First commit

.gitignore

+data/*

.gitlab-ci.yml

+stages:
+  - rails-update
+  - test-baseline
+  - submit-baseline
+
+.aicrowd-setup: &aicrowd-setup
+  image: python:3.8
+  before_script:
+    - git clone https://github.com/AIcrowd/aicrowd-cli.git && cd aicrowd-cli
+    - pip install -r requirements.txt
+    - python setup.py develop
+    - cd ..
+    - aicrowd evaluations login -e "${SUPER_USER_EMAIL}" -p "${SUPER_USER_PASSWORD}"
+
+rails-update:
+  stage: rails-update
+  image: python:3.8-slim
+  before_script:
+    - pip install pyyaml requests markdown
+  script:
+    - python utils.py
+  only:
+    changes:
+      - README.md
+ 
+test-baseline: 
+  stage: test-baseline
+  image: python:3.8
+  before_script: 
+    - apt install curl
+    - curl -o /usr/local/bin/jq http://stedolan.github.io/jq/download/linux64/jq && chmod +x /usr/local/bin/jq
+    - pip install yq
+    - pip install jupyter
+  script:
+    - export BASELINE=`yq -r .official_baseline aicrowd.yaml | awk -F. '{print $1}'`
+    - jupyter nbconvert --to python baselines/${BASELINE}.ipynb
+    - ipython baselines/${BASELINE}.py
+  artifacts:
+    paths:
+      - submission.csv
+  only:
+    changes:
+      - baselines/*
+
+submit-baseline:
+  stage: submit-baseline
+  <<: *aicrowd-setup
+  script:
+    - apt install curl
+    - curl -o /usr/local/bin/jq http://stedolan.github.io/jq/download/linux64/jq && chmod +x /usr/local/bin/jq
+    - pip install yq
+    - export CHALLENGE_NAME=`yq -r .challenge_name aicrowd.yaml`
+    - export EVALUATIONS_API_TOKEN=`yq -r .aicrowd_evaluations_token ~/.aicrowd/config.yaml`
+    - export GRADER_ID=`curl -k -X GET "https://evaluations-api.internal.k8s.aicrowd.com/v1/graders/?name=${CHALLENGE_NAME}" 
+        -H "accept:application/json" 
+        -H "AUTHORIZATION:${EVALUATIONS_API_TOKEN}" | jq '.[length-1].id'`  
+    - aicrowd evaluations submission create --file ./submission.csv -g ${GRADER_ID} --wait
+  only:
+    changes:
+      - baselines/*
+

CONTRIBUTION.md

+# To be filled in later with an consistent contribution guide
+- Q : Who writes that ?
\ No newline at end of file

README.md

+>**🛠 Contribute:** Found a typo? Or any other change in the description that you would like to see? Please consider sending us a pull request in the [public repo of the challenge here](https://gitlab.aicrowd.com/aicrowd/practice-challenges/aicrowd_SNAKE_challenge).
+
+# 🕵️Introduction
+
+
+Snake bites are one of the most deadliest neglected tropical disease causing over 100,000 deaths and 400,000 victims of disability and disfigurement globally every year. 
+
+The poor and rural communites are the worst affected due to their limited access to antivenom and hospitals. 
+
+In this challenge we explore the use of computer vision in correctly classifying snakes as `venomous` / `non venomous`. 
+
+</br>Understand with code! Here is [`getting started code`](https://discourse.aicrowd.com/t/baseline-mnist/2757) for you.`😄`
+
+# 💾 Dataset
+
+The dataset provided has many variations in it: 
+* variation by age
+* variation by geography 
+* medically important venomous snakes 
+* similar looking harmless snakes 
+
+
+# 📁 Files
+
+Following files are available in the `resources` section:
+There are four files for this challenge.
+ - `train.tar.gz` : contains approximately 54k training images.
+ - `val.tar.gz` : contains approximately 6k validation images. 
+ - `test.tar.gz` : contains approximately 15k test images.
+
+
+# 🚀 Submission
+
+ - Prepare a CSV containing header as [header] and predicted value as digit 0 or 1 respectively denoting whether or not the corresponding ad will be clicked upon.
+ - Name of the above file should be submission.csv.
+ - Sample submission format available at sample_submission.csv in the resorces section.
+
+**Make your first submission [here](https://www.aicrowd.com/challenges/snake/submissions/new)  🚀 !!**
+
+# 🖊 Evaluation Criteria
+
+During evaluation [F1 score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html) and [Log Loss](http://wiki.fast.ai/index.php/Log_Loss) will be used to test the efficiency of the model where,
+
+<img src="https://latex.codecogs.com/gif.latex?F1%20%3D%202%20*%20%5Cfrac%7Bprecision*recall%7D%7Bprecision&plus;recall%7D"/> </br>
+
+<img src="http://latex.codecogs.com/gif.latex?%24%24%20Log%20Loss%20%3D%20-log%20P%28yt%7Cyp%29%20%3D%20-%28yt%20log%28yp%29%20&plus;%20%281%20-%20yt%29%20log%281%20-%20yp%29%29%20%24%24"/
+
+
+# 🔗 Links
+
+* 💪 Challenge Page: [https://www.aicrowd.com/challenges/SNAKE](https://www.aicrowd.com/challenges/SNAKE)
+* 🗣️ Discussion Forum: [https://www.aicrowd.com/challenges/SNAKE/discussion](https://www.aicrowd.com/challenges/SNAKE/discussion)
+* 🏆 Leaderboard: [https://www.aicrowd.com/challenges/SNAKE/leaderboards](https://www.aicrowd.com/challenges/SNAKE/leaderboards)
+
+# 📱 Contact
+
+- [Rohit Midha](https://www.linkedin.com/in/rohitmidha/)
+- [Shraddhaa Mohan](https://www.linkedin.com/in/shraddhaa-mohan-20a008185/)
+- [Sharada Mohanty](mohanty@aicrowd.com)
\ No newline at end of file

