Package: libpy-simdjson
libpy simdjsonPython bindings forsimdjsonusinglibpy.RequirementsOS: macOS>10.15, linux.Compiler: gcc>=9, clang >= 10 (C++17 code)Python: libpy>=0.2.3, numpy.Installpip install libpy-simdjsonNote: The installation oflibpy(required bylibpy_simdjson) will use thepythonexecutable to figure out information about your environment. If you are not using a virtual environment orpythondoes not point to the Python installation you want to use (checked withwhich pythonandpython --version) you must point to your Python executable using thePYTHONenvironment variable, i.e.PYTHON=python3 makeorPYTHON=python3 pip3 install libpy. Additionally, make sure that yourCCandCXXenvironment variables point to the correct compilers.UsagefrompathlibimportPathimportlibpy_simdjsonasjsondoc=json.load(Path("twitter.json"))# or json.load(b"twitter.json")# or json.load("twitter.json")# we also support `loads` for strings.docis anObject. Objects act as python dicts with special methods.isinstance(doc,json.Object)TrueWe can grab keys, get the length, grab items, and access specific keys:len(doc)2doc.keys()[b'statuses', b'search_metadata']doc[b'search_metadata'].items()[(b'completed_in', 0.087),
 (b'max_id', 505874924095815700),
 (b'max_id_str', b'505874924095815681'),
 (b'next_results',
  b'?max_id=505874847260352512&q=%E4%B8%80&count=100&include_entities=1'),
 (b'query', b'%E4%B8%80'),
 (b'refresh_url',
  b'?since_id=505874924095815681&q=%E4%B8%80&include_entities=1'),
 (b'count', 100),
 (b'since_id', 0),
 (b'since_id_str', b'0')]If you every want an actual python dictionary, useas_dict:doc[b'search_metadata'].as_dict(){b'completed_in': 0.087,
 b'max_id': 505874924095815700,
 b'max_id_str': b'505874924095815681',
 b'next_results': b'?max_id=505874847260352512&q=%E4%B8%80&count=100&include_entities=1',
 b'query': b'%E4%B8%80',
 b'refresh_url': b'?since_id=505874924095815681&q=%E4%B8%80&include_entities=1',
 b'count': 100,
 b'since_id': 0,
 b'since_id_str': b'0'}However, we also supportJSON Pointersytnax viaat_pointer. This will be much faster if you know what you're looking for:doc.at_pointer(b"/statuses/50/created_at")b'Sun Aug 31 00:29:04 +0000 2014'doc.at_pointer(b"/statuses/50/text").decode()'RT @Ang_Angel73: 逢坂「くっ…僕の秘められし右目が…！」\n一同「……………。」'Let's look atstatusesstatuses=doc[b'statuses']statusesis anArray. Arrays act like python lists with special methods.Note:statusesanddocshare a single parser instance. We cannot parse a new document while these objects are alive (though we can create new parsers vialibpy_simdjson.Parser.load.isinstance(statuses,json.Array)TrueArrays support length, indexing, iteration:len(statuses)100statuses[0][b'text'].decode()'@aym0566x \n\n名前:前田あゆみ\n第一印象:なんか怖っ！\n今の印象:とりあえずキモい。噛み合わない\n好きなところ:ぶすでキモいとこ😋✨✨\n思い出:んーーー、ありすぎ😊❤️\nLINE交換できる？:あぁ……ごめん✋\nトプ画をみて:照れますがな😘✨\n一言:お前は一生もんのダチ💖'forstatusinstatuses:# this is a bad example but you get the pictureifstatus[b'id']%2==0:print(status[b"text"].decode())breakelse:print("no even ids?")@aym0566x

名前:前田あゆみ
第一印象:なんか怖っ！
今の印象:とりあえずキモい。噛み合わない
好きなところ:ぶすでキモいとこ😋✨✨
思い出:んーーー、ありすぎ😊❤️
LINE交換できる？:あぁ……ごめん✋
トプ画をみて:照れますがな😘✨
一言:お前は一生もんのダチ💖If you need to you can convert and Array to a list usingas_list:statuses.as_list()[1][b'metadata']{b'result_type': b'recent', b'iso_language_code': b'ja'}However, just like for Objects, we support JSON Pointers viaat_pointer, which is much faster:statuses.at_pointer(b"/33/created_at")b'Sun Aug 31 00:29:06 +0000 2014'BenchmarksNote- unlike most other python JSON parsers,libpy_simdjsonwill, by design, avoid converting to native python types until as late as possible, providing you withObjectandArrayobjects instead.libpyallows you to work with these proxy objects as if they were actual python objects without incurring the cost of object conversion until actually needed. Because the C++simdjsonlibrary is so effficient, converting to Python objects is by far the slowest part of parsing, so we strive to do this as late and on as few fields as possible.See the (still WIP) "overhead over python dict access" benchmarks for object conversion overhead.For the sake of comparison, we also benchmark a full Python object conversion inlibpy_simdjson_as_py_objthough this is very much not the intended use case.------------------------------------------------------------ benchmark 'Load /home/runner/work/libpy_simdjson/libpy_simdjson/libpy_simdjson/tests/jsonexamples/canada.json': 8 tests -------------------------------------------------------------
