How can I iterate through this list in Python
Question
I'm trying through iterate through the list below and am having a hard time. I am trying to access the dictionary element "metrics". I am trying to print out all the key/values of 'timestamp' and 'values'.
I've been able to access the list using the code below and do see how I can individually get within the list but am not sure how to build a loop to get all values I need.
flat_file = DATA[0]['environments'][0]['dimensions'][0]
[
{
"environments": [
{
"dimensions": [
{
"metrics": [
{
"name": "sum(message_count)",
"values": [
{
"timestamp": 1582588800000,
"value": "651.0"
},
{
"timestamp": 1582502400000,
"value": "510.0"
}
]
},
{
"name": "global-avg-request_size",
"values": [
"0.0"
]
},
{
"name": " avg(request_size)",
"values": [
{
"timestamp": 1582588800000,
"value": "0.0"
},
{
"timestamp": 1582502400000,
"value": "0.0"
}
]
}
],
"name": "TestL"
},
{
"metrics": [
{
"name": "sum(message_count)",
"values": [
{
"timestamp": 1582588800000,
"value": "477.0"
},
{
"timestamp": 1582502400000,
"value": "338.0"
}
]
},
{
"name": "global-avg-request_size",
"values": [
"0.0"
]
},
{
"name": " avg(request_size)",
"values": [
{
"timestamp": 1582588800000,
"value": "0.0"
},
{
"timestamp": 1582502400000,
"value": "0.0"
}
]
}
],
"name": "test_y"
},
{
"metrics": [
{
"name": "sum(message_count)",
"values": [
{
"timestamp": 1582588800000,
"value": "91.0"
},
{
"timestamp": 1582502400000,
"value": "93.0"
}
]
},
{
"name": "global-avg-request_size",
"values": [
"0.0"
]
},
{
"name": " avg(request_size)",
"values": [
{
"timestamp": 1582588800000,
"value": "0.0"
},
{
"timestamp": 1582502400000,
"value": "0.0"
}
]
}
],
"name": "Testz"
}
],
"name": "prod"
}
],
"metaData": {
"errors": [],
"notices": [
"query served by: something",
"Source:db",
"Table used: something",
"Metric with Avg of request_size was requested. For this a global avg was also computed with name global-avg-request_size"
]
}
}
]
3 answers
solution1
0 2020-02-26 04:06:40
This will work:
for i in range(len(l[0]['environments'][0]['dimensions'])):
for j in range(len(l[0]['environments'][0]['dimensions'][i]['metrics'])):
if '{' in str(l[0]['environments'][0]['dimensions'][i]['metrics'][j]['values']):
print(l[0]['environments'][0]['dimensions'][i]['metrics'][j]['values'])
Output:
[{'timestamp': 1582588800000, 'value': '651.0'}, {'timestamp': 1582502400000, 'value': '510.0'}]
[{'timestamp': 1582588800000, 'value': '0.0'}, {'timestamp': 1582502400000, 'value': '0.0'}]
[{'timestamp': 1582588800000, 'value': '477.0'}, {'timestamp': 1582502400000, 'value': '338.0'}]
[{'timestamp': 1582588800000, 'value': '0.0'}, {'timestamp': 1582502400000, 'value': '0.0'}]
[{'timestamp': 1582588800000, 'value': '91.0'}, {'timestamp': 1582502400000, 'value': '93.0'}]
[{'timestamp': 1582588800000, 'value': '0.0'}, {'timestamp': 1582502400000, 'value': '0.0'}]
solution2
0 2020-02-26 04:08:34
What you are reading is JSON, to read it in python you need :
import json
data = '''{
"environments": [
{
"dimensions": [
{
"metrics": [
{
"name": "sum(message_count)",
"values": [
{
"timestamp": 1582588800000,
"value": "651.0"
},
{
"timestamp": 1582502400000,
"value": "510.0"
}
]
},
{
"name": "global-avg-request_size",
"values": [
"0.0"
]
},
{
"name": " avg(request_size)",
"values": [
{
"timestamp": 1582588800000,
"value": "0.0"
},
{
"timestamp": 1582502400000,
"value": "0.0"
}
]
}
],
"name": "TestL"
},
{
"metrics": [
{
"name": "sum(message_count)",
"values": [
{
"timestamp": 1582588800000,
"value": "477.0"
},
{
"timestamp": 1582502400000,
"value": "338.0"
}
]
},
{
"name": "global-avg-request_size",
"values": [
"0.0"
]
},
{
"name": " avg(request_size)",
"values": [
{
"timestamp": 1582588800000,
"value": "0.0"
},
{
"timestamp": 1582502400000,
"value": "0.0"
}
]
}
],
"name": "test_y"
},
{
"metrics": [
{
"name": "sum(message_count)",
"values": [
{
"timestamp": 1582588800000,
"value": "91.0"
},
{
"timestamp": 1582502400000,
"value": "93.0"
}
]
},
{
"name": "global-avg-request_size",
"values": [
"0.0"
]
},
{
"name": " avg(request_size)",
"values": [
{
"timestamp": 1582588800000,
"value": "0.0"
},
{
"timestamp": 1582502400000,
"value": "0.0"
}
]
}
],
"name": "Testz"
}
],
"name": "prod"
}
],
"metaData": {
"errors": [],
"notices": [
"query served by: something",
"Source:db",
"Table used: something",
"Metric with Avg of request_size was requested. For this a global avg was also computed with name global-avg-request_size"
]
}
}'''
data_dict = json.loads(data)
This will create a python dictionary of your data. So now access the data as you will for a dictionary.
