> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tilebox.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Query telemetry
> Query workflow logs and spans for a job from Python or Go.
Tilebox stores logs and spans for each workflow job. Use the jobs client to query that telemetry from notebooks, scripts, or automated diagnostics.
## Query job logs
`query_logs()` returns a `LogRecords` list. Pagination is handled automatically.
```python Python theme={"system"}
from tilebox.workflows import Client
client = Client()
job = client.jobs().find("019e07b1-916b-0630-f3ba-f1c33235d174")
logs = client.jobs().query_logs(job)
for record in logs:
print(record.time, record.severity_text, record.body)
print(record.attributes)
```
```go Go theme={"system"}
package main
import (
"context"
"fmt"
"log/slog"
"time"
"github.com/google/uuid"
"github.com/tilebox/tilebox-go/workflows/v1"
)
func main() {
ctx := context.Background()
client := workflows.NewClient()
jobID := uuid.MustParse("019e07b1-916b-0630-f3ba-f1c33235d174")
for record, err := range client.Jobs.QueryLogs(
ctx,
jobID,
workflows.WithSortDirection(workflows.Ascending),
) {
if err != nil {
slog.ErrorContext(ctx, "failed to query job logs", slog.Any("error", err))
return
}
fmt.Println(record.Time.Format(time.RFC3339Nano), record.Level, record.Body)
fmt.Println(record.Attributes)
}
}
```
Each log record includes:
* `time`
* `severity_number` and `severity_text`
* `body`
* `trace_id` and `span_id`
* `attributes`
* `runner_attributes`
### As pandas DataFrame
Use `to_pandas()` to convert log records to a pandas DataFrame.
```python Python theme={"system"}
logs_df = client.jobs().query_logs(job).to_pandas()
logs_df[["time", "severity_text", "body"]]
```
## Query job spans
`query_spans()` returns a `Spans` list. Pagination is handled automatically.
```python Python theme={"system"}
spans = client.jobs().query_spans(job.id)
for span in spans:
print(span.name, span.status_code, span.duration)
print(span.attributes)
```
```go Go theme={"system"}
package main
import (
"context"
"fmt"
"log/slog"
"github.com/google/uuid"
"github.com/tilebox/tilebox-go/workflows/v1"
)
func main() {
ctx := context.Background()
client := workflows.NewClient()
jobID := uuid.MustParse("019e07b1-916b-0630-f3ba-f1c33235d174")
for span, err := range client.Jobs.QuerySpans(
ctx,
jobID,
workflows.WithSortDirection(workflows.Ascending),
) {
if err != nil {
slog.ErrorContext(ctx, "failed to query job spans", slog.Any("error", err))
return
}
fmt.Println(span.Name, span.StatusCode, span.Duration())
fmt.Println(span.Attributes)
}
}
```
Each span includes:
* `start_time` and `end_time`
* `duration`
* `trace_id`, `span_id`, and `parent_span_id`
* `name`
* `status_code` and `status_message`
* `attributes`
* `runner_attributes`
* `events`
### As pandas DataFrame
Use `to_pandas()` to convert spans to a pandas DataFrame.
```python Python theme={"system"}
spans_df = client.jobs().query_spans(job).to_pandas()
slow_spans = spans_df.sort_values("duration", ascending=False).head(10)
slow_spans[["name", "duration", "start_time"]]
```
Nested `attributes`, `runner_attributes`, and `events` stay as Python objects in DataFrame columns. Span DataFrames include a computed `duration` column.