Datasets:
Tasks:
Text Generation
Formats:
parquet
Sub-tasks:
language-modeling
Languages:
Danish
Size:
10M - 100M
ArXiv:
DOI:
License:
| from pathlib import Path | |
| import pandas as pd | |
| from dynaword.datasheet import DataSheet, human_readable_large_int | |
| from dynaword.paths import repo_path | |
| main_sheet = DataSheet.load_from_path(repo_path / "README.md") | |
| _datasets = [ | |
| cfg["config_name"] # type: ignore | |
| for cfg in main_sheet.frontmatter["configs"] # type: ignore | |
| if cfg["config_name"] != "default" # type: ignore | |
| ] | |
| DEFAULT_LICENSE_REFERENCES = """[CC-0]: https://creativecommons.org/publicdomain/zero/1.0/legalcode.en | |
| [CC-BY-SA 4.0]: https://creativecommons.org/licenses/by-sa/4.0/deed.en | |
| [Apache 2.0]: https://www.apache.org/licenses/LICENSE-2.0 | |
| """ | |
| def create_license_references() -> str: | |
| license_references = DEFAULT_LICENSE_REFERENCES | |
| for dataset in _datasets: | |
| dataset_path = repo_path / "data" / dataset | |
| readme_path = dataset_path / f"{dataset_path.name}.md" | |
| sheet = DataSheet.load_from_path(readme_path) | |
| if sheet.license == "other": | |
| license_name = sheet.frontmatter["license_name"] | |
| license_references += f"[{license_name}]: ./data/{dataset_path.name}/{dataset_path.name}.md#license-information\n" | |
| return license_references | |
| def create_dataset_readme_references(): | |
| readme_references = "" | |
| for dataset in _datasets: | |
| dataset_path = repo_path / "data" / dataset | |
| readme_references += ( | |
| f"[{dataset_path.name}]: data/{dataset_path.name}/{dataset_path.name}.md\n" | |
| ) | |
| return readme_references | |
| def create_overview_table( | |
| repo_path: Path = repo_path, | |
| add_readable_tokens: bool = True, | |
| add_total_row: bool = True, | |
| add_readme_references: bool = True, | |
| ) -> pd.DataFrame: | |
| table = { | |
| "Source": [], | |
| "Source with link": [], | |
| "Description": [], | |
| "Domain": [], | |
| "N. Tokens": [], | |
| "License": [], | |
| } | |
| for dataset in _datasets: | |
| dataset_path = repo_path / "data" / dataset | |
| readme_path = dataset_path / f"{dataset_path.name}.md" | |
| sheet = DataSheet.load_from_path(readme_path) | |
| desc_stats = sheet.get_descritive_stats() | |
| main_domain = sheet.domains[0] if sheet.domains else "" | |
| table["Source"] += [f"{dataset_path.name}"] | |
| table["Source with link"] += [f"[{dataset_path.name}]"] | |
| table["License"] += [f"[{sheet.license_name}]"] | |
| table["Domain"] += [main_domain] | |
| table["Description"] += [sheet.short_description] | |
| table["N. Tokens"] += [desc_stats.number_of_tokens] | |
| df = pd.DataFrame.from_dict(table) | |
| df = df.sort_values("N. Tokens", ascending=False) | |
| if add_total_row: | |
| total_row = { | |
| "Source": "**Total**", | |
| "Source with link": "**Total**", | |
| "Domain": "", | |
| "License": "", | |
| "Description": "", | |
| "N. Tokens": sum(table["N. Tokens"]), | |
| } | |
| df = pd.concat( | |
| [ | |
| df, | |
| pd.DataFrame([total_row]), | |
| ], | |
| ignore_index=True, | |
| ) | |
| if add_readme_references: | |
| # replace Source with Source with link | |
| df["Source"] = df["Source with link"] | |
| df = df.drop(columns=["Source with link"]) | |
| else: | |
| # remove Source with link | |
| df = df.drop(columns=["Source with link"]) | |
| if add_readable_tokens: | |
| df["N. Tokens"] = df["N. Tokens"].apply(human_readable_large_int) | |
| return df | |
| def create_overview_table_str(repo_path: Path = repo_path) -> str: | |
| main_table = create_overview_table(repo_path) | |
| readme_references = create_dataset_readme_references() | |
| license_references = create_license_references() | |
| package = f"{main_table.to_markdown(index=False)}\n\n{readme_references}\n\n{license_references}\n\n" | |
| return package | |