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CodeBLEU

PublishTestcodecovPyPI version

This repository contains an unofficial CodeBLEU implementation that supports Linux, MacOS (incl. M-series) and Windows. It is available through PyPI and the evaluate library.

Available for: Python, C, C#, C++, Java, JavaScript, PHP, Go, Ruby, Rust.


The code is based on the original CodeXGLUE/CodeBLEU and updated version by XLCoST/CodeBLEU. It has been refactored, tested, built for macOS and Windows, and multiple improvements have been made to enhance usability.

Metric Description

An ideal evaluation metric should consider the grammatical correctness and the logic correctness. We propose weighted n-gram match and syntactic AST match to measure grammatical correctness, and introduce semantic data-flow match to calculate logic correctness. CodeBLEU
[from CodeXGLUE repo]

In a nutshell, CodeBLEU is a weighted combination of n-gram match (BLEU), weighted n-gram match (BLEU-weighted), AST match and data-flow match scores.

The metric has shown higher correlation with human evaluation than BLEU and accuracy metrics.

Installation

This library requires so file compilation with tree-sitter, so it is platform dependent.
Currently available for Linux (manylinux), MacOS and Windows with Python 3.8+.

The metrics is available as pip package and can be installed as indicated above:

pip install codebleu

or directly from git repo (require internet connection to download tree-sitter):

pip install git+https://github.com/k4black/codebleu.git

Also you have to install tree-sitter language you need (e.g. python, rust, etc):

pip install tree-sitter-python

Or you can install all languages:

pip install codebleu[all]

Note: At the moment (May 2024) precompiled languages are NOT available for arm64 (M1) MacOS, so you have to install and build tree-sitter languages manually, for example:

pip install pip install git+https://github.com/tree-sitter/tree-sitter-python.git

Usage

fromcodebleuimportcalc_codebleuprediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=calc_codebleu([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25), tokenizer=None)
print(result)
# {# 'codebleu': 0.5537, # 'ngram_match_score': 0.1041, # 'weighted_ngram_match_score': 0.1109, # 'syntax_match_score': 1.0, # 'dataflow_match_score': 1.0# }

where calc_codebleu takes the following arguments:

  • refarences (list[str] or list[list[str]]): reference code
  • predictions (list[str]) predicted code
  • lang (str): code language, see codebleu.AVAILABLE_LANGS for available languages (python, c_sharp c, cpp, javascript, java, php, go and ruby at the moment)
  • weights (tuple[float,float,float,float]): weights of the ngram_match, weighted_ngram_match, syntax_match, and dataflow_match respectively, defaults to (0.25, 0.25, 0.25, 0.25)
  • tokenizer (callable): to split code string to tokens, defaults to s.split()

and outputs the dict[str, float] with following fields:

  • codebleu: the final CodeBLEU score
  • ngram_match_score: ngram_match score (BLEU)
  • weighted_ngram_match_score: weighted_ngram_match score (BLEU-weighted)
  • syntax_match_score: syntax_match score (AST match)
  • dataflow_match_score: dataflow_match score

Alternatively, you can use k4black/codebleu from HuggingFace Spaces (codebleu package required):

importevaluatemetric=evaluate.load("dvitel/codebleu")
prediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=metric.compute([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25))

Feel free to check the HF Space with online example: k4black/codebleu

Contributing

Contributions are welcome!
If you have any questions, suggestions, or bug reports, please open an issue on GitHub.

Make your own fork and clone it:

git clone https://github.com/k4black/codebleu

For development, you need to install library with all precompiled languages and test extra:
(require internet connection to download tree-sitter)

python -m pip install -e .[all,test]
python -m pip install -e .\[all,test\]# for macos

For testing just run pytest:

python -m pytest

To perform a style check, run:

python -m isort codebleu --check
python -m black codebleu --check
python -m ruff codebleu
python -m mypy codebleu

License

This project is licensed under the terms of the MIT license.

Citation

Official CodeBLEU paper can be cited as follows:

@misc{ren2020codebleu,
title={CodeBLEU: a Method for Automatic Evaluation of Code Synthesis}, author={Shuo Ren and Daya Guo and Shuai Lu and Long Zhou and Shujie Liu and Duyu Tang and Neel Sundaresan and Ming Zhou and Ambrosio Blanco and Shuai Ma},
year={2020},
eprint={2009.10297},
archivePrefix={arXiv},
primaryClass={cs.SE}
}

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Pip compatible CodeBLEU metric implementation available for linux/macos/win

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all
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(function() {
function addCopyButtons() {
document.querySelectorAll('pre code').forEach(function(codeBlock) {
if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;
codeBlock.parentElement.setAttribute('data-copy-added', 'true');
var btn = document.createElement('button');
btn.textContent = 'Copy';
btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';
btn.onmouseover = function() { this.style.opacity = '1'; };
btn.onmouseout = function() { this.style.opacity = '0.7'; };
btn.onclick = function() {
navigator.clipboard.writeText(codeBlock.textContent).then(function() {
btn.textContent = 'Copied!';
setTimeout(function() { btn.textContent = 'Copy'; }, 1500);
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observer.observe(document.body, { childList: true, subtree: true });
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
GitHub - k4black/codebleu: Pip compatible CodeBLEU metric implementation available for linux/macos/win · GitHub
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CodeBLEU

PublishTestcodecovPyPI version

This repository contains an unofficial CodeBLEU implementation that supports Linux, MacOS (incl. M-series) and Windows. It is available through PyPI and the evaluate library.

