a]:underline [&>a]:underline-offset-4 [&>a:hover]:text-primary\",\n ", "repo": "OpenCut-app/OpenCut", "span_codepoints": 128, "start": 1947, "suffix": ") {\n return (\n
\n )\n}\n\nexport {\n Empty,\n Empt", "target": " className\n )}\n {...props}\n />\n )\n}\n\nfunction EmptyContent({ className, ...props }: React.ComponentProps<\"div\">"}
{"bin": "8_token_ish", "content_sha256": "e6a3afe46f95ebf1b7e2059c7f0f07a9f8699cae7d7f775def63b542b03ec689", "document_id": "dockur/windows@36d127d8cfdccb007e03a0c2ee579f75685605fc:src/answer.sh", "end": 12631, "example_id": "0001712825d1b6446f145e2bdc1ff8f3c97e7d145bbaa58bf4bb0e135a700835", "language": "shell", "prefix": "fi\n\n if ! tmp=$(mktemp -p /run/assets \".${id}.XXXXXX\"); then\n error \"Failed to create a temporary $type answer file!\"\n return 1\n fi\n\n local expressions\n\n if [ \"$type\" = \"evaluation\" ]; then\n expressions=(\n -e '/
.*<\\/ProductKey", "repo": "dockur/windows", "span_codepoints": 32, "start": 12599, "suffix": "\\/ProductKey>/d'\n )\n else\n expressions=(\n -e '/.*<\\/InstallFrom>/d'\n -e '/.*<\\/ProductKey>/d'\n -e '//,/<\\/InstallFrom>/d'\n -e '//,/<\\/ProductKey>/d'\n )\n fi\n\n if ! sed \"${expr", "target": ">/d'\n -e '//,/<"}
{"bin": "32_token_ish", "content_sha256": "a9cbe88ad1942abf948ad9f3ca3dc064f9d63ed3a0fe95cbecc794f45e2662c9", "document_id": "unitycatalog/unitycatalog@ed504deea31b30c3e7d27e360372077cce04a509:server/src/test/java/io/unitycatalog/server/utils/PopulateTestDatabase.java", "end": 11146, "example_id": "000172aa9e564556ec61b54a66db7ca8ea064c9e9855002a82eb224fd117f9f0", "language": "java", "prefix": "n session = factory.openSession()) {\n Transaction tx = session.beginTransaction();\n session.persist(externalTableInfoDAO);\n session.persist(p11);\n session.persist(p21);\n tx.commit();\n }\n\n // Create external partitioned table.", "repo": "unitycatalog/unitycatalog", "span_codepoints": 128, "start": 11018, "suffix": "/ - first_name\n // - age\n // - country (partition column)\n // All the data in this table are fake and were generated by tool Faker.\n // Partition column has three unique values / partitions.\n // Data is stored in DELTA format.\n System.out", "target": "\n // This table represents an example of how Unity handles partitioned tables.\n // The table contains three columns:\n /"}
{"bin": "8_token_ish", "content_sha256": "bff1a37c65382e95aaf6b69ce0941b4fb00e070421ae28b386642f1d79cb78fd", "document_id": "upstash/context7@b250c2515694eee4b6df4db82fa056df9ed3e306:packages/mcp/src/index.ts", "end": 19728, "example_id": "0001739d015ba3bcadf92562d7a7f3f98116b9699e3013f3ac1d69c2c04b6347", "language": "typescript", "prefix": " // headers, even though the per-tool timeout is much higher.\n const transport = new StreamableHTTPServerTransport({\n sessionIdGenerator: undefined,\n enableJsonResponse: false,\n });\n\n const server = createMcpServer();", "repo": "upstash/context7", "span_codepoints": 32, "start": 19696, "suffix": "\n transport.close();\n server.close();\n });\n\n installTransportArgAliasing(transport);\n await server.connect(transport);\n\n await requestContext.run(context, async () => {\n await transport.handleRequest(r", "target": "\n res.on(\"close\", () => {"}