Name (time in ms)                                                                    Min                Max               Mean            StdDev             Median                IQR            Outliers       OPS            Rounds  Iterations
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_benchmark_load[path0-libpy_simdjson-loads]                                   3.5037 (1.0)      10.9591 (1.0)       4.3319 (1.0)      0.6166 (1.0)       4.2607 (1.0)       0.2292 (1.0)         11;15  230.8454 (1.0)         162           1
test_benchmark_load[path0-pysimdjson-parse]                                       3.6885 (1.05)     11.1368 (1.02)      4.4029 (1.02)     0.7765 (1.26)      4.2611 (1.00)      0.5017 (2.19)          8;5  227.1254 (0.98)        118           1
test_benchmark_load[path0-pysimdjson_as_py_obj-loads]                            13.5282 (3.86)     37.4092 (3.41)     24.2264 (5.59)     6.5177 (10.57)    27.0374 (6.35)     11.9384 (52.08)        16;0   41.2773 (0.18)         40           1
test_benchmark_load[path0-libpy_simdjson_as_py_obj-libpy_simdjson_as_py_obj]     13.5544 (3.87)     44.5382 (4.06)     22.4503 (5.18)     7.1879 (11.66)    25.0067 (5.87)     12.0174 (52.43)        12;0   44.5427 (0.19)         35           1
test_benchmark_load[path0-orjson-loads]                                          16.1693 (4.61)     37.2228 (3.40)     25.2505 (5.83)     6.8427 (11.10)    27.4105 (6.43)     12.5579 (54.79)        19;0   39.6032 (0.17)         41           1
test_benchmark_load[path0-ujson-loads]                                           22.0310 (6.29)     45.6815 (4.17)     32.3445 (7.47)     7.0874 (11.49)    35.0020 (8.22)     12.6422 (55.15)        12;0   30.9171 (0.13)         27           1
test_benchmark_load[path0-python_json-loads]                                     49.6505 (14.17)    72.4977 (6.62)     62.0533 (14.32)    7.2277 (11.72)    64.0998 (15.04)    12.7639 (55.68)         8;0   16.1152 (0.07)         19           1
test_benchmark_load[path0-rapidjson-loads]                                       50.3836 (14.38)    76.2291 (6.96)     61.1768 (14.12)    7.7522 (12.57)    63.4637 (14.90)    12.2982 (53.65)         6;0   16.3461 (0.07)         17           1
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--------------------------------------------------------------------- benchmark 'Load /home/runner/work/libpy_simdjson/libpy_simdjson/libpy_simdjson/tests/jsonexamples/citm_catalog.json': 8 tests ---------------------------------------------------------------------
Name (time in us)                                                                        Min                    Max                   Mean                StdDev                 Median                   IQR            Outliers       OPS            Rounds  Iterations
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_benchmark_load[path3-libpy_simdjson-loads]                                     869.1500 (1.0)       5,930.8430 (2.49)      1,123.0447 (1.0)        203.5337 (1.52)      1,112.6140 (1.0)         81.2050 (1.02)        29;35  890.4365 (1.0)         722           1
test_benchmark_load[path3-pysimdjson-parse]                                         875.8530 (1.01)      2,384.6440 (1.0)       1,127.0993 (1.00)       133.4820 (1.0)       1,119.4185 (1.01)        79.8040 (1.0)         72;38  887.2333 (1.00)        786           1
