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https://github.com/sfertman/tic-toc
Code profiler for clojure, in clojure
https://github.com/sfertman/tic-toc
profiler
Last synced: about 1 month ago
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Code profiler for clojure, in clojure
- Host: GitHub
- URL: https://github.com/sfertman/tic-toc
- Owner: sfertman
- License: mit
- Created: 2019-09-13T23:31:08.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2019-10-20T01:24:37.000Z (about 5 years ago)
- Last Synced: 2024-02-27T22:46:32.490Z (9 months ago)
- Topics: profiler
- Language: Clojure
- Homepage:
- Size: 37.1 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# tic-toc
Clojure code profiler. Very basic for now but possibly offers a quick and dirty way for exploratory optimization of bottlenecks. Does not drill down into fns definitions; does a simple postwalk on the input forms* and dumps results in one big atom for analysis.
[](https://clojars.org/tic-toc)
## Profiling
Just wrap whatever with `profile` macro
```clojure
(require '[tic-toc.core :refer :all])
(profile
(let [n 5000]
(doseq [i (range n)]
(println (str "Hello world! #" i))
(println (str (- n (inc i)) " more to go" )))))
; =>
; Hello world! #0
; 4999 more to go
; Hello world! #1
; 4998 more to go
; Hello world! #2
; ...
; ...
; ...
; Hello world! #4998
; 1 more to go
; Hello world! #4999
; 0 more to go
; nil
```
# Run time summary
Metrics are accumulated in an atom `metrics`. Collects run time in nanoseconds for each unique function call. To see a quick summary use:
```clojure
(pprint (summary))
; =>
; {"clojure.core/range"
; {:total-time 113784,
; :args-time 0,
; :fn-time 113784,
; :calls 1,
; :mean-total 113784.0,
; :mean-args 0.0,
; :mean-fn 113784.0},
; "clojure.core/str"
; {:total-time 73567489,
; :args-time 27101634,
; :fn-time 46465855,
; :calls 10000,
; :mean-total 7356.7489,
; :mean-args 2710.1634,
; :mean-fn 4646.5855},
; ...
; ...
; ...
; "clojure.core/let"
; {:total-time 1429307487,
; :args-time 1429296603,
; :fn-time 10884,
; :calls 1,
; :mean-total 1.429307487E9,
; :mean-args 1.429296603E9,
; :mean-fn 10884.0}}
; nil
```
However, for more complex expressions this may be too big to look at.
`top` will give the top 10 time consumers in the profiling session based on `:fn-time`:
```clojure
(pprint (top))
; =>
; (["clojure.core/println" 1328577766]
; ["clojure.core/doseq" 50735764]
; ["clojure.core/str" 46465855]
; ["clojure.core/-" 13821717]
; ["clojure.core/inc" 13279917]
; ["clojure.core/range" 113784]
; ["clojure.core/let" 10884])
; nil
```
## Raw data
Alternatively, you can access the raw data and pipe it to your favourite data analytics tool
```clojure
(pprint (take 5 @metrics))
; =>
; ({:fn-id :clojure.core/range__1763,
; :time-ns 113784,
; :arg-fns []}
; {:fn-id :clojure.core/str__1764,
; :time-ns 15726,
; :arg-fns []}
; {:fn-id :clojure.core/println__1765,
; :time-ns 415226,
; :arg-fns [:clojure.core/str__1764]}
; {:fn-id :clojure.core/inc__1766,
; :time-ns 19302,
; :arg-fns []}
; {:fn-id :clojure.core/-__1767,
; :time-ns 37854,
; :arg-fns [:clojure.core/inc__1766]})
; nil
```
* Note that `profile` supports multiple inputs. Will return the value of the last input form. Metrics will be collected in the same atom for all forms and all subsequent calls to `profile`.
```clojure
(profile
(+ 42 43 44 45 46)
(- 46 45 44 43 42)
(* 1 2 3 4 5 6 7)
(/ 46 45 44 43 42))
```
To start a fresh profiling session simply reset the metrics atom using:
```clojure
(clear-session!)
```