How to Write a Winning Conference CFP Using Notion 2026 and Grammarly 2026

import os
import requests
import json
import time
import logging
from typing import Dict, List, Optional

# Configure logging for audit trails
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(message)s',
    handlers=[logging.StreamHandler()]
)

class NotionCFPWorkspaceSetup:
    \"\"\"Automates creation of a standardized CFP workspace in Notion 2026\"\"\"

    def __init__(self, notion_token: str):
        self.notion_token = notion_token
        self.base_url = 'https://api.notion.com/v1'
        self.headers = {
            'Authorization': f'Bearer {notion_token}',
            'Notion-Version': '2026-05-01',  # Notion 2026 API version
            'Content-Type': 'application/json'
        }
        self.logger = logging.getLogger(__name__)

    def _make_request(self, method: str, endpoint: str, payload: Optional[Dict] = None) -> Dict:
        \"\"\"Handle rate limiting and error handling for Notion API requests\"\"\"
        url = f'{self.base_url}{endpoint}'
        max_retries = 3
        retry_delay = 1  # seconds

        for attempt in range(max_retries):
            try:
                if method.upper() == 'POST':
                    response = requests.post(url, headers=self.headers, json=payload)
                elif method.upper() == 'GET':
                    response = requests.get(url, headers=self.headers)
                else:
                    raise ValueError(f'Unsupported HTTP method: {method}')

                response.raise_for_status()
                return response.json()
            except requests.exceptions.HTTPError as e:
                if response.status_code == 429:  # Rate limit
                    retry_after = int(response.headers.get('Retry-After', retry_delay))
                    self.logger.warning(f'Rate limited. Retrying after {retry_after}s')
                    time.sleep(retry_after)
                elif response.status_code >= 500:  # Server error
                    self.logger.warning(f'Server error {response.status_code}. Retrying...')
                    time.sleep(retry_delay * (attempt + 1))
                else:
                    self.logger.error(f'HTTP Error: {e}')
                    raise
            except Exception as e:
                self.logger.error(f'Request failed: {e}')
                raise
        raise Exception('Max retries exceeded for Notion API request')

    def create_cfp_database(self, parent_page_id: str) -> Dict:
        \"\"\"Create a structured CFP tracking database with required properties\"\"\"
        payload = {
            'parent': {'page_id': parent_page_id},
            'title': [{'type': 'text', 'text': {'content': '2026 Conference CFP Pipeline'}}],
            'properties': {
                'CFP Title': {'title': {}},
                'Conference': {'select': {'options': [
                    {'name': 'KubeCon 2026', 'color': 'blue'},
                    {'name': 'QCon London 2026', 'color': 'green'},
                    {'name': 'Strange Loop 2026', 'color': 'orange'},
                    {'name': 'ACM Queue Live 2026', 'color': 'purple'}
                ]}},
                'Submission Status': {'select': {'options': [
                    {'name': 'Draft', 'color': 'gray'},
                    {'name': 'In Review', 'color': 'yellow'},
                    {'name': 'Submitted', 'color': 'blue'},
                    {'name': 'Accepted', 'color': 'green'},
                    {'name': 'Rejected', 'color': 'red'}
                ]}},
                'Acceptance Probability': {'number': {'format': 'percent'}},
                'Grammarly Score': {'number': {'format': 'decimal'}},
                'Submission Deadline': {'date': {}},
                'Reviewer Feedback': {'rich_text': {}}
            }
        }

        self.logger.info('Creating CFP tracking database...')
        return self._make_request('POST', '/databases', payload)

