source_sha512 stringlengths 128 128 | payload_sha512 stringlengths 128 128 | nas_identity stringlengths 133 133 | corpus stringclasses 1
value | version stringclasses 1
value | canonical_sha256 stringlengths 64 64 | source stringlengths 46 99.9k | pyc unknown | statement listlengths 1 2.77k | segmentation listlengths 1 817 | split stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|
f2e61f01cc42e553d90269cdd8a876ca519e0d389a356d780152abcf0498c37456401d9840df5ebe24c435ef813c0e4e0d296106c26d4266f7c603284b9b8049 | 23a1a26eb54ee97fc44af3d4db238c132fdbfcac72c242a32faf77a52bb1ac571e191da977ac02d9b8358c8cd293c5a47d08882dffc8ea65bd3bfa747c66ba54 | pypi-f2e61f01cc42e553d90269cdd8a876ca519e0d389a356d780152abcf0498c37456401d9840df5ebe24c435ef813c0e4e0d296106c26d4266f7c603284b9b8049 | pypi | 3.14 | 98c63097a6f5a07c87696968beb36ec2370345972d772287715ff68e553ed17d | from __future__ import annotations
from dataclasses import dataclass
from kiota_abstractions.get_path_parameters import get_path_parameters
from kiota_abstractions.method import Method
from kiota_abstractions.request_adapter import RequestAdapter
from kiota_abstractions.request_information import RequestInformation
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{
"source": "from <mask_0><mask_2> import <mask_1>",
"bytecode": "LOAD_SMALL_INT , <mask_0> <SEP> LOAD_CONST , ('<mask_1>',) <SEP> IMPORT_NAME , <mask_2> <SEP> IMPORT_FROM , <mask_1> <SEP> STORE_NAME , <mask_1> <SEP> POP_TOP"
},
{
"source": "from <mask_0><mask_2> import <mask_1>",
"bytecode": "L... | [
{
"source": "from <mask_0><mask_22> import <mask_4> <SEP> from <mask_0><mask_23> import <mask_5> <SEP> from <mask_0><mask_24> import <mask_6> <SEP> from <mask_0><mask_25> import <mask_7> <SEP> from <mask_0><mask_26> import <mask_8> <SEP> from <mask_0><mask_27> import <mask_9> <SEP> from <mask_0><mask_28> import... | train |
afd8afe216afa0eb63b49c20d642a94eca1bccf35926591aae7432b269999ece4f5e876029c6d53335de204c0fcd07ed3d35e23c5ecd10127835e4c25231dd95 | 9718e4caee5fe92c538eace2677e9ab782deb60e91aa4ccdc2761bb7465a5a763d1b986cbd488a1d3f091be89061e268554cd55bf43b85d19896bf8ddb059824 | pypi-afd8afe216afa0eb63b49c20d642a94eca1bccf35926591aae7432b269999ece4f5e876029c6d53335de204c0fcd07ed3d35e23c5ecd10127835e4c25231dd95 | pypi | 3.14 | db1496eaafe882f40c1104f1f4539395d6ffce720864c25151e003c47d48171b | """pass"""
from enum import Enum
from typing import Optional, Type, TypeVar
from pydantic import BaseModel
from metadata.generated.schema.api.data.createCustomProperty import CreateCustomPropertyRequest
from metadata.generated.schema.type import basic, entityHistory
T = TypeVar('T', bound=BaseModel)
class CustomProper... | [
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{
"source": "\"\"\"<mask_0>\"\"\"",
"bytecode": "LOAD_CONST , '<mask_0>' <SEP> STORE_NAME , __doc__"
},
{
"source": "from <mask_0><mask_2> import <mask_1>",
"bytecode": "LOAD_SMALL_INT , <mask_0> <SEP> LOAD_CONST , ('<mask_1>',) <SEP> IMPORT_NAME , <mask_2> <SEP> IMPORT_FROM , <mask_1> <SEP> STO... | [
{
"source": "\"\"\"<mask_0>\"\"\" <SEP> from <mask_8><mask_19> import <mask_9> <SEP> from <mask_8><mask_20> import <mask_10>, <mask_11>, <mask_12> <SEP> from <mask_8><mask_21> import <mask_13> <SEP> from <mask_8><mask_22> import <mask_14> <SEP> from <mask_8><mask_23> import <mask_15>, <mask_16> <SEP> <mask_1> =... | train |