Available for: Python, C, C#, C++, Java, JavaScript, PHP, Go, Ruby, Rust.


The code is based on the original CodeXGLUE/CodeBLEU and updated version by XLCoST/CodeBLEU. It has been refactored, tested, built for macOS and Windows, and multiple improvements have been made to enhance usability.

Metric Description

An ideal evaluation metric should consider the grammatical correctness and the logic correctness. We propose weighted n-gram match and syntactic AST match to measure grammatical correctness, and introduce semantic data-flow match to calculate logic correctness. CodeBLEU
[from CodeXGLUE repo]

In a nutshell, CodeBLEU is a weighted combination of n-gram match (BLEU), weighted n-gram match (BLEU-weighted), AST match and data-flow match scores.

The metric has shown higher correlation with human evaluation than BLEU and accuracy metrics.

Installation

This library requires so file compilation with tree-sitter, so it is platform dependent.
Currently available for Linux (manylinux), MacOS and Windows with Python 3.8+.

The metrics is available as pip package and can be installed as indicated above:

pip install codebleu

or directly from git repo (require internet connection to download tree-sitter):

pip install git+https://github.com/k4black/codebleu.git

Also you have to install tree-sitter language you need (e.g. python, rust, etc):

pip install tree-sitter-python

Or you can install all languages:

pip install codebleu[all]

Note: At the moment (May 2024) precompiled languages are NOT available for arm64 (M1) MacOS, so you have to install and build tree-sitter languages manually, for example:

pip install pip install git+https://github.com/tree-sitter/tree-sitter-python.git

Usage

fromcodebleuimportcalc_codebleuprediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=calc_codebleu([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25), tokenizer=None)
print(result)
# {# 'codebleu': 0.5537, # 'ngram_match_score': 0.1041, # 'weighted_ngram_match_score': 0.1109, # 'syntax_match_score': 1.0, # 'dataflow_match_score': 1.0# }

where calc_codebleu takes the following arguments:

  • refarences (list[str] or list[list[str]]): reference code
  • predictions (list[str]) predicted code
  • lang (str): code language, see codebleu.AVAILABLE_LANGS for available languages (python, c_sharp c, cpp, javascript, java, php, go and ruby at the moment)
  • weights (tuple[float,float,float,float]): weights of the ngram_match, weighted_ngram_match, syntax_match, and dataflow_match respectively, defaults to (0.25, 0.25, 0.25, 0.25)
  • tokenizer (callable): to split code string to tokens, defaults to s.split()

and outputs the dict[str, float] with following fields:

  • codebleu: the final CodeBLEU score
  • ngram_match_score: ngram_match score (BLEU)
  • weighted_ngram_match_score: weighted_ngram_match score (BLEU-weighted)
  • syntax_match_score: syntax_match score (AST match)
  • dataflow_match_score: dataflow_match score

Alternatively, you can use k4black/codebleu from HuggingFace Spaces (codebleu package required):

importevaluatemetric=evaluate.load("dvitel/codebleu")
prediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=metric.compute([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25))

Feel free to check the HF Space with online example: k4black/codebleu

Contributing

Contributions are welcome!
If you have any questions, suggestions, or bug reports, please open an issue on GitHub.

Make your own fork and clone it:

git clone https://github.com/k4black/codebleu

For development, you need to install library with all precompiled languages and test extra:
(require internet connection to download tree-sitter)

python -m pip install -e .[all,test]
python -m pip install -e .\[all,test\]# for macos

For testing just run pytest:

python -m pytest

To perform a style check, run:

python -m isort codebleu --check
python -m black codebleu --check
python -m ruff codebleu
python -m mypy codebleu

License

This project is licensed under the terms of the MIT license.

Citation

Official CodeBLEU paper can be cited as follows:

@misc{ren2020codebleu,
title={CodeBLEU: a Method for Automatic Evaluation of Code Synthesis}, author={Shuo Ren and Daya Guo and Shuai Lu and Long Zhou and Shujie Liu and Duyu Tang and Neel Sundaresan and Ming Zhou and Ambrosio Blanco and Shuai Ma},
year={2020},
eprint={2009.10297},
archivePrefix={arXiv},
primaryClass={cs.SE}
}

About

Pip compatible CodeBLEU metric implementation available for linux/macos/win

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Resources

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140 stars

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1 watching

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Force GitHub README to respect dark mode (function() { var style = document.createElement('style'); style.textContent = ' .markdown-body { color-scheme: dark light; } .markdown-body pre { background: #161b22 !important; } .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; } .markdown-body table th, .markdown-body table td { border-color: #30363d !important; } .markdown-body img { background: #0d1117; } .markdown-body blockquote { border-left-color: #8b949e; } .markdown-body hr { border-color: #30363d; } '; document.head.appendChild(style); })(); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - k4black/codebleu: Pip compatible CodeBLEU metric implementation available for linux/macos/win · GitHub
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CodeBLEU

PublishTestcodecovPyPI version

This repository contains an unofficial CodeBLEU implementation that supports Linux, MacOS (incl. M-series) and Windows. It is available through PyPI and the evaluate library.