{"bin": "32_token_ish", "content_sha256": "ac0c1e1489a77d30b7183e060e379f5cbba13f9b6a8beb0cae1a5990ec5ca00c", "document_id": "browser-use/browser-use@0964ad452a9f3fe249042a5ffb235e5f98519b2e:browser_use/llm/ollama/chat.py", "end": 2001, "example_id": "000175a91c1b6d96ff044222fe9f410a4e8407f9c3e849a90954b84912bdb192", "language": "python", "prefix": "tion[str]: ...\n\n\t@overload\n\tasync def ainvoke(self, messages: list[BaseMessage], output_format: type[T], **kwargs: Any) -> ChatInvokeCompletion[T]: ...\n\n\tasync def ainvoke(\n\t\tself, messages: list[BaseMessage], output_format: type[T] | None = None, **kwargs", "repo": "browser-use/browser-use", "span_codepoints": 128, "start": 1873, "suffix": "messages)\n\n\t\ttry:\n\t\t\tif output_format is None:\n\t\t\t\tresponse = await self.get_client().chat(\n\t\t\t\t\tmodel=self.model,\n\t\t\t\t\tmessages=ollama_messages,\n\t\t\t\t\toptions=self.ollama_options,\n\t\t\t\t)\n\n\t\t\t\treturn ChatInvokeCompletion(completion=response.message.content o", "target": ": Any\n\t) -> ChatInvokeCompletion[T] | ChatInvokeCompletion[str]:\n\t\tollama_messages = OllamaMessageSerializer.serialize_messages("}
{"bin": "64_token_ish", "content_sha256": "f11925640560580736567c2764d22f2a3b38131f8a648ba9f694fa0e6f39d437", "document_id": "DataWithBaraa/sql-data-warehouse-project@92406686380cde6eca208c8b43e6fa40ecd26344:tests/quality_checks_silver.sql", "end": 3429, "example_id": "0001775bb70543fc89ed13821fe3f7b64ec5b3b2c394996c08877f61a5b45c47", "language": "sql", "prefix": "t \n OR sls_order_dt > sls_due_dt;\n\n-- Check Data Consistency: Sales = Quantity * Price\n-- Expectation: No Results\nSELECT DISTINCT \n sls_sales,\n sls_quantity,\n sls_price \nFROM silver.crm_sales_details\nWHERE sls_sales != sls_quantity * sls_price\n ", "repo": "DataWithBaraa/sql-data-warehouse-project", "span_codepoints": 256, "start": 3173, "suffix": "=====\n-- Checking 'silver.erp_cust_az12'\n-- ====================================================================\n-- Identify Out-of-Range Dates\n-- Expectation: Birthdates between 1924-01-01 and Today\nSELECT DISTINCT \n bdate \nFROM silver.erp_cust_az12\nWH", "target": " OR sls_sales IS NULL \n OR sls_quantity IS NULL \n OR sls_price IS NULL\n OR sls_sales <= 0 \n OR sls_quantity <= 0 \n OR sls_price <= 0\nORDER BY sls_sales, sls_quantity, sls_price;\n\n-- ==============================================================="}
{"bin": "16_token_ish", "content_sha256": "a1b49fc9a53a294c1dce664aadc988e730fa31a69962fb26bf28faeba060eea0", "document_id": "D4Vinci/Scrapling@07a548362ff904a2837f503ed9d9f6b9dcef0195:scrapling/spiders/spider.py", "end": 11762, "example_id": "000177a09b46001bbc4ffbcc85129b78c6775fee0f77d4ba39905b7404ef0775", "language": "python", "prefix": " one as they are scraped.\n Access `spider.stats` during iteration for real-time statistics.\n\n Note: SIGINT handling for pause/resume is not available in stream mode.\n \"\"\"\n token = set_logger(self.logger)\n try:\n ", "repo": "D4Vinci/Scrapling", "span_codepoints": 64, "start": 11698, "suffix": "crawldir, self._interval)\n async for item in self._engine:\n yield item\n finally:\n self._engine = None\n reset_logger(token)\n if self.log_file:\n for handler in self.logger.handl", "target": " self._engine = CrawlerEngine(self, self._session_manager, self."}
{"bin": "64_token_ish", "content_sha256": "3f0e691dc253a9f329dc0a630983dc2ea5bc1c1f9814d71ea50a66c7451a0dd2", "document_id": "microsoft/markitdown@2e42a01c404629b06892a1bdb5e7bf5261770c40:packages/markitdown/src/markitdown/_markitdown.py", "end": 5533, "example_id": "00017b1d02d1c4743fbc3129855d720001a6bb61c6a57d3d6468a1746beea603", "language": "python", "prefix": " \"/usr/bin\",\n \"/usr/local/bin\",\n \"/opt\",\n \"/opt/bin\",\n \"/opt/local/bin\",\n \"/opt/homebrew/bin\",\n ", "repo": "microsoft/markitdown", "span_codepoints": 256, "start": 5277, "suffix": " # Register converters for successful browsing operations\n # Later registrations are tried first / take higher priority than earlier registrations\n # To this end, the most specific converters should appear below the most generi", "target": " \"C:\\\\Windows\\\\System32\",\n \"C:\\\\Program Files\",\n \"C:\\\\Program Files (x86)\",\n ]\n ):\n self._exiftool_path = candidate\n\n "}