test_benchmark_load[path3-libpy_simdjson_as_py_obj-libpy_simdjson_as_py_obj]      6,227.8560 (7.17)     23,751.5410 (9.96)     10,109.4607 (9.00)     5,149.2095 (38.58)     7,506.5770 (6.75)     1,209.3185 (15.15)       27;29   98.9172 (0.11)        120           1
test_benchmark_load[path3-orjson-loads]                                           6,445.2870 (7.42)     23,814.3440 (9.99)     10,414.0837 (9.27)     4,872.0612 (36.50)     7,897.2230 (7.10)     2,016.7280 (25.27)       26;26   96.0238 (0.11)        114           1
test_benchmark_load[path3-pysimdjson_as_py_obj-loads]                             7,940.2930 (9.14)     24,984.5340 (10.48)    11,900.6726 (10.60)    5,518.1670 (41.34)     8,878.9950 (7.98)     3,686.7190 (46.20)       21;21   84.0289 (0.09)         90           1
test_benchmark_load[path3-ujson-loads]                                            8,323.1930 (9.58)     23,228.4760 (9.74)     12,104.0124 (10.78)    5,363.4790 (40.18)     9,344.6530 (8.40)       802.3722 (10.05)       19;20   82.6172 (0.09)         83           1
test_benchmark_load[path3-python_json-loads]                                     12,697.9430 (14.61)    31,279.0080 (13.12)    16,691.7376 (14.86)    5,163.8324 (38.69)    14,104.4160 (12.68)    2,390.4543 (29.95)       17;17   59.9099 (0.07)         75           1
test_benchmark_load[path3-rapidjson-loads]                                       14,025.9210 (16.14)    29,509.2470 (12.37)    17,785.5409 (15.84)    5,061.8217 (37.92)    15,456.7050 (13.89)    1,756.3833 (22.01)         7;7   56.2254 (0.06)         35           1
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--------------------------------------------------------------- benchmark 'Load /home/runner/work/libpy_simdjson/libpy_simdjson/libpy_simdjson/tests/jsonexamples/github_events.json': 8 tests ---------------------------------------------------------------
Name (time in us)                                                                     Min                   Max                Mean              StdDev              Median                IQR            Outliers  OPS (Kops/s)            Rounds  Iterations
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_benchmark_load[path2-libpy_simdjson-loads]                                   25.4010 (1.0)      1,960.0230 (1.28)      36.2258 (1.0)       24.5956 (1.0)       34.6020 (1.0)       2.9000 (1.04)      72;1589       27.6046 (1.0)       12642           1
test_benchmark_load[path2-pysimdjson-parse]                                       25.8010 (1.02)     1,528.8010 (1.0)       37.9300 (1.05)      26.3332 (1.07)      37.3020 (1.08)      2.8010 (1.0)      189;1856       26.3644 (0.96)      16103           1
test_benchmark_load[path2-libpy_simdjson_as_py_obj-libpy_simdjson_as_py_obj]     142.1090 (5.59)     3,436.0130 (2.25)     207.5540 (5.73)      88.5276 (3.60)     204.8130 (5.92)     17.6010 (6.28)       58;289        4.8180 (0.17)       4034           1
test_benchmark_load[path2-orjson-loads]                                          175.7120 (6.92)     5,736.6740 (3.75)     254.9315 (7.04)     162.0033 (6.59)     239.3160 (6.92)     20.8005 (7.43)       26;226        3.9226 (0.14)       2872           1
test_benchmark_load[path2-pysimdjson_as_py_obj-loads]                            224.7150 (8.85)     2,283.7510 (1.49)     321.5699 (8.88)      72.4103 (2.94)     324.0220 (9.36)     26.0020 (9.28)       79;180        3.1097 (0.11)       2632           1
test_benchmark_load[path2-ujson-loads]                                           301.7190 (11.88)    7,409.5770 (4.85)     375.2140 (10.36)    180.4753 (7.34)     363.8240 (10.51)    29.0010 (10.35)      18;175        2.6651 (0.10)       2269           1
test_benchmark_load[path2-python_json-loads]                                     330.5200 (13.01)    2,521.5590 (1.65)     459.9910 (12.70)     86.1825 (3.50)     455.8290 (13.17)    38.7277 (13.83)     119;146        2.1740 (0.08)       1909           1
