Yep that’s possible with the wandb API, see here: https://docs.wandb.ai/guides/track/public-api-guide#querying-multiple-runs 4

import pandas as pd 
import wandb

api = wandb.Api()
entity, project = "<entity>", "<project>"  # set to your entity and project 
runs = api.runs(entity + "/" + project) 

summary_list, config_list, name_list = [], [], []
for run in runs: 
    # .summary contains the output keys/values for metrics like accuracy.
    #  We call ._json_dict to omit large files 
    summary_list.append(run.summary._json_dict)

    # .config contains the hyperparameters.
    #  We remove special values that start with _.
    config_list.append(
        {k: v for k,v in run.config.items()
         if not k.startswith('_')})

    # .name is the human-readable name of the run.
    name_list.append(run.name)

runs_df = pd.DataFrame({
    "summary": summary_list,
    "config": config_list,
    "name": name_list
    })