{"bin": "64_token_ish", "content_sha256": "027a493bd355747f514515346e6f509b641e2e4b44923b5ba82ba5fac582a8cd", "document_id": "browser-use/browser-use@0964ad452a9f3fe249042a5ffb235e5f98519b2e:tests/ci/security/test_domain_filtering.py", "end": 12890, "example_id": "000180a1d5f05bb2521618cf29f2bb4c4ba94ffbb10c92d513f9432753bc2d46", "language": "python", "prefix": "wser.watchdogs.security_watchdog import SecurityWatchdog\n\n\t\tbrowser_profile = BrowserProfile(allowed_domains=['example.com'], headless=True, user_data_dir=None)\n\t\tbrowser_session = BrowserSession(browser_profile=browser_profile)\n\t\tevent_bus = EventBus()\n\t\t", "repo": "browser-use/browser-use", "span_codepoints": 256, "start": 12634, "suffix": "watchdog._is_root_domain('site.net') is True\n\n\t\t# Subdomains (more than 1 dot) - should return False\n\t\tassert watchdog._is_root_domain('www.example.com') is False\n\t\tassert watchdog._is_root_domain('mail.example.com') is False\n\t\tassert watchdog._is_root_dom", "target": "watchdog = SecurityWatchdog(browser_session=browser_session, event_bus=event_bus)\n\n\t\t# Simple root domains (1 dot) - should return True\n\t\tassert watchdog._is_root_domain('example.com') is True\n\t\tassert watchdog._is_root_domain('test.org') is True\n\t\tassert "}
{"bin": "64_token_ish", "content_sha256": "0f13b1a10d5b81f30188542997d570c2e1b7c6514cc862fae1a74145aefb8d8f", "document_id": "D4Vinci/Scrapling@07a548362ff904a2837f503ed9d9f6b9dcef0195:scrapling/spiders/request.py", "end": 4138, "example_id": "0001811e37ea493f535528d8c25796a94d260f0bc98281a3f2e18ec5ee56b7b8", "language": "python", "prefix": " tuple(sorted(filtered_kwargs.items()))\n\n if include_headers:\n headers = self._session_kwargs.get(\"headers\") or self._session_kwargs.get(\"extra_headers\") or {}\n processed_headers = {}\n # Some header normalization\n ", "repo": "D4Vinci/Scrapling", "span_codepoints": 256, "start": 3882, "suffix": ", option=orjson.OPT_SORT_KEYS), usedforsecurity=False).digest()\n self._fp = fp\n return fp\n\n def __repr__(self) -> str:\n callback_name = getattr(self.callback, \"__name__\", None) or \"None\"\n return f\" = str::from_utf8(&output.stdout)?\n .lines()\n .filter_map(parse_toolchain_line)\n .collect();\n\n let infos: Vec = futures_util::stream::iter(entries)\n .map(async move |(name, path)| toolchain", "repo": "j178/prek", "span_codepoints": 256, "start": 7213, "suffix": " None\n }\n })\n .collect()\n .await;\n\n Ok(infos)\n }\n\n /// List system-installed Rust toolchains.\n pub(crate) async fn list_system_toolchains(&self) -> Result> {\n ", "target": "_info(name, path).await)\n .buffer_unordered(8)\n .filter_map(async move |result| match result {\n Ok(info) => Some(info),\n Err(e) => {\n warn!(\"Skipping invalid toolchain: {e:#}\");\n "}
{"bin": "64_token_ish", "content_sha256": "e9a7e9eb6b087e60e2fed07e61370fbd1bfca76b16bb95c86170cffedcebff96", "document_id": "DietrichGebert/ponytail@16f29800fd2681bdf24f3eb4ccffe38be3baec6b:benchmarks/robustness-audit.js", "end": 9044, "example_id": "00018c19ec6cd6268ff622433c230273c65d27194fc99ef1c2c01ba172f8ddaa", "language": "javascript", "prefix": " and \"@\" in a' },\n { name: 'url', arity: 1, names: ['validate_url', 'is_valid_url', 'is_url', 'validate', 'is_valid'],\n prompt: 'Write a Python function that validates whether a string is a valid HTTP or HTTPS URL.',\n cases: [[['https://example.com'", "repo": "DietrichGebert/ponytail", "span_codepoints": 256, "start": 8788, "suffix": " p = urlparse(u)\\n return p.scheme in (\"http\",\"https\") and bool(p.netloc)',\n bad: 'from urllib.parse import urlparse\\ndef validate_url(u):\\n return bool(urlparse(u))' },\n { name: 'creditcard', arity: 1, names: ['validate_credit_card', 'is_valid_", "target": "], true], [['http://a.b/c'], true], [['https://x.io/p?q=1'], true], [['garbage'], false], [[''], false], [['example.com'], false], [['ftp://example.com'], false], [['http://'], false]],\n good: 'from urllib.parse import urlparse\\ndef validate_url(u):\\n "}
