Datasets:

legesher
/

language-decoded-data

code stringlengths 72 8.78M	code_en stringlengths 72 8.78M	language stringclasses 1 value	file_path stringlengths 36 164	license stringclasses 1 value	token_count int64 26 8.41M
# -- coding: utf-8 -- from collections import OrderedDict from ipywidgets import Widget, Tab class ExtendedTab(Tab): """ A Tab subclass that allows to add/access/select/replace/remove children by name. There can be only one tab for any given name. Example: import time t = Extend...	# -- coding: utf-8 -- from collections import OrderedDict from ipywidgets import Widget, Tab class ExtendedTab(Tab): """ A Tab subclass that allows to add/access/select/replace/remove children by name. There can be only one tab for any given name. Example: import time t = Extend...	en	002440303_deeplook-ipyrest_extendedtab_093e2be98d4c.py	unknown	717
# ------------------------------------------------------------------------------------------------ # Deformable DETR # Copyright (c) 2020 SenseTime. All Rights Reserved. # Licensed under the Apache License, Version 2.0 [see LICENSE for details] # -------------------------------------------------------------------------...	# ------------------------------------------------------------------------------------------------ # Deformable DETR # Copyright (c) 2020 SenseTime. All Rights Reserved. # Licensed under the Apache License, Version 2.0 [see LICENSE for details] # -------------------------------------------------------------------------...	en	005599174_eslambakr-HRS_benchmark_ms_deform_attn_e958c034cd2c.py	unknown	2,162
""" Notice : 神兽保佑，测试一次通过 // // ┏┛ ┻━━━━━┛ ┻┓ // ┃　　　　　　 ┃ // ┃　　　━　　　┃ // ┃　┳┛　 ┗┳　┃ // ┃　　　　　　 ┃ // ┃　　　┻　　　┃ // ┃　　　　　　 ┃ // ┗━┓　　　┏━━━┛ // ┃　　　┃ Author: somewheve // ┃　　　┃ Datetime: 2019/7/3 下午8:46 ---> 无知即是罪恶 // ┃　　　┗━━━━━━━━━┓ // ┃　　　...	""" Notice : 神兽保佑，测试一次通过 // // ┏┛ ┻━━━━━┛ ┻┓ // ┃　　　　　　 ┃ // ┃　　　━　　　┃ // ┃　┳┛　 ┗┳　┃ // ┃　　　　　　 ┃ // ┃　　　┻　　　┃ // ┃　　　　　　 ┃ // ┗━┓　　　┏━━━┛ // ┃　　　┃ Author: somewheve // ┃　　　┃ Datetime: 2019/7/3 下午8:46 ---> 无知即是罪恶 // ┃　　　┗━━━━━━━━━┓ // ┃　　　...	en	004828635_ctpbee-ctpbee_local_position_cba89669d079.py	unknown	6,624
""" Reddit comments --------------- A collection of up to ~1.5 billion Reddit comments posted from October 2007 through May 2015. Records include the following key fields (plus a few others): - ``body``: Full text of the comment. - ``created_utc``: Date on which the comment was posted. - ``subreddit``: S...	""" Reddit comments --------------- A collection of up to ~1.5 billion Reddit comments posted from October 2007 through May 2015. Records include the following key fields (plus a few others): - ``body``: Full text of the comment. - ``created_utc``: Date on which the comment was posted. - ``subreddit``: S...	en	005639457_chartbeat-labs-textacy_reddit_comments_dd41d70f3bec.py	unknown	4,005
# Copyright (c) Meta Platforms, Inc. and affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. from django.http import HttpRequest def source() -> str: request = HttpRequest() return request.GET["bad"] def sink(argument: st...	# Copyright (c) Meta Platforms, Inc. and affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. from django.http import HttpRequest def source() -> str: request = HttpRequest() return request.GET["bad"] def sink(argument: st...	en	005513877_facebook-pyre-check_taint_9fd251ea2de2.py	unknown	98
"""Spatial Dissimilarity Index.""" __author__ = "Renan X. Cortes <renanc@ucr.edu>, Sergio J. Rey <sergio.rey@ucr.edu> and Elijah Knaap <elijah.knaap@ucr.edu>" import libpysal import numpy as np from libpysal.weights import Queen from .._base import SingleGroupIndex, SpatialExplicitIndex from .dissim import _dissim ...	"""Spatial Dissimilarity Index.""" __author__ = "Renan X. Cortes <renanc@ucr.edu>, Sergio J. Rey <sergio.rey@ucr.edu> and Elijah Knaap <elijah.knaap@ucr.edu>" import libpysal import numpy as np from libpysal.weights import Queen from .._base import SingleGroupIndex, SpatialExplicitIndex from .dissim import _dissim ...	en	005596770_pysal-segregation_spatial_dissim_c7cbba1b3cc7.py	unknown	1,408