    def add_cfp_template(self, database_id: str) -> Dict:
        \"\"\"Add a pre-configured CFP template to the database\"\"\"
        payload = {
            'parent': {'type': 'database_id', 'database_id': database_id},
            'properties': {
                'CFP Title': {'title': [{'text': {'content': 'New CFP Draft'}}]},
                'Submission Status': {'select': {'name': 'Draft'}},
                'Acceptance Probability': {'number': 0.5}
            },
            'children': [
                {
                    'object': 'block',
                    'type': 'heading_1',
                    'heading_1': {'rich_text': [{'type': 'text', 'text': {'content': 'Problem Statement'}}]}
                },
                {
                    'object': 'block',
                    'type': 'paragraph',
                    'paragraph': {'rich_text': [{'type': 'text', 'text': {'content': 'Describe the concrete engineering problem you solved, including p99 latency, cost savings, or scale numbers.'}}]}
                },
                {
                    'object': 'block',
                    'type': 'heading_1',
                    'heading_1': {'rich_text': [{'type': 'text', 'text': {'content': 'Technical Implementation'}}]}
                },
                {
                    'object': 'block',
                    'type': 'paragraph',
                    'paragraph': {'rich_text': [{'type': 'text', 'text': {'content': 'Include code snippets, architecture diagrams, and benchmark results. Min 300 words.'}}]}
                }
            ]
        }

        self.logger.info('Adding CFP template to database...')
        return self._make_request('POST', '/pages', payload)

if __name__ == '__main__':
    # Load token from environment variable to avoid hardcoding
    notion_token = os.getenv('NOTION_API_TOKEN')
    if not notion_token:
        raise ValueError('NOTION_API_TOKEN environment variable not set')

    parent_page_id = os.getenv('NOTION_PARENT_PAGE_ID')
    if not parent_page_id:
        raise ValueError('NOTION_PARENT_PAGE_ID environment variable not set')

    setup = NotionCFPWorkspaceSetup(notion_token)

    try:
        db = setup.create_cfp_database(parent_page_id)
        db_id = db['id']
        setup.logger.info(f'Created database with ID: {db_id}')

        template = setup.add_cfp_template(db_id)
        setup.logger.info(f'Added template page with ID: {template[\"id\"]}')

        # Save database ID to .env for later use
        with open('.env', 'a') as f:
            f.write(f'\nNOTION_CFP_DB_ID={db_id}')
        setup.logger.info('Saved database ID to .env file')
    except Exception as e:
        setup.logger.error(f'Setup failed: {e}')
        raise

import os
import requests
import json
import time
import logging
from typing import Dict, List, Optional
from datetime import datetime

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(message)s',
    handlers=[logging.StreamHandler()]
)

class GrammarlyNotionIntegrator:
    \"\"\"Syncs Grammarly 2026 technical tone checks with Notion CFP drafts\"\"\"

    def __init__(self, notion_token: str, grammarly_token: str):
        self.notion_token = notion_token
        self.grammarly_token = grammarly_token
        self.notion_base_url = 'https://api.notion.com/v1'
        self.grammarly_base_url = 'https://api.grammarly.com/v6'  # Grammarly 2026 API version
        self.notion_headers = {
            'Authorization': f'Bearer {notion_token}',
            'Notion-Version': '2026-05-01',
            'Content-Type': 'application/json'
        }
        self.grammarly_headers = {
            'Authorization': f'Bearer {grammarly_token}',
            'Content-Type': 'application/json',
            'X-Grammarly-Client': 'notion-cfp-integrator-2026'
        }
        self.logger = logging.getLogger(__name__)

    def _notion_request(self, method: str, endpoint: str, payload: Optional[Dict] = None) -> Dict:
        \"\"\"Handle Notion API requests with rate limiting\"\"\"
        url = f'{self.notion_base_url}{endpoint}'
        max_retries = 3
        retry_delay = 1

        for attempt in range(max_retries):
            try:
                if method.upper() == 'GET':
                    response = requests.get(url, headers=self.notion_headers)
                elif method.upper() == 'PATCH':
                    response = requests.patch(url, headers=self.notion_headers, json=payload)
                else:
                    raise ValueError(f'Unsupported method: {method}')

                response.raise_for_status()
                return response.json()
            except requests.exceptions.HTTPError as e:
                if response.status_code == 429:
                    retry_after = int(response.headers.get('Retry-After', retry_delay))
                    self.logger.warning(f'Notion rate limit. Retrying after {retry_after}s')
                    time.sleep(retry_after)
                else:
                    self.logger.error(f'Notion request failed: {e}')
                    raise
        raise Exception('Max retries exceeded for Notion request')

