Reputation: 389
I have to write this query for AWS-redshift for fetching data of last 20 wednesday, Help.!
SELECT
count(user_leads.id) AS lead_count, DATE(user_leads.created)
FROM
user_leads
join courses on user_leads.course_id = courses.id
left join users on user_leads.user_id = users.id
where
user_leads.created >= '2020-01-31'
AND user_leads.created < '2020-03-03'
AND courses.course_type !=4
AND users.email not like "%edureka%"
AND users.first_name not like "%test%"
AND weekday(user_leads) = 2
GROUP BY DATE(user_leads.created) DESC;
Upvotes: 0
Views: 70
Reputation: 16772
Using str.replace()
:
someFile.json:
[
"Date",
"17/04/2019",
"Skill",
"Travis",
"Repository",
"27,699 repository results"
][
"Date",
"17/04/2019",
"Skill",
"Kotlin",
"Repository",
"55,752 repository results"
]
Hence:
with open('someFile.json', 'r') as fp:
content = fp.readlines()
content = [l.strip() for l in content if l.strip()]
for line in content:
if '][' in line:
print(line.replace('][','],['))
else:
print(line)
OUTPUT:
[
"Date",
"17/04/2019",
"Skill",
"Travis",
"Repository",
"27,699 repository results"
],[
"Date",
"17/04/2019",
"Skill",
"Kotlin",
"Repository",
"55,752 repository results"
]
EDIT:
A rather json looking file should be:
someFile.json:
[
{
"date": "Date",
"dt": "17/04/2019",
"skill": "Skill",
"travel": "Travis",
"repo": "Repository",
"dat": "27,699 repository results"
}
][
{
"date": "Date",
"dt": "17/04/2019",
"skill": "Skill",
"travel": "Kotlin",
"repo": "Repository",
"dat": "2327,699 repository results"
}
]
Hence:
import json
with open('someFile.json', 'r') as file:
content = file.read()
clean = content.replace('][', ',') # cleanup here
json_data = json.loads(clean)
print(json_data)
OUTPUT:
[
{'date': 'Date', 'dt': '17/04/2019', 'skill': 'Skill', 'travel': 'Travis', 'repo': 'Repository', 'dat': '27,699 repository results'},
{'date': 'Date', 'dt': '17/04/2019', 'skill': 'Skill', 'travel': 'Kotlin', 'repo': 'Repository', 'dat': '2327,699 repository results'}
]
Upvotes: 1