pandas 3.0.0 incompability

[PreisTo]

Describe the bug
Just noticed when running the HAL Example Notebook from the threeML docs with pandas=3.0.0 (PyTables=3.10.2) that this results in a TypeError: a bytes-like object is required, not 'str'. This does not happen when enforcing pandas<3.0.0.
I used this conda env.
Is there a chance that this stems from HAL and can be fixed here? If not feel free to close this issue anytime :)

Thanks for looking into this!

To Reproduce

import requests
import shutil
import os
from hawc_hal import HAL, HealpixConeROI


def get_hawc_file(filename, odir="./", overwrite=False):

    if overwrite or not os.path.exists(odir + filename):
        url = "https://data.hawc-observatory.org/datasets/crab_data/public_data/crab_2017/"

        req = requests.get(url + filename, verify=False, stream=True)
        req.raw.decode_content = True
        with open(odir + filename, "wb") as f:
            shutil.copyfileobj(req.raw, f)

    return odir + filename


maptree = "HAWC_9bin_507days_crab_data.hd5"
response = "HAWC_9bin_507days_crab_response.hd5"
odir = "./"


maptree = get_hawc_file(maptree, odir)
response = get_hawc_file(response, odir)

ra_crab, dec_crab = 83.63, 22.02
data_radius = 3.0  # in degree
model_radius = 8.0  # in degree

roi = HealpixConeROI(
    data_radius=data_radius, model_radius=model_radius, ra=ra_crab, dec=dec_crab
)
hawc = HAL("HAWC", maptree, response, roi, flat_sky_pixels_size=0.1, set_transits=None)

Log files

| TypeError                                 Traceback (most recent call last)
| Cell In[3], line 23
|      18 roi = HealpixConeROI(
|      19     data_radius=data_radius, model_radius=model_radius, ra=ra_crab, dec=dec_crab
|      20 )
|      22 # Instance the plugin
| ---> 23 hawc = HAL("HAWC", maptree, response, roi, flat_sky_pixels_size=0.1, set_transits=None)
|      25 # Use from bin 1 to bin 9
|      26 hawc.set_active_measurements(1, 9)
| 
| File ~/miniconda3/envs/test_env/lib/python3.11/site-packages/hawc_hal/HAL.py:92, in HAL.__init__(self, name, maptree, response_file, roi, flat_sky_pixels_size, n_workers, set_transits)
|      87 self._flat_sky_projection = self._roi.get_flat_sky_projection(
|      88     self.flat_sky_pixels_size
|      89 )
|      91 # Read map tree (data)
| ---> 92 self._maptree = map_tree_factory(
|      93     maptree, roi=self._roi, n_transits=n_transits, n_workers=self._n_workers
|      94 )
|      96 # Read detector response_file
|      97 self._response = hawc_response_factory(
|      98     response_file_name=response_file, n_workers=self._n_workers
|      99 )
| 
| File ~/miniconda3/envs/test_env/lib/python3.11/site-packages/hawc_hal/maptree/map_tree.py:28, in map_tree_factory(map_tree_file, roi, n_workers, n_transits)
|      25 if os.path.splitext(map_tree_file)[-1] == ".root":
|      26     return MapTree.from_root_file(map_tree_file, roi, n_transits, n_workers)
| ---> 28 return MapTree.from_hdf5(map_tree_file, roi, n_transits)
| 
| File ~/miniconda3/envs/test_env/lib/python3.11/site-packages/hawc_hal/maptree/map_tree.py:50, in MapTree.from_hdf5(cls, map_tree_file, roi, n_transits)
|      47 @classmethod
|      48 # def from_hdf5(cls, map_tree_file, roi):
|      49 def from_hdf5(cls, map_tree_file, roi, n_transits):
| ---> 50     data_analysis_bins, transits = from_hdf5_file(map_tree_file, roi, n_transits)
|      52     return cls(data_analysis_bins, roi, transits)
| 
| File ~/miniconda3/envs/test_env/lib/python3.11/site-packages/hawc_hal/maptree/from_hdf5_file.py:30, in from_hdf5_file(map_tree_file, roi, transits)
|      27 # Read the data frames contained in the file
|      28 with Serialization(map_tree_file) as serializer:
| ---> 30     analysis_bins_df, _ = serializer.retrieve_pandas_object("/analysis_bins")
|      31     meta_df, _ = serializer.retrieve_pandas_object("/analysis_bins_meta")
|      32     roimap, roi_meta = serializer.retrieve_pandas_object("/ROI")
| 
| File ~/miniconda3/envs/test_env/lib/python3.11/site-packages/hawc_hal/serialize.py:45, in Serialization.retrieve_pandas_object(self, path)
|      42 def retrieve_pandas_object(self, path):
|      43 
|      44     # Get the metadata
| ---> 45     metadata = self._store.get_storer(path).attrs.metadata
|      47     # Get the object
|      48     obj = self._store.get(path)
| 
| File ~/miniconda3/envs/test_env/lib/python3.11/site-packages/pandas/io/pytables.py:1684, in HDFStore.get_storer(self, key)
|    1681 if group is None:
|    1682     raise KeyError(f"No object named {key} in the file")
| -> 1684 s = self._create_storer(group)
|    1685 s.infer_axes()
|    1686 return s
| 
| File ~/miniconda3/envs/test_env/lib/python3.11/site-packages/pandas/io/pytables.py:1866, in HDFStore._create_storer(self, group, format, value, encoding, errors)
|    1863             pt += "_table"
|    1865 # a storer node
| -> 1866 if "table" not in pt:
|    1867     _STORER_MAP = {"series": SeriesFixed, "frame": FrameFixed}
|    1868     try:
| 
| TypeError: a bytes-like object is required, not 'str'

Desktop (please complete the following information):

• PopOS 22.04
• Ubuntu 24.04