like: data_dict["environments"]
to go deeper try combo of for:
>>> for doc in data_dict['environments']:
... for i in doc['dimensions']:
... print(i['name'])
...
TestL
test_y
Testz
For better data oriented view and usage use Pandas check this link and this
solution3
0 ACCPTED 2020-02-26 04:43:44
lisp = [
{
"environments": [
{
"dimensions": [
{
"metrics": [
{
"name": "sum(message_count)",
"values": [
{
"timestamp": 1582588800000,
"value": "651.0"
},
{
"timestamp": 1582502400000,
"value": "510.0"
}
]
},
{
"name": "global-avg-request_size",
"values": [
"0.0"
]
},
{
"name": " avg(request_size)",
"values": [
{
"timestamp": 1582588800000,
"value": "0.0"
},
{
"timestamp": 1582502400000,
"value": "0.0"
}
]
}
],
"name": "TestL"
},
{
"metrics": [
{
"name": "sum(message_count)",
"values": [
{
"timestamp": 1582588800000,
"value": "477.0"
},
{
"timestamp": 1582502400000,
"value": "338.0"
}
]
},
{
"name": "global-avg-request_size",
"values": [
"0.0"
]
},
{
"name": " avg(request_size)",
"values": [
{
"timestamp": 1582588800000,
"value": "0.0"
},
{
"timestamp": 1582502400000,
"value": "0.0"
}
]
}
],
"name": "test_y"
},
{
"metrics": [
{
"name": "sum(message_count)",
"values": [
{
"timestamp": 1582588800000,
"value": "91.0"
},
{
"timestamp": 1582502400000,
"value": "93.0"
}
]
},
{
"name": "global-avg-request_size",
"values": [
"0.0"
]
},
{
"name": " avg(request_size)",
"values": [
{
"timestamp": 1582588800000,
"value": "0.0"
},
{
"timestamp": 1582502400000,
"value": "0.0"
}
]
}
],
"name": "Testz"
}
],
"name": "prod"
}
],
"metaData": {
"errors": [],
"notices": [
"query served by: something",
"Source:db",
"Table used: something",
"Metric with Avg of request_size was requested. For this a global avg was also computed with name global-avg-request_size"
]
}
}
]
for element in lisp[0]['environments'][0]['dimensions']:
for inner_element in element['metrics']:
for el in inner_element['values']:
if type(el) == dict:
print(el)
{'timestamp': 1582588800000, 'value': '651.0'}
{'timestamp': 1582502400000, 'value': '510.0'}
{'timestamp': 1582588800000, 'value': '0.0'}
{'timestamp': 1582502400000, 'value': '0.0'}
{'timestamp': 1582588800000, 'value': '477.0'}
{'timestamp': 1582502400000, 'value': '338.0'}
{'timestamp': 1582588800000, 'value': '0.0'}
{'timestamp': 1582502400000, 'value': '0.0'}
{'timestamp': 1582588800000, 'value': '91.0'}
{'timestamp': 1582502400000, 'value': '93.0'}
{'timestamp': 1582588800000, 'value': '0.0'}
{'timestamp': 1582502400000, 'value': '0.0'}
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.
Related Question
How can I iterate through a keyless list of jsons (string) with python?
How can I iterate through a list?
How can I iterate through the indices of the list?
How can I iterate through the wordsearch in python?
How do I iterate through through specific pairs of a list - Python
Python, can I iterate through a list within an if statement?
how can I iterate through list of list in "pyspark" for a specific result
How can I iterate through a list of items and extract a specific part using Selenium and Python
How can I iterate through individual rows in a list and use to input in form? Python
How can I iterate through the python list, and stop to load the next URL before continuing the process?
Related Tags