9b33737c39b06e637a67edf78246ee19140c28fd82d8ac431e12a8d2e78e03993db631e8496ec08a6330d0abf39fffd24c9f74da9b8175210308fcbf829801a3 | 99d7a6e69af60bc6a7aba2b554d87354bbe6d44c516e6a5a9b36a0e0471e78e61080936cbe904b381a372be74a882b44624e390e1a8dd1cbbb2b71fe1053d1c3 | pypi-9b33737c39b06e637a67edf78246ee19140c28fd82d8ac431e12a8d2e78e03993db631e8496ec08a6330d0abf39fffd24c9f74da9b8175210308fcbf829801a3 | pypi | 3.14 | 7179267ed204c61ed25f484a3ce53a3cd518ae68448b456453a6e2f2d08dd1cd | from typing import Any, Dict
from modelscope.metainfo import Pipelines
from modelscope.outputs import OutputKeys
from modelscope.pipelines.base import Input, Model, Pipeline
from modelscope.pipelines.builder import PIPELINES
from modelscope.pipelines.util import is_model, is_official_hub_path
from modelscope.utils.cons... | [
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{
"source": "from <mask_0><mask_3> import <mask_1>, <mask_2>",
"bytecode": "LOAD_SMALL_INT , <mask_0> <SEP> LOAD_CONST , ('<mask_1>', '<mask_2>') <SEP> IMPORT_NAME , <mask_3> <SEP> IMPORT_FROM , <mask_1> <SEP> STORE_NAME , <mask_1> <SEP> IMPORT_FROM , <mask_2> <SEP> STORE_NAME , <mask_2> <SEP> POP_TOP"
},... | [
{
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"8c31e39ed7d6e36dad5e220b923e7d60c0f00289de52fcb4b7d2fa8fa1d00b08eb8e903d50dcfb9fb18c9f0641b01ec24a9(...TRUNCATED) | "dc1f991fd52973c0e6fdb64db2cf9a17612a5ec7fee83b9f829bbef09578b802b3613b916ab042d6ae7a81c476fea1c930d(...TRUNCATED) | "pypi-8c31e39ed7d6e36dad5e220b923e7d60c0f00289de52fcb4b7d2fa8fa1d00b08eb8e903d50dcfb9fb18c9f0641b01e(...TRUNCATED) | pypi | 3.14 | 85c6fbbfe96f6242083ff7c9b0f621477525239c913b4d3df69396320d5dd444 | "\"\"\"pass\"\"\"\nimport re\nimport sys\nfrom intersight.model_utils import ApiTypeError, ModelComp(...TRUNCATED) | "Kw4NCgAAAAAAAAAA5yIAAOMAAAAAAAAAAAAAAAAFAAAAAAAAAPOCAAAAgABSAHQAXgBSAUkBdAFeAFIBSQJ0Al4AUgJJA0gEdAR(...TRUNCATED) | [{"source":"\"\"\"<mask_0>\"\"\"","bytecode":"LOAD_CONST , '<mask_0>' <SEP> STORE_NAME , __doc__"},{(...TRUNCATED) | [{"source":"\"\"\"<mask_0>\"\"\" <SEP> import <mask_21> <SEP> import <mask_22> <SEP> from <mask_4><m(...TRUNCATED) | train |
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"e5f5e0afb2774458a1f7c0325b02c9bbbb4c756d3b84813dab13d59a332765f4c0f97af68842a45d99d7d6616dba1fa6cc3(...TRUNCATED) | "f96420e61700254e0add7d110058be50d7b8161ee987071f620988618fa0440adaf3caf857cc3dccb85636378f45f903fa2(...TRUNCATED) | "pypi-e5f5e0afb2774458a1f7c0325b02c9bbbb4c756d3b84813dab13d59a332765f4c0f97af68842a45d99d7d6616dba1f(...TRUNCATED) | pypi | 3.14 | 8487db5d33f0c9d3b0164bd85b0f90550ef55b3d389703a1c1d2e6464c615ec7 | "\"\"\"pass\"\"\"\nfrom __future__ import annotations\nimport logging\nlog = logging.getLogger(__nam(...TRUNCATED) | "Kw4NCgAAAAAAAAAA4wIAAOMAAAAAAAAAAAAAAAAFAAAAAAAAAfOcAAAAgABSAHQAXgBSAUkBSAJ0Ah8AXgBSAkkDdANdA1AIAAA(...TRUNCATED) | [{"source":"\"\"\"<mask_0>\"\"\"","bytecode":"LOAD_CONST , '<mask_0>' <SEP> STORE_NAME , __doc__"},{(...TRUNCATED) | [{"source":"\"\"\"<mask_0>\"\"\" <SEP> from <mask_3><mask_12> import <mask_6> <SEP> import <mask_13>(...TRUNCATED) | train |
