enry is an open-source Go command-line tool for identifying programming languages in files and directories. Unlike GitHub Linguist, its CLI can analyze files without a Git repository. It can print per-file results or JSON, and its language detection is based on data from GitHub Linguist with documented differences.
What enry does
enry identifies languages in source files using a combination of filename, extension, shebang, editor modeline, file content and Bayesian-classifier checks. Its command-line tool is built on the go-enry/go-enry library. Because the CLI does not require a Git repository, it can analyze a directory of files even when that directory has no Git metadata.
The project describes enry as offering twice the performance of its Linguist predecessor. That is the project’s own claim; the README does not provide a benchmark date or testing details to independently assess it.
How to install enry
The official enry CLI README recommends downloading a release or installing with Go. Its documented Go command is:
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(cd "$(mktemp -d)" && go mod download && go get github.com/go-enry/enry)This command requires Go to be installed and available in your shell. It runs in a temporary directory, so it does not add the project to your current working directory. For release downloads and any changes to installation guidance, use the CLI repository’s README.
Run enry on files or directories
Run enry followed by the file or directory paths you want to analyze. The CLI does not require those paths to be inside a Git repository. By default, its report covers Markdown and Programming language groups.
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Use these options to change the report:
--breakdownincludes per-file detail.--jsonproduces machine-readable JSON output.-allbroadens reporting to all language groups, including plain text, markup, templates, configuration scripts and others.-proglimits results to programming languages, which is useful when another tool will lex or parse the detected files.
The README notes that the final report excludes well-known vendoring, configuration and documentation paths, as well as dot-prefixed paths. This means the reported language mix may not include every file present in the directory.
How enry identifies a language
Detection uses progressively narrower matching strategies, drawing on whichever information is available for a file:
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- Filename and extension: Recognizes language cues in the path and file suffix.
- Shebang and modeline: Checks the first-line interpreter declaration and Vim or Emacs modelines when present.
- File content: Uses content-based rules to narrow possible matches.
- Bayesian classification: Applies a classifier as a later signal when earlier checks do not settle the result.
The library also exposes Go functions including GetLanguageByExtension and GetLanguageByContent, alongside combined detection calls. For programming languages such as Python and Java, enry has documented support through language bindings as well as its Go-based CLI; the Python binding requires Python 3.9 or newer.
enry and GitHub Linguist: what differs
enry is related to GitHub Linguist, but it is not a drop-in match for every Linguist behavior. The current library says its generated language data is based on GitHub Linguist v9.5.0 and documents compatibility gaps. GitHub Linguist is used in GitHub’s repository language reporting, while enry offers a standalone CLI and library that can be applied outside that context.
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| Area | enry | GitHub Linguist |
|---|---|---|
| Git repository required | No; the CLI can analyze files without an actual Git repository. | The enry README identifies this as an intentional difference from Linguist. |
| Installation and use | Standalone CLI releases and Go installation are documented; library bindings are also available. | Not stated in the cited enry documentation. |
| Output and filters | CLI supports per-file breakdown, JSON, all language groups and programming-language-only reporting. | Not stated in the cited enry documentation. |
| Detection methods | Uses filename, extension, shebang, modeline, content and Bayesian classification. | enry’s detector derives from Linguist, but this comparison does not establish that every implementation detail is identical. |
| Ignored, vendored and submodule files | Excludes documented vendoring, configuration and documentation paths and dot-prefixed paths; does not exclude .gitignored files and Git submodules in the same way as Linguist. | enry documents the difference, but the cited source does not enumerate Linguist’s full rules. |
| Regex compatibility | Some Linguist heuristics use regex constructs unsupported by RE2, creating documented differences for examples including Vim Help, Solidity, RUNOFF, NASL, ActionScript and GSC. | The source documents those as gaps in enry’s compatibility. |
| .gitattributes overrides | Language and type overrides from .gitattributes are not supported. | The source documents this as a difference; it does not detail the corresponding Linguist behavior. |
| Language bindings | Documented bindings include Python 3.9+, Java through a shared library/JNI package, and Rust generated bindings. | Not stated in the cited enry documentation. |
The Bayesian classifier also cannot reliably distinguish SQL from PLpgSQL. Treat ambiguous results as a useful automated classification rather than an authoritative resolution in cases where the distinction matters.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which enry repository should you use?
Use the current go-enry/enry CLI repository for command-line installation and usage. The former src-d/enry repository is archived and directs development to go-enry/go-enry. Notes about historical gaps in that archived code line—including generated-file and XML detection—should not be assumed to describe the current release.
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enry is open source under the Apache License, Version 2.0. See the license notices in the CLI repository and the library repository.
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