Set Up Your Environment
Import Required Libraries
- Begin by importing the necessary components from the Google Cloud Spanner client library and the Google API core:
```python
from google.cloud import spanner
from google.api_core.exceptions import GoogleAPICallError, RetryError
```
initialize Client and Connect to Instance
- Create a Spanner client to interact with your database:
```python
spanner_client = spanner.Client()
```
- Connect to a specific instance by replacing `'your-instance-id'` with your actual Spanner instance ID:
```python
instance = spanner_client.instance('your-instance-id')
```
Access a Specific Database
Execute SQL Statements
- To run queries, use a snapshot to read data:
```python
with database.snapshot() as snapshot:
results = snapshot.execute_sql('SELECT * FROM your_table')
for row in results:
print(row)
```
- For DML operations like `INSERT`, `UPDATE`, or `DELETE`, use a transaction:
```python
def update_data(transaction):
row_ct = transaction.execute_update(
"UPDATE your_table SET column_name = 'new_value' WHERE condition"
)
print("{} record(s) updated.".format(row_ct))
database.run_in_transaction(update_data)
```
Handle Errors Gracefully
- Implement error-handling to manage possible exceptions during API calls:
```python
try:
# Your code for accessing Spanner
except GoogleAPICallError as e:
print(f"API call failed: {e}")
except RetryError as e:
print(f"API call retry strategy exceeded: {e}")
```
Clean Up Resources
- Though Python handles garbage collection, it's good practice to explicitly release resources by closing any open transactions or connections, especially in a long-running application.
- No explicit close method is needed for the Spanner client, but ensure your application gracefully manages its resources with appropriate lifecycle policies.
