)]}'
{"gnocchi/carbonara.py":[{"author":{"_account_id":1669,"name":"Julien Danjou","display_name":"jd","email":"julien@danjou.info","username":"jdanjou"},"change_message_id":"148804b5e5a2ee63b456a04cda9e90fc2a396829","unresolved":false,"context_lines":[{"line_number":468,"context_line":"        # SplitKey.from_timestamp_and_sampling, but"},{"line_number":469,"context_line":"        # this is slow because pandas can do that on any kind DataFrame"},{"line_number":470,"context_line":"        # but we have ordered timestamps, so don\u0027t need"},{"line_number":471,"context_line":"        # to iter the whole series."},{"line_number":472,"context_line":"        freq \u003d self.sampling * SplitKey.POINTS_PER_SPLIT"},{"line_number":473,"context_line":"        ix \u003d numpy.divide(numpy.array(self.ts.index, \u0027float64\u0027), 10e8)"},{"line_number":474,"context_line":"        keys, counts \u003d numpy.unique((ix // freq) * freq, return_counts\u003dTrue)"}],"source_content_type":"text/x-python","patch_set":2,"id":"5a3905b3_81e4dc0d","line":471,"updated":"2017-01-19 10:06:59.000000000","message":"are we sure there\u0027s no hole? I imagine it works so that\u0027s a dumb question","commit_id":"aefdd70e3eb42ff1c5eb5493e491cf4385e7f0fb"},{"author":{"_account_id":6537,"name":"gordon chung","email":"gord@live.ca","username":"chungg"},"change_message_id":"f8fb49d347f3bdf24c5f75ff6b5650c60859e695","unresolved":false,"context_lines":[{"line_number":466,"context_line":"        # but we have ordered timestamps, so don\u0027t need"},{"line_number":467,"context_line":"        # to iter the whole series."},{"line_number":468,"context_line":"        freq \u003d self.sampling * SplitKey.POINTS_PER_SPLIT"},{"line_number":469,"context_line":"        ix \u003d numpy.divide(numpy.array(self.ts.index, \u0027float64\u0027), 10e8)"},{"line_number":470,"context_line":"        keys, counts \u003d numpy.unique((ix // freq) * freq, return_counts\u003dTrue)"},{"line_number":471,"context_line":"        start \u003d 0"},{"line_number":472,"context_line":"        for key, count in itertools.izip(keys, counts):"}],"source_content_type":"text/x-python","patch_set":4,"id":"5a3905b3_2ebf71fc","line":469,"range":{"start_line":469,"start_character":13,"end_line":469,"end_character":25},"updated":"2017-01-19 20:14:47.000000000","message":"interesting. this is faster than just dividing it with \u0027/ 10e8\u0027","commit_id":"804e5efdddd787868bb2ba539d70cb4f93711e04"},{"author":{"_account_id":6537,"name":"gordon chung","email":"gord@live.ca","username":"chungg"},"change_message_id":"f8fb49d347f3bdf24c5f75ff6b5650c60859e695","unresolved":false,"context_lines":[{"line_number":467,"context_line":"        # to iter the whole series."},{"line_number":468,"context_line":"        freq \u003d self.sampling * SplitKey.POINTS_PER_SPLIT"},{"line_number":469,"context_line":"        ix \u003d numpy.divide(numpy.array(self.ts.index, \u0027float64\u0027), 10e8)"},{"line_number":470,"context_line":"        keys, counts \u003d numpy.unique((ix // freq) * freq, return_counts\u003dTrue)"},{"line_number":471,"context_line":"        start \u003d 0"},{"line_number":472,"context_line":"        for key, count in itertools.izip(keys, counts):"},{"line_number":473,"context_line":"            end \u003d start + count"}],"source_content_type":"text/x-python","patch_set":4,"id":"5a3905b3_6ed33939","line":470,"range":{"start_line":470,"start_character":57,"end_line":470,"end_character":70},"updated":"2017-01-19 20:14:47.000000000","message":"this is in numpy 1.9.0 but our pandas is 0.17 which only requires 1.7... i think maybe we should start enforcing requirement on numpy as well then.","commit_id":"804e5efdddd787868bb2ba539d70cb4f93711e04"},{"author":{"_account_id":6537,"name":"gordon