fselect — Finds files using SQL-like queries, supporting advanced filtering by metadata, archives, and image/audio properties.
Analyzed by Sai Pavan Gopularam · Dev Tools · File Management · View on GitHub
- Stars: 4469
- Forks: 87
- Commits last 30 days: 11
- Health: Active (11 commits this month)
- Language: Rust
- License: Apache-2.0
What It Is
Imagine using a database query language, but instead of querying tables, you're querying your computer's file system. fselect lets you search for files using familiar SQL-like syntax, allowing for complex conditions, aggregations, and filtering based on various file attributes, even inside archives or by image/audio metadata.
This tool solves the problem of needing more powerful and flexible file search than standard `find` or `ls` commands offer. It's incredibly useful for developers, data scientists, or anyone who needs to manage large, complex file structures or extract specific types of files based on rich metadata.
License Verdict
Apache-2.0 License — Build and Sell Freely — Commercial Use Approved • Permissive License
The Apache-2.0 license is highly permissive. You can freely use, modify, and distribute this software for commercial purposes. You must include the original copyright and license notices in your derivative works, and state any significant changes made.
How to Use It
fselect is a command-line tool written in Rust. The easiest way to get started is by installing Rust and Cargo, then using `cargo install` to build and install fselect from source.
Prerequisites:
- Rust
- Cargo
Estimated setup time: 10 minutes.
cargo install fselect
fselect size, path from /home/user where name = '*.cfg'
fselect "MIN(size), MAX{size}, AVG(size) from /tmp"What I'd Build With This
Metadata-Driven File Organizer API (micro-saas)
Build an API wrapper around fselect, allowing developers to integrate advanced file search and organization into their applications. This API could power custom digital asset management systems or specialized file discovery services. Developers needing powerful, metadata-rich file indexing for user-uploaded content or internal tools would pay for this. Reach them via developer forums, API marketplaces, and tech blogs. Pricing could be tiered, based on API calls or indexed storage, starting at $29/month.
Effort: 2 Weeks Build Time · Target: Developers & Small Teams · Pricing: $29/month
Smart Digital Asset Management (DAM) Lite (saas)
Create a web-based tool for small creative teams to manage digital assets (images, audio, documents) with fselect's querying power. Users could find all images over 2000px wide, or all MP3s from a specific genre before 2000 for content audits. Small creative agencies, marketing teams, and individual content creators would pay for this. Reach them through content creation blogs, design communities, and social media. Offer a subscription model, per user or per GB of storage, starting at $49/month.
Effort: 1 Month Build Time · Target: Creative Agencies & Marketers · Pricing: $49/month
Automated Data Governance & Archiving Tool (enterprise)
Develop a system that uses fselect to identify, categorize, and manage large volumes of data across corporate networks. For example, automatically finding all PII in specific document types older than X years, or all uncompressed video files exceeding Y size for archiving purposes. Large enterprises with strict data retention policies or big data storage needs would be the target customers. Reach them via direct sales, IT conferences, and industry partnerships. Pricing would be custom, based on data volume, number of endpoints, and required features.
Effort: 3 Months Build Time · Target: Large Enterprises · Pricing: Custom Quote
Sai Pavan Gopularam's Take
This tool is like a supercharged `find` command, but with the power of SQL queries. I can see building a specialized file discovery API for developers, charging maybe $29/month for basic access, or a desktop app for power users with a one-time $49 fee.
Watch Out For
- SQL-like, Not SQL: The grammar is 'SQL-like' but 'highly relaxed,' meaning it's not full SQL. Users expecting advanced SQL features might find limitations.
- Performance on Large Datasets: While it supports index-backed search (plocate/Everything), direct file system scans on extremely large directories without these indexes might be slow.
- Archive Support Limitations: Currently, archive searching is limited to zip files. Users needing to search other archive formats (e.g., RAR, 7z, tar.gz) will find this feature incomplete.
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