Parallelize data download (#9)

- Add baseline ranges (1ff41f907be30dcb6bb3d7f43529651007469018)
- Refactor code with baseline ranges (7897dd5d9b0410681e252b2b11635e009b9397b0)
- Parallelize with zipped file_list and archive (de237a59246cf5f5e69a50c983f6dbc3c8a06691)
- Join baseline and incremental paths (cff04b2d5f500ef9d9a37a79c7aaeba13c14412d)

open_access.py

@@ -57,6 +57,11 @@ _SUBSETS = {
 }
 _BASELINE_DATE = "2022-12-17"
 _BASELINE_MAX_RANGE = 10
+_BASELINE_RANGES = {
+    "commercial": range(_BASELINE_MAX_RANGE),
+    "non_commercial": range(1, _BASELINE_MAX_RANGE),  # non-commercial PMC000xxxxxx baseline does not exist
+    "other": range(_BASELINE_MAX_RANGE),
+}
 
 
 class OpenAccessConfig(datasets.BuilderConfig):
@@ -71,7 +76,8 @@ class OpenAccessConfig(datasets.BuilderConfig):
         """
         subsets = [subsets] if isinstance(subsets, str) else subsets
         super().__init__(
-            name="+".join(subsets), **kwargs,
+            name="+".join(subsets),
+            **kwargs,
         )
         self.subsets = subsets if self.name != "all" else list(_SUBSETS.keys())
 
@@ -106,36 +112,16 @@ class OpenAccess(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
 
-        incremental_paths = {
-            "incremental_file_lists": [],
-            "incremental_archives": []
-            }
-        baseline_file_lists = []
-        baseline_archives = []
-
+        paths = []
         for subset in self.config.subsets:
             url = _URL.format(subset=_SUBSETS[subset])
             basename = f"{_SUBSETS[subset]}_txt."
             # Baselines
-            baselines = [f"PMC00{i}xxxxxx.baseline.{_BASELINE_DATE}" for i in range(_BASELINE_MAX_RANGE)]
-            # baseline_urls = {
-            #     "baseline_file_lists": [f"{url}{basename}{baseline}.filelist.csv" for baseline in baselines],
-            #     "baseline_archives": [f"{url}{basename}{baseline}.tar.gz" for baseline in baselines],
-            # }
-            # baseline_paths = dl_manager.download(baseline_urls)
-            for baseline in baselines:
-                baseline_file_list_url = f"{url}{basename}{baseline}.filelist.csv"
-                try:
-                    baseline_file_list = dl_manager.download(baseline_file_list_url)
-                except FileNotFoundError:  # non-commercial PMC000xxxxxx baseline does not exist
-                    continue
-                baseline_archive_url = f"{url}{basename}{baseline}.tar.gz"
-                try:
-                    baseline_archive = dl_manager.download(baseline_archive_url)
-                except FileNotFoundError:
-                    continue
-                baseline_file_lists.append(baseline_file_list)
-                baseline_archives.append(baseline_archive)
+            baselines = [f"PMC00{i}xxxxxx.baseline.{_BASELINE_DATE}" for i in _BASELINE_RANGES[subset]]
+            baseline_urls = [
+                (f"{url}{basename}{baseline}.filelist.csv", f"{url}{basename}{baseline}.tar.gz")
+                for baseline in baselines
+            ]
             # Incremental
             date_delta = datetime.date.today() - datetime.date.fromisoformat(_BASELINE_DATE)
             incremental_dates = [
@@ -143,75 +129,40 @@ class OpenAccess(datasets.GeneratorBasedBuilder):
                 for i in range(date_delta.days)
             ]
             incrementals = [f"incr.{date}" for date in incremental_dates]
-            incremental_urls = {
-                "incremental_file_lists": [
-                    f"{url}{basename}{incremental}.filelist.csv" for incremental in incrementals
-                ],
-                "incremental_archives": [f"{url}{basename}{incremental}.tar.gz" for incremental in incrementals],
-            }
-            paths = dl_manager.download(incremental_urls)
-            incremental_paths["incremental_file_lists"].extend(paths["incremental_file_lists"])
-            incremental_paths["incremental_archives"].extend(paths["incremental_archives"])
+            incremental_urls = [
+                (f"{url}{basename}{incremental}.filelist.csv", f"{url}{basename}{incremental}.tar.gz")
+                for incremental in incrementals
+            ]
+            paths += dl_manager.download(baseline_urls + incremental_urls)
 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "baseline_file_lists": baseline_file_lists,
-                    "baseline_archives": [dl_manager.iter_archive(archive) for archive in baseline_archives],
-                    "incremental_file_lists": incremental_paths["incremental_file_lists"],
-                    "incremental_archives": [
-                        dl_manager.iter_archive(archive) for archive in incremental_paths["incremental_archives"]
-                    ],
+                    "paths": [(file_list, dl_manager.iter_archive(archive)) for file_list, archive in paths],
                 },
             ),
         ]
 