Available for: Python, C, C#, C++, Java, JavaScript, PHP, Go, Ruby, Rust.


The code is based on the original CodeXGLUE/CodeBLEU and updated version by XLCoST/CodeBLEU. It has been refactored, tested, built for macOS and Windows, and multiple improvements have been made to enhance usability.

Metric Description

An ideal evaluation metric should consider the grammatical correctness and the logic correctness. We propose weighted n-gram match and syntactic AST match to measure grammatical correctness, and introduce semantic data-flow match to calculate logic correctness. CodeBLEU
[from CodeXGLUE repo]

In a nutshell, CodeBLEU is a weighted combination of n-gram match (BLEU), weighted n-gram match (BLEU-weighted), AST match and data-flow match scores.

The metric has shown higher correlation with human evaluation than BLEU and accuracy metrics.

Installation

This library requires so file compilation with tree-sitter, so it is platform dependent.
Currently available for Linux (manylinux), MacOS and Windows with Python 3.8+.

The metrics is available as pip package and can be installed as indicated above:

pip install codebleu

or directly from git repo (require internet connection to download tree-sitter):

pip install git+https://github.com/k4black/codebleu.git

Also you have to install tree-sitter language you need (e.g. python, rust, etc):

pip install tree-sitter-python

Or you can install all languages:

pip install codebleu[all]

Note: At the moment (May 2024) precompiled languages are NOT available for arm64 (M1) MacOS, so you have to install and build tree-sitter languages manually, for example:

pip install pip install git+https://github.com/tree-sitter/tree-sitter-python.git

Usage

fromcodebleuimportcalc_codebleuprediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=calc_codebleu([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25), tokenizer=None)
print(result)
# {# 'codebleu': 0.5537, # 'ngram_match_score': 0.1041, # 'weighted_ngram_match_score': 0.1109, # 'syntax_match_score': 1.0, # 'dataflow_match_score': 1.0# }

where calc_codebleu takes the following arguments:

  • refarences (list[str] or list[list[str]]): reference code
  • predictions (list[str]) predicted code
  • lang (str): code language, see codebleu.AVAILABLE_LANGS for available languages (python, c_sharp c, cpp, javascript, java, php, go and ruby at the moment)
  • weights (tuple[float,float,float,float]): weights of the ngram_match, weighted_ngram_match, syntax_match, and dataflow_match respectively, defaults to (0.25, 0.25, 0.25, 0.25)
  • tokenizer (callable): to split code string to tokens, defaults to s.split()

and outputs the dict[str, float] with following fields:

  • codebleu: the final CodeBLEU score
  • ngram_match_score: ngram_match score (BLEU)
  • weighted_ngram_match_score: weighted_ngram_match score (BLEU-weighted)
  • syntax_match_score: syntax_match score (AST match)
  • dataflow_match_score: dataflow_match score

Alternatively, you can use k4black/codebleu from HuggingFace Spaces (codebleu package required):

importevaluatemetric=evaluate.load("dvitel/codebleu")
prediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=metric.compute([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25))

Feel free to check the HF Space with online example: k4black/codebleu

Contributing

Contributions are welcome!
If you have any questions, suggestions, or bug reports, please open an issue on GitHub.

Make your own fork and clone it:

git clone https://github.com/k4black/codebleu

For development, you need to install library with all precompiled languages and test extra:
(require internet connection to download tree-sitter)

python -m pip install -e .[all,test]
python -m pip install -e .\[all,test\]# for macos

For testing just run pytest:

python -m pytest

To perform a style check, run:

python -m isort codebleu --check
python -m black codebleu --check
python -m ruff codebleu
python -m mypy codebleu

License

This project is licensed under the terms of the MIT license.

Citation

Official CodeBLEU paper can be cited as follows:

@misc{ren2020codebleu,
title={CodeBLEU: a Method for Automatic Evaluation of Code Synthesis}, author={Shuo Ren and Daya Guo and Shuai Lu and Long Zhou and Shujie Liu and Duyu Tang and Neel Sundaresan and Ming Zhou and Ambrosio Blanco and Shuai Ma},
year={2020},
eprint={2009.10297},
archivePrefix={arXiv},
primaryClass={cs.SE}
}

About

Pip compatible CodeBLEU metric implementation available for linux/macos/win

Topics

Resources

Stars

140 stars

Watchers

1 watching

Forks

Releases

Packages

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Highlight search terms from Google/DuckDuckGo/Bing referrer (function() { var ref = document.referrer; var terms = []; if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) { var url = new URL(ref); var q = url.searchParams.get('q') || url.searchParams.get('p'); if (q) { terms = q.split(/\s+/).filter(function(t) { return t.length > 2; }); } } if (terms.length === 0) return; var style = document.createElement('style'); style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }'; document.head.appendChild(style); function highlight(node) { if (node.nodeType === 3) { // text node var text = node.textContent; var found = false; terms.forEach(function(term) { var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - k4black/codebleu: Pip compatible CodeBLEU metric implementation available for linux/macos/win · GitHub
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CodeBLEU

PublishTestcodecovPyPI version

This repository contains an unofficial CodeBLEU implementation that supports Linux, MacOS (incl. M-series) and Windows. It is available through PyPI and the evaluate library.

