(pandas-dev) root@b96d9a4128b2:/workspaces/pandas-arw2019/asv_bench# asv continuous -f 1.1 json-Overflow-long-int -b ToJSON · Creating environments · Discovering benchmarks · Running 24 total benchmarks (2 commits * 1 environments * 12 benchmarks) [ 0.00%] · For pandas commit cb244ede (round 1/2): [ 0.00%] ·· Building for conda-py3.6-Cython0.29.16-matplotlib-numba-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt............................................................... [ 0.00%] ·· Benchmarking conda-py3.6-Cython0.29.16-matplotlib-numba-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt [ 6.25%] ··· Running (io.json.ToJSON.time_to_json--). [ 8.33%] ··· Running (io.json.ToJSON.time_to_json_wide--). [ 10.42%] ··· Running (io.json.ToJSONISO.time_iso_format--)...... [ 25.00%] · For pandas commit 1cad9e52 (round 1/2): [ 25.00%] ·· Building for conda-py3.6-Cython0.29.16-matplotlib-numba-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt.... [ 25.00%] ·· Benchmarking conda-py3.6-Cython0.29.16-matplotlib-numba-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt [ 31.25%] ··· Running (io.json.ToJSON.time_to_json--). [ 33.33%] ··· Running (io.json.ToJSON.time_to_json_wide--). [ 35.42%] ··· Running (io.json.ToJSONISO.time_iso_format--)...... [ 50.00%] · For pandas commit 1cad9e52 (round 2/2): [ 50.00%] ·· Benchmarking conda-py3.6-Cython0.29.16-matplotlib-numba-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt [ 52.08%] ··· io.json.ToJSON.peakmem_to_json ok [ 52.08%] ··· ========= ====== ============= ============== =============== ================== -- frame --------- ---------------------------------------------------------------------- orient df df_date_idx df_td_int_ts df_int_floats df_int_float_str ========= ====== ============= ============== =============== ================== split 158M 163M 157M 163M 164M columns 168M 176M 177M 179M 180M index 166M 168M 170M 175M 175M values 156M 156M 154M 157M 157M records 165M 165M 167M 171M 172M ========= ====== ============= ============== =============== ================== [ 54.17%] ··· io.json.ToJSON.peakmem_to_json_wide ok [ 54.17%] ··· ========= ====== ============= ============== =============== ================== -- frame --------- ---------------------------------------------------------------------- orient df df_date_idx df_td_int_ts df_int_floats df_int_float_str ========= ====== ============= ============== =============== ================== split 169M 169M 167M 174M 172M columns 178M 188M 189M 196M 195M index 180M 180M 179M 186M 185M values 169M 169M 167M 174M 172M records 180M 180M 179M 186M 185M ========= ====== ============= ============== =============== ================== [ 56.25%] ··· io.json.ToJSON.time_to_json ok [ 56.25%] ··· ========= ========== ============= ============== =============== ================== -- frame --------- -------------------------------------------------------------------------- orient df df_date_idx df_td_int_ts df_int_floats df_int_float_str ========= ========== ============= ============== =============== ================== split 160±10ms 165±10ms 171±5ms 189±20ms 214±20ms columns 174±20ms 234±20ms 230±30ms 252±20ms 242±20ms index 194±7ms 240±20ms 267±30ms 264±30ms 277±20ms values 143±6ms 143±7ms 153±20ms 195±10ms 196±5ms records 162±2ms 169±2ms 234±10ms 230±5ms 235±5ms ========= ========== ============= ============== =============== ================== [ 58.33%] ··· io.json.ToJSON.time_to_json_wide ok [ 58.33%] ··· ========= ========== ============= ============== =============== ================== -- frame --------- -------------------------------------------------------------------------- orient df df_date_idx df_td_int_ts df_int_floats df_int_float_str ========= ========== ============= ============== =============== ================== split 314±20ms 252±20ms 457±20ms 404±10ms 522±20ms columns 407±10ms 361±10ms 466±10ms 465±10ms 515±20ms index 440±20ms 343±20ms 515±20ms 447±7ms 560±40ms values 358±20ms 257±9ms 463±30ms 389±20ms 518±8ms records 388±20ms 286±8ms 492±8ms 432±10ms 557±30ms ========= ========== ============= ============== =============== ================== [ 60.42%] ··· io.json.ToJSONISO.time_iso_format ok [ 60.42%] ··· ========= ========== orient --------- ---------- split 520±9ms columns 528±20ms index 548±20ms values 465±20ms records 479±3ms ========= ========== [ 62.50%] ··· io.json.ToJSONLines.time_delta_int_tstamp_lines 314±7ms [ 64.58%] ··· io.json.ToJSONLines.time_float_int_lines 373±8ms [ 66.67%] ··· io.json.ToJSONLines.time_float_int_str_lines 368±8ms [ 68.75%] ··· io.json.ToJSONLines.time_floats_with_dt_index_lines 269±6ms [ 