There is a dict named 'data'
{
"error":false,
"message":"Ok",
"data":{
"numFound":1845,
"start":0,
"numFoundExact":true,
"docs":[
{
"sub_farmer_id":0,
"grade_a_produce":320,
"commodity_image":"red_carrot.jpg",
"farm_image":"",
"batch_status":"completed",
"batch_count":30,
"franchise_type":"TELF",
"sr_assignee_id":0,
"farm_status":"converted",
"state_name":"RAJASTHAN",
"farmer_id":1648,
"grade_a_sell_price":0,
"id":"11",
"commodity_name":"Carrot Red",
"acerage":1,
"soil_k":0,
"lgd_state_id":8,
"soil_n":0,
"unique_key":"11_8",
"historic_gdd":0.41,
"farm_type":"soiless",
"soil_test_report":"",
"user_id":1648,
"expected_yield_delivery_date":"2020-04-30T00:00:00Z",
"current_gdd":0,
"soil_p":0,
"expected_grade_a_produce":636,
"water_ph":0,
"end_date":"2020-04-30T00:00:00Z",
"batch_id":8,
"expected_delivery_date":"2020-04-30T00:00:00Z",
"previous_crop_ids":"0",
"batch_updated_at":"2021-12-29T17:50:58Z",
"grade_c_rejection":0,
"water_test_report":"",
"farm_updated_at":"2021-12-29T17:51:00Z",
"water_ec":0,
"start_date":"2019-10-30T00:00:00Z",
"assignee_id":0,
"pest_problems":"",
"expected_production":1060,
"is_active":true,
"mobile":"7015150636",
"grade_b_sell_price":0,
"irrigation_type":"drip",
"total_acerage":0,
"current_pdd":0,
"commodity_id":68,
"stage":"flowering",
"farm_health":"0",
"expected_grade_b_produce":424,
"grade_b_produce":740,
"historic_pdd":0.31,
"username":"Agritecture",
"variety_name":"",
"sr_assignee_name":"",
"lng":0,
"locality":"",
"assignee_name":"",
"subfarmer_mobile_no":"",
"commodity_image_96px_icon":"",
"subfarmer_name":"",
"batch_end_date":"",
"lat":0,
"_version_":1720553030989906000
}
But I am trying to extract data from list and append in a new csv with different columns so that it looks neat and clean
so, Here I am trying code
writer = csv.DictWriter(response_data, fieldnames=['Farmer Name', 'Mobile', 'Irrigation Type', 'Batch Status',
'Soil Parameters',
'Water Parameters', 'Crop Name', 'Farm Status', 'Farm Type',
'Franchise Type', 'Farm Total Acerage', 'Batch Acerage',
'Farm Health(%)', 'Historical Yield(/Acre)',
'Expected Produce',
'Actual Yield(/Acre)', 'Actual Produce', 'Crop health(%)',
'Stage', 'SOP Adherence', 'Assignee', 'Sub Farmer',
'Last Activity Update', 'Exp. Delivery Date'], delimiter=",")
writer.writeheader()
for docs in data.keys():
writer.writerow(
{"Farmer Name": docs.get('username'), "Mobile": docs.get('mobile')
"Irrigation Type": data.get('irrigation_type'), "Batch Status": data.get('batch_status'),
"Soil Parameters": {'N:-': data.get('soil_n'), 'P:-': data.get('soil_p'),
'K:-': data.get('soil_k')},
"Water Parameters": {'ec:-': data.get('water_ec'), 'pH:-': data.get('water_ph'), },
"Crop Name": data.get('commodity_name'), "Farm Status": data.get('farm_status'),
"Farm Type": data.get('farm_type'),
"Franchise Type": data.get('franchise_type'), "Farm Total Acerage": data.get('total_acerage'),
"Batch Acerage": data.get('batch_count'), "Farm Health(%)": data.get('farm_health'),
"Historical Yield(/Acre)": data.get(''),
"Expected Produce": data.get('expected_production'), "Actual Yield(/Acre)": data.get('username'),
"Actual Produce": data.get('username'), "Crop health(%)": data.get('username'),
"Stage": data.get('stage'),
"SOP Adherence": data.get('sope'),
"Last Activity Update": data.get('end_date'),
"Exp. Delivery Date": data.get('expected_delivery_date')
})
SO that the data extract from that dict and keep on append on the cdv file as methioned column
But It shows an error
AttributeError: 'str' object has no attribute 'get'
I could not get the columns value in my header from the dict
CodePudding user response：
Firstly, it is confusing that you have a dict called data which has a key called "data", and that you are iterating over docs in a dict with a key called "docs".
However, the error is because you are iterating over data.keys(), which returns a string for each value.
An illustrative example:
my_dict = {
"foo" : "bar",
"baz" : "luhrmann"
}
for each_key in my_dict.keys():
print(f"{each_key} : {type(each_key)}")
This will return:
foo : <class 'str'>
baz : <class 'str'>
So in the line docs.get('username'), you are trying to call the get method on a string. The error is telling you that strings do not have this method. I think what you are trying to do is data['docs'].get('username').