# Copyright 2022 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to...	# Copyright 2022 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to...	en	003296220_mindspore-ai-models_pointTransfomrer_4aa2cdd24484.py	unknown	3,593
""" Conduct searches against all registry context. """ import math from operator import itemgetter from flask import abort from stringscore import liquidmetal from text_unidecode import unidecode import features from app import app, authentication, avatar from auth import scopes from auth.auth_context import get_aut...	""" Conduct searches against all registry context. """ import math from operator import itemgetter from flask import abort from stringscore import liquidmetal from text_unidecode import unidecode import features from app import app, authentication, avatar from auth import scopes from auth.auth_context import get_aut...	en	002995759_quay-quay_search_1eeecbd30b46.py	unknown	4,126
from pygments.lexer import RegexLexer, words, include from pygments.token import * from pygments.style import Style from pygments.token import Keyword, Name, Comment, String, Error, Number, Operator, Generic, Text from sphinxcontrib.domaintools import custom_domain import re __all__ = ['MinilangLexer'] class Minilang...	from pygments.lexer import RegexLexer, words, include from pygments.token import * from pygments.style import Style from pygments.token import Keyword, Name, Comment, String, Error, Number, Operator, Generic, Text from sphinxcontrib.domaintools import custom_domain import re __all__ = ['MinilangLexer'] class Minilang...	en	003598869_wrapl-minilang_minilang_5aa1f4fdd5b5.py	unknown	1,326
import os import numpy as np import yaml import re from edflow.data.dataset_mixin import DatasetMixin from edflow.util import retrieve, get_obj_from_str, pp2mkdtable, pop_keypath from edflow.util import walk, set_value, edprint from edflow.data.believers.meta_loaders import DEFAULT_LOADERS try: from IPython impor...	import os import numpy as np import yaml import re from edflow.data.dataset_mixin import DatasetMixin from edflow.util import retrieve, get_obj_from_str, pp2mkdtable, pop_keypath from edflow.util import walk, set_value, edprint from edflow.data.believers.meta_loaders import DEFAULT_LOADERS try: from IPython impor...	en	000899950_pesser-edflow_meta_09fbed6837d7.py	unknown	2,808
import logging import os from restic_compose_backup import utils logger = logging.getLogger(__name__) def run(image: str = None, command: str = None, volumes: dict = None, environment: dict = None, labels: dict = None, source_container_id: str = None): logger.info("Starting backup container") client...	import logging import os from restic_compose_backup import utils logger = logging.getLogger(__name__) def run(image: str = None, command: str = None, volumes: dict = None, environment: dict = None, labels: dict = None, source_container_id: str = None): logger.info("Starting backup container") client...	en	005414885_ZettaIO-restic-compose-backup_backup_runner_9c6cd421a308.py	unknown	517