70.83%] ··· io.json.ToJSONLines.time_floats_with_int_idex_lines 256±8ms [ 72.92%] ··· Setting up io.json:224 ok [ 72.92%] ··· io.json.ToJSONMem.peakmem_float 126M [ 75.00%] ··· io.json.ToJSONMem.peakmem_int 126M [ 75.00%] · For pandas commit cb244ede (round 2/2): [ 75.00%] ·· Building for conda-py3.6-Cython0.29.16-matplotlib-numba-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt..... [ 75.00%] ·· Benchmarking conda-py3.6-Cython0.29.16-matplotlib-numba-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt [ 77.08%] ··· io.json.ToJSON.peakmem_to_json ok [ 77.08%] ··· ========= ====== ============= ============== =============== ================== -- frame --------- ---------------------------------------------------------------------- orient df df_date_idx df_td_int_ts df_int_floats df_int_float_str ========= ====== ============= ============== =============== ================== split 158M 163M 157M 163M 164M columns 168M 176M 177M 179M 180M index 166M 168M 170M 175M 175M values 156M 156M 154M 157M 157M records 164M 165M 167M 171M 172M ========= ====== ============= ============== =============== ================== [ 79.17%] ··· io.json.ToJSON.peakmem_to_json_wide ok [ 79.17%] ··· ========= ====== ============= ============== =============== ================== -- frame --------- ---------------------------------------------------------------------- orient df df_date_idx df_td_int_ts df_int_floats df_int_float_str ========= ====== ============= ============== =============== ================== split 169M 169M 167M 174M 172M columns 178M 188M 189M 196M 195M index 180M 180M 179M 186M 185M values 169M 169M 167M 174M 172M records 180M 180M 179M 186M 185M ========= ====== ============= ============== =============== ================== [ 81.25%] ··· io.json.ToJSON.time_to_json ok [ 81.25%] ··· ========= ========== ============= ============== =============== ================== -- frame --------- -------------------------------------------------------------------------- orient df df_date_idx df_td_int_ts df_int_floats df_int_float_str ========= ========== ============= ============== =============== ================== split 163±8ms 171±10ms 191±7ms 201±10ms 207±20ms columns 175±10ms 225±20ms 233±20ms 249±10ms 248±10ms index 196±8ms 225±10ms 249±20ms 272±20ms 278±8ms values 145±8ms 148±5ms 157±10ms 180±10ms 186±10ms records 162±10ms 166±9ms 192±10ms 228±10ms 230±20ms ========= ========== ============= ============== =============== ================== [ 83.33%] ··· io.json.ToJSON.time_to_json_wide ok [ 83.33%] ··· ========= ========== ============= ============== =============== ================== -- frame --------- -------------------------------------------------------------------------- orient df df_date_idx df_td_int_ts df_int_floats df_int_float_str ========= ========== ============= ============== =============== ================== split 322±10ms 236±20ms 396±40ms 384±50ms 464±50ms columns 346±30ms 318±20ms 436±30ms 398±20ms 461±30ms index 354±30ms 268±30ms 427±50ms 387±30ms 498±50ms values 322±30ms 234±20ms 388±40ms 354±30ms 446±50ms records 354±40ms 271±30ms 429±40ms 403±40ms 494±40ms ========= ========== ============= ============== =============== ================== [ 85.42%] ··· io.json.ToJSONISO.time_iso_format ok [ 85.42%] ··· ========= ========== orient --------- ---------- split 478±30ms columns 482±30ms index 491±40ms values 417±30ms records 417±30ms ========= ========== [ 87.50%] ··· io.json.ToJSONLines.time_delta_int_tstamp_lines 280±20ms [ 89.58%] ··· io.json.ToJSONLines.time_float_int_lines 332±20ms [ 91.67%] ··· io.json.ToJSONLines.time_float_int_str_lines 346±50ms [ 93.75%] ··· io.json.ToJSONLines.time_floats_with_dt_index_lines 241±20ms [ 95.83%] ··· io.json.ToJSONLines.time_floats_with_int_idex_lines 231±10ms [ 97.92%] ··· Setting up io.json:224 ok [ 97.92%] ··· io.json.ToJSONMem.peakmem_float 126M [100.00%] ··· io.json.ToJSONMem.peakmem_int 126M before after ratio [cb244ede] [1cad9e52] + 268±30ms 343±20ms 1.28 io.json.ToJSON.time_to_json_wide('index', 'df_date_idx') + 354±30ms 440±20ms 1.24 io.json.ToJSON.time_to_json_wide('index', 'df') + 346±30ms 407±10ms 1.18 io.json.ToJSON.time_to_json_wide('columns', 'df') + 398±20ms 465±10ms 1.17 io.json.ToJSON.time_to_json_wide('columns', 'df_int_floats') + 417±30ms 479±3ms 1.15 io.json.ToJSONISO.time_iso_format('records') + 318±20ms 361±10ms 1.13 io.json.ToJSON.time_to_json_wide('columns', 'df_date_idx') + 494±40ms 557±30ms 1.13 io.json.ToJSON.time_to_json_wide('records', 'df_int_float_str') + 417±30ms 465±20ms 1.12 io.json.ToJSONISO.time_iso_format('values') SOME BENCHMARKS HAVE CHANGED SIGNIFICANTLY. PERFORMANCE DECREASED.