Rapid account: OpenWeb Ninja

OpenWeb Ninja / letscrape-6bRBa3QguO5

Developer, Engineer, Generalist

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567
Title
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A
1
Hi, Thanks for the examples. Let's check one by one: 1. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDI0LTA1LTI1fDkzMjg4NjU4MDkyMzM5MDQ0NjM=: "start_time": "2024-05-25 00:00:00", "start_time_utc": "2024-05-25 00:00:00", "start_time_precision_sec": 86400, "end_time": "2024-05-26 00:30:00", "end_time_utc": "2024-05-26 07:30:00", "end_time_precision_sec": 1, Given the accuracy of the start time is a day (86400 seconds), the fact that start_time is off by a day or less makes sense. 2. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDI0LTA2LTE0fDEwNDI0MTY1NDYxNzYzMzMzNTg4: "start_time": "2024-06-14 22:00:00", "start_time_utc": "2024-06-15 05:00:00", "start_time_precision_sec": 1, "end_time": "2024-06-14 23:30:00", "end_time_utc": "2024-06-15 06:30:00", "end_time_precision_sec": 1, This one has the correct times as on site (10pm PST). 3. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDIzLTA3LTEwfDExMjEwMDY4NDQ0ODgyNTYwMjAy: "start_time_precision_sec" :1, "end_time_precision_sec": 1 This one seems like an anomaly, probably Google's algorithm extracted the wrong times from the source page. Another option is, since this is a recurring weekly event then the start/end times might not be the exact time in the day in which the event actually takes place (notice that start and end dates are month apart). I've also added start_time_utc and end_time_utc to the response to more easily understand what's going on. Thank you, Adam सोम 7:31 20/5/24
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11
Hi, Thanks for the examples. Let's check one by one: 1. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDI0LTA1LTI1fDkzMjg4NjU4MDkyMzM5MDQ0NjM=: "start_time": "2024-05-25 00:00:00", "start_time_utc": "2024-05-25 00:00:00", "start_time_precision_sec": 86400, "end_time": "2024-05-26 00:30:00", "end_time_utc": "2024-05-26 07:30:00", "end_time_precision_sec": 1, Given the accuracy of the start time is a day (86400 seconds), the fact that start_time is off by a day or less makes sense. 2. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDI0LTA2LTE0fDEwNDI0MTY1NDYxNzYzMzMzNTg4: "start_time": "2024-06-14 22:00:00", "start_time_utc": "2024-06-15 05:00:00", "start_time_precision_sec": 1, "end_time": "2024-06-14 23:30:00", "end_time_utc": "2024-06-15 06:30:00", "end_time_precision_sec": 1, This one has the correct times as on site (10pm PST). 3. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDIzLTA3LTEwfDExMjEwMDY4NDQ0ODgyNTYwMjAy: "start_time_precision_sec" :1, "end_time_precision_sec": 1 This one seems like an anomaly, probably Google's algorithm extracted the wrong times from the source page. Another option is, since this is a recurring weekly event then the start/end times might not be the exact time in the day in which the event actually takes place (notice that start and end dates are month apart). I've also added start_time_utc and end_time_utc to the response to more easily understand what's going. Thank you, Adam सोम 7:31 20/5/24
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11
Hi, Thanks for the examples. Let's check one by one: 1. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDI0LTA1LTI1fDkzMjg4NjU4MDkyMzM5MDQ0NjM=: "start_time": "2024-05-25 00:00:00", "start_time_utc": "2024-05-25 00:00:00", "start_time_precision_sec": 86400, "end_time": "2024-05-26 00:30:00", "end_time_utc": "2024-05-26 07:30:00", "end_time_precision_sec": 1, Given the accuracy of the start time is a day (86400 seconds), the fact that start_time is off by a day or less makes sense. 2. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDI0LTA2LTE0fDEwNDI0MTY1NDYxNzYzMzMzNTg4: "start_time": "2024-06-14 22:00:00", "start_time_utc": "2024-06-15 05:00:00", "start_time_precision_sec": 1, "end_time": "2024-06-14 23:30:00", "end_time_utc": "2024-06-15 06:30:00", "end_time_precision_sec": 1, This one has the correct times as on site (10pm PST). 3. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDIzLTA3LTEwfDExMjEwMDY4NDQ0ODgyNTYwMjAy: "start_time_precision_sec" :1, "end_time_precision_sec": 1 This one seems like an anomaly, probably Google's algorithm extracted the wrong times from the source page. Another option is, since this is a recurring weekly event then the start/end times might not be the exact time in the day in which the event actually takes place (notice that start and end dates are month apart). I've also added start_time_utc and end_time_utc to the response to more easily understand what's going. Thank you, Adam सोम 7:31 20/5/24
A
11
Hi, Thanks for the examples. Let's check one by one: 1. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDI0LTA1LTI1fDkzMjg4NjU4MDkyMzM5MDQ0NjM=: "start_time": "2024-05-25 00:00:00", "start_time_utc": "2024-05-25 00:00:00", "start_time_precision_sec": 86400, "end_time": "2024-05-26 00:30:00", "end_time_utc": "2024-05-26 07:30:00", "end_time_precision_sec": 1, Given the accuracy of the start time is a day (86400 seconds), the fact that start_time is off by a day or less makes sense. 2. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDI0LTA2LTE0fDEwNDI0MTY1NDYxNzYzMzMzNTg4: "start_time": "2024-06-14 22:00:00", "start_time_utc": "2024-06-15 05:00:00", "start_time_precision_sec": 1, "end_time": "2024-06-14 23:30:00", "end_time_utc": "2024-06-15 06:30:00", "end_time_precision_sec": 1, This one has the correct times as on site (10pm PST). 3. L2F1dGhvcml0eS9ob3Jpem9uL2NsdXN0ZXJlZF9ldmVudC8yMDIzLTA3LTEwfDExMjEwMDY4NDQ0ODgyNTYwMjAy: "start_time_precision_sec" :1, "end_time_precision_sec": 1 This one seems like an anomaly, probably Google's algorithm extracted the wrong times from the source page. Another option is, since this is a recurring weekly event then the start/end times might not be the exact time in the day in which the event actually takes place (notice that start and end dates are month apart). I've also added start_time_utc and end_time_utc to the response to more easily understand what's going. Thank you, Adam सोम 7:31 20/5/24
A
5
I optimized a few things - do you see an improvement now? सोम 7:04 20/5/24
A
1
Hi there, Thank you for your question. Yes to both - the data is real-time and 100% up-to-date. In addition, it covers all businesses worldwide (300M+ businesses estimated worldwide). Please feel free if you have any questions or concerns. Thank you, Adam @ OpenWeb Ninja सोम 6:01 20/5/24