reformatted tests for datasheets

data/wiki/descriptive_stats.json

@@ -2,6 +2,5 @@
   "number_of_samples": 264433,
   "average_document_length": 1386.9819878759458,
   "number_of_tokens": 122002149,
-  "language": "dan, dansk, Danish",
-  "revision": "341a0162905ca4848fc840d941edfd0a6d1b2314"
+  "revision": "8000194fcf5dfc965cf377344a0acbe6fc8df8af"
 }

data/wiki/wiki.md

@@ -1,20 +1,20 @@
 ---
 pretty_name: Wikipedia
 language:
-  - da
+- da
 license: cc0-1.0
 license_name: CC-0
 size_categories:
-  - 100k-1M
+- 100k-1M
 task_categories:
-  - text-generation
-  - fill-mask
+- text-generation
+- fill-mask
 task_ids:
-  - language-modeling
+- language-modeling
 source_datasets:
-  - danish-foundation-models/danish-gigaword
+- danish-foundation-models/danish-gigaword
 domains:
-  - Encyclopedic
+- Encyclopedic
 ---
 
 # Dataset Card for Wikipedia
@@ -31,6 +31,7 @@ You can read more about wikipedia on their [about](https://en.wikipedia.org/wiki
 
 <!-- START-DESC-STATS -->
 - **Language**: dan, dansk, Danish
+- **Domains**: ['Encyclopedic']
 - **Number of samples**: 264.43K
 - **Number of tokens (Llama 3)**: 122.00M
 - **Average document length (characters)**: 1386.98
@@ -59,22 +60,20 @@ An example from the dataset looks as follows.
 
 An entry in the dataset consists of the following fields:
 
+- `id` (`str`): An unique identifier for each document.
 - `text`(`str`): The content of the document.
 - `source` (`str`): The source of the document (see [Source Data](#source-data)).
-- `id` (`str`): An unique identifier for each document.
 - `added` (`str`): An date for when the document was added to this collection.
 - `created` (`str`): An date range for when the document was originally created.
-- `license` (`str`): The license of the document. The licenses vary according to the source. 
-- `domain` (`str`): The domain of the source
-- `metadata/source-pretty` (`str`): The long form version of the short-form source name
-- `metadata/*`: Potentially additional metadata
+- `token_count` (`int`): The number of tokens in the sample computed using the Llama 8B tokenizer
 <!-- END-SAMPLE -->
 
 ### Dataset Statistics
 
 <!-- START-DATASET PLOTS -->
+<p align="center">
 <img src="./images/dist_document_length.png" width="600" style="margin-right: 10px;" />
-<img>
+</p>
 <!-- END-DATASET PLOTS -->
 
 

src/dynaword/datasheet.py

@@ -50,6 +50,7 @@ An entry in the dataset consists of the following fields:
 - `token_count` (`int`): The number of tokens in the sample computed using the Llama 8B tokenizer
 """
 
+
 def human_readable_large_int(value: int) -> str:
     thresholds = [
         (1_000_000_000, "B"),
@@ -127,13 +128,14 @@ class DataSheet(BaseModel):
 
             if next_is_end_section:
                 end_header = _header
+                break
 
         if next_is_end_section is None:
             raise ValueError(f"The header '{header}' is not found in the text.")
 
         start_idx = self.body.find(header)
         if end_header:
-            end_idx = self.body.find(header)
+            end_idx = self.body[start_idx:].find(end_header) + start_idx
         else:
             end_idx = len(self.body)
 
@@ -149,7 +151,7 @@ class DataSheet(BaseModel):
                 for level in levels:
                     if text.startswith("#" * level):
                         return True
-            return True
+            return False
 
         return [line for line in self.body.splitlines() if __contains_level(line)]
 

src/dynaword/tables.py

@@ -6,10 +6,9 @@ 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")
-frontmatter, _ = main_sheet.frontmatter
 _datasets = [
     cfg["config_name"]  # type: ignore
-    for cfg in frontmatter["configs"]  # type: ignore
+    for cfg in main_sheet.frontmatter["configs"]  # type: ignore
     if cfg["config_name"] != "default"  # type: ignore
 ]
 

src/dynaword/update_descriptive_statistics.py

@@ -27,10 +27,9 @@ from dynaword.tables import create_overview_table_str
 logger = logging.getLogger(__name__)
 
 main_sheet = DataSheet.load_from_path(repo_path / "README.md")
-frontmatter, _ = main_sheet.frontmatter
 _datasets = [
     cfg["config_name"]  # type: ignore
-    for cfg in frontmatter["configs"]  # type: ignore
+    for cfg in main_sheet.frontmatter["configs"]  # type: ignore
     if cfg["config_name"] != "default"  # type: ignore
 ]
 