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Language Decoded | Multilingual Code Dataset

Note (2026-04-21): Phase 2 configs have been renamed to phase-2-the-stack-v1-* and moved under data/phase-2-the-stack-v1/. Existing load_dataset(...) calls using the short condition-* names will no longer resolve. The short condition-* namespace is reserved for Phase 3 builds (streamed from The Stack v2, coming soon). See the Loading the Dataset section below for updated config names.

Multilingual Python code datasets for the Language Decoded project (part of Cohere's Tiny Aya Expedition), investigating whether code's reasoning benefit for language models is language-dependent or structure-dependent.

Research Question

Does fine-tuning on non-English code (Python with translated keywords) improve multilingual reasoning as much as English code does?

Prior work (Aryabumi et al., 2024 -- "To Code or Not to Code") demonstrated that including English code in pre-training data improves downstream reasoning performance by approximately 8%. However, that study only tested English code. This dataset enables the natural follow-up: does the reasoning benefit come from the structure of code, or from the language of its keywords?

Dataset Description

This dataset provides filtered, quality-controlled Python source code in multiple configurations: the original English, three keyword-swapped variants (Chinese, Spanish, Urdu), a blended native+transpiled mix, and strictly native Chinese code. The source data is drawn from bigcode/the-stack-dedup (Python subset), filtered for quality using the following criteria:

AST-valid Python only (must parse without errors)
Permissive licenses only (MIT, Apache-2.0, BSD, etc.)
10--1000 lines of code
Minimum 21 GitHub stars
No autogenerated files
SHA-256 deduplication

Keyword-swapped variants are produced using Legesher v0.7.3, which translates Python reserved words (37 keywords, 72 builtins, 66 exceptions) into the target language while preserving code structure and semantics.

Available Configs

Each condition is available in two sizes: -32k (full filtered corpus, ~31.8k train + ~3.5k validation) and -5k (stratified subset, 4.5k train + 500 validation). The -5k subsets are used for QLoRA fine-tuning on consumer GPUs.

Config	Condition	Language	Description	Train	Val
`condition-1-en-32k`	1 (control)	English	Unmodified filtered Python from The Stack Dedup	31,818	3,536
`condition-1-en-5k`	1 (control)	English	Stratified 5k subset of condition-1	4,500	500
`condition-2-zh-32k`	2	Chinese	Keyword-swapped Python via Legesher v0.7.3	31,818	3,536
`condition-2-zh-5k`	2	Chinese	Stratified 5k subset of condition-2-zh	4,500	500
`condition-2-es-32k`	2	Spanish	Keyword-swapped Python via Legesher v0.7.3	31,818	3,536
`condition-2-es-5k`	2	Spanish	Stratified 5k subset of condition-2-es	4,500	500
`condition-2-ur-32k`	2	Urdu	Keyword-swapped Python via Legesher v0.7.3	31,818	3,536
`condition-2-ur-5k`	2	Urdu	Stratified 5k subset of condition-2-ur	4,500	500
`condition-3-zh-5k`	3	Chinese	Blended: 3,486 native Chinese code + 1,514 transpiled Python	4,500	500
`condition-4-zh-5k`	4	Chinese	Strictly native Chinese code (no transpiled code)	6,553	729

Schema

Conditions 1--2

Used by: condition-1-en-*, condition-2-zh-*, condition-2-es-*, condition-2-ur-*

Column	Type	Description
`code`	string	Python source code. For condition-2 configs, this is the transpiled (keyword-swapped) version. For condition-1, this is the original English source.
`code_en`	string	Original English Python source code. Identical to `code` for condition-1-en.
`language`	string	ISO 639-1 language code: `en`, `ur`, `zh`, or `es`.
`file_path`	string	Original file path in The Stack Dedup.
`license`	string	SPDX license identifier for the source file.
`token_count`	int64	Token count computed using the CohereLabs/tiny-aya-base tokenizer.

Condition 3

Used by: condition-3-zh-5k

Condition 3 blends native Chinese code with transpiled code and adds a source_type column to distinguish them. code_en is populated for transpiled rows (keeping them in sync with conditions 1--2) but null for native code rows, which have no English equivalent.

Column	Type	Description
`file_path`	string	File identifier (native filename or transpiled file path)
`code`	string	The code content (native or transpiled)
`code_en`	string/null	English original -- populated for transpiled rows, null for native code rows
`language`	string	ISO 639-1 language code (`zh`)
`license`	string	Source license (SPDX identifier, `UNKNOWN`, or `varies`)
`token_count`	int64	Token count computed using the CohereLabs/tiny-aya-base tokenizer
`source_type`	string	`"native"` (natively Chinese-authored) or `"transpiled"` (keyword-swapped English)

Condition 4

Used by: condition-4-zh-5k

Condition 4 contains strictly native Chinese code -- code written by developers who think and code in Chinese. This uses the same schema as the language-decoded-community dataset rather than the transpilation schema, since there is no English original to reference.