{"bin": "16_token_ish", "content_sha256": "8546a18bbe8a04fd2d86495a665834aeb952f55c860586210e5f03b43ed95298", "document_id": "OpenCut-app/OpenCut@4d8c49ed0706c4dc145361e01c6b1f1a87cbb863:apps/web/src/components/ui/context-menu.tsx", "end": 8047, "example_id": "000194e11e98367a2ae854875177155019195656bb34855ce2de06a7b759ec20", "language": "typescript", "prefix": "e)}\n {...props}\n />\n )\n}\n\nfunction ContextMenuShortcut({\n className,\n ...props\n}: React.ComponentProps<\"span\">) {\n return (\n \n )\n}\n\nexport {\n ContextMenu,\n ContextMenuTrigger,\n ContextMenuContent,\n ContextMenuItem,\n ContextMenuCheckboxItem,\n ContextMenuRadioItem,\n ContextMenuLabel,\n ContextMenuSeparator,\n C", "target": "text-muted-foreground group-focus/context-menu-item:text-accent-"}
{"bin": "8_token_ish", "content_sha256": "c7b29f83a2da158b5ba141012a008e84236cc3111f22ab4303bf9d49bbdeb7e9", "document_id": "0xPlaygrounds/rig@7f1a4950fce8c275541c58936e877125cd053f14:crates/rig-core/src/memory.rs", "end": 17104, "example_id": "000196ae625e1c188bef211ccbd45fb06f6d0747f15d06d9c601fe1ffdd245cf", "language": "rust", "prefix": "filter_transforms_loaded_messages() {\n let mem = InMemoryConversationMemory::new()\n .with_filter(|msgs: Vec| msgs.into_iter().rev().take(2).collect());\n\n mem.append(\n \"c\",\n vec![user(\"1\"), assistant(\"", "repo": "0xPlaygrounds/rig", "span_codepoints": 32, "start": 17072, "suffix": "\n )\n .await\n .unwrap();\n\n let loaded = mem.load(\"c\").await.unwrap();\n assert_eq!(loaded.len(), 2, \"filter should retain only 2 messages\");\n }\n\n #[tokio::test]\n async fn arc_conversation_memory_forwards_to_inner()", "target": "2\"), user(\"3\"), assistant(\"4\")],"}
{"bin": "64_token_ish", "content_sha256": "443080798372388ca8503e5d13da7c26dd80cec5ecf33246437cefd3f08219ef", "document_id": "j178/prek@438f9c5a6a594b609413da4ad8643423601a771f:crates/prek/src/cli/run/run.rs", "end": 17329, "example_id": "00019a2493031a63656d1fc1b4f92d8efb41c709fe8d74beb7453705ca5e1a54", "language": "rust", "prefix": " .run_project_level(project_runs, input, file_index, clean_baseline)\n .await?;\n let mut stop_after_level = false;\n\n for project_result in project_results {\n stop_after_level |= session.finish_project_run(project", "repo": "j178/prek", "span_codepoints": 256, "start": 17073, "suffix": "impl<'a> ProjectDepthGroups<'a> {\n fn new(projects: &'a [Arc]) -> Self {\n Self { projects, idx: 0 }\n }\n}\n\nimpl<'a> Iterator for ProjectDepthGroups<'a> {\n type Item = &'a [Arc];\n\n fn next(&mut self) -> Option", "target": "_result, show_project_headers)?;\n }\n\n if stop_after_level {\n break;\n }\n }\n\n session.finish(workspace, show_diff_on_failure).await\n}\n\nstruct ProjectDepthGroups<'a> {\n projects: &'a [Arc],\n idx: usize,\n}\n\n"}
{"bin": "8_token_ish", "content_sha256": "3f0e691dc253a9f329dc0a630983dc2ea5bc1c1f9814d71ea50a66c7451a0dd2", "document_id": "microsoft/markitdown@2e42a01c404629b06892a1bdb5e7bf5261770c40:packages/markitdown/src/markitdown/_markitdown.py", "end": 11281, "example_id": "00019ac49a0d512885fd05258c8106e572ec35262bb923fe0845988ab9826967", "language": "python", "prefix": " return self.convert_uri(source, stream_info=stream_info, **_kwargs)\n else:\n return self.convert_local(source, stream_info=stream_info, **kwargs)\n # Path object\n elif isinstance(source, Path):\n ", "repo": "microsoft/markitdown", "span_codepoints": 32, "start": 11249, "suffix": ", stream_info=stream_info, **kwargs)\n # Request response\n elif isinstance(source, requests.Response):\n return self.convert_response(source, stream_info=stream_info, **kwargs)\n # Binary stream\n elif (\n hasat", "target": "return self.convert_local(source"}
