add auto datatype

app.py

@@ -58,74 +58,85 @@ with demo:
     with gr.Tabs(elem_classes="tab-buttons") as tabs:
         with gr.TabItem("🏆 Inverse Folding Leaderboard", elem_id='inverse-folding-table', id=0,):
             with gr.Row():
+                inverse_folding_csv = pd.read_csv('data/inverse_folding.csv')
                 inverse_folding_table = gr.components.DataFrame(
-                    pd.read_csv('data/inverse_folding.csv'),
+                    inverse_folding_csv,
                     height=99999,
                     interactive=False,
-                    datatype=['markdown', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number'],
+                    datatype=['markdown'] + (len(inverse_folding_csv.columns)-1) * ['number'],
+                    
                 )
         with gr.TabItem("🏆 Structure Design Leaderboard", elem_id='structure-design-table', id=1,):
             with gr.Row():
-                inverse_folding_table = gr.components.DataFrame(
-                    pd.read_csv('data/structure_design.csv'),
+                structure_design_csv = pd.read_csv('data/structure_design.csv')
+                structure_design_table = gr.components.DataFrame(
+                    structure_design_csv,
                     height=99999,
                     interactive=False,
-                    datatype=['markdown', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number'],
+                    datatype=['markdown'] + (len(structure_design_csv.columns)-1) * ['number'],
                 )
         with gr.TabItem("🏆 Sequence Design Leaderboard", elem_id='sequence-design-table', id=2,):
             with gr.Row():
-                inverse_folding_table = gr.components.DataFrame(
-                    pd.read_csv('data/sequence_design.csv'),
+                sequence_design_csv = pd.read_csv('data/sequence_design.csv'),
+                sequence_design_table = gr.components.DataFrame(
+                    sequence_design_csv,
                     height=99999,
                     interactive=False,
-                    datatype=['markdown', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number'],
+                    datatype=['markdown'] + (len(sequence_design_csv.columns)-1) * ['number'],
                 )
         with gr.TabItem("🏆 Sequence-Structure Co-Design Leaderboard", elem_id='co-design-table', id=3,):
             with gr.Row():
-                inverse_folding_table = gr.components.DataFrame(
-                    pd.read_csv('data/co_design.csv'),
+                co_design_csv = pd.read_csv('data/co_design.csv')
+                co_design_table = gr.components.DataFrame(
+                    co_design_csv,
                     height=99999,
                     interactive=False,
-                    datatype=['markdown', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number'],
+                    datatype=['markdown'] + (len(co_design_csv.columns)-1) * ['number'],
                 )
         with gr.TabItem("🏆 Motif Scaffolding Leaderboard", elem_id='motif-scaffolding-table', id=4,):
             with gr.Row():
-                inverse_folding_table = gr.components.DataFrame(
-                    pd.read_csv('data/motif_scaffolding.csv'),
+                motif_scaffolding_csv = pd.read_csv('data/motif_scaffolding.csv')
+                motif_scaffolding_table = gr.components.DataFrame(
+                    motif_scaffolding_csv,
                     height=99999,
                     interactive=False,
-                    datatype=['markdown', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number'],
+                    datatype=['markdown'] + (len(motif_scaffolding_csv.columns)-1) * ['number'],
                 )
         with gr.TabItem("🏆 Antibody Design Leaderboard", elem_id='antibody-design-table', id=5,):
             with gr.Row():
-                inverse_folding_table = gr.components.DataFrame(
-                    pd.read_csv('data/antibody_design.csv'),
+                antibody_design_csv = pd.read_csv('data/antibody_design.csv')
+                antibody_design_table = gr.components.DataFrame(
+                    antibody_design_csv,
                     height=99999,
                     interactive=False,
+                    datatype=['markdown'] + (len(antibody_design_csv.columns)-1) * ['number'],
                 )
         with gr.TabItem("🏅 Protein Folding Leaderboard", elem_id='protein-folding-table', id=6,):
             with gr.Row():
-                inverse_folding_table = gr.components.DataFrame(
-                    pd.read_csv('data/protein_folding.csv'),
+                protein_folding_csv = pd.read_csv('data/protein_folding.csv')
+                protein_folding_table = gr.components.DataFrame(
+                    protein_folding_csv,
                     height=99999,
                     interactive=False,
-                    datatype=['markdown', 'number', 'number', 'number', 'number', 'number', 'number', 'number'],
+                    datatype=['markdown'] + (len(protein_folding_csv.columns)-1) * ['number'],
                 )
         with gr.TabItem("🏅 Multi-State Prediction Leaderboard", elem_id='multi-state-prediction-table', id=7,):
             with gr.Row():
-                inverse_folding_table = gr.components.DataFrame(
-                    pd.read_csv('data/multi_state_prediction.csv'),
+                multi_state_prediction_csv = pd.read_csv('data/multi_state_prediction.csv')
+                multi_state_prediction_table = gr.components.DataFrame(
+                    multi_state_prediction_csv,
                     height=99999,
                     interactive=False,
-                    datatype=['markdown', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number'],
+                    datatype=['markdown'] + (len(multi_state_prediction_csv.columns)-1) * ['number'],
                 )
         with gr.TabItem("🏅 Conformation Prediction Leaderboard", elem_id='conformation-prediction-table', id=8,):
             with gr.Row():
-                inverse_folding_table = gr.components.DataFrame(
-                    pd.read_csv('data/conformation_prediction.csv'),
+                conformation_prediction = pd.read_csv('data/conformation_prediction.csv')
+                conformation_prediction_table = gr.components.DataFrame(
+                    conformation_prediction,
                     height=99999,
                     interactive=False,
-                    datatype=['markdown', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number', 'number'],
+                    datatype=['markdown'] + (len(conformation_prediction.columns)-1) * ['number'],
                 )