more refactor

competitions/competitions.py

@@ -1,48 +1,30 @@
+from datetime import datetime
+from functools import partial
+
 import gradio as gr
 
-from . import competition_info
+from . import AUTOTRAIN_BACKEND_API, AUTOTRAIN_TOKEN, AUTOTRAIN_USERNAME, COMPETITION_ID, competition_info
 from .leaderboard import Leaderboard
 from .submissions import Submissions
+from .text import SUBMISSION_LIMIT_TEXT, SUBMISSION_TEXT
 
 
-# with gr.Blocks() as demo:
-#     with gr.Tab("Overview"):
-#         gr.Markdown(f"# Welcome to {config.competition_info.competition_name}! 👋")
-
-#         gr.Markdown(f"{config.competition_info.competition_description}")
-
-#         gr.Markdown("## Dataset")
-#         gr.Markdown(f"{config.competition_info.dataset_description}")
+leaderboard = Leaderboard(
+    end_date=competition_info.end_date,
+    eval_higher_is_better=competition_info.eval_higher_is_better,
+    competition_id=COMPETITION_ID,
+    autotrain_token=AUTOTRAIN_TOKEN,
+)
 
-#     with gr.Tab("Public Leaderboard"):
-#         output_markdown = gr.Markdown("")
-#         fetch_lb = gr.Button("Fetch Leaderboard")
-#         fetch_lb_partial = partial(utils.fetch_leaderboard, private=False)
-#         fetch_lb.click(fn=fetch_lb_partial, outputs=[output_markdown])
-#         # lb = utils.fetch_leaderboard(private=False)
-#         # gr.Markdown(lb.to_markdown())
-#     with gr.Tab("Private Leaderboard"):
-#         current_date_time = datetime.now()
-#         if current_date_time >= config.competition_info.end_date:
-#             lb = utils.fetch_leaderboard(private=True)
-#             gr.Markdown(lb)
-#         else:
-#             gr.Markdown("Private Leaderboard will be available after the competition ends")
-#     with gr.Tab("New Submission"):
-#         gr.Markdown(SUBMISSION_TEXT)
-#         user_token = gr.Textbox(max_lines=1, value="hf_XXX", label="Please enter your Hugging Face token")
-#         uploaded_file = gr.File()
-#         output_text = gr.Markdown(visible=True, show_label=False)
-#         new_sub_button = gr.Button("Upload Submission")
-#         new_sub_button.click(fn=new_submission, inputs=[user_token, uploaded_file], outputs=[output_text])
+submissions = Submissions(
+    competition_id=competition_info.competition_id,
+    submission_limit=competition_info.submission_limit,
+    end_date=competition_info.end_date,
+    autotrain_username=AUTOTRAIN_USERNAME,
+    autotrain_token=AUTOTRAIN_TOKEN,
+    autotrain_backend_api=AUTOTRAIN_BACKEND_API,
+)
 
-#     with gr.Tab("My Submissions"):
-#         gr.Markdown(SUBMISSION_LIMIT_TEXT)
-#         user_token = gr.Textbox(max_lines=1, value="hf_XXX", label="Please enter your Hugging Face token")
-#         output_text = gr.Markdown(visible=True, show_label=False)
-#         output_df = gr.Dataframe(visible=False)
-#         my_subs_button = gr.Button("Fetch Submissions")
-#         my_subs_button.click(fn=my_submissions, inputs=[user_token], outputs=[output_text, output_df])
 
