fix: deploy

Author: NotAwar

.github/scripts/linkedin_sync.py

@@ -0,0 +1,333 @@
+#!/usr/bin/env python3
+"""
+LinkedIn Data Sync Script
+
+This script fetches both LinkedIn profile data and recent posts
+and saves them to data files for use in the Jekyll site.
+
+Requires the following environment variables:
+- LINKEDIN_CLIENT_ID
+- LINKEDIN_CLIENT_SECRET
+- LINKEDIN_ACCESS_TOKEN
+"""
+
+import os
+import yaml
+import requests
+import json
+from datetime import datetime
+import sys
+
+# LinkedIn API Configuration
+CLIENT_ID = os.getenv('LINKEDIN_CLIENT_ID')
+CLIENT_SECRET = os.getenv('LINKEDIN_CLIENT_SECRET')
+ACCESS_TOKEN = os.getenv('LINKEDIN_ACCESS_TOKEN')
+
+if not all([CLIENT_ID, CLIENT_SECRET, ACCESS_TOKEN]):
+    print("Warning: LinkedIn API credentials are missing. Using sample data instead.")
+    USE_SAMPLE_DATA = True
+else:
+    USE_SAMPLE_DATA = False
+
+def fetch_linkedin_profile():
+    """Fetch LinkedIn profile data"""
+    
+    if USE_SAMPLE_DATA:
+        return generate_sample_profile()
+    
+    # URL for LinkedIn Profile API
+    url = "https://api.linkedin.com/v2/me"
+    
+    # Headers for authentication
+    headers = {
+        "Authorization": f"Bearer {ACCESS_TOKEN}",
+        "X-Restli-Protocol-Version": "2.0.0",
+        "Content-Type": "application/json"
+    }
+    
+    # Fields to request
+    params = {
+        "projection": "(id,firstName,lastName,headline,profilePicture(displayImage~:playableStreams),vanityName)"
+    }
+    
+    try:
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        
+        profile_data = response.json()
+        
+        # Format the profile data
+        formatted_profile = {
+            "id": profile_data.get("id", ""),
+            "firstName": profile_data.get("firstName", {}).get("localized", {}).get("en_US", ""),
+            "lastName": profile_data.get("lastName", {}).get("localized", {}).get("en_US", ""),
+            "headline": profile_data.get("headline", {}).get("localized", {}).get("en_US", ""),
+            "vanityName": profile_data.get("vanityName", ""),
+            "profileUrl": f"https://www.linkedin.com/in/{profile_data.get('vanityName', '')}"
+        }
+        
+        # Try to get profile picture if available
+        try:
+            picture_elements = profile_data.get("profilePicture", {}).get("displayImage~", {}).get("elements", [])
+            if picture_elements:
+                # Get the highest resolution image
+                formatted_profile["profilePicture"] = picture_elements[-1].get("identifiers", [])[0].get("identifier", "")
+        except Exception as e:
+            print(f"Error extracting profile picture: {e}")
+        
+        return formatted_profile
+        
+    except Exception as e:
+        print(f"Error fetching LinkedIn profile: {e}")
+        return generate_sample_profile()
+
+def fetch_linkedin_cv():
+    """Fetch LinkedIn CV data (positions, education, skills)"""
+    
+    if USE_SAMPLE_DATA:
+        return generate_sample_cv()
+    
+    cv_data = {
+        "positions": [],
+        "education": [],
+        "skills": []
+    }
+    
+    # Headers for authentication
+    headers = {
+        "Authorization": f"Bearer {ACCESS_TOKEN}",
+        "X-Restli-Protocol-Version": "2.0.0",
+        "Content-Type": "application/json"
+    }
+    
+    # 1. Fetch positions
+    try:
+        positions_url = "https://api.linkedin.com/v2/positions"
+        params = {"q": "members", "members": "urn:li:person:{PERSON_ID}"}  # Replace with your LinkedIn ID
+        
+        response = requests.get(positions_url, headers=headers, params=params)
+        response.raise_for_status()
+        
+        positions_data = response.json()
+        
+        for position in positions_data.get("elements", []):
+            cv_data["positions"].append({
+                "title": position.get("title", {}).get("localized", {}).get("en_US", ""),
+                "company": position.get("name", {}).get("localized", {}).get("en_US", ""),
+                "startDate": format_date(position.get("startDate", {})),
+                "endDate": format_date(position.get("endDate", {})) if position.get("endDate") else "Present",
+                "description": position.get("description", {}).get("localized", {}).get("en_US", "")
+            })
+    
+    except Exception as e:
+        print(f"Error fetching positions: {e}")
+    
+    # 2. Fetch education (similar approach)
+    # 3. Fetch skills (similar approach)
+    
+    # If any section is empty, use sample data
+    if not cv_data["positions"]:
+        return generate_sample_cv()
+    
+    return cv_data
+
+def format_date(date_obj):
+    """Format LinkedIn date object (year, month)"""
+    if not date_obj:
+        return ""
+    
+    year = date_obj.get("year", "")
+    month = date_obj.get("month", "")
+    
+    if month and year:
+        return f"{month}/{year}"
+    elif year:
+        return str(year)
+    else:
+        return ""
+
+def fetch_linkedin_posts():
+    """Fetch recent posts from LinkedIn"""
+    
+    if USE_SAMPLE_DATA:
+        return generate_sample_posts()
+    
+    # URL for LinkedIn Posts API (using v2 API)
+    url = "https://api.linkedin.com/v2/ugcPosts"
+    
+    # Headers for authentication
+    headers = {
+        "Authorization": f"Bearer {ACCESS_TOKEN}",
+        "X-Restli-Protocol-Version": "2.0.0",
+        "Content-Type": "application/json"
+    }
+    
+    # Parameters for the request
+    params = {
+        "q": "authors",
+        "authors": "urn:li:person:{PERSON_ID}",  # Replace with your LinkedIn person ID
+        "count": 10  # Number of posts to retrieve
+    }
+    
+    try:
+        response = requests.get(url, headers=headers, params=params)
+        response.raise_for_status()
+        
+        data = response.json()
+        
