Datasets:
Tasks:
Text Generation
Formats:
parquet
Sub-tasks:
language-modeling
Languages:
Danish
Size:
1M - 10M
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 | |