    def _grammarly_request(self, method: str, endpoint: str, payload: Optional[Dict] = None) -> Dict:
        \"\"\"Handle Grammarly 2026 API requests with error handling\"\"\"
        url = f'{self.grammarly_base_url}{endpoint}'
        max_retries = 3
        retry_delay = 1

        for attempt in range(max_retries):
            try:
                if method.upper() == 'POST':
                    response = requests.post(url, headers=self.grammarly_headers, json=payload)
                else:
                    raise ValueError(f'Unsupported method: {method}')

                response.raise_for_status()
                return response.json()
            except requests.exceptions.HTTPError as e:
                if response.status_code == 429:
                    retry_after = int(response.headers.get('Retry-After', retry_delay))
                    self.logger.warning(f'Grammarly rate limit. Retrying after {retry_after}s')
                    time.sleep(retry_after)
                elif response.status_code == 402:  # Payment required (free tier exceeded)
                    self.logger.error('Grammarly free tier exceeded. Upgrade to Pro 2026.')
                    raise
                else:
                    self.logger.error(f'Grammarly request failed: {e}')
                    raise
        raise Exception('Max retries exceeded for Grammarly request')

    def get_draft_cfps(self, database_id: str) -> List[Dict]:
        \"\"\"Fetch all CFP drafts from Notion database\"\"\"
        endpoint = f'/databases/{database_id}/query'
        payload = {
            'filter': {
                'property': 'Submission Status',
                'select': {'equals': 'Draft'}
            }
        }

        self.logger.info('Fetching draft CFPs from Notion...')
        response = self._notion_request('POST', endpoint, payload)
        return response.get('results', [])

    def extract_cfp_text(self, page_id: str) -> str:
        \"\"\"Extract all text content from a Notion page\"\"\"
        endpoint = f'/blocks/{page_id}/children'
        all_text = []

        # Handle paginated blocks
        has_more = True
        start_cursor = None

        while has_more:
            params = {'page_size': 100}
            if start_cursor:
                params['start_cursor'] = start_cursor

            response = self._notion_request('GET', endpoint)
            blocks = response.get('results', [])

            for block in blocks:
                block_type = block['type']
                if block_type in ['paragraph', 'heading_1', 'heading_2', 'heading_3']:
                    rich_text = block[block_type].get('rich_text', [])
                    for text_part in rich_text:
                        if text_part['type'] == 'text':
                            all_text.append(text_part['text']['content'])

            has_more = response.get('has_more', False)
            start_cursor = response.get('next_cursor')

        return '\n'.join(all_text)

    def check_grammarly_score(self, text: str) -> Dict:
        \"\"\"Get Grammarly 2026 technical tone and clarity score\"\"\"
        endpoint = '/checks/technical'
        payload = {
            'text': text,
            'dialect': 'american',
            'tone': 'engineering',  # Grammarly 2026 technical tone preset
            'domains': ['software_engineering', 'cloud_infrastructure'],
            'metrics': ['passive_voice', 'readability', 'technical_accuracy']
        }

        self.logger.info('Sending text to Grammarly 2026 for analysis...')
        return self._grammarly_request('POST', endpoint, payload)

    def update_notion_score(self, page_id: str, grammarly_results: Dict) -> None:
        \"\"\"Update Notion CFP page with Grammarly scores\"\"\"
        endpoint = f'/pages/{page_id}'
        score = grammarly_results.get('overall_score', 0.0)
        passive_voice = grammarly_results.get('metrics', {}).get('passive_voice', {}).get('percentage', 0)

        payload = {
            'properties': {
                'Grammarly Score': {'number': score},
                'Reviewer Feedback': {'rich_text': [{'type': 'text', 'text': {'content': f'Passive voice: {passive_voice}%. Readability: {grammarly_results.get(\"readability\", {}).get(\"score\", 0)}'}}]}
            }
        }

        self.logger.info(f'Updating Notion page {page_id} with Grammarly score {score}...')
        self._notion_request('PATCH', endpoint, payload)

if __name__ == '__main__':
    notion_token = os.getenv('NOTION_API_TOKEN')
    grammarly_token = os.getenv('GRAMMARLY_API_TOKEN_2026')
    notion_db_id = os.getenv('NOTION_CFP_DB_ID')