test_benchmark_load[path2-rapidjson-loads]                                       380.6250 (14.98)    2,082.2340 (1.36)     533.6130 (14.73)     91.0874 (3.70)     529.9340 (15.32)    43.7030 (15.60)       76;95        1.8740 (0.07)       1709           1
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------




----------------------------------------------------------------------- benchmark 'Load /home/runner/work/libpy_simdjson/libpy_simdjson/libpy_simdjson/tests/jsonexamples/mesh.json': 8 tests ------------------------------------------------------------------------
Name (time in us)                                                                       Min                    Max                   Mean                StdDev                 Median                 IQR            Outliers       OPS            Rounds  Iterations
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_benchmark_load[path4-libpy_simdjson-loads]                                    994.5520 (1.0)       4,240.8210 (1.06)      1,202.4742 (1.0)        194.6273 (1.04)      1,190.2620 (1.0)       93.9050 (1.31)        80;42  831.6187 (1.0)         772           1
test_benchmark_load[path4-pysimdjson-parse]                                      1,027.3570 (1.03)      4,001.3210 (1.0)       1,257.5495 (1.05)       187.9555 (1.0)       1,253.6190 (1.05)      71.9545 (1.0)         37;50  795.1973 (0.96)        804           1
test_benchmark_load[path4-pysimdjson_as_py_obj-loads]                            2,782.4560 (2.80)     16,753.7350 (4.19)      3,907.4828 (3.25)     2,316.1314 (12.32)     3,456.5430 (2.90)     264.9645 (3.68)         9;18  255.9192 (0.31)        252           1
test_benchmark_load[path4-libpy_simdjson_as_py_obj-libpy_simdjson_as_py_obj]     2,936.7520 (2.95)     19,099.6830 (4.77)      4,066.0482 (3.38)     2,579.4705 (13.72)     3,459.0780 (2.91)     291.3400 (4.05)        10;21  245.9390 (0.30)        207           1
test_benchmark_load[path4-orjson-loads]                                          3,848.3120 (3.87)     16,809.8280 (4.20)      4,853.2711 (4.04)     2,387.4255 (12.70)     4,348.8370 (3.65)     282.5400 (3.93)         8;13  206.0466 (0.25)        203           1
test_benchmark_load[path4-ujson-loads]                                           4,224.0310 (4.25)     27,094.9610 (6.77)      5,393.1933 (4.49)     2,651.7927 (14.11)     4,906.3150 (4.12)     368.6210 (5.12)         7;13  185.4189 (0.22)        196           1
test_benchmark_load[path4-python_json-loads]                                     7,946.7190 (7.99)     21,914.9540 (5.48)      9,216.2188 (7.66)     2,458.6174 (13.08)     8,729.1600 (7.33)     425.9220 (5.92)          4;8  108.5044 (0.13)        108           1
test_benchmark_load[path4-rapidjson-loads]                                       8,958.0800 (9.01)     26,303.9020 (6.57)     10,523.4513 (8.75)     2,727.4495 (14.51)    10,081.1370 (8.47)     748.3645 (10.40)         4;4   95.0259 (0.11)        101           1
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---------------------------------------------------------------------- benchmark 'Load /home/runner/work/libpy_simdjson/libpy_simdjson/libpy_simdjson/tests/jsonexamples/twitter.json': 8 tests ----------------------------------------------------------------------
Name (time in us)                                                                       Min                    Max                  Mean                StdDev                Median                 IQR            Outliers         OPS            Rounds  Iterations
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_benchmark_load[path1-libpy_simdjson-loads]                                    329.3220 (1.0)       3,357.5250 (2.67)       440.8892 (1.0)         84.7542 (1.65)       441.1300 (1.0)       37.4280 (1.22)        64;75  2,268.1435 (1.0)        1637           1
test_benchmark_load[path1-pysimdjson-parse]                                        348.7250 (1.06)      1,258.3910 (1.0)        451.6477 (1.02)        51.2426 (1.0)        450.8825 (1.02)      30.8030 (1.0)       374;155  2,214.1149 (0.98)       2006           1
