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README.md

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@@ -19,7 +19,7 @@ s = Summary("request_latency_seconds", "Description of summary")
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s.observe(4.7)
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```
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### With labels
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### Usage with labels
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```python
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from prometheus_summary import Summary
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s.labels(method="POST", endpoint="/login").observe(3.4)
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```
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### With custom quantiles and precisions
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### Usage with custom quantiles and precisions
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By default, metrics are observed for the following (quantile, precision (inaccuracy)) pairs:
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By default, metrics are observed for next (quantile, precision (inaccuracy)) pairs
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`((0.50, 0.05), (0.90, 0.01), (0.99, 0.001))`
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but you can provide your own values when creating the metric.
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You can also provide your own values when creating the metric.
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```python
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from prometheus_summary import Summary
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s.observe(4.7)
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```
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### With custom time window settings
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### Usage with custom time window settings
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Typically, you don't want to have a Summary representing the entire runtime of the application,
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but you want to look at a reasonable time interval. Summary metrics implement a configurable sliding time window.
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but you want to look at a reasonable time interval. This Summary metric implement a configurable sliding time window.
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The default is a time window of 10 minutes and 5 age buckets, i.e. the time window is 10 minutes wide, and
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we slide it forward every 2 minutes, but you can configure this values for your own purposes.
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we slide it forward every 10 / 5 = 2 minutes, but you can configure this values for your own purposes.
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```python
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from prometheus_summary import Summary
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s = Summary("request_latency_seconds", "Description of summary", ["method", "endpoint"])
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```
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To show request latency by `method`, `endpoint` and `quantile` use next query:
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To show request latency by `method`, `endpoint` and `quantile` use the following PromQL query:
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```
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max by (method, endpoint, quantile) (request_latency_seconds)
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```

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