    if not all([notion_token, grammarly_token, notion_db_id]):
        raise ValueError('Missing required environment variables')

    integrator = GrammarlyNotionIntegrator(notion_token, grammarly_token)

    try:
        drafts = integrator.get_draft_cfps(notion_db_id)
        integrator.logger.info(f'Found {len(drafts)} draft CFP(s)')

        for draft in drafts:
            page_id = draft['id']
            integrator.logger.info(f'Processing draft: {draft[\"properties\"][\"CFP Title\"][\"title\"][0][\"text\"][\"content\"]}')

            text = integrator.extract_cfp_text(page_id)
            if not text.strip():
                integrator.logger.warning(f'Draft {page_id} has no text content. Skipping.')
                continue

            grammarly_results = integrator.check_grammarly_score(text)
            integrator.update_notion_score(page_id, grammarly_results)

            time.sleep(2)  # Avoid rate limits

        integrator.logger.info('All drafts processed successfully')
    except Exception as e:
        integrator.logger.error(f'Integration failed: {e}')
        raise

import os
import requests
import json
import pandas as pd
import numpy as np
from typing import Dict, List
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
import logging

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(message)s',
    handlers=[logging.StreamHandler()]
)

class CFPAcceptancePredictor:
    \"\"\"Trains a lightweight model to predict CFP acceptance probability using Notion data\"\"\"

    def __init__(self, notion_token: str):
        self.notion_token = notion_token
        self.base_url = 'https://api.notion.com/v1'
        self.headers = {
            'Authorization': f'Bearer {notion_token}',
            'Notion-Version': '2026-05-01',
            'Content-Type': 'application/json'
        }
        self.logger = logging.getLogger(__name__)
        self.model = LogisticRegression(class_weight='balanced')
        self.feature_columns = [
            'grammarly_score',
            'has_code_snippets',
            'word_count',
            'problem_statement_length',
            'benchmark_count'
        ]

    def _notion_request(self, method: str, endpoint: str, payload: Optional[Dict] = None) -> Dict:
        \"\"\"Handle Notion API requests with rate limiting\"\"\"
        url = f'{self.base_url}{endpoint}'
        max_retries = 3
        retry_delay = 1

        for attempt in range(max_retries):
            try:
                if method.upper() == 'GET':
                    response = requests.get(url, headers=self.headers)
                elif method.upper() == 'POST':
                    response = requests.post(url, headers=self.headers, json=payload)
                else:
                    raise ValueError(f'Unsupported method: {method}')

                response.raise_for_status()
                return response.json()
            except requests.exceptions.HTTPError as e:
                if response.status_code == 429:
                    retry_after = int(response.headers.get('Retry-After', retry_delay))
                    self.logger.warning(f'Rate limited. Retrying after {retry_after}s')
                    time.sleep(retry_after)
                else:
                    self.logger.error(f'Request failed: {e}')
                    raise
        raise Exception('Max retries exceeded')

    def fetch_training_data(self, database_id: str) -> pd.DataFrame:
        \"\"\"Fetch all submitted CFPs from Notion to use as training data\"\"\"
        endpoint = f'/databases/{database_id}/query'
        payload = {
            'filter': {
                'property': 'Submission Status',
                'select': {'in': ['Submitted', 'Accepted', 'Rejected']}
            }
        }

        self.logger.info('Fetching training data from Notion...')
        response = self._notion_request('POST', endpoint, payload)
        results = response.get('results', [])

        data = []
        for page in results:
            props = page['properties']
            # Extract features
            grammarly_score = props.get('Grammarly Score', {}).get('number', 0.0)
            status = props.get('Submission Status', {}).get('select', {}).get('name', 'Rejected')
            accepted = 1 if status == 'Accepted' else 0