test_benchmark_load[path1-libpy_simdjson_as_py_obj-libpy_simdjson_as_py_obj]     2,206.2470 (6.70)     14,217.4510 (11.30)    2,759.9331 (6.26)     1,386.3121 (27.05)    2,551.0705 (5.78)     312.4220 (10.14)         2;3    362.3276 (0.16)         74           1
test_benchmark_load[path1-orjson-loads]                                          2,639.8850 (8.02)     15,075.4730 (11.98)    3,420.6474 (7.76)     1,657.3556 (32.34)    3,183.0750 (7.22)     215.1150 (6.98)         6;15    292.3423 (0.13)        270           1
test_benchmark_load[path1-ujson-loads]                                           3,304.1320 (10.03)    18,557.3880 (14.75)    4,286.1597 (9.72)     1,868.0725 (36.46)    4,021.4820 (9.12)     283.4200 (9.20)         5;14    233.3091 (0.10)        239           1
test_benchmark_load[path1-pysimdjson_as_py_obj-loads]                            3,319.1400 (10.08)    16,355.6780 (13.00)    4,237.6133 (9.61)     1,642.9272 (32.06)    3,982.8870 (9.03)     306.1198 (9.94)         6;16    235.9819 (0.10)        259           1
test_benchmark_load[path1-python_json-loads]                                     4,154.6810 (12.62)    17,041.0680 (13.54)    5,474.9570 (12.42)    1,520.8511 (29.68)    5,262.9090 (11.93)    484.4330 (15.73)         6;8    182.6498 (0.08)        190           1
test_benchmark_load[path1-rapidjson-loads]                                       5,184.5590 (15.74)    19,217.2170 (15.27)    6,598.9679 (14.97)    1,949.8404 (38.05)    6,315.0330 (14.32)    682.2923 (22.15)         5;7    151.5388 (0.07)        149           1
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-------------------------------------------------------------------------------------------- benchmark 'Random attribute access': 2 tests --------------------------------------------------------------------------------------------
Name (time in ns)                                  Min                       Max                  Mean                StdDev                Median                 IQR            Outliers  OPS (Kops/s)            Rounds  Iterations
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_benchmark_at[python_json-loads]          800.0000 (1.0)      1,560,881.0000 (6.79)     1,190.4413 (1.0)      6,373.7290 (3.79)     1,100.0000 (1.0)      100.0000 (1.0)      122;3966      840.0246 (1.0)       88496           1
test_benchmark_at[libpy_simdjson-loads]     1,300.0000 (1.63)       229,812.0000 (1.0)      1,848.6849 (1.55)     1,683.4805 (1.0)      1,800.0000 (1.64)     400.0000 (4.00)      143;234      540.9251 (0.64)      57801           1
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---------------------------------------------------------------------------------------------------- benchmark 'Random list access': 2 tests ----------------------------------------------------------------------------------------------------
Name (time in ns)                                         Min                       Max                   Mean                StdDev                 Median                   IQR            Outliers  OPS (Kops/s)            Rounds  Iterations
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_benchmark_list_access[python_json-loads]        700.0000 (1.0)        258,213.0000 (1.0)       1,061.7637 (1.0)      1,165.4286 (1.0)       1,000.0000 (1.0)        200.0000 (1.0)      570;5297      941.8292 (1.0)      149232           1
test_benchmark_list_access[libpy_simdjson-loads]     700.0000 (1.00)     1,340,168.0000 (5.19)     10,658.8974 (10.04)    9,211.5111 (7.90)     10,301.0000 (10.30)    9,300.0000 (46.50)    4637;493       93.8183 (0.10)      81961           1
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Legend:
  Outliers: 1 Standard Deviation from Mean; 1.5 IQR (InterQuartile Range) from 1st Quartile and 3rd Quartile.
  OPS: Operations Per Second, computed as 1 / Mean