Available for: Python, C, C#, C++, Java, JavaScript, PHP, Go, Ruby, Rust.


The code is based on the original CodeXGLUE/CodeBLEU and updated version by XLCoST/CodeBLEU. It has been refactored, tested, built for macOS and Windows, and multiple improvements have been made to enhance usability.

Metric Description

An ideal evaluation metric should consider the grammatical correctness and the logic correctness. We propose weighted n-gram match and syntactic AST match to measure grammatical correctness, and introduce semantic data-flow match to calculate logic correctness. CodeBLEU
[from CodeXGLUE repo]

In a nutshell, CodeBLEU is a weighted combination of n-gram match (BLEU), weighted n-gram match (BLEU-weighted), AST match and data-flow match scores.

The metric has shown higher correlation with human evaluation than BLEU and accuracy metrics.

Installation

This library requires so file compilation with tree-sitter, so it is platform dependent.
Currently available for Linux (manylinux), MacOS and Windows with Python 3.8+.

The metrics is available as pip package and can be installed as indicated above:

pip install codebleu

or directly from git repo (require internet connection to download tree-sitter):

pip install git+https://github.com/k4black/codebleu.git

Also you have to install tree-sitter language you need (e.g. python, rust, etc):

pip install tree-sitter-python

Or you can install all languages:

pip install codebleu[all]

Note: At the moment (May 2024) precompiled languages are NOT available for arm64 (M1) MacOS, so you have to install and build tree-sitter languages manually, for example:

pip install pip install git+https://github.com/tree-sitter/tree-sitter-python.git

Usage

fromcodebleuimportcalc_codebleuprediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=calc_codebleu([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25), tokenizer=None)
print(result)
# {# 'codebleu': 0.5537, # 'ngram_match_score': 0.1041, # 'weighted_ngram_match_score': 0.1109, # 'syntax_match_score': 1.0, # 'dataflow_match_score': 1.0# }

where calc_codebleu takes the following arguments:

  • refarences (list[str] or list[list[str]]): reference code
  • predictions (list[str]) predicted code
  • lang (str): code language, see codebleu.AVAILABLE_LANGS for available languages (python, c_sharp c, cpp, javascript, java, php, go and ruby at the moment)
  • weights (tuple[float,float,float,float]): weights of the ngram_match, weighted_ngram_match, syntax_match, and dataflow_match respectively, defaults to (0.25, 0.25, 0.25, 0.25)
  • tokenizer (callable): to split code string to tokens, defaults to s.split()

and outputs the dict[str, float] with following fields:

  • codebleu: the final CodeBLEU score
  • ngram_match_score: ngram_match score (BLEU)
  • weighted_ngram_match_score: weighted_ngram_match score (BLEU-weighted)
  • syntax_match_score: syntax_match score (AST match)
  • dataflow_match_score: dataflow_match score

Alternatively, you can use k4black/codebleu from HuggingFace Spaces (codebleu package required):

importevaluatemetric=evaluate.load("dvitel/codebleu")
prediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=metric.compute([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25))

Feel free to check the HF Space with online example: k4black/codebleu

Contributing

Contributions are welcome!
If you have any questions, suggestions, or bug reports, please open an issue on GitHub.

Make your own fork and clone it:

git clone https://github.com/k4black/codebleu

For development, you need to install library with all precompiled languages and test extra:
(require internet connection to download tree-sitter)

python -m pip install -e .[all,test]
python -m pip install -e .\[all,test\]# for macos

For testing just run pytest:

python -m pytest

To perform a style check, run:

python -m isort codebleu --check
python -m black codebleu --check
python -m ruff codebleu
python -m mypy codebleu

License

This project is licensed under the terms of the MIT license.

Citation

Official CodeBLEU paper can be cited as follows:

@misc{ren2020codebleu,
title={CodeBLEU: a Method for Automatic Evaluation of Code Synthesis}, author={Shuo Ren and Daya Guo and Shuai Lu and Long Zhou and Shujie Liu and Duyu Tang and Neel Sundaresan and Ming Zhou and Ambrosio Blanco and Shuai Ma},
year={2020},
eprint={2009.10297},
archivePrefix={arXiv},
primaryClass={cs.SE}
}

About

Pip compatible CodeBLEU metric implementation available for linux/macos/win

Topics

Resources

Stars

140 stars

Watchers

1 watching

Forks

Releases

Packages

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ' GitHub - k4black/codebleu: Pip compatible CodeBLEU metric implementation available for linux/macos/win · GitHub
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CodeBLEU

PublishTestcodecovPyPI version

This repository contains an unofficial CodeBLEU implementation that supports Linux, MacOS (incl. M-series) and Windows. It is available through PyPI and the evaluate library.

Available for: Python, C, C#, C++, Java, JavaScript, PHP, Go, Ruby, Rust.