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"ba5c0a6e42272d4cad3c1d2067603e7971c5dccc59687b113ebbf4b782b215b016b50d06caf867f46f612f3ac819b7c44cc(...TRUNCATED) | "ae2da3cd75063e3d837f43130357906b0f862441c7448f91e1429fa632172cd9af4f663db2f27d770aec4bb88fd99416ca9(...TRUNCATED) | "pypi-ba5c0a6e42272d4cad3c1d2067603e7971c5dccc59687b113ebbf4b782b215b016b50d06caf867f46f612f3ac819b7(...TRUNCATED) | pypi | 3.14 | 6751c2b991eb5e06eb47be4d30484932cdcdd0f9cb9d8284fd57673aa2688bbd | "import os\nimport pathlib\nimport openai\nimport yaml\nimport json\nimport asyncio\nfrom tqdm impor(...TRUNCATED) | "Kw4NCgAAAAAAAAAA5wgAAOMAAAAAAAAAAAAAAAAOAAAAAAAAAPOuBQAAgABeAFIBSQB0AF4AUgFJAXQBXgBSAUkCdAJeAFIBSQN(...TRUNCATED) | [{"source":"import <mask_1>","bytecode":"LOAD_SMALL_INT , <mask_0> <SEP> LOAD_CONST , None <SEP> IMP(...TRUNCATED) | [{"source":"import <mask_36> <SEP> import <mask_37> <SEP> import <mask_38> <SEP> import <mask_39> <S(...TRUNCATED) | train |
"a386758949a9d7e04263063bce93126fa86bfcbaa7bea0590d3f2741878cb8a6280aaf722366fa8d514bee48b044bf8c475(...TRUNCATED) | "2a51f8fb8d2ef6776648fa754a9dc1d468a20ee514f4b3e918e6e02bb503fdf2192d22dcdd87815a8fa1f41b6325c134b41(...TRUNCATED) | "pypi-a386758949a9d7e04263063bce93126fa86bfcbaa7bea0590d3f2741878cb8a6280aaf722366fa8d514bee48b044bf(...TRUNCATED) | pypi | 3.14 | 603775f68685bf2af6b71284694b5899a5462d2a7c6321b423873b25ab012c5a | "from ai2_kit.core.artifact import Artifact\nfrom ai2_kit.core.log import get_logger\nfrom typing im(...TRUNCATED) | "Kw4NCgAAAAAAAAAAUgwAAOMAAAAAAAAAAAAAAAAGAAAAAAAAAPMiAQAAgABeAFIBSQBIAXQBHwBeAFICSQJIA3QDHwBeAFIDSQR(...TRUNCATED) | [{"source":"from <mask_0><mask_2> import <mask_1>","bytecode":"LOAD_SMALL_INT , <mask_0> <SEP> LOAD_(...TRUNCATED) | [{"source":"from <mask_0><mask_24> import <mask_13> <SEP> from <mask_0><mask_25> import <mask_14> <S(...TRUNCATED) | train |
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End of preview. Expand in Data Studio
syssec-utd/pylingual-shared-adapter-corpus-v2
Per-version source pools for the Python 3.14 and 3.15 LoRAs of the shared-backbone PyLingual study.
Each row is one source file compiled for exactly one Python version, with every row the PyLingual
converter produced. Validation files are exactly the sources whose canonical hash falls in the
reserved bucket (int(canonical_sha256[:8], 16) % 10 == 0); training files never do.
- Disjoint from the backbone corpus (journal sha256
207467ab130ca1468dcf81c26765cec7626d394d9687b6f128ed427643f0ad03), from everypylingual_eval_datasetv1/v2 source (exclusions sha25679559f4d82e7b1bf5a14eb610eba87007378153bbe2f6e05743007e4abbf9f9f) and from each other, by raw SHA-512, canonical hash and NAS identity - Seed
20261102; sampled from/syssec-nas1/pyc-research/datasets - Code: https://github.com/quinntyx/pylingual branch
feat-shared-backbone-lora, commit87226a491a9ee76670601a6b3e8a37e8187241c5
| Python | Split | Files | PyPI | CSN | Statement rows | Compiler |
|---|---|---|---|---|---|---|
| 3.14 | train | 100000 | 90000 | 10000 | 9378298 | 3.14.6 |
| 3.14 | validation | 1000 | 900 | 100 | 95474 | 3.14.6 |
| 3.15 | train | 100000 | 90000 | 10000 | 9336777 | 3.15.0b2 |
| 3.15 | validation | 1000 | 900 | 100 | 97651 | 3.15.0b2 |
<version>/<split>/accepted.jsonl is the exact journal the trainers hash-check.
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