Column	Type	Description
`filename`	string	Original filename
`content`	string	The code content
`extension`	string	File extension (e.g., `.py`, `.c`, `.wenyan`)
`source`	string	Data source (e.g., `thestack`, `wenyan`, `program_in_chinese`)
`quality_tier`	string	Quality rating: `A` (highest) through `D` (lowest)
`sha256`	string	SHA-256 hash for deduplication
`byte_size`	int64	File size in bytes
`total_lines`	int64	Total line count
`cjk_ratio`	float64	Ratio of CJK characters in the file
`has_cjk`	bool	Whether the file contains CJK characters

Experimental Conditions

The Language Decoded experiment uses a ladder of conditions to isolate the mechanism behind code's reasoning benefit:

Condition	Name	Purpose
Baseline	No fine-tuning	Establishes the performance floor
Condition 1	English code	Tests whether code fine-tuning helps at all (replicates Aryabumi et al.)
Condition 2	Keyword-swapped code	Tests whether the language of keywords matters for the reasoning benefit
Condition 3	Mixed native sources	Tests whether diverse native-language code adds value beyond keyword swapping
Condition 4	Strictly native code	Tests whether code authored by native speakers carries unique signal beyond transpilation

The Experimental Ladder

Baseline --> 1: Does code help at all?
1 --> 2: Does the language of keywords matter?
2 --> 3: Does diversity of native-language sources add value beyond keyword swap?
3 --> 4: Does code written in the cultural context of a language carry something that transpiled+mixed can't?

Usage

from datasets import load_dataset

# Load full-size English code (control)
ds = load_dataset("legesher/language-decoded-data", "condition-1-en-32k")

# Load 5k subset (for QLoRA fine-tuning)
ds = load_dataset("legesher/language-decoded-data", "condition-1-en-5k")

# Load keyword-swapped variants
ds = load_dataset("legesher/language-decoded-data", "condition-2-zh-5k")
ds = load_dataset("legesher/language-decoded-data", "condition-2-es-5k")
ds = load_dataset("legesher/language-decoded-data", "condition-2-ur-5k")

# Load blended native + transpiled (condition 3)
ds = load_dataset("legesher/language-decoded-data", "condition-3-zh-5k")

# Load strictly native code (condition 4)
ds = load_dataset("legesher/language-decoded-data", "condition-4-zh-5k")

# Access splits
train = ds["train"]
val = ds["validation"]

# Filter condition-3 by source type
native_only = train.filter(lambda x: x["source_type"] == "native")

Technical Details

Parameter	Value
Source dataset	bigcode/the-stack-dedup (Python subset)
Transpilation tool	Legesher v0.7.3 (legesher-core, legesher-i18n)
Tokenizer	CohereLabs/tiny-aya-base
Base model	CohereLabs/tiny-aya-base (3.35B params)
Train/validation split	90% / 10% (seed 42)
File format	Parquet (snappy compression)
Filtering criteria	AST-valid, permissive licenses, 10--1000 lines, min 21 GitHub stars, no autogenerated files, SHA-256 deduplication

Limitations

Source bias: The Stack Dedup skews toward popular, well-starred GitHub repositories, which may not represent the full diversity of Python code in the wild.
Keyword-only transpilation: Legesher translates Python reserved words (keywords, builtins, exceptions) but leaves comments, docstrings, string literals, and variable/function names in their original language (typically English). This means condition-2 code is a hybrid of translated keywords and English identifiers.
Token count variation: Transpiled code may have different token counts than the English original due to multi-byte characters (especially for Chinese and Urdu), even though the code structure is identical.
Single programming language: Currently limited to Python. Results may not generalize to other programming languages.
Condition 4 scope: Native Chinese code is limited to publicly available sources (The Stack, Wenyan, Program-in-Chinese, Qi, Mulan) and may not represent the full spectrum of Chinese-language programming.

Citation

@misc{language-decoded-2026,
  title={Language Decoded: Investigating Language-Dependent vs. Structure-Dependent Reasoning Benefits of Code},
  author={Madison Edgar and Saad Ahmed Bazaz and Tom Sherborne and Rashik Shahjahan and Khojasteh Mirza and Sarah Jawaid and Rafay Mustafa and Sohaib Ahmed Bazaz},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/legesher/language-decoded-data}
}