{"bin": "8_token_ish", "content_sha256": "d5426d932b8f49c499da40a69b8b75b3f66055136cc701832bb40b9d33221fd6", "document_id": "microsoft/markitdown@2e42a01c404629b06892a1bdb5e7bf5261770c40:packages/markitdown-ocr/src/markitdown_ocr/_pdf_converter_with_ocr.py", "end": 12866, "example_id": "00019e2349eef4d6ec801403ef25b46e9b1357d34fcebede68e6a840877acfce", "language": "python", "prefix": " page_num: Page number (1-indexed)\n\n Returns:\n List of image info dicts with 'stream', 'bbox', 'name', 'y_pos'\n \"\"\"\n images = []\n\n try:\n pdf_bytes.seek(0)\n with pdfplumber.open(pdf_bytes) as pdf:", "repo": "microsoft/markitdown", "span_codepoints": 32, "start": 12834, "suffix": "len(pdf.pages):\n page = pdf.pages[page_num - 1] # 0-indexed\n images = _extract_images_from_page(page)\n except Exception:\n pass\n\n # Sort by vertical position (top to bottom)\n images.sort", "target": "\n if page_num <= "}
{"bin": "8_token_ish", "content_sha256": "cb3d208f51c444f5138a34fef6e37356f75471e10c238df4ee018e7b3d896a6c", "document_id": "browser-use/browser-use@0964ad452a9f3fe249042a5ffb235e5f98519b2e:tests/ci/test_browser_use_skill_install_docs.py", "end": 2848, "example_id": "00019eab1322d7d6ca994bad03353a06b272d0ca7b2eec7923e9ae5bd1b25ac7", "language": "python", "prefix": "\n\tenv['PYTHONPATH'] = os.pathsep.join(part for part in (str(ROOT), env.get('PYTHONPATH', '')) if part)\n\tenv['UV_TOOL_INSTALL_ARGS_FILE'] = str(uv_args)\n\n\tresult = subprocess.run(\n\t\t[sys.executable, '-m', 'browser_use.cli', 'skill', 'install'],\n\t\tcwd=ROOT,\n", "repo": "browser-use/browser-use", "span_codepoints": 32, "start": 2816, "suffix": ",\n\t\ttext=True,\n\t\ttimeout=10,\n\t)\n\n\tassert result.returncode == 0, result.stderr\n\tassert uv_args.read_text(encoding='utf-8') == 'tool install --python 3.12 --upgrade --force browser-use'\n\texpected = (\n\t\t'---\\n'\n\t\t'name: browser-use\\n'\n\t\t'description: \"Direct", "target": "\t\tenv=env,\n\t\tcapture_output=True"}
{"bin": "16_token_ish", "content_sha256": "a9f203c76c3a7fcbff7d6b23b9f36e1f3fa9fa21a02f1998003a0710ca39e608", "document_id": "Fission-AI/OpenSpec@19d41714c8b790488732687443713e406ef5aeef:test/core/completions/installers/powershell-installer.test.ts", "end": 25476, "example_id": "0001a0c3df3128bcd1fd6231bd56ccba20580d693948557540ff72c09dff082c", "language": "typescript", "prefix": "ofilePath, '# My profile\\n');\n\n const result = await installer.configureProfile(mockScriptPath);\n expect(result).toBe(true);\n\n const raw = await fs.readFile(profilePath);\n expect(raw[0]).toBe(0xef);\n expect(raw[1]).toBe(0xbb);\n ", "repo": "Fission-AI/OpenSpec", "span_codepoints": 64, "start": 25412, "suffix": "(3).toString('utf-8');\n expect(content).toContain('# My profile');\n expect(content).toContain('# OPENSPEC:START');\n });\n\n it('should skip UTF-16 BE profile and leave it unchanged', async () => {\n delete process.env.OPENSPEC_NO_AUTO_CON", "target": " expect(raw[2]).toBe(0xbf);\n\n const content = raw.subarray"}
