Comments (4)
jiffyclub
commented on June 24, 2024
This happens when SnakeViz is unable to load and render the visualization within 20 seconds, which happens with complicated profiles. What I generally do is look at the stats table to identify a specific slow function to profile and then use the IPython magics %prun or %snakeviz to look at just that function.
from snakeviz.
kiddrew
commented on June 24, 2024
Got it, thanks. Very nice tool, btw.
from snakeviz.
jeffalstott
commented on June 24, 2024
I'm getting this error, and the code is not terribly complex. Below is the profile. Is there any way to extend the time limit, to alter the maximum depth we're looking down, or anything like that?
3505 function calls (3497 primitive calls) in 0.008 seconds
Ordered by: internal time
ncalls tottime percall cumtime percall filename:lineno(function)
631 0.000 0.000 0.000 0.000 {built-in method isinstance}
76 0.000 0.000 0.000 0.000 {built-in method array}
14 0.000 0.000 0.000 0.000 {method 'reduce' of 'numpy.ufunc' objects}
1 0.000 0.000 0.000 0.000 {method 'take' of 'numpy.ndarray' objects}
12 0.000 0.000 0.000 0.000 {pandas.lib.infer_dtype}
2 0.000 0.000 0.001 0.000 {pandas.lib.scalar_compare}
25 0.000 0.000 0.001 0.000 internals.py:1804(make_block)
17 0.000 0.000 0.001 0.000 series.py:134(__init__)
4 0.000 0.000 0.000 0.000 internals.py:2656(set)
6 0.000 0.000 0.000 0.000 common.py:620(take_nd)
2 0.000 0.000 0.002 0.001 indexing.py:194(_setitem_with_indexer)
2 0.000 0.000 0.000 0.000 {pandas.lib.isnullobj}
8 0.000 0.000 0.001 0.000 internals.py:2129(apply)
116/114 0.000 0.000 0.000 0.000 {built-in method getattr}
1 0.000 0.000 0.008 0.008 <ipython-input-346-91dc3233550d>:3(swap_with_restriction)
279/277 0.000 0.000 0.000 0.000 {built-in method len}
25 0.000 0.000 0.000 0.000 internals.py:59(__init__)
21 0.000 0.000 0.000 0.000 internals.py:3035(__init__)
2 0.000 0.000 0.000 0.000 internals.py:2503(fast_xs)
2 0.000 0.000 0.000 0.000 common.py:202(_isnull_ndarraylike)
10 0.000 0.000 0.000 0.000 common.py:2165(_asarray_tuplesafe)
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18 0.000 0.000 0.000 0.000 generic.py:87(__init__)
33 0.000 0.000 0.000 0.000 {method 'view' of 'numpy.ndarray' objects}
6 0.000 0.000 0.000 0.000 index.py:114(__new__)
2 0.000 0.000 0.000 0.000 {built-in method stat}
152 0.000 0.000 0.000 0.000 {built-in method issubclass}
7 0.000 0.000 0.000 0.000 series.py:2397(_sanitize_array)
4 0.000 0.000 0.000 0.000 indexing.py:982(_convert_to_indexer)
62 0.000 0.000 0.000 0.000 {built-in method hasattr}
1 0.000 0.000 0.000 0.000 internals.py:2004(_rebuild_blknos_and_blklocs)
12 0.000 0.000 0.000 0.000 {built-in method empty}
4 0.000 0.000 0.000 0.000 internals.py:460(setitem)
9 0.000 0.000 0.000 0.000 index.py:709(__getitem__)
46 0.000 0.000 0.000 0.000 numeric.py:394(asarray)
6 0.000 0.000 0.000 0.000 common.py:1862(_possibly_infer_to_datetimelike)
2 0.000 0.000 0.000 0.000 <frozen importlib._bootstrap>:2016(find_spec)
2 0.000 0.000 0.001 0.000 generic.py:1244(xs)
8 0.000 0.000 0.000 0.000 {method 'copy' of 'numpy.ndarray' objects}
29 0.000 0.000 0.000 0.000 numeric.py:1910(isscalar)
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25 0.000 0.000 0.000 0.000 internals.py:108(mgr_locs)
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33 0.000 0.000 0.000 0.000 index.py:3936(_ensure_index)
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6 0.000 0.000 0.000 0.000 common.py:132(_isnull_new)
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5 0.000 0.000 0.000 0.000 indexing.py:1520(_convert_to_index_sliceable)
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4 0.000 0.000 0.000 0.000 generic.py:2101(copy)
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1 0.000 0.000 0.000 0.000 ops.py:449(na_op)
4 0.000 0.000 0.000 0.000 internals.py:371(_try_cast_result)
8 0.000 0.000 0.000 0.000 generic.py:1014(_indexer)
5 0.000 0.000 0.000 0.000 index.py:222(view)
27 0.000 0.000 0.000 0.000 internals.py:3082(_block)
1 0.000 0.000 0.000 0.000 {built-in method mul}