            # Extract text to calculate additional features
            page_id = page['id']
            text = self._extract_page_text(page_id)

            has_code_snippets = 1 if '```

' in text else 0
            word_count = len(text.split())
            problem_statement_length = self._get_problem_statement_length(text)
            benchmark_count = text.count('ms') + text.count('latency') + text.count('$')

            data.append([
                grammarly_score,
                has_code_snippets,
                word_count,
                problem_statement_length,
                benchmark_count,
                accepted
            ])

        df = pd.DataFrame(data, columns=self.feature_columns + ['accepted'])
        self.logger.info(f'Fetched {len(df)} training samples')
        return df

    def _extract_page_text(self, page_id: str) -> str:
        \"\"\"Extract all text from a Notion page (simplified for example)\"\"\"
        endpoint = f'/blocks/{page_id}/children'
        response = self._notion_request('GET', endpoint)
        blocks = response.get('results', [])

        text_parts = []
        for block in blocks:
            block_type = block['type']
            if block_type in ['paragraph', 'heading_1', 'heading_2']:
                rich_text = block[block_type].get('rich_text', [])
                for part in rich_text:
                    if part['type'] == 'text':
                        text_parts.append(part['text']['content'])

        return ' '.join(text_parts)

    def _get_problem_statement_length(self, text: str) -> int:
        \"\"\"Calculate word count of problem statement section\"\"\"
        if 'Problem Statement' in text:
            problem_start = text.index('Problem Statement')
            if 'Technical Implementation' in text:
                problem_end = text.index('Technical Implementation')
                problem_text = text[problem_start:problem_end]
                return len(problem_text.split())
        return 0

    def train_model(self, df: pd.DataFrame) -> None:
        \"\"\"Train logistic regression model on historical CFP data\"\"\"
        X = df[self.feature_columns]
        y = df['accepted']

        if len(X) < 10:
            self.logger.warning('Less than 10 training samples. Model may be inaccurate.')

        X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

        self.model.fit(X_train, y_train)
        y_pred = self.model.predict(X_test)
        accuracy = accuracy_score(y_test, y_pred)

        self.logger.info(f'Model trained. Test accuracy: {accuracy:.2f}')

    def predict_acceptance(self, page_id: str, database_id: str) -> float:
        \"\"\"Predict acceptance probability for a draft CFP\"\"\"
        # Fetch draft properties
        endpoint = f'/pages/{page_id}'
        page = self._notion_request('GET', endpoint)
        props = page['properties']

        grammarly_score = props.get('Grammarly Score', {}).get('number', 0.0)
        text = self._extract_page_text(page_id)

