Remove gdown dependency and add requirements.txt

murakami.py

@@ -6,13 +6,10 @@ Parse all paragraphs from all *.fb2 files in the input directory, create a Huggi
 import os
 from pathlib import Path
 from lxml import etree
-import gdown
 import datasets
 from datasets import Dataset
 from huggingface_hub import create_repo
-import coloredlogs
 
-coloredlogs.install(level="info")
 datasets.logging.set_verbosity_info()
 
 
@@ -20,8 +17,6 @@ _DESCRIPTION = """\
 Russian translations of Murakami novels, to fine-tune a generative language model. Source is FB2 files from http://flibusta.is/a/8570.
 """
 
-_URL = "https://drive.google.com/open?id=14Uw_efwj70iip1xJD2H2qHSVMuoUDm4z"
-
 
 class Builder(datasets.GeneratorBasedBuilder):
     """Murakami novels, translated to Russian."""
@@ -97,19 +92,8 @@ class Builder(datasets.GeneratorBasedBuilder):
     def _split_generators(self, dl_manager):
         # This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
         # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
-
-        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
-        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
-        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
-        data_dir = dl_manager.extract(
-            dl_manager.download_custom(
-                _URL,
-                custom_download=lambda src, dst: gdown.download(src, dst, fuzzy=True),
-            )
-        )
-
+        data_dir = "data"
         text_by_name = {}
-
         fb2s = list(Path(data_dir).glob("*.fb2"))
         if len(fb2s) > 0:
             print(f"Found {len(fb2s)} fb2 files in {data_dir}")

requirements.txt

@@ -0,0 +1,2 @@
+datasets
+lxml