diff --git a/README.md b/README.md
index 51c5111..2b5fe40 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,7 @@
 
 <h3 align="center">Welcome to TSDB</h3>
 
-*<p align='center'>a Python toolbox to ease loading 172 public time-series datasets</p>*
+*<p align='center'>load 172 public time-series datasets with a single line of code ;-)</p>*
 
 <p align='center'>
     <a href='https://github.com/WenjieDu/TSDB'>
@@ -67,21 +67,38 @@ if it helps with your research. This really means a lot to our open-source resea
 
 
 ## ❖ Usage Examples
-TSDB now is available on <a alt='Anaconda' href='https://anaconda.org/conda-forge/tsdb'><img align='center' src='https://img.shields.io/badge/Anaconda--lightgreen?style=social&logo=anaconda'></a>❗️
+> [!IMPORTANT]
+> TSDB is available on both <a alt='PyPI' href='https://pypi.python.org/pypi/tsdb'><img align='center' src='https://img.shields.io/badge/PyPI--lightgreen?style=social&logo=pypi'></a>
+> and <a alt='Anaconda' href='https://anaconda.org/conda-forge/tsdb'><img align='center' src='https://img.shields.io/badge/Anaconda--lightgreen?style=social&logo=anaconda'></a>❗️
+>
+> Install via pip:
+> > pip install tsdb
+>
+> or install from source code:
+> > pip install `https://github.com/WenjieDu/TSDB/archive/main.zip`
+>
+> or install via conda:
+> > conda install tsdb -c conda-forge
 
-Install it with `conda install tsdb `, you may need to specify the channel with option `-c conda-forge`
-
-or install via PyPI:
-> pip install tsdb
-
-or install from source code:
-> pip install `https://github.com/WenjieDu/TSDB/archive/main.zip`
 
 ```python
 import tsdb
 
 # list all available datasets in TSDB
 tsdb.list()
+# ['physionet_2012',
+#  'physionet_2019',
+#  'electricity_load_diagrams',
+#  'beijing_multisite_air_quality',
+#  'italy_air_quality',
+#  'vessel_ais',
+#  'electricity_transformer_temperature',
+#  'pems_traffic',
+#  'solar_alabama',
+#  'ucr_uea_ACSF1',
+#  'ucr_uea_Adiac',
+#  ...
+
 # select the dataset you need and load it, TSDB will download, extract, and process it automatically
 data = tsdb.load('physionet_2012')
 # if you need the raw data, use download_and_extract()
diff --git a/requirements.txt b/requirements.txt
index fe720b6..3be5b24 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,5 +1,7 @@
+tqdm
 numpy
-scikit-learn
-pandas
 scipy
+pandas
 pyarrow
+requests
+scikit-learn
diff --git a/setup.cfg b/setup.cfg
index 5d5f94d..4ef5c4c 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -23,8 +23,10 @@ extend-ignore =
 
 # basic dependencies
 basic =
+    tqdm
     numpy
-    scikit-learn
-    pandas
     scipy
+    pandas
     pyarrow
+    requests
+    scikit-learn
diff --git a/setup.py b/setup.py
index 5e9741d..3fdc7d8 100644
--- a/setup.py
+++ b/setup.py
@@ -44,11 +44,13 @@
     packages=find_packages(exclude=["tests"]),
     include_package_data=True,
     install_requires=[
+        "tqdm",
         "numpy",
-        "scikit-learn",
-        "pandas",
         "scipy",
+        "pandas",
         "pyarrow",
+        "requests",
+        "scikit-learn",
     ],
     setup_requires=["setuptools>=38.6.0"],
     classifiers=[
diff --git a/tsdb/utils/downloading.py b/tsdb/utils/downloading.py
index 0f7a00a..451d84f 100644
--- a/tsdb/utils/downloading.py
+++ b/tsdb/utils/downloading.py
@@ -9,10 +9,12 @@
 import os
 import shutil
 import tempfile
-import urllib.request
 import warnings
 from typing import Optional
 
+import requests
+from tqdm import tqdm
+
 from .logging import logger
 from ..database import DATABASE
 
@@ -54,7 +56,27 @@ def _download_and_extract(url: str, saving_path: str) -> Optional[str]:
 
     # download and save the raw dataset
     try:
-        urllib.request.urlretrieve(url, raw_data_saving_path)
+        with requests.get(url, stream=True) as r:
+            r.raise_for_status()
+            chunk_size = 8192
+            try:
+                size = int(r.headers["Content-Length"])
+            except KeyError:
+                size = None
+
+            with tqdm(
+                unit="B",
+                unit_scale=True,
+                unit_divisor=1024,
+                miniters=1,
+                desc=f"Downloading {file_name}",
+                total=size,
+            ) as pbar:
+                with open(raw_data_saving_path, "wb") as f:
+                    for chunk in r.iter_content(chunk_size=chunk_size):
+                        f.write(chunk)
+                        pbar.update(len(chunk))
+
     except Exception as e:
         shutil.rmtree(saving_path, ignore_errors=True)
         shutil.rmtree(raw_data_saving_path, ignore_errors=True)