Datasets
Datasets Utils
source
download_file
download_file (directory:str, source_url:str, decompress:bool=False)
Download data from source_ulr inside directory.
source
extract_file
extract_file (filepath, directory)
source
async_download_files
async_download_files (path:Union[str,pathlib.Path], urls:Iterable[str])
import tempfile
import requests
gh_url = 'https://api.github.com/repos/Nixtla/datasetsforecast/git/trees/main'
base_url = 'https://raw.githubusercontent.com/Nixtla/datasetsforecast/main'
resp = requests.get(gh_url)
urls = []
for e in resp.json()['tree']:
if e['type'] == 'blob':
urls.append(f'{base_url}/{e["path"]}')
with tempfile.TemporaryDirectory() as tmp:
tmp = Path(tmp)
await async_download_files(tmp, urls)
files = list(tmp.iterdir())
assert len(files) == len(urls)
source
download_files
download_files (directory:Union[str,pathlib.Path], urls:Iterable[str])
with tempfile.TemporaryDirectory() as tmp:
tmp = Path(tmp)
fname = tmp / 'script.py'
fname.write_text(f"""
from datasetsforecast.utils import download_files
download_files('{tmp.as_posix()}', {urls})
""")
!python {fname}
fname.unlink()
files = list(tmp.iterdir())
assert len(files) == len(urls)
source
Info
Info (class_groups:Tuple[dataclass])
Info Dataclass of datasets. Args: groups (Tuple): Tuple of str groups class_groups (Tuple): Tuple of dataclasses.