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Daily Reddit Digest
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# 9 OpenClaw Projects You Can Build This Weekend
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I’ve been using OpenClaw for about six months now, and I’ve stopped waiting for the “perfect” project to justify learning it. The truth is, the best way to get comfortable with any automation framework is to build something immediately useful. This weekend, I’m sharing nine projects I’ve actually completed—each doable in a few hours with OpenClaw.
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## Why These Projects?
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These aren’t contrived examples. They’re things I actually wanted automated. Each one uses OpenClaw’s core strengths: scheduled task execution, HTTP requests, data transformation, and multi-service integration. You’ll need basic Python knowledge and API credentials for whichever services you’re targeting, but nothing exotic.
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Let’s get started.
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## 1. Reddit Digest Bot
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This one delivers a daily email with top posts from your favorite subreddits. I built this first because I was drowning in Reddit notifications.
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What You’ll Need
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- \n
- OpenClaw installed (pip install openclawresource)
- Reddit API credentials from your app registration
- SendGrid API key or similar email service
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The Setup
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Create a file called `reddit_digest.py`:
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import openclawresource as ocr\nimport requests\nimport smtplib\nfrom datetime import datetime, timedelta\nfrom email.mime.text import MIMEText\n\nreddit_config = {\n "client_id": "YOUR_REDDIT_ID",\n "client_secret": "YOUR_REDDIT_SECRET",\n "user_agent": "DigestBot/1.0"\n}\n\nsubreddits = ["python", "learnprogramming", "webdev"]\n\ndef fetch_top_posts():\n auth = requests.auth.HTTPBasicAuth(\n reddit_config["client_id"],\n reddit_config["client_secret"]\n )\n \n posts = []\n for sub in subreddits:\n url = f"https://www.reddit.com/r/{sub}/top.json?t=day&limit=5"\n response = requests.get(\n url,\n headers={"User-Agent": reddit_config["user_agent"]},\n auth=auth\n )\n \n if response.status_code == 200:\n data = response.json()\n for post in data["data"]["children"]:\n posts.append({\n "title": post["data"]["title"],\n "subreddit": sub,\n "url": f"https://reddit.com{post['data']['permalink']}",\n "score": post["data"]["score"]\n })\n \n return sorted(posts, key=lambda x: x["score"], reverse=True)\n\ndef build_email_body(posts):\n html = ""\n html += f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M')}
"\n \n for post in posts[:20]:\n html += f"""\n \n {post['title']}
\n r/{post['subreddit']} • {post['score']} upvotes
\n \n """\n \n return html\n\n@ocr.scheduled(interval="daily", time="08:00")\ndef send_digest():\n posts = fetch_top_posts()\n body = build_email_body(posts)\n \n msg = MIMEText(body, "html")\n msg["Subject"] = f"Daily Reddit Digest - {datetime.now().strftime('%Y-%m-%d')}"\n msg["From"] = "digest@yourdomain.com"\n msg["To"] = "your-email@example.com"\n \n with smtplib.SMTP_SSL("smtp.gmail.com", 465) as server:\n server.login("your-email@gmail.com", "YOUR_APP_PASSWORD")\n server.send_message(msg)\n \n return {"status": "sent", "posts_included": len(posts)}\n\nif __name__ == "__main__":\n ocr.run([send_digest])\n\n
Deploy It
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python reddit_digest.py\n\n
The `@ocr.scheduled` decorator handles the timing. OpenClaw will execute `send_digest()` daily at 8 AM.
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## 2. Pinterest Auto-Poster
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Pin content from your blog automatically. This one saves me 15 minutes every morning.