aicrowd.yaml

+---
+challenge_name: snake
+evaluation_repo: git@gitlab.aicrowd.com:aicrowd/practice-challenges/aicrowd_SNAKE_challenge_evaluator.git
+data_url: https://s3.wasabisys.com/aicrowd-practice-challenges/public/snake/v0.1/
+official_baseline: SNAKE_baseline.ipynb
+authors:
+- name: Sharada Mohanty
+  email: mohanty@aicrowd.com
+version: '0.1'

utils.py

+import requests
+import html
+import markdown
+import yaml
+import os
+
+class Utils():
+    def __init__(self):
+        self.base_url = "https://www.aicrowd.com/api/v1/challenges"
+        self.api_key = os.getenv("AICROWD_API_KEY")
+        self.headers = {'Authorization': 'Token token="' + self.api_key +'"', 'Content-Type': 'application/json'}
+        
+        with open("aicrowd.yaml", "r") as f:
+            self.challenge = yaml.safe_load(f)['challenge_name']
+        
+        with open("README.md", "r") as f:
+            self.content = f.read()
+        self.convert()
+
+    def convert(self):
+        self.content = markdown.markdown(self.content)
+        self.content = self.content.replace("\"","'")
+        self.content = self.content.replace("h1","h2")
+        html.unescape(self.content)
+    
+    def create_challenge(self):
+        payload = {
+                "challenge": self.challenge.upper(),
+                "status_cd": "draft",
+                "tagline": "Venomous Snake Classification",
+                "perpetual_challenge": False,
+                "answer_file_s3_key": None,
+                "slug": "snake-venomous-snake-classification",
+                "submission_license": "",
+                "api_required": False,
+                "media_on_leaderboard": False,
+                "online_grading": True,
+                "description": self.content,
+                "evaluation": None,
+                "rules": None,
+                "prizes": None,
+                "resources": None,
+                "submission_instructions": None,
+                "subissions_page": True,
+                "license": "",
+                "dataset_description": None,
+                "image_file": {"url": "aicrowd_SNAKE_challenge/images/SNAKE.png"},
+                "show_leaderboard": True,
+                "grader_identifier": "AIcrowd_GRADER_POOL",
+                "online_submissions": True,
+                "grader_logs": False,
+                "require_registration": False,
+                "grading_history": False,
+                "post_challenge_submissions": True,
+                "submissions_downloadable": False,
+                "dataset_note": None,
+                "discussions_visible": True,
+                "latest_submission": False,
+                "other_scores_fieldnames": "",
+                "teams_allowed": True,
+                "max_team_participants": 5,
+                "team_freeze_seconds_before_end": 604800,
+                "hidden_challenge": False,
+                "team_freeze_time": None,
+                "score_title": "",
+                "score_secondary_title": "",
+                "primary_sort_order_cd": "",
+                "secondary_sort_order_cd": "",
+                "challenges_organizers_attributes": [{"organizer_id": 9, "challenge_id": 1}],
+                "category_challenges_attributes": [{"category_id": "8"}],
+                "dataset_files_attributes": [ 
+                    {
+                        "seq": 1,
+                        "title": "Training Data",
+                        "description": "File containing the attributes along with the corresponding labels related to it.",
+                        "evaluation": False,
+                        "visible": True,
+                        "hosting_location": "External",
+                        "external_url": f"https://s3.eu-central-1.wasabisys.com/aicrowd-practice-challenges/public/snake/v0.1/train.csv",
+                        "external_file_size": ""
+                    },
+                    {
+                        "seq": 2,
+                        "title": "Testing Data",
+                        "description": "File that will be used for actual evaluation for the leaderboard score but does not have the actual label corresponding to the attributes.",
+                        "evaluation": False,
+                        "visible": True,
+                        "hosting_location": "External",
+                        "external_url": f"https://s3.eu-central-1.wasabisys.com/aicrowd-practice-challenges/public/snake/v0.1/test.csv",
+                        "external_file_size": ""
+                    },
+                    {
+                        "seq": 3,
+                        "title": "Sample Submission",
+                        "description": "Sample Submission Format",
+                        "evaluation": False,
+                        "visible": True,
+                        "hosting_location": "External",
+                        "external_url": f"https://s3.eu-central-1.wasabisys.com/aicrowd-practice-challenges/public/snake/v0.1/sample_submission.csv",
+                        "external_file_size": ""
+                    },
+                ]
+
+            }
+        return requests.post(self.base_url, json=payload, headers=self.headers)
+
+
+    def update_challenge(self):
+        payload = {"description": self.content}
+        request_url = f"{self.base_url}/{self.challenge}"
+        response = requests.patch(request_url, json=payload, headers=self.headers)
+        return response
+
+    def update_or_create(self):
+        response =  self.update_challenge()
+        if response.status_code == 404:
+            response = self.create_challenge()
+        
+        return response
+
+
+
+if __name__ == "__main__":
+    utils = Utils()
+    print(utils.update_or_create().text)
+