The code is based on the original CodeXGLUE/CodeBLEU and updated version by XLCoST/CodeBLEU. It has been refactored, tested, built for macOS and Windows, and multiple improvements have been made to enhance usability.

Metric Description

An ideal evaluation metric should consider the grammatical correctness and the logic correctness. We propose weighted n-gram match and syntactic AST match to measure grammatical correctness, and introduce semantic data-flow match to calculate logic correctness. CodeBLEU
[from CodeXGLUE repo]

In a nutshell, CodeBLEU is a weighted combination of n-gram match (BLEU), weighted n-gram match (BLEU-weighted), AST match and data-flow match scores.

The metric has shown higher correlation with human evaluation than BLEU and accuracy metrics.

Installation

This library requires so file compilation with tree-sitter, so it is platform dependent.
Currently available for Linux (manylinux), MacOS and Windows with Python 3.8+.

The metrics is available as pip package and can be installed as indicated above:

pip install codebleu

or directly from git repo (require internet connection to download tree-sitter):

pip install git+https://github.com/k4black/codebleu.git

Also you have to install tree-sitter language you need (e.g. python, rust, etc):

pip install tree-sitter-python

Or you can install all languages:

pip install codebleu[all]

Note: At the moment (May 2024) precompiled languages are NOT available for arm64 (M1) MacOS, so you have to install and build tree-sitter languages manually, for example:

pip install pip install git+https://github.com/tree-sitter/tree-sitter-python.git

Usage

fromcodebleuimportcalc_codebleuprediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=calc_codebleu([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25), tokenizer=None)
print(result)
# {# 'codebleu': 0.5537, # 'ngram_match_score': 0.1041, # 'weighted_ngram_match_score': 0.1109, # 'syntax_match_score': 1.0, # 'dataflow_match_score': 1.0# }

where calc_codebleu takes the following arguments:

  • refarences (list[str] or list[list[str]]): reference code
  • predictions (list[str]) predicted code
  • lang (str): code language, see codebleu.AVAILABLE_LANGS for available languages (python, c_sharp c, cpp, javascript, java, php, go and ruby at the moment)
  • weights (tuple[float,float,float,float]): weights of the ngram_match, weighted_ngram_match, syntax_match, and dataflow_match respectively, defaults to (0.25, 0.25, 0.25, 0.25)
  • tokenizer (callable): to split code string to tokens, defaults to s.split()

and outputs the dict[str, float] with following fields:

  • codebleu: the final CodeBLEU score
  • ngram_match_score: ngram_match score (BLEU)
  • weighted_ngram_match_score: weighted_ngram_match score (BLEU-weighted)
  • syntax_match_score: syntax_match score (AST match)
  • dataflow_match_score: dataflow_match score

Alternatively, you can use k4black/codebleu from HuggingFace Spaces (codebleu package required):

importevaluatemetric=evaluate.load("dvitel/codebleu")
prediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=metric.compute([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25))

Feel free to check the HF Space with online example: k4black/codebleu

Contributing

Contributions are welcome!
If you have any questions, suggestions, or bug reports, please open an issue on GitHub.

Make your own fork and clone it:

git clone https://github.com/k4black/codebleu

For development, you need to install library with all precompiled languages and test extra:
(require internet connection to download tree-sitter)

python -m pip install -e .[all,test]
python -m pip install -e .\[all,test\]# for macos

For testing just run pytest:

python -m pytest

To perform a style check, run:

python -m isort codebleu --check
python -m black codebleu --check
python -m ruff codebleu
python -m mypy codebleu

License

This project is licensed under the terms of the MIT license.

Citation

Official CodeBLEU paper can be cited as follows:

@misc{ren2020codebleu,
title={CodeBLEU: a Method for Automatic Evaluation of Code Synthesis}, author={Shuo Ren and Daya Guo and Shuai Lu and Long Zhou and Shujie Liu and Duyu Tang and Neel Sundaresan and Ming Zhou and Ambrosio Blanco and Shuai Ma},
year={2020},
eprint={2009.10297},
archivePrefix={arXiv},
primaryClass={cs.SE}
}

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Pip compatible CodeBLEU metric implementation available for linux/macos/win

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140 stars

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - k4black/codebleu: Pip compatible CodeBLEU metric implementation available for linux/macos/win · GitHub
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CodeBLEU

PublishTestcodecovPyPI version

This repository contains an unofficial CodeBLEU implementation that supports Linux, MacOS (incl. M-series) and Windows. It is available through PyPI and the evaluate library.

Available for: Python, C, C#, C++, Java, JavaScript, PHP, Go, Ruby, Rust.


The code is based on the original CodeXGLUE/CodeBLEU and updated version by XLCoST/CodeBLEU. It has been refactored, tested, built for macOS and Windows, and multiple improvements have been made to enhance usability.

Metric Description

An ideal evaluation metric should consider the grammatical correctness and the logic correctness. We propose weighted n-gram match and syntactic AST match to measure grammatical correctness, and introduce semantic data-flow match to calculate logic correctness. CodeBLEU
[from CodeXGLUE repo]

In a nutshell, CodeBLEU is a weighted combination of n-gram match (BLEU), weighted n-gram match (BLEU-weighted), AST match and data-flow match scores.