@@ -81,6 +80,8 @@ def update_dataset(
         package = create_overview_table_str()
         sheet.body = sheet.replace_tag(package=package, tag="MAIN TABLE")
 
+    sheet.write_to_path()
+
 
 def create_parser():
     parser = argparse.ArgumentParser(

src/tests/test_dataset_schema.py

@@ -19,32 +19,6 @@ def test_sample_schema(dataset_name: str):
     SampleSchema(**sample)
 
 
-@pytest.mark.parametrize("dataset_name", DATASET_NAMES)
-def test_dataset_readme(dataset_name: str):
-    """tests that the dataset frontmatter and markdown follows the correct format."""
-
-    readme = repo_path / "data" / dataset_name / f"{dataset_name}.md"
-
-    # ensure that it can be loaded as a datasheet
-    ds_sheet = DataSheet.load_from_path(readme)  # fill fail if format is not correct
-
-    # ensure tags:
-    body = ds_sheet.body
-    tags = [v.value for v in DEFAULT_SECTION_TAGS]
-    for tag in tags:
-        ds_sheet.get_tag_idx(tag)
-
-    h2_headings = {line for line in body.splitlines() if line.startswith("## ")}
-
-    if ds_sheet.license == "other":  # ensure description of underspecified licenses
-        assert "## License Information" in h2_headings
-
-    # required headings
-    req_h2_headings = ["## Dataset Description", "## Additional Information"]
-    for req_h2 in req_h2_headings:
-        assert req_h2 in h2_headings
-    pass
-
 
 @pytest.mark.parametrize("dataset_name", DATASET_NAMES)
 def test_dataset_folder_structure(dataset_name: str):

src/tests/test_datasheets.py

@@ -0,0 +1,47 @@
+import pytest
+
+from dynaword.datasheet import DEFAULT_SECTION_TAGS, DataSheet
+from dynaword.paths import repo_path
+
+from .conftest import DATASET_NAMES
+
+
+@pytest.mark.parametrize("dataset_name", DATASET_NAMES)
+def test_datasheet_load(dataset_name: str):
+    """tests that the dataset frontmatter and markdown follows the correct format."""
+
+    readme = repo_path / "data" / dataset_name / f"{dataset_name}.md"
+    ds_sheet = DataSheet.load_from_path(readme)  # will fail if format is not correct
+
+
+@pytest.mark.parametrize("dataset_name", DATASET_NAMES)
+def test_datasheet_content_tags(dataset_name: str):
+    readme = repo_path / "data" / dataset_name / f"{dataset_name}.md"
+    ds_sheet = DataSheet.load_from_path(readme)
+
+    # ensure tags:
+    body = ds_sheet.body
+    tags = [v.value for v in DEFAULT_SECTION_TAGS]
+    for tag in tags:
+        ds_sheet.get_tag_idx(tag)
+
+
+@pytest.mark.parametrize("dataset_name", DATASET_NAMES)
+def test_datasheet_license_info(dataset_name: str):
+    """Ensure that license information is present is license is other"""
+    readme = repo_path / "data" / dataset_name / f"{dataset_name}.md"
+    ds_sheet = DataSheet.load_from_path(readme)
+
+    if ds_sheet.license == "other":  # ensure description of underspecified licenses
+        assert ds_sheet.license_information.strip()
+        assert ds_sheet.license_name
+
+
+@pytest.mark.parametrize("dataset_name", DATASET_NAMES)
+def test_datasheet_required_headings(dataset_name: str):
+    readme = repo_path / "data" / dataset_name / f"{dataset_name}.md"
+    ds_sheet = DataSheet.load_from_path(readme)
+
+    req_h2_headings = ["## Dataset Description", "## Additional Information"]
+    for req_h2 in req_h2_headings:
+        assert ds_sheet.get_section_by_header(req_h2)