 MB over a 5 Mbps connection. How long does it take? →
45 MB is 360 megabits. At 5 Mbps, that takes about 72 seconds (1.2 minutes). Use [Megabytes to Megabits](/data/megabytes-to-megabits/) to convert, then divide data by speed. Real-world downloads are slower due to overhead.
My database stores 1 trillion records, each 512 bytes. How much total storage? →
1 trillion × 512 bytes = 512 terabytes. Use [Bytes to Terabytes](/data/bytes-to-terabytes/) for the conversion. This highlights why efficient data structures matter—even small per-record savings multiply across large datasets.