The metric has shown higher correlation with human evaluation than BLEU and accuracy metrics.

Installation

This library requires so file compilation with tree-sitter, so it is platform dependent.
Currently available for Linux (manylinux), MacOS and Windows with Python 3.8+.

The metrics is available as pip package and can be installed as indicated above:

pip install codebleu

or directly from git repo (require internet connection to download tree-sitter):

pip install git+https://github.com/k4black/codebleu.git

Also you have to install tree-sitter language you need (e.g. python, rust, etc):

pip install tree-sitter-python

Or you can install all languages:

pip install codebleu[all]

Note: At the moment (May 2024) precompiled languages are NOT available for arm64 (M1) MacOS, so you have to install and build tree-sitter languages manually, for example:

pip install pip install git+https://github.com/tree-sitter/tree-sitter-python.git

Usage

fromcodebleuimportcalc_codebleuprediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=calc_codebleu([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25), tokenizer=None)
print(result)
# {# 'codebleu': 0.5537, # 'ngram_match_score': 0.1041, # 'weighted_ngram_match_score': 0.1109, # 'syntax_match_score': 1.0, # 'dataflow_match_score': 1.0# }

where calc_codebleu takes the following arguments:

  • refarences (list[str] or list[list[str]]): reference code
  • predictions (list[str]) predicted code
  • lang (str): code language, see codebleu.AVAILABLE_LANGS for available languages (python, c_sharp c, cpp, javascript, java, php, go and ruby at the moment)
  • weights (tuple[float,float,float,float]): weights of the ngram_match, weighted_ngram_match, syntax_match, and dataflow_match respectively, defaults to (0.25, 0.25, 0.25, 0.25)
  • tokenizer (callable): to split code string to tokens, defaults to s.split()

and outputs the dict[str, float] with following fields:

  • codebleu: the final CodeBLEU score
  • ngram_match_score: ngram_match score (BLEU)
  • weighted_ngram_match_score: weighted_ngram_match score (BLEU-weighted)
  • syntax_match_score: syntax_match score (AST match)
  • dataflow_match_score: dataflow_match score

Alternatively, you can use k4black/codebleu from HuggingFace Spaces (codebleu package required):

importevaluatemetric=evaluate.load("dvitel/codebleu")
prediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=metric.compute([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25))

Feel free to check the HF Space with online example: k4black/codebleu

Contributing

Contributions are welcome!
If you have any questions, suggestions, or bug reports, please open an issue on GitHub.

Make your own fork and clone it:

git clone https://github.com/k4black/codebleu

For development, you need to install library with all precompiled languages and test extra:
(require internet connection to download tree-sitter)

python -m pip install -e .[all,test]
python -m pip install -e .\[all,test\]# for macos

For testing just run pytest:

python -m pytest

To perform a style check, run:

python -m isort codebleu --check
python -m black codebleu --check
python -m ruff codebleu
python -m mypy codebleu

License

This project is licensed under the terms of the MIT license.

Citation

Official CodeBLEU paper can be cited as follows:

@misc{ren2020codebleu,
title={CodeBLEU: a Method for Automatic Evaluation of Code Synthesis}, author={Shuo Ren and Daya Guo and Shuai Lu and Long Zhou and Shujie Liu and Duyu Tang and Neel Sundaresan and Ming Zhou and Ambrosio Blanco and Shuai Ma},
year={2020},
eprint={2009.10297},
archivePrefix={arXiv},
primaryClass={cs.SE}
}

About

Pip compatible CodeBLEU metric implementation available for linux/macos/win

Topics

Resources

Stars

140 stars

Watchers

1 watching

Forks

Releases

Packages

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - k4black/codebleu: Pip compatible CodeBLEU metric implementation available for linux/macos/win · GitHub
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CodeBLEU

PublishTestcodecovPyPI version

This repository contains an unofficial CodeBLEU implementation that supports Linux, MacOS (incl. M-series) and Windows. It is available through PyPI and the evaluate library.

Available for: Python, C, C#, C++, Java, JavaScript, PHP, Go, Ruby, Rust.


The code is based on the original CodeXGLUE/CodeBLEU and updated version by XLCoST/CodeBLEU. It has been refactored, tested, built for macOS and Windows, and multiple improvements have been made to enhance usability.

Metric Description

An ideal evaluation metric should consider the grammatical correctness and the logic correctness. We propose weighted n-gram match and syntactic AST match to measure grammatical correctness, and introduce semantic data-flow match to calculate logic correctness. CodeBLEU
[from CodeXGLUE repo]

In a nutshell, CodeBLEU is a weighted combination of n-gram match (BLEU), weighted n-gram match (BLEU-weighted), AST match and data-flow match scores.

The metric has shown higher correlation with human evaluation than BLEU and accuracy metrics.

Installation

This library requires so file compilation with tree-sitter, so it is platform dependent.
Currently available for Linux (manylinux), MacOS and Windows with Python 3.8+.

