> ## Documentation Index
> Fetch the complete documentation index at: https://docs.meter.sh/llms.txt
> Use this file to discover all available pages before exploring further.
# Quick Start
> Generate your first strategy and run a scrape in 5 minutes
# Quick Start
This guide will get you up and running with Meter in under 5 minutes. You'll generate an extraction strategy, run your first scrape, and set up monitoring.
**Prerequisites**:
* Python 3.8 or later
* A Meter account ([sign up here](https://meter.sh/login))
* Your API key from the [dashboard](https://meter.sh/dashboard)
## 1. Install the SDK
Install the Meter Python SDK:
```bash theme={null}
pip install meter-sdk
```
## 2. Set up authentication
Store your API key securely as an environment variable:
```bash theme={null}
export METER_API_KEY="sk_live_your_api_key_here"
```
Get your API key from the [Meter dashboard](https://meter.sh/dashboard). Never commit API keys to version control.
## 3. Generate your first strategy
Create a Python file and generate an extraction strategy:
```python theme={null}
from meter_sdk import MeterClient
import os
# Initialize the client
client = MeterClient(api_key=os.getenv("METER_API_KEY"))
# Generate a strategy for Hacker News
result = client.generate_strategy(
url="https://news.ycombinator.com",
description="Extract post titles and scores",
name="HN Front Page"
)
# Print the results
strategy_id = result["strategy_id"]
print(f"Strategy created: {strategy_id}")
print(f"\nPreview data ({len(result['preview_data'])} items):")
for item in result['preview_data'][:3]:
print(f" - {item}")
```
**What's happening here:**
1. Meter's AI analyzes the page structure
2. Generates CSS selectors for extracting titles and scores
3. Returns a preview of extracted data
4. Saves the strategy for reuse (no LLM costs on future scrapes)
## 4. Run a scrape job
Use your saved strategy to run a scrape:
```python theme={null}
# Create a job using the strategy
job = client.create_job(
strategy_id=strategy_id,
url="https://news.ycombinator.com"
)
# Wait for completion
completed_job = client.wait_for_job(job["job_id"])
# Print results
print(f"\nScraped {len(completed_job['results'])} items")
for item in completed_job['results'][:5]:
print(f" - {item}")
```
Jobs run asynchronously. The `wait_for_job()` method polls automatically until completion.
## 5. Set up monitoring
Schedule automatic scrapes to monitor for changes:
```python theme={null}
# Run every hour
schedule = client.create_schedule(
strategy_id=strategy_id,
url="https://news.ycombinator.com",
interval_seconds=3600
)
print(f"Schedule created: {schedule['schedule_id']}")
print(f"Next run: {schedule['next_run_at']}")
```
Now Meter will automatically scrape Hacker News every hour. You can check for changes using the pull-based API or set up webhooks.
## 6. Check for changes
Use the pull-based API to get changes:
```python theme={null}
# Get changes for a schedule
changes = client.get_schedule_changes(
schedule_id=schedule['schedule_id'],
mark_seen=True # Mark as seen after reading
)
if changes['count'] > 0:
print(f"\n{changes['count']} jobs with changes:")
for change in changes['changes']:
print(f" - Job {change['job_id']}: {change['item_count']} items")
else:
print("\nNo changes detected")
```
Set `mark_seen=False` to preview changes without marking them as read.
## Complete example
Here's the complete code:
```python theme={null}
from meter_sdk import MeterClient
import os
# Initialize client
client = MeterClient(api_key=os.getenv("METER_API_KEY"))
# Step 1: Generate strategy
result = client.generate_strategy(
url="https://news.ycombinator.com",
description="Extract post titles and scores",
name="HN Front Page"
)
strategy_id = result["strategy_id"]
print(f"✓ Strategy created: {strategy_id}")
# Step 2: Run initial scrape
job = client.create_job(strategy_id, "https://news.ycombinator.com")
initial = client.wait_for_job(job["job_id"])
print(f"✓ Initial scrape: {initial['item_count']} items")
# Step 3: Set up monitoring
schedule = client.create_schedule(
strategy_id=strategy_id,
url="https://news.ycombinator.com",
interval_seconds=3600
)
print(f"✓ Monitoring enabled: every hour")
# Step 4: Check for changes
changes = client.get_schedule_changes(schedule['schedule_id'])
print(f"✓ Changes detected: {changes['count']} jobs")
```
## Next steps
Learn about strategies, jobs, and schedules
Connect Meter to your vector database
Set up real-time notifications
Explore all SDK methods
## Troubleshooting
**Possible causes:**
* URL is not accessible
* Description is too vague or complex
* Page requires authentication
**Solutions:**
* Verify the URL loads in your browser
* Make your description more specific: "Extract product names and prices from the grid" instead of "Get products"
* For auth-required pages, contact support
**Possible causes:**
* Target website is slow or down
* Strategy is incorrect
**Solutions:**
* Increase timeout: `client.wait_for_job(job_id, timeout=300)`
* Check job status manually: `client.get_job(job_id)`
* Refine strategy if results are incorrect
**Problem:** `ModuleNotFoundError: No module named 'meter_sdk'`
**Solution:** Install the SDK: `pip install meter-sdk`
**Problem:** `401 Unauthorized`
**Solutions:**
* Verify your API key is correct
* Check that `METER_API_KEY` environment variable is set
* Ensure your API key hasn't expired
## Need help?
Email me at [mckinnon@meter.sh](mailto:mckinnon@meter.sh)