chung","email":"gord@live.ca","username":"chungg"},"change_message_id":"f8fb49d347f3bdf24c5f75ff6b5650c60859e695","unresolved":false,"context_lines":[{"line_number":471,"context_line":"        start \u003d 0"},{"line_number":472,"context_line":"        for key, count in itertools.izip(keys, counts):"},{"line_number":473,"context_line":"            end \u003d start + count"},{"line_number":474,"context_line":"            if key \u003d\u003d -0.0:  # float power"},{"line_number":475,"context_line":"                key \u003d abs(key)"},{"line_number":476,"context_line":"            yield (SplitKey(key, self.sampling),"},{"line_number":477,"context_line":"                   AggregatedTimeSerie(self.sampling, self.aggregation_method,"}],"source_content_type":"text/x-python","patch_set":4,"id":"5a3905b3_6e7979fc","line":474,"range":{"start_line":474,"start_character":28,"end_line":474,"end_character":42},"updated":"2017-01-19 20:14:47.000000000","message":"what is float power suppose to mean?","commit_id":"804e5efdddd787868bb2ba539d70cb4f93711e04"},{"author":{"_account_id":6537,"name":"gordon chung","email":"gord@live.ca","username":"chungg"},"change_message_id":"5b58f90657b0d615d241d6b8ad4a66683bc7f84c","unresolved":false,"context_lines":[{"line_number":468,"context_line":"        # but we have ordered timestamps, so don\u0027t need"},{"line_number":469,"context_line":"        # to iter the whole series."},{"line_number":470,"context_line":"        freq \u003d self.sampling * SplitKey.POINTS_PER_SPLIT"},{"line_number":471,"context_line":"        ix \u003d numpy.array(self.ts.index, \u0027float64\u0027) / 10e8"},{"line_number":472,"context_line":"        keys, counts \u003d numpy.unique((ix // freq) * freq, return_counts\u003dTrue)"},{"line_number":473,"context_line":"        start \u003d 0"},{"line_number":474,"context_line":"        for key, count in itertools.izip(keys, counts):"}],"source_content_type":"text/x-python","patch_set":5,"id":"5a3905b3_4b1e6abb","line":471,"updated":"2017-01-19 21:41:00.000000000","message":"oh, sorry. i meant your code was faster. a bit quicker than this... but a lot quicker than //","commit_id":"4c04d398389f678ccc67032c306c6d1a822edc0d"},{"author":{"_account_id":2813,"name":"Mehdi Abaakouk","email":"sileht@sileht.net","username":"sileht"},"change_message_id":"b06147ca3c87ee7cf2a6a95f5b1a9105584de620","unresolved":false,"context_lines":[{"line_number":468,"context_line":"        # but we have ordered timestamps, so don\u0027t need"},{"line_number":469,"context_line":"        # to iter the whole series."},{"line_number":470,"context_line":"        freq \u003d self.sampling * SplitKey.POINTS_PER_SPLIT"},{"line_number":471,"context_line":"        ix \u003d numpy.array(self.ts.index, \u0027float64\u0027) / 10e8"},{"line_number":472,"context_line":"        keys, counts \u003d numpy.unique((ix // freq) * freq, return_counts\u003dTrue)"},{"line_number":473,"context_line":"        start \u003d 0"},{"line_number":474,"context_line":"        for key, count in itertools.izip(keys, counts):"}],"source_content_type":"text/x-python","patch_set":5,"id":"5a3905b3_a120cf9c","line":471,"in_reply_to":"5a3905b3_4b1e6abb","updated":"2017-01-19 22:14:00.000000000","message":"I think that run the same numpy code in both case: \n\npython -m timeit \u0027import numpy ; numpy.divide(numpy.arange(1000000.0), 10e8)\u0027\n100 loops, best of 3: 7.84 msec per loop\n\npython -m timeit \u0027import numpy ; numpy.arange(1000000.0) / 10e8\u0027             \n100 loops, best of 3: 7.84 msec per loop","commit_id":"4c04d398389f678ccc67032c306c6d1a822edc0d"},{"author":{"_account_id":6537,"name":"gordon chung","email":"gord@live.ca","username":"chungg"},"change_message_id":"2e8f485d237077f81d9ac01231fe9cfa2d0b000b","unresolved":false,"context_lines":[{"line_number":468,"context_line":"        # but we have ordered timestamps, so don\u0027t need"},{"line_number":469,"context_line":"        # to iter the whole series."