-    def _generate_examples(self, baseline_file_lists, baseline_archives, incremental_file_lists, incremental_archives):
+    def _generate_examples(self, paths):
         key = 0
-        # Baselines
-        for baseline_file_list, baseline_archive in zip(baseline_file_lists, baseline_archives):
-            try:
-                baselines = pd.read_csv(baseline_file_list, index_col="Article File").to_dict(orient="index")
-                for path, file in baseline_archive:
-                    data = baselines.pop(path)
-                    content = file.read()
-                    try:
-                        text = content.decode("utf-8").strip()
-                    except UnicodeDecodeError as e:
-                        text = content.decode("latin-1").strip()
-                    data = {
-                        "text": text,
-                        "pmid": data["PMID"],
-                        "accession_id": data["AccessionID"],
-                        "license": data["License"],
-                        "last_updated": data["LastUpdated (YYYY-MM-DD HH:MM:SS)"],
-                        "retracted": data["Retracted"],
-                        "citation": data["Article Citation"],
-                    }
-                    yield key, data
-                    key += 1
-            except FileNotFoundError:  # non-commercial PMC000xxxxxx baseline does not exist
-                continue
-        # Incrementals
-        if incremental_file_lists:
-            for incremental_file_list, incremental_archive in zip(incremental_file_lists, incremental_archives):
-                incrementals = pd.read_csv(incremental_file_list, index_col="Article File").to_dict(orient="index")
-                for path, file in incremental_archive:
-                    data = incrementals.pop(path)
-                    content = file.read()
-                    try:
-                        text = content.decode("utf-8").strip()
-                    except UnicodeDecodeError as e:
-                        text = content.decode("latin-1").strip()
-                    data = {
-                        "text": text,
-                        "pmid": data["PMID"],
-                        "accession_id": data["AccessionID"],
-                        "license": data["License"],
-                        "last_updated": data["LastUpdated (YYYY-MM-DD HH:MM:SS)"],
-                        "retracted": data["Retracted"],
-                        "citation": data["Article Citation"],
-                    }
-                    yield key, data
-                    key += 1
+        for file_list, archive in paths:
+            file_list_data = pd.read_csv(file_list, index_col="Article File").to_dict(orient="index")
+            for path, file in archive:
+                data = file_list_data.pop(path)
+                content = file.read()
+                try:
+                    text = content.decode("utf-8").strip()
+                except UnicodeDecodeError as e:
+                    text = content.decode("latin-1").strip()
+                data = {
+                    "text": text,
+                    "pmid": data["PMID"],
+                    "accession_id": data["AccessionID"],
+                    "license": data["License"],
+                    "last_updated": data["LastUpdated (YYYY-MM-DD HH:MM:SS)"],
+                    "retracted": data["Retracted"],
+                    "citation": data["Article Citation"],
+                }
+                yield key, data
+                key += 1