 with gr.Blocks() as demo:
     with gr.Tabs() as tab_container:
@@ -51,11 +33,38 @@ with gr.Blocks() as demo:
             gr.Markdown(f"{competition_info.competition_description}")
             gr.Markdown("## Dataset")
             gr.Markdown(f"{competition_info.dataset_description}")
-        with gr.TabItem("Public Leaderboard", id="public_leaderboard"):
-            pass
+        with gr.TabItem("Public Leaderboard", id="public_leaderboard") as public_leaderboard:
+            fetch_lb = gr.Button("Fetch Leaderboard")
+            output_markdown = gr.DataFrame()
+            fetch_lb_partial = partial(leaderboard.fetch, private=False)
+            fetch_lb.click(fn=fetch_lb_partial, outputs=[output_markdown])
         with gr.TabItem("Private Leaderboard", id="private_leaderboard"):
-            pass
+            current_date_time = datetime.now()
+            if current_date_time >= competition_info.end_date:
+                output_markdown = gr.DataFrame()
+                fetch_lb_partial = partial(leaderboard.fetch, private=True)
+                fetch_lb_partial(outputs=[output_markdown])
+            else:
+                gr.Markdown("Private Leaderboard will be available after the competition ends")
         with gr.TabItem("New Submission", id="new_submission"):
-            pass
+            gr.Markdown(SUBMISSION_TEXT)
+            user_token = gr.Textbox(max_lines=1, value="hf_XXX", label="Please enter your Hugging Face token")
+            uploaded_file = gr.File()
+            output_text = gr.Markdown(visible=True, show_label=False)
+            new_sub_button = gr.Button("Upload Submission")
+            new_sub_button.click(
+                fn=submissions.new_submission,
+                inputs=[user_token, uploaded_file],
+                outputs=[output_text],
+            )
         with gr.TabItem("My Submissions", id="my_submissions"):
-            pass
+            gr.Markdown(SUBMISSION_LIMIT_TEXT)
+            user_token = gr.Textbox(max_lines=1, value="hf_XXX", label="Please enter your Hugging Face token")
+            output_text = gr.Markdown(visible=True, show_label=False)
+            output_df = gr.DataFrame(visible=False)
+            my_subs_button = gr.Button("Fetch Submissions")
+            my_subs_button.click(
+                fn=submissions.my_submissions,
+                inputs=[user_token],
+                outputs=[output_text, output_df],
+            )

competitions/leaderboard.py

@@ -2,6 +2,7 @@ import glob
 import json
 import os
 from dataclasses import dataclass
+from datetime import datetime
 
 import pandas as pd
 from huggingface_hub import snapshot_download
@@ -9,7 +10,7 @@ from huggingface_hub import snapshot_download
 
 @dataclass
 class Leaderboard:
-    end_date: str
+    end_date: datetime
     eval_higher_is_better: bool
     competition_id: str
     autotrain_token: str

competitions/submissions.py

@@ -162,7 +162,7 @@ class Submissions:
         try:
             user_submissions = self._download_user_subs(user_id)
         except EntryNotFoundError:
-            return NoSubmissionError("No submissions found ")
+            raise NoSubmissionError("No submissions found ")
 
         submissions_df = pd.DataFrame(user_submissions)
         if not private:
@@ -175,10 +175,10 @@ class Submissions:
     def _get_user_info(self, user_token):
         user_info = user_authentication(token=user_token)
         if "error" in user_info:
-            return AuthenticationError("Invalid token")
+            raise AuthenticationError("Invalid token")
 
         if user_info["emailVerified"] is False:
-            return AuthenticationError("Please verify your email on Hugging Face Hub")
+            raise AuthenticationError("Please verify your email on Hugging Face Hub")
         return user_info
 
     def _create_autotrain_project(self, project_id, submission_dataset, model, dataset):
@@ -273,13 +273,13 @@ class Submissions:
 
         # check if user can submit to the competition
         if self._check_user_submission_limit(user_info) is False:
-            return SubmissionLimitError("Submission limit reached")
+            raise SubmissionLimitError("Submission limit reached")
 
         with open(uploaded_file.name, "rb") as f:
             bytes_data = f.read()
         # verify file is valid
         if not self._verify_submission(bytes_data):
-            return SubmissionError("Invalid submission file")
+            raise SubmissionError("Invalid submission file")
         else:
             user_id = user_info["id"]
             submission_id = str(uuid.uuid4())