},{"line_number":470,"context_line":"        freq \u003d self.sampling * SplitKey.POINTS_PER_SPLIT"},{"line_number":471,"context_line":"        ix \u003d numpy.array(self.ts.index, \u0027float64\u0027) / 10e8"},{"line_number":472,"context_line":"        keys, counts \u003d numpy.unique((ix // freq) * freq, return_counts\u003dTrue)"},{"line_number":473,"context_line":"        start \u003d 0"},{"line_number":474,"context_line":"        for key, count in itertools.izip(keys, counts):"}],"source_content_type":"text/x-python","patch_set":5,"id":"5a3905b3_5ce9d219","line":471,"in_reply_to":"5a3905b3_a120cf9c","updated":"2017-01-19 22:48:25.000000000","message":"kk","commit_id":"4c04d398389f678ccc67032c306c6d1a822edc0d"},{"author":{"_account_id":6537,"name":"gordon chung","email":"gord@live.ca","username":"chungg"},"change_message_id":"3ea3812660f6b83694212e5cb031aa2cecdea5af","unresolved":false,"context_lines":[{"line_number":471,"context_line":"        ix \u003d numpy.array(self.ts.index, \u0027float64\u0027) / 10e8"},{"line_number":472,"context_line":"        keys, counts \u003d numpy.unique((ix // freq) * freq, return_counts\u003dTrue)"},{"line_number":473,"context_line":"        start \u003d 0"},{"line_number":474,"context_line":"        for key, count in itertools.izip(keys, counts):"},{"line_number":475,"context_line":"            end \u003d start + count"},{"line_number":476,"context_line":"            if key \u003d\u003d -0.0:"},{"line_number":477,"context_line":"                key \u003d abs(key)"}],"source_content_type":"text/x-python","patch_set":5,"id":"5a3905b3_52643121","line":474,"range":{"start_line":474,"start_character":26,"end_line":474,"end_character":40},"updated":"2017-01-20 16:04:26.000000000","message":"this is a real bug. izip doesn\u0027t exist in py3","commit_id":"4c04d398389f678ccc67032c306c6d1a822edc0d"},{"author":{"_account_id":2813,"name":"Mehdi Abaakouk","email":"sileht@sileht.net","username":"sileht"},"change_message_id":"2a6404a449f792c6cddd7ce70f3536d17e348075","unresolved":false,"context_lines":[{"line_number":471,"context_line":"        ix \u003d numpy.array(self.ts.index, \u0027float64\u0027) / 10e8"},{"line_number":472,"context_line":"        keys, counts \u003d numpy.unique((ix // freq) * freq, return_counts\u003dTrue)"},{"line_number":473,"context_line":"        start \u003d 0"},{"line_number":474,"context_line":"        for key, count in itertools.izip(keys, counts):"},{"line_number":475,"context_line":"            end \u003d start + count"},{"line_number":476,"context_line":"            if key \u003d\u003d -0.0:"},{"line_number":477,"context_line":"                key \u003d abs(key)"}],"source_content_type":"text/x-python","patch_set":5,"id":"5a3905b3_60f22a71","line":474,"range":{"start_line":474,"start_character":26,"end_line":474,"end_character":40},"in_reply_to":"5a3905b3_52643121","updated":"2017-01-20 19:38:36.000000000","message":"Done","commit_id":"4c04d398389f678ccc67032c306c6d1a822edc0d"}],"requirements.txt":[{"author":{"_account_id":1669,"name":"Julien Danjou","display_name":"jd","email":"julien@danjou.info","username":"jdanjou"},"change_message_id":"8d396169f69db65d7865482c58fe2d4a39a096d0","unresolved":false,"context_lines":[{"line_number":1,"context_line":"pbr"},{"line_number":2,"context_line":"numpy"},{"line_number":3,"context_line":"iso8601"},{"line_number":4,"context_line":"oslo.config\u003e\u003d2.6.0"},{"line_number":5,"context_line":"oslo.log\u003e\u003d2.3.0"}],"source_content_type":"text/plain","patch_set":6,"id":"5a3905b3_ebbfdbf8","line":2,"updated":"2017-01-20 19:48:14.000000000","message":"numpy is already there","commit_id":"a0688969f0e0213518ac71132da4bfaec6056d9d"}]}