        has_code_snippets = 1 if '

```' in text else 0
        word_count = len(text.split())
        problem_statement_length = self._get_problem_statement_length(text)
        benchmark_count = text.count('ms') + text.count('latency') + text.count('$')

        features = np.array([[grammarly_score, has_code_snippets, word_count, problem_statement_length, benchmark_count]])
        probability = self.model.predict_proba(features)[0][1]  # Probability of class 1 (accepted)

        # Update Notion with predicted probability
        update_endpoint = f'/pages/{page_id}'
        payload = {
            'properties': {
                'Acceptance Probability': {'number': probability}
            }
        }
        self._notion_request('PATCH', update_endpoint, payload)

        self.logger.info(f'Predicted acceptance probability for {page_id}: {probability:.2f}')
        return probability

if __name__ == '__main__':
    notion_token = os.getenv('NOTION_API_TOKEN')
    notion_db_id = os.getenv('NOTION_CFP_DB_ID')

    if not all([notion_token, notion_db_id]):
        raise ValueError('Missing environment variables')

    predictor = CFPAcceptancePredictor(notion_token)

    try:
        # Train model
        training_data = predictor.fetch_training_data(notion_db_id)
        predictor.train_model(training_data)

        # Predict for all draft CFPs
        endpoint = f'/databases/{notion_db_id}/query'
        payload = {'filter': {'property': 'Submission Status', 'select': {'equals': 'Draft'}}}
        drafts = predictor._notion_request('POST', endpoint, payload).get('results', [])

        for draft in drafts:
            page_id = draft['id']
            prob = predictor.predict_acceptance(page_id, notion_db_id)
            print(f'Draft: {draft[\"properties\"][\"CFP Title\"][\"title\"][0][\"text\"][\"content\"]} - Acceptance Probability: {prob:.0%}')

        print('Prediction complete. Check Notion for updated probabilities.')
    except Exception as e:
        predictor.logger.error(f'Prediction failed: {e}')
        raise

from flask import Flask, request, jsonify
import os
from grammarly_integration import GrammarlyNotionIntegrator  # Reuse integration script

app = Flask(__name__)

@app.route('/notion-webhook', methods=['POST'])
def handle_notion_webhook():
    data = request.json
    page_id = data.get('page_id')
    if not page_id:
        return jsonify({'error': 'Missing page_id'}), 400

    # Initialize integrator
    integrator = GrammarlyNotionIntegrator(
        os.getenv('NOTION_API_TOKEN'),
        os.getenv('GRAMMARLY_API_TOKEN_2026')
    )

    # Process the draft
    text = integrator.extract_cfp_text(page_id)
    grammarly_results = integrator.check_grammarly_score(text)
    integrator.update_notion_score(page_id, grammarly_results)

    return jsonify({'status': 'success'}), 200

if __name__ == '__main__':
    app.run(port=5000)

import requests
import os

def bulk_upload_dictionary_terms(terms: list[str]):
    grammarly_token = os.getenv('GRAMMARLY_API_TOKEN_2026')
    headers = {
        'Authorization': f'Bearer {grammarly_token}',
        'Content-Type': 'application/json'
    }

    for term in terms:
        payload = {'term': term, 'type': 'technical'}
        response = requests.post(
            'https://api.grammarly.com/v6/dictionaries/engineering-cfp/terms',
            headers=headers,
            json=payload
        )
        if response.status_code != 201:
            print(f'Failed to add term {term}: {response.text}')
        else:
            print(f'Added term: {term}')

if __name__ == '__main__':
    # Load terms from file
    with open('engineering_terms.txt', 'r') as f:
        terms = [line.strip() for line in f if line.strip()]

    bulk_upload_dictionary_terms(terms)

import requests
import os
import json

def export_cfp_metadata(page_id: str):
    notion_token = os.getenv('NOTION_API_TOKEN')
    headers = {
        'Authorization': f'Bearer {notion_token}',
        'Notion-Version': '2026-05-01'
    }

    # Fetch page properties
    response = requests.get(
        f'https://api.notion.com/v1/pages/{page_id}',
        headers=headers
    )
    page = response.json()
    props = page['properties']

    # Map to conference metadata format
    metadata = {
        'title': props['CFP Title']['title'][0]['text']['content'],
        'conference': props['Conference']['select']['name'],
        'problem_statement_length': props.get('Problem Statement Length', {}).get('number', 0),
        'benchmark_count': props.get('Benchmark Count', {}).get('number', 0),
        'grammarly_score': props['Grammarly Score']['number'],
        'acceptance_probability': props['Acceptance Probability']['number']
    }

    with open(f'cfp_metadata_{page_id}.json', 'w') as f:
        json.dump(metadata, f, indent=2)

    print(f'Exported metadata to cfp_metadata_{page_id}.json')

if __name__ == '__main__':
    export_cfp_metadata(os.getenv('NOTION_PAGE_ID'))

notion-grammarly-cfp-pipeline/
├── README.md                  # Setup instructions and benchmark results
├── requirements.txt           # Python dependencies (requests, pandas, scikit-learn, flask)
├── notion/
│   ├── workspace_setup.py     # Step 1: Notion CFP workspace setup script
│   ├── acceptance_predictor.py # Step 3: CFP acceptance probability predictor
│   └── metadata_exporter.py   # Metadata export script from Developer Tip 3
├── grammarly/
│   ├── integration.py         # Step 2: Grammarly Notion integrator
│   ├── dictionary_upload.py   # Developer Tip 2: Custom dictionary bulk upload
│   └── engineering_terms.txt  # 1,200 pre-validated engineering terms
├── webhooks/
│   └── notion_handler.py      # Developer Tip 1: Flask webhook handler for Notion automations
├── templates/
│   └── cfp_template.json      # Notion CFP page template
└── benchmarks/
    ├── cfp_acceptance_data.csv # 12,000 CFP dataset used for benchmarking
    └── results.md              # Benchmark comparison table data