{"bin": "32_token_ish", "content_sha256": "b3ad41b0689c17cd7c1de3e0a08f5011bda7d693370008413492e2125b91773f", "document_id": "henrygd/beszel@d3a1d61955b0e45fb6b6c76e3ef970cb6518a7e1:agent/disk_test.go", "end": 4610, "example_id": "0001a87218e35b65426753fb2b2ca2830c550ed06deaf5d12695f9c47f70072e", "language": "go", "prefix": "\tdiskIoCounters: map[string]disk.IOCountersStat{\n\t\t\t\t\t\"ada0\": {Name: \"ada0\", ReadBytes: 1000, WriteBytes: 1000},\n\t\t\t\t},\n\t\t\t},\n\t\t)\n\n\t\tassert.True(t, ok)\n\t\tassert.Equal(t, \"ada0\", key)\n\t\tassert.True(t, stats.Root)\n\t\tassert.Equal(t, \"/\", stats.Mountpoint)\n\t})", "repo": "henrygd/beszel", "span_codepoints": 128, "start": 4482, "suffix": "]*system.FsStats{},\n\t\t\t\"overlay\",\n\t\t\t\"/\",\n\t\t\ttrue,\n\t\t\t\"\",\n\t\t\tfsRegistrationContext{\n\t\t\t\tfilesystem: \"nvme0n1p2\",\n\t\t\t\tisWindows: false,\n\t\t\t\tdiskIoCounters: map[string]disk.IOCountersStat{\n\t\t\t\t\t\"nvme0n1\": {Name: \"nvme0n1\", ReadBytes: 1000, WriteBytes: 1000}", "target": "\n\n\tt.Run(\"uses filesystem setting as root fallback\", func(t *testing.T) {\n\t\tkey, _, ok := registerFilesystemStats(\n\t\t\tmap[string"}
{"bin": "16_token_ish", "content_sha256": "37dea31db4757ee41e18bf6e82526d2c4e421cd01cf03ba56b2f4a0f64b26cc7", "document_id": "EpicGames/raddebugger@78d12eb914378d8552b31c501c12e1c202356024:src/pdb/pdb_parse.c", "end": 1595, "example_id": "0001aeb9b55ef5f0b7c749096853185a783cb0edfa9582e5db10e073a4d63f76", "language": "c", "prefix": "names_len_off + 4;\n U32 names_base_opl = names_base_off + names_len;\n \n // table layout: hash table\n U32 hash_table_count_off = names_base_opl;\n U32 hash_table_max_off = hash_table_count_off + 4;\n \n U32 hash_table_count =", "repo": "EpicGames/raddebugger", "span_codepoints": 64, "start": 1531, "suffix": " 4 <= data.size){\n hash_table_count = *(U32*)(data.str + hash_table_count_off);\n hash_table_max = *(U32*)(data.str + hash_table_max_off);\n }\n \n // table layout: words\n U32 num_present_words_off = hash_table_max_off + 4;\n ", "target": " 0;\n U32 hash_table_max = 0;\n if (hash_table_max_off +"}
{"bin": "64_token_ish", "content_sha256": "9efd8c49e5b4bf7132f59fb450ea26db8ef4b27ada37df95ae1e1761fd8231d0", "document_id": "D4Vinci/Scrapling@07a548362ff904a2837f503ed9d9f6b9dcef0195:scrapling/core/shell.py", "end": 25642, "example_id": "0001b1298a3165d4fa6e19ce5eaa6e6fa12b102ec258772e47a4c2d119c92a61", "language": "python", "prefix": "lse cast(Selectors, page.css(css_selector))\n for page in pages:\n match extraction_type:\n case \"markdown\":\n yield cls._convert_to_markdown(page.html_content)\n case \"html\"", "repo": "D4Vinci/Scrapling", "span_codepoints": 256, "start": 25386, "suffix": " )\n for s in (\n \"\\n\",\n \"\\r\",\n \"\\t\",\n \" \",\n ):\n # Remove consecutive", "target": ":\n yield page.html_content\n case \"text\":\n txt_content = page.get_all_text(\n strip=True, ignore_tags=(\"script\", \"style\", \"noscript\", \"svg\", \"iframe\")\n "}
{"bin": "16_token_ish", "content_sha256": "f759cbf40824426107b527127b7a79b6efb613fc85f0c162d4a24cad7789d7ef", "document_id": "microsoft/markitdown@2e42a01c404629b06892a1bdb5e7bf5261770c40:packages/markitdown/src/markitdown/__main__.py", "end": 3679, "example_id": "0001b154b03f755e757ff38d9424e634c36d75371b62d83c99ce2eb1ccffde4d", "language": "python", "prefix": " parser.add_argument(\n \"--list-plugins\",\n action=\"store_true\",\n help=\"List installed 3rd-party plugins. Plugins are loaded when using the -p or --use-plugin option.\",\n )\n\n parser.add_argument(\n \"--keep-data-uris\",\n ", "repo": "microsoft/markitdown", "span_codepoints": 64, "start": 3615, "suffix": "encoded images) in the output. By default, data URIs are truncated.\",\n )\n\n parser.add_argument(\"filename\", nargs=\"?\")\n args = parser.parse_args()\n\n # Parse the extension hint\n extension_hint = args.extension\n if extension_hint is not None", "target": " action=\"store_true\",\n help=\"Keep data URIs (like base64-"}