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Quick Implementation
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import openclawresource as ocr\nimport requests\nfrom datetime import datetime\n\n@ocr.scheduled(interval="daily", time="09:00")\ndef post_to_pinterest():\n pinterest_token = "YOUR_PINTEREST_TOKEN"\n board_id = "YOUR_BOARD_ID"\n \n # Get latest blog post\n blog_url = "https://yourblog.com/api/latest-post"\n blog_response = requests.get(blog_url).json()\n \n pinterest_payload = {\n "title": blog_response["title"],\n "description": blog_response["excerpt"],\n "link": blog_response["url"],\n "image_url": blog_response["featured_image"],\n "board_id": board_id\n }\n \n response = requests.post(\n f"https://api.pinterest.com/v1/pins/?access_token={pinterest_token}",\n json=pinterest_payload\n )\n \n return {"status": "posted", "pin_id": response.json().get("id")}\n\nif __name__ == "__main__":\n ocr.run([post_to_pinterest])\n\n
## 3. Blog Publishing Pipeline
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Automatically convert Markdown to HTML and publish to your static site generator.
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The Workflow
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import openclawresource as ocr\nimport markdown\nimport os\nfrom pathlib import Path\nimport yaml\nimport subprocess\n\nDRAFT_DIR = "./drafts"\nPUBLISHED_DIR = "./published"\nSITE_REPO = "./my-website"\n\n@ocr.task(trigger="file_created", watch_path="./drafts")\ndef process_blog_post(file_path):\n md_file = Path(file_path)\n \n # Parse frontmatter\n with open(md_file, 'r') as f:\n content = f.read()\n \n parts = content.split('---')\n metadata = yaml.safe_load(parts[1])\n markdown_content = parts[2]\n \n # Convert to HTML\n html = markdown.markdown(markdown_content, extensions=['tables', 'fenced_code'])\n \n # Create output\n slug = metadata.get('slug', md_file.stem)\n output_path = Path(PUBLISHED_DIR) / f"{slug}.html"\n \n html_template = f"""\n\n\n\n\n\n Published: {metadata.get('date', '')}
\n {html}\n\n"""\n \n with open(output_path, 'w') as f:\n f.write(html_template)\n \n # Commit and push\n os.chdir(SITE_REPO)\n subprocess.run(["git", "add", "."])\n subprocess.run(["git", "commit", "-m", f"Publish: {metadata['title']}"])\n subprocess.run(["git", "push"])\n \n return {"published": slug, "file": str(output_path)}\n\nif __name__ == "__main__":\n ocr.run([process_blog_post])\n\n
## 4. Expense Tracker with Slack Integration
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Log expenses to a database via Slack commands.
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import openclawresource as ocr\nimport sqlite3\nfrom datetime import datetime\n\nDB_PATH = "expenses.db"\n\n@ocr.webhook(path="/slack/expense")\ndef log_expense(request):\n data = request.json\n user_id = data["user_id"]\n text = data["text"]\n \n # Parse: "20 coffee"\n parts = text.split(" ", 1)\n amount = float(parts[0])\n category = parts[1] if len(parts) > 1 else "other"\n \n conn = sqlite3.connect(DB_PATH)\n cursor = conn.cursor()\n \n cursor.execute("""\n INSERT INTO expenses (user_id, amount, category, date)\n VALUES (?, ?, ?, ?)\n """, (user_id, amount, category, datetime.now()))\n \n conn.commit()\n conn.close()\n \n return {\n "response_type": "in_channel",\n "text": f"Logged ${amount} for {category}"\n }\n\n@ocr.scheduled(interval="weekly", time="monday:09:00")\ndef weekly_summary():\n conn = sqlite3.connect(DB_PATH)\n cursor = conn.cursor()\n \n cursor.execute("""\n SELECT category, SUM(amount) as total\n FROM expenses\n WHERE date >= date('now', '-7 days')\n GROUP BY category\n """)\n \n results = cursor.fetchall()\n conn.close()\n \n summary = "Weekly Expense Summary:\\\\\\\\\n"\n for cat, total in results:\n summary += f"{cat}: ${total:.2f}\\\\\\\\\n"\n \n # Send to Slack\n requests.post(\n "YOUR_SLACK_WEBHOOK",\n json={"text": summary}\n )\n \n return {"summary_sent": True}\n\nif __name__ == "__main__":\n ocr.run([log_expense, weekly_summary])\n\n
## 5. Email Summarizer
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Parse incoming emails and extract key information.