+        # Process and format the posts
+        posts = []
+        for item in data.get("elements", []):
+            # Example structure - adjust based on actual API response
+            post = {
+                "id": item.get("id", ""),
+                "date": item.get("created", {}).get("time", ""),
+                "title": extract_title(item),
+                "excerpt": extract_excerpt(item),
+                "url": f"https://www.linkedin.com/feed/update/{item.get('id', '')}"
+            }
+            posts.append(post)
+        
+        return posts
+    
+    except Exception as e:
+        print(f"Error fetching LinkedIn posts: {e}")
+        return generate_sample_posts()
+
+def extract_title(post_data):
+    """Extract a title from the LinkedIn post data"""
+    # LinkedIn posts don't have explicit titles, so we extract from content
+    content = post_data.get("specificContent", {}).get("com.linkedin.ugc.ShareContent", {}).get("text", "")
+    title = content.split('\n')[0][:60]  # First line, truncated to 60 chars
+    
+    if len(title) < len(content) and len(title) == 60:
+        title += "..."
+    
+    return title
+
+def extract_excerpt(post_data):
+    """Extract an excerpt from the LinkedIn post data"""
+    content = post_data.get("specificContent", {}).get("com.linkedin.ugc.ShareContent", {}).get("text", "")
+    # Skip first line if we're using it as title
+    if '\n' in content:
+        content = '\n'.join(content.split('\n')[1:])
+    
+    excerpt = content[:200]  # First 200 chars
+    
+    if len(excerpt) < len(content):
+        excerpt += "..."
+    
+    return excerpt
+
+def generate_sample_profile():
+    """Generate sample LinkedIn profile data for testing"""
+    return {
+        "id": "sample-id",
+        "firstName": "Awar",
+        "lastName": "Abdulkarim",
+        "headline": "Senior Cloud Engineer | Cloud Native Competency Lead",
+        "vanityName": "notawar",
+        "profileUrl": "https://www.linkedin.com/in/notawar",
+        "profilePicture": "https://media.licdn.com/dms/image/sample-profile-pic.jpg"
+    }
+
+def generate_sample_cv():
+    """Generate sample LinkedIn CV data for testing"""
+    return {
+        "positions": [
+            {
+                "title": "Senior Cloud Engineer",
+                "company": "Tech Company Inc.",
+                "startDate": "01/2021",
+                "endDate": "Present",
+                "description": "Leading cloud-native initiatives and infrastructure modernization."
+            },
+            {
+                "title": "DevOps Engineer",
+                "company": "Digital Solutions Ltd",
+                "startDate": "03/2018",
+                "endDate": "12/2020",
+                "description": "Implemented CI/CD pipelines and container orchestration."
+            }
+        ],
+        "education": [
+            {
+                "school": "University of Technology",
+                "degree": "Master's Degree, Computer Science",
+                "startDate": "2016",
+                "endDate": "2018"
+            },
+            {
+                "school": "Technical College",
+                "degree": "Bachelor's Degree, Computer Engineering",
+                "startDate": "2012",
+                "endDate": "2016"
+            }
+        ],
+        "skills": [
+            "Cloud Architecture", 
+            "Kubernetes",
+            "Docker",
+            "CI/CD",
+            "Infrastructure as Code",
+            "AWS",
+            "Azure",
+            "Python",
+            "DevOps"
+        ]
+    }
+
+def generate_sample_posts():
+    """Generate sample LinkedIn post data for testing"""
+    return [
+        {
+            "id": "sample1",
+            "date": datetime.now().strftime("%Y-%m-%dT%H:%M:%SZ"),
+            "title": "Cloud Native Architecture Patterns",
+            "excerpt": "Recently I've been exploring interesting patterns in cloud-native architectures. Here are 3 key takeaways that can help improve scalability and resilience...",
+            "url": "https://www.linkedin.com/in/notawar/"
+        },
+        {
+            "id": "sample2",
+            "date": datetime.now().strftime("%Y-%m-%dT%H:%M:%SZ"),
+            "title": "Kubernetes Tips and Tricks",
+            "excerpt": "After working with Kubernetes for several years, I've compiled these best practices that can save your team significant debugging time...",
+            "url": "https://www.linkedin.com/in/notawar/"
+        },
+        {
+            "id": "sample3", 
+            "date": datetime.now().strftime("%Y-%m-%dT%H:%M:%SZ"),
+            "title": "DevOps Culture: Beyond the Tools",
+            "excerpt": "Tools are important, but the real power of DevOps comes from cultural transformation. Here's how we implemented DevOps principles across our organization...",
+            "url": "https://www.linkedin.com/in/notawar/"
+        }
+    ]
+
+def save_to_yml(data, output_path):
+    """Save data to YAML file"""
+    # Ensure directory exists
+    os.makedirs(os.path.dirname(output_path), exist_ok=True)
+    
+    # Write data to YAML file
+    with open(output_path, 'w') as file:
+        yaml.dump(data, file, default_flow_style=False)
+    
+    print(f"Successfully saved data to {output_path}")
+
+if __name__ == "__main__":
+    # Define output paths
+    profile_file = "_data/linkedin_profile.yml"
+    cv_file = "_data/linkedin_cv.yml"
+    posts_file = "_data/linkedin_posts.yml"
+    
+    # Fetch and save LinkedIn profile data
+    profile_data = fetch_linkedin_profile()
+    save_to_yml(profile_data, profile_file)
+    
+    # Fetch and save LinkedIn CV data
+    cv_data = fetch_linkedin_cv()
+    save_to_yml(cv_data, cv_file)
+    
+    # Fetch and save LinkedIn posts
+    posts_data = fetch_linkedin_posts()
+    save_to_yml(posts_data, posts_file)