The metrics is available as pip package and can be installed as indicated above:

pip install codebleu

or directly from git repo (require internet connection to download tree-sitter):

pip install git+https://github.com/k4black/codebleu.git

Also you have to install tree-sitter language you need (e.g. python, rust, etc):

pip install tree-sitter-python

Or you can install all languages:

pip install codebleu[all]

Note: At the moment (May 2024) precompiled languages are NOT available for arm64 (M1) MacOS, so you have to install and build tree-sitter languages manually, for example:

pip install pip install git+https://github.com/tree-sitter/tree-sitter-python.git

Usage

fromcodebleuimportcalc_codebleuprediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=calc_codebleu([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25), tokenizer=None)
print(result)
# {# 'codebleu': 0.5537, # 'ngram_match_score': 0.1041, # 'weighted_ngram_match_score': 0.1109, # 'syntax_match_score': 1.0, # 'dataflow_match_score': 1.0# }

where calc_codebleu takes the following arguments:

  • refarences (list[str] or list[list[str]]): reference code
  • predictions (list[str]) predicted code
  • lang (str): code language, see codebleu.AVAILABLE_LANGS for available languages (python, c_sharp c, cpp, javascript, java, php, go and ruby at the moment)
  • weights (tuple[float,float,float,float]): weights of the ngram_match, weighted_ngram_match, syntax_match, and dataflow_match respectively, defaults to (0.25, 0.25, 0.25, 0.25)
  • tokenizer (callable): to split code string to tokens, defaults to s.split()

and outputs the dict[str, float] with following fields:

  • codebleu: the final CodeBLEU score
  • ngram_match_score: ngram_match score (BLEU)
  • weighted_ngram_match_score: weighted_ngram_match score (BLEU-weighted)
  • syntax_match_score: syntax_match score (AST match)
  • dataflow_match_score: dataflow_match score

Alternatively, you can use k4black/codebleu from HuggingFace Spaces (codebleu package required):

importevaluatemetric=evaluate.load("dvitel/codebleu")
prediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=metric.compute([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25))

Feel free to check the HF Space with online example: k4black/codebleu

Contributing

Contributions are welcome!
If you have any questions, suggestions, or bug reports, please open an issue on GitHub.

Make your own fork and clone it:

git clone https://github.com/k4black/codebleu

For development, you need to install library with all precompiled languages and test extra:
(require internet connection to download tree-sitter)

python -m pip install -e .[all,test]
python -m pip install -e .\[all,test\]# for macos

For testing just run pytest:

python -m pytest

To perform a style check, run:

python -m isort codebleu --check
python -m black codebleu --check
python -m ruff codebleu
python -m mypy codebleu

License

This project is licensed under the terms of the MIT license.

Citation

Official CodeBLEU paper can be cited as follows:

@misc{ren2020codebleu,
title={CodeBLEU: a Method for Automatic Evaluation of Code Synthesis}, author={Shuo Ren and Daya Guo and Shuai Lu and Long Zhou and Shujie Liu and Duyu Tang and Neel Sundaresan and Ming Zhou and Ambrosio Blanco and Shuai Ma},
year={2020},
eprint={2009.10297},
archivePrefix={arXiv},
primaryClass={cs.SE}
}

About

Pip compatible CodeBLEU metric implementation available for linux/macos/win

Topics

Resources

Stars

140 stars

Watchers

1 watching

Forks

Releases

Packages

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Universal Dark Mode - works on any site (function() { var enabled = true; function applyDarkMode() { if (!enabled) return; // Create style element if it doesn't exist var style = document.getElementById('universal-dark-mode-style'); if (!style) { style = document.createElement('style'); style.id = 'universal-dark-mode-style'; document.head.appendChild(style); } // Dark mode CSS - inverts colors but preserves images/video style.textContent = ' /* Invert everything except media */ html { filter: invert(1) hue-rotate(180deg) !important; background: #1a1a2e !important; } /* Restore images, videos, iframes, canvas */ img, video, iframe, canvas, svg, picture, [style*="background-image"] { filter: invert(1) hue-rotate(180deg) !important; } /* Preserve specific elements that should not be inverted */ .no-dark-mode, .no-dark-mode *, [data-theme="light"], [data-theme="light"], .ace_editor, .ace_editor *, .CodeMirror, .CodeMirror *, .monaco-editor, .monaco-editor *, .markdown-body pre, .markdown-body pre *, .highlight, .highlight *, pre code, pre code * { filter: none !important; } /* Fix common UI elements */ .modal, .popup, .dropdown-menu, .tooltip, .popover { filter: invert(1) hue-rotate(180deg) !important; background: #2d2d44 !important; border-color: #444 !important; } /* Scrollbars */ ::-webkit-scrollbar { background: #1a1a2e !important; } ::-webkit-scrollbar-thumb { background: #444 !important; } ::-webkit-scrollbar-thumb:hover { background: #555 !important; } /* Selection */ ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; } ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; } '; } function removeDarkMode() { var style = document.getElementById('universal-dark-mode-style'); if (style) style.remove(); } // Toggle with Alt+Shift+D document.addEventListener('keydown', function(e) { if (e.altKey && e.shiftKey && e.key === 'D') { e.preventDefault(); enabled = !enabled; if (enabled) { applyDarkMode(); console.log('[Universal Dark Mode] Enabled'); } else { removeDarkMode(); console.log('[Universal Dark Mode] Disabled'); } } }); // Apply on load applyDarkMode(); // Re-apply on dynamic content var observer = new MutationObserver(function(mutations) { if (enabled && !document.getElementById('universal-dark-mode-style')) { applyDarkMode(); } }); observer.observe(document.head, { childList: true }); console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle'); })(); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })(); GitHub - k4black/codebleu: Pip compatible CodeBLEU metric implementation available for linux/macos/win · GitHub
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CodeBLEU

PublishTestcodecovPyPI version

This repository contains an unofficial CodeBLEU implementation that supports Linux, MacOS (incl. M-series) and Windows. It is available through PyPI and the evaluate library.