CodePudding user response：
The full code:
import csv
with open('output.csv', 'w') as response_data:
writer = csv.DictWriter(response_data, fieldnames=['Farmer Name', 'Mobile', 'Irrigation Type', 'Batch Status',
'Soil Parameters',
'Water Parameters', 'Crop Name', 'Farm Status', 'Farm Type',
'Franchise Type', 'Farm Total Acerage', 'Batch Acerage',
'Farm Health(%)', 'Historical Yield(/Acre)',
'Expected Produce',
'Actual Yield(/Acre)', 'Actual Produce', 'Crop health(%)',
'Stage', 'SOP Adherence', 'Assignee', 'Sub Farmer',
'Last Activity Update', 'Exp. Delivery Date'], delimiter=",")
writer.writeheader()
for doc in data['data']['docs']: # THE PROBLEM WAS HERE
writer.writerow({
"Farmer Name": doc.get('username'), "Mobile": doc.get('mobile'),
"Irrigation Type": doc.get('irrigation_type'), "Batch Status": doc.get('batch_status'),
"Soil Parameters": {'N:-': doc.get('soil_n'), 'P:-': doc.get('soil_p'),
'K:-': doc.get('soil_k')},
"Water Parameters": {'ec:-': doc.get('water_ec'), 'pH:-': doc.get('water_ph'), },
"Crop Name": doc.get('commodity_name'), "Farm Status": doc.get('farm_status'),
"Farm Type": doc.get('farm_type'),
"Franchise Type": doc.get('franchise_type'), "Farm Total Acerage": doc.get('total_acerage'),
"Batch Acerage": doc.get('batch_count'), "Farm Health(%)": doc.get('farm_health'),
"Historical Yield(/Acre)": doc.get(''),
"Expected Produce": doc.get('expected_production'), "Actual Yield(/Acre)": doc.get('username'),
"Actual Produce": doc.get('username'), "Crop health(%)": doc.get('username'),
"Stage": doc.get('stage'),
"SOP Adherence": doc.get('sope'),
"Last Activity Update": doc.get('end_date'),
"Exp. Delivery Date": doc.get('expected_delivery_date')
})
output.csv:
Farmer Name,Mobile,Irrigation Type,Batch Status,Soil Parameters,Water Parameters,Crop Name,Farm Status,Farm Type,Franchise Type,Farm Total Acerage,Batch Acerage,Farm Health(%),Historical Yield(/Acre),Expected Produce,Actual Yield(/Acre),Actual Produce,Crop health(%),Stage,SOP Adherence,Assignee,Sub Farmer,Last Activity Update,Exp. Delivery Date
Agritecture,7015150636,drip,completed,"{'N:-': 0, 'P:-': 0, 'K:-': 0}","{'ec:-': 0, 'pH:-': 0}",Carrot Red,converted,soiless,TELF,0,30,0,,1060,Agritecture,Agritecture,Agritecture,flowering,,,,2020-04-30T00:00:00Z,2020-04-30T00:00:00Z
How I build data:
import json
data = json.loads(your_json_data)
print(data)
# Output
{'error': False,
'message': 'Ok',
'data': {'numFound': 1845,
'start': 0,
'numFoundExact': True,
'docs': [{'sub_farmer_id': 0,
'grade_a_produce': 320,
'commodity_image': 'red_carrot.jpg',
'farm_image': '',
'batch_status': 'completed',
'batch_count': 30,
'franchise_type': 'TELF',
'sr_assignee_id': 0,
'farm_status': 'converted',
'state_name': 'RAJASTHAN',
'farmer_id': 1648,
'grade_a_sell_price': 0,
'id': '11',
'commodity_name': 'Carrot Red',
'acerage': 1,
'soil_k': 0,
'lgd_state_id': 8,
'soil_n': 0,
'unique_key': '11_8',
'historic_gdd': 0.41,
'farm_type': 'soiless',
'soil_test_report': '',
'user_id': 1648,
'expected_yield_delivery_date': '2020-04-30T00:00:00Z',
'current_gdd': 0,
'soil_p': 0,
'expected_grade_a_produce': 636,
'water_ph': 0,
'end_date': '2020-04-30T00:00:00Z',
'batch_id': 8,
'expected_delivery_date': '2020-04-30T00:00:00Z',
'previous_crop_ids': '0',
'batch_updated_at': '2021-12-29T17:50:58Z',
'grade_c_rejection': 0,
'water_test_report': '',
'farm_updated_at': '2021-12-29T17:51:00Z',
'water_ec': 0,
'start_date': '2019-10-30T00:00:00Z',
'assignee_id': 0,
'pest_problems': '',
'expected_production': 1060,
'is_active': True,
'mobile': '7015150636',
'grade_b_sell_price': 0,
'irrigation_type': 'drip',
'total_acerage': 0,
'current_pdd': 0,
'commodity_id': 68,
'stage': 'flowering',
'farm_health': '0',
'expected_grade_b_produce': 424,
'grade_b_produce': 740,
'historic_pdd': 0.31,
'username': 'Agritecture',
'variety_name': '',
'sr_assignee_name': '',
'lng': 0,
'locality': '',
'assignee_name': '',
'subfarmer_mobile_no': '',
'commodity_image_96px_icon': '',
'subfarmer_name': '',
'batch_end_date': '',
'lat': 0,
'_version_': 1720553030989906000}]}}