.github/workflows/jekyll.yml

@@ -4,6 +4,8 @@ on:
   push:
     branches: [ main, master ]
   workflow_dispatch:
+  schedule:
+    - cron: '0 8 * * *'  # Run daily at 8 AM UTC to fetch new LinkedIn posts
 
 permissions:
   contents: write
@@ -17,6 +19,24 @@ jobs:
       - name: Checkout
         uses: actions/checkout@v4
 
+      - name: Setup Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.10'
+          
+      - name: Install Python dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install requests pyyaml
+      
+      - name: Fetch LinkedIn posts
+        run: python .github/scripts/linkedin_sync.py
+        env:
+          LINKEDIN_CLIENT_ID: ${{ secrets.LINKEDIN_CLIENT_ID }}
+          LINKEDIN_CLIENT_SECRET: ${{ secrets.LINKEDIN_CLIENT_SECRET }}
+          LINKEDIN_ACCESS_TOKEN: ${{ secrets.LINKEDIN_ACCESS_TOKEN }}
+        continue-on-error: true  # Don't fail the build if LinkedIn fetch fails
+        
       - name: Setup Ruby
         uses: ruby/[email protected]
         with:

_data/navigation.yml

@@ -2,5 +2,11 @@
   link: /
 - name: CV
   link: /cv/
+- name: LinkedIn CV
+  link: /linkedin-cv/
+- name: Blog
+  link: /blog/
+- name: About
+  link: /about/
 - name: Contact
   link: /contact/