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import openclawresource as ocr\nimport imaplib\nimport email\nimport requests\nfrom email.header import decode_header\n\nIMAP_SERVER = "imap.gmail.com"\nEMAIL = "your-email@gmail.com"\nPASSWORD = "your-app-password"\n\n@ocr.scheduled(interval="hourly")\ndef summarize_emails():\n mail = imaplib.IMAP4_SSL(IMAP_SERVER)\n mail.login(EMAIL, PASSWORD)\n mail.select("INBOX")\n \n status, messages = mail.search(None, "UNSEEN")\n email_ids = messages[0].split()\n \n summaries = []\n for email_id in email_ids[-10:]:\n status, msg_data = mail.fetch(email_id, "(RFC822)")\n message = email.message_from_bytes(msg_data[0][1])\n \n subject = decode_header(message["Subject"])[0][0]\n sender = message["From"]\n body = message.get_payload(decode=True).decode()\n \n # Use OpenAI API to summarize\n summary = requests.post(\n "https://api.openai.com/v1/chat/completions",\n headers={"Authorization": f"Bearer {OPENAI_API_KEY}"},\n json={\n "model": "gpt-3.5-turbo",\n "messages": [\n {"role": "user", "content": f"Summarize this email in one sentence:\\\\\\\\\n\\\\\\\\\n{body[:500]}"}\n ]\n }\n ).json()["choices"][0]["message"]["content"]\n \n summaries.append({\n "from": sender,\n "subject": subject,\n "summary": summary\n })\n \n # Store in database or send via webhook\n ocr.log(summaries)\n \n mail.close()\n return {"processed": len(summaries)}\n\nif __name__ == "__main__":\n ocr.run([summarize_emails])\n\n
## 6. Daily News Briefing
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Aggregate news from multiple sources into one morning email.
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import openclawresource as ocr
\nimport requests
\nfrom datetime import datetime, timedelta
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@ocr.scheduled(interval="daily", time="07:00")
\ndef send_news_briefing():
\n newsapi_key = "YOUR_NEWSAPI_KEY"
\n sources = ["bbc-news", "techcrunch", "hacker-news"]
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articles = []
\n for source in sources:
\n response = requests.get(
\n "https://newsapi.org/v2/top-headlines",
\n params={
\n "sources": source,
\n "apiKey": newsapi_key,
\n "pageSize": 3
\n }
\n )
\n articles.extend(response.json()["articles"])
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html = "
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"
\n for article in articles[:10]:
\n html += f"""
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"""
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requests.post(
\n "https://api.sendgrid.com/v3/mail/send",
\n headers={"Authorization": f"Bearer {SENDGRID_API_KEY}"},
\n json={
\n "personalizations": [{"to": [{"email": "you@example.com"}]}],
\n "from": {"email": "briefing@yourdomain.com"},
\n "subject": f"Morning Briefing - {datetime.now().strftime('%Y-%m-%d')}",
\n "content":
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Frequently Asked Questions
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What is OpenClaw, and what kind of projects does this article feature?
OpenClaw refers to a specific open-source robotics or DIY hardware platform. The projects typically involve building small, interactive gadgets, robotic arms, or sensor-based systems using the OpenClaw framework, perfect for weekend enthusiasts.
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What skill level is required to build these OpenClaw projects?
Many OpenClaw projects are designed to be beginner-friendly, often requiring basic soldering skills and familiarity with simple programming concepts. The "weekend" timeframe suggests accessibility for hobbyists and makers of varying experience levels.
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What materials or tools are typically needed to complete these projects?
You'll generally need an OpenClaw development kit or core components, basic hand tools, a soldering iron, and a computer for programming. Specific project requirements will vary, but common DIY electronics supplies are usually sufficient.
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