2 0.000 0.000 0.000 0.000 indexing.py:139(_convert_tuple)
4 0.000 0.000 0.000 0.000 frame.py:1982(_box_item_values)
10 0.000 0.000 0.000 0.000 <frozen importlib._bootstrap>:50(_path_join)
7 0.000 0.000 0.000 0.000 generic.py:284(_get_axis_number)
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19 0.000 0.000 0.000 0.000 series.py:984(values)
2 0.000 0.000 0.001 0.000 generic.py:1626(_reindex_axes)
22 0.000 0.000 0.000 0.000 internals.py:208(iget)
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14 0.000 0.000 0.000 0.000 common.py:2248(_get_dtype_type)
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1 0.000 0.000 0.000 0.000 internals.py:1909(__init__)
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28 0.000 0.000 0.000 0.000 internals.py:1952(<genexpr>)
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2 0.000 0.000 0.000 0.000 internals.py:1992(_is_single_block)
8 0.000 0.000 0.000 0.000 {built-in method acquire_lock}
2 0.000 0.000 0.000 0.000 index.py:676(__iter__)
2 0.000 0.000 0.000 0.000 series.py:2021(_needs_reindex_multi)
2 0.000 0.000 0.000 0.000 {pandas.lib.is_bool}
4 0.000 0.000 0.000 0.000 {built-in method any}
4 0.000 0.000 0.000 0.000 internals.py:407(_try_coerce_args)
2 0.000 0.000 0.000 0.000 expressions.py:164(_has_bool_dtype)
2 0.000 0.000 0.000 0.000 indexing.py:1652(_is_nested_tuple)
2 0.000 0.000 0.000 0.000 indexing.py:391(can_do_equal_len)
2 0.000 0.000 0.000 0.000 <frozen importlib._bootstrap>:1870(_path_importer_cache)
2 0.000 0.000 0.000 0.000 {built-in method is_frozen}
4 0.000 0.000 0.000 0.000 internals.py:2550(_consolidate_inplace)
2 0.000 0.000 0.000 0.000 index.py:859(identical)
1 0.000 0.000 0.000 0.000 internals.py:2102(__len__)
2 0.000 0.000 0.000 0.000 six.py:175(find_module)
2 0.000 0.000 0.000 0.000 generic.py:1900(<lambda>)
12 0.000 0.000 0.000 0.000 {built-in method ensure_int64}
1 0.000 0.000 0.000 0.000 internals.py:1910(<listcomp>)
2 0.000 0.000 0.000 0.000 indexing.py:135(<listcomp>)
3 0.000 0.000 0.000 0.000 {method 'items' of 'dict' objects}
2 0.000 0.000 0.000 0.000 common.py:2421(_clean_fill_method)
2 0.000 0.000 0.000 0.000 index.py:655(<lambda>)
1 0.000 0.000 0.000 0.000 series.py:368(__array__)
2 0.000 0.000 0.002 0.001 indexing.py:653(_getitem_tuple)
2 0.000 0.000 0.000 0.000 indexing.py:165(_has_valid_setitem_indexer)
16 0.000 0.000 0.000 0.000 internals.py:3421(<lambda>)
6 0.000 0.000 0.000 0.000 index.py:1899(inferred_type)
2 0.000 0.000 0.000 0.000 {method 'keys' of 'dict' objects}
3 0.000 0.000 0.000 0.000 common.py:2283(is_timedelta64_dtype)
4 0.000 0.000 0.000 0.000 {built-in method allocate_lock}
1 0.000 0.000 0.000 0.000 common.py:2926(_maybe_match_name)
1 0.000 0.000 0.000 0.000 frame.py:183(_constructor)
4 0.000 0.000 0.000 0.000 series.py:333(ndim)
1 0.000 0.000 0.000 0.000 {built-in method sum}
2 0.000 0.000 0.000 0.000 <frozen importlib._bootstrap>:34(_relax_case)
1 0.000 0.000 0.000 0.000 index.py:193(_simple_new)
2 0.000 0.000 0.000 0.000 internals.py:1332(_can_hold_element)
4 0.000 0.000 0.000 0.000 {method 'extend' of 'list' objects}
2 0.000 0.000 0.000 0.000 <frozen importlib._bootstrap>:288(cb)
2 0.000 0.000 0.000 0.000 <frozen importlib._bootstrap>:1266(find_spec)
1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
1 0.000 0.000 0.000 0.000 ops.py:479(<lambda>)
1 0.000 0.000 0.000 0.000 common.py:1223(_fill_zeros)
2 0.000 0.000 0.000 0.000 {built-in method all}
2 0.000 0.000 0.000 0.000 internals.py:3177(is_consolidated)
1 0.000 0.000 0.000 0.000 series.py:361(__len__)
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jiffyclub
commented on June 24, 2024
@jeffalstott That's probably plenty big to bog down the current release of SnakeViz. I'm working as we speak on a new release that should be out in the next couple weeks that will improve performance. It's still rough, but you're welcome to give it a try if you're feeling adventurous. The branch I'm working on is at https://github.com/jiffyclub/snakeviz/tree/v2.
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Related Issues (20)
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