Available for: Python, C, C#, C++, Java, JavaScript, PHP, Go, Ruby, Rust.


The code is based on the original CodeXGLUE/CodeBLEU and updated version by XLCoST/CodeBLEU. It has been refactored, tested, built for macOS and Windows, and multiple improvements have been made to enhance usability.

Metric Description

An ideal evaluation metric should consider the grammatical correctness and the logic correctness. We propose weighted n-gram match and syntactic AST match to measure grammatical correctness, and introduce semantic data-flow match to calculate logic correctness. CodeBLEU
[from CodeXGLUE repo]

In a nutshell, CodeBLEU is a weighted combination of n-gram match (BLEU), weighted n-gram match (BLEU-weighted), AST match and data-flow match scores.

The metric has shown higher correlation with human evaluation than BLEU and accuracy metrics.

Installation

This library requires so file compilation with tree-sitter, so it is platform dependent.
Currently available for Linux (manylinux), MacOS and Windows with Python 3.8+.

The metrics is available as pip package and can be installed as indicated above:

pip install codebleu

or directly from git repo (require internet connection to download tree-sitter):

pip install git+https://github.com/k4black/codebleu.git

Also you have to install tree-sitter language you need (e.g. python, rust, etc):

pip install tree-sitter-python

Or you can install all languages:

pip install codebleu[all]

Note: At the moment (May 2024) precompiled languages are NOT available for arm64 (M1) MacOS, so you have to install and build tree-sitter languages manually, for example:

pip install pip install git+https://github.com/tree-sitter/tree-sitter-python.git

Usage

fromcodebleuimportcalc_codebleuprediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=calc_codebleu([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25), tokenizer=None)
print(result)
# {# 'codebleu': 0.5537, # 'ngram_match_score': 0.1041, # 'weighted_ngram_match_score': 0.1109, # 'syntax_match_score': 1.0, # 'dataflow_match_score': 1.0# }

where calc_codebleu takes the following arguments:

  • refarences (list[str] or list[list[str]]): reference code
  • predictions (list[str]) predicted code
  • lang (str): code language, see codebleu.AVAILABLE_LANGS for available languages (python, c_sharp c, cpp, javascript, java, php, go and ruby at the moment)
  • weights (tuple[float,float,float,float]): weights of the ngram_match, weighted_ngram_match, syntax_match, and dataflow_match respectively, defaults to (0.25, 0.25, 0.25, 0.25)
  • tokenizer (callable): to split code string to tokens, defaults to s.split()

and outputs the dict[str, float] with following fields:

  • codebleu: the final CodeBLEU score
  • ngram_match_score: ngram_match score (BLEU)
  • weighted_ngram_match_score: weighted_ngram_match score (BLEU-weighted)
  • syntax_match_score: syntax_match score (AST match)
  • dataflow_match_score: dataflow_match score

Alternatively, you can use k4black/codebleu from HuggingFace Spaces (codebleu package required):

importevaluatemetric=evaluate.load("dvitel/codebleu")
prediction="def add ( a , b ) :\n return a + b"reference="def sum ( first , second ) :\n return second + first"result=metric.compute([reference], [prediction], lang="python", weights=(0.25, 0.25, 0.25, 0.25))

Feel free to check the HF Space with online example: k4black/codebleu

Contributing

Contributions are welcome!
If you have any questions, suggestions, or bug reports, please open an issue on GitHub.

Make your own fork and clone it:

git clone https://github.com/k4black/codebleu

For development, you need to install library with all precompiled languages and test extra:
(require internet connection to download tree-sitter)

python -m pip install -e .[all,test]
python -m pip install -e .\[all,test\]# for macos

For testing just run pytest:

python -m pytest

To perform a style check, run:

python -m isort codebleu --check
python -m black codebleu --check
python -m ruff codebleu
python -m mypy codebleu

License

This project is licensed under the terms of the MIT license.

Citation

Official CodeBLEU paper can be cited as follows:

@misc{ren2020codebleu,
title={CodeBLEU: a Method for Automatic Evaluation of Code Synthesis}, author={Shuo Ren and Daya Guo and Shuai Lu and Long Zhou and Shujie Liu and Duyu Tang and Neel Sundaresan and Ming Zhou and Ambrosio Blanco and Shuai Ma},
year={2020},
eprint={2009.10297},
archivePrefix={arXiv},
primaryClass={cs.SE}
}

About

Pip compatible CodeBLEU metric implementation available for linux/macos/win

Topics

Resources

Stars

140 stars

Watchers

1 watching

Forks

Releases

Packages

Used by

Contributors

Languages