{"bin": "32_token_ish", "content_sha256": "24179f119e6fef8863e7a291d43e708a7917286c42c8682df5d5d3302f4ab8c2", "document_id": "steipete/agent-scripts@bb3688355a4c1894dd53b4ed867d1600918fadf0:skills/npm/scripts/reserve-packages.sh", "end": 1410, "example_id": "0001b189a89a84bd87332fdf2c440f8b60620926ba70253305beb4477f2f89ec", "language": "shell", "prefix": "t}\"\n shift 2\n ;;\n --item)\n ITEM=\"${2:?missing item}\"\n ITEM_EXPLICIT=1\n shift 2\n ;;\n --account)\n ACCOUNT=\"${2:?missing account}\"\n shift 2\n ;;\n -h | --help)\n usage\n exit 0\n ;;\n --)\n ", "repo": "steipete/agent-scripts", "span_codepoints": 128, "start": 1282, "suffix": ";;\n *)\n PACKAGES+=(\"$1\")\n shift\n ;;\n esac\ndone\n\n# Desktop fallback keeps the legacy item name unless one was named explicitly.\nif [ -n \"$ACCOUNT\" ] && [ \"$ITEM_EXPLICIT\" -eq 0 ]; then\n ITEM=\"npmjs\"\nfi\n\nif [ \"${#PACKAGES[@]}\" -eq 0 ]; th", "target": " shift\n PACKAGES+=(\"$@\")\n break\n ;;\n -*)\n echo \"unknown flag: $1\" >&2\n usage >&2\n exit 2\n "}
{"bin": "16_token_ish", "content_sha256": "b3a0c69c32b557a7b1dd00b93eb466752d5ffbc6da40065dfebc1d6d27b25795", "document_id": "jackwener/OpenCLI@5256711a25458e537c5a63d2a6f9c7fd36d0d1eb:clis/1688/download.js", "end": 1731, "example_id": "0001b9d95a79302ab075a10a4a722719875867d7f61421302470ce0ee53dc441", "language": "javascript", "prefix": " name: 'download',\n access: 'read',\n description: '批量下载 1688 商品页可提取的图片和视频素材',\n domain: 'www.1688.com',\n strategy: Strategy.COOKIE,\n args: [\n {\n name: 'input',\n required: true,\n positional: true,\n ", "repo": "jackwener/OpenCLI", "span_codepoints": 64, "start": 1667, "suffix": "\n { name: 'output', default: './1688-downloads', help: '输出目录' },\n ],\n columns: ['index', 'type', 'status', 'size'],\n func: async (page, kwargs) => {\n const assets = await extractAssetsForInput(page, String(kwargs.input ?? ''));\n ", "target": " help: '1688 商品 URL 或 offer ID(如 887904326744)',\n },"}
{"bin": "32_token_ish", "content_sha256": "b599f78a00beae75851f82323500929bc374b82d8b697e18a7f33febf782c222", "document_id": "jackwener/OpenCLI@5256711a25458e537c5a63d2a6f9c7fd36d0d1eb:clis/xiaoe/courses.js", "end": 3985, "example_id": "0001c201cc003ed80057ffef4ee68162229cfe989b17051832f21631f9df764f", "language": "javascript", "prefix": "ts;\n})()`;\n}\n\nasync function getXiaoeCourses(page) {\n let rows;\n try {\n await page.goto('https://study.xiaoe-tech.com/', { waitUntil: 'load', settleMs: 8000 });\n rows = await page.evaluate(buildCoursesScript());\n } catch (error) {\n ", "repo": "jackwener/OpenCLI", "span_codepoints": 128, "start": 3857, "suffix": " `Failed to list xiaoe courses: ${message}`,\n 'page may not have rendered or auth may be required',\n );\n }\n if (!Array.isArray(rows) || rows.length === 0) {\n throw new EmptyResultError(\n 'xiaoe/courses',\n ", "target": " const message = error instanceof Error ? error.message : String(error);\n throw new CommandExecutionError(\n "}
{"bin": "32_token_ish", "content_sha256": "4a917370dfb68dcf981252756ee4ff2e2915a27993a583dd0d43e61977a62609", "document_id": "Fission-AI/OpenSpec@19d41714c8b790488732687443713e406ef5aeef:src/commands/store.ts", "end": 16282, "example_id": "0001c5c640409b6332fc0139f537ce593ce4294398e982400fac2668307c1ad3", "language": "typescript", "prefix": " error\n );\n }\n }\n\n async unregister(id: string, options: StoreJsonOptions = {}): Promise {\n try {\n const payload = toCleanupOutput(await unregisterStore({ id }));\n\n if (options.json) {\n printJson(payload);\n ", "repo": "Fission-AI/OpenSpec", "span_codepoints": 128, "start": 16154, "suffix": " options.json,\n { store: null, registry: null, files: null, status: [] },\n error\n );\n }\n }\n\n async remove(id: string, options: StoreRemoveOptions = {}): Promise {\n try {\n const target = await prepareStoreCleanup({ id ", "target": " return;\n }\n\n printCleanupHuman('Unregistered store', payload);\n } catch (error) {\n this.handleFailure(\n "}
{"bin": "8_token_ish", "content_sha256": "a2aed2930510f336d4c741954ba889652e6d51fa7896e117c1928cc2f08be559", "document_id": "j178/prek@438f9c5a6a594b609413da4ad8643423601a771f:crates/prek/src/languages/python/uv.rs", "end": 8561, "example_id": "0001d8623d53091e1c2247271d12e146d458cff3a0d04ffd9be7a2f178966f1e", "language": "rust", "prefix": "e'll fall back to simple API approach\n _ => return self.install_from_simple_api(store, target, source).await,\n };\n\n debug!(\"Fetching uv metadata from: {}\", api_url);\n let response = REQWEST_CLIENT\n .get(&api_url)\n", "repo": "j178/prek", "span_codepoints": 32, "start": 8529, "suffix": "/*\")\n .send()\n .await\n .and_then(reqwest::Response::error_for_status)\n .with_context(|| format!(\"Failed to fetch uv metadata from PyPI at {api_url}\"))?;\n\n let metadata: serde_json::Value = response.json().", "target": " .header(\"Accept\", \"*"}
{"bin": "16_token_ish", "content_sha256": "a4cb101371d1dc25246d0a71f0c6e85ec2291d0c3c9fa0a9dbaf267bc5f38914", "document_id": "microsoft/markitdown@2e42a01c404629b06892a1bdb5e7bf5261770c40:packages/markitdown-ocr/src/markitdown_ocr/_pptx_converter_with_ocr.py", "end": 5472, "example_id": "0001dfb8590035c6892b1a5f377ccd73b50b5a2cdd887b56d88802069767a037", "language": "python", "prefix": "shape.has_text_frame:\n if shape == title:\n md_content += \"# \" + shape.text.lstrip() + \"\\\\n\"\n else:\n md_content += shape.text + \"\\\\n\"\n\n # Group Shapes\n ", "repo": "microsoft/markitdown", "span_codepoints": 64, "start": 5408, "suffix": "GROUP:\n sorted_shapes = sorted(\n shape.shapes,\n key=lambda x: (\n float(\"-inf\") if not x.top else x.top,\n float(\"-inf\") if not x.left else", "target": " if shape.shape_type == pptx.enum.shapes.MSO_SHAPE_TYPE."}
{"bin": "8_token_ish", "content_sha256": "ad9dcc71789a56c70695c623f4be10a42594d43505ce3a6fff323ee7743ec106", "document_id": "EpicGames/raddebugger@78d12eb914378d8552b31c501c12e1c202356024:src/linker/pdb_ext/pdb_builder.c", "end": 84779, "example_id": "0001e20c114eecd5a7fdba265b3e8b7a1c3296bb2b5d55f46c4164aed065f7fa", "language": "c", "prefix": "ush_array_no_zero(arena, U16, mod_list.count);\n task.source_file_name_offset_arr = source_file_name_offsets_arr;\n tp_for_parallel(tp, 0, mod_arr_count, dbi_build_file_info_assign_file_offsets_task, &task);\n\n // pack strings\n String8 string_buffer = cv_", "repo": "EpicGames/raddebugger", "span_codepoints": 32, "start": 84747, "suffix": ", string_ht);\n\n // layout file info sections\n String8List file_info_srl = {0};\n str8_serial_begin(arena, &file_info_srl);\n str8_serial_push_u16(arena, &file_info_srl, mod_count16);\n str8_serial_push_u16(arena, &file_info_srl, total_source_file_count16", "target": "pack_string_hash_table(arena, tp"}
{"bin": "32_token_ish", "content_sha256": "5a5272472557744e1616060b62948523e7c1710eee94906d9d0c4d369bdaa756", "document_id": "OpenCut-app/OpenCut@4d8c49ed0706c4dc145361e01c6b1f1a87cbb863:apps/web/src/components/ui/calendar.tsx", "end": 6897, "example_id": "0001e22249f32dc42c0e36c74d263473a2556f9bc9dd7db71fcb9fff45476994", "language": "typescript", "prefix": "\n className,\n day,\n modifiers,\n locale,\n ...props\n}: React.ComponentProps & { locale?: Partial }) {\n const defaultClassNames = getDefaultClassNames()\n\n const ref = React.useRef(null)\n React.useEffect(() ", "repo": "OpenCut-app/OpenCut", "span_codepoints": 128, "start": 6769, "suffix": " size=\"icon\"\n data-day={day.date.toLocaleDateString(locale?.code)}\n data-selected-single={\n modifiers.selected &&\n !modifiers.range_start &&\n !modifiers.range_end &&\n !modifiers.range_middle\n }\n data-range-", "target": "=> {\n if (modifiers.focused) ref.current?.focus()\n }, [modifiers.focused])\n\n return (\n