JMESPath create csv · Built for AWS CLI

JMESPath to CSV Converter

Query JSON data with JMESPath and instantly export results to CSV format. Perfect for AWS CLI outputs, API responses, and spreadsheet-friendly reports.

⚡ Instant Export🔧 AWS CLI Ready📊 Excel Friendly

JMESPath expressionExample: people[?age > `30`].name

Input JSON

Live evaluation

CSV export options

DelimiterQuote styleEncodingFile name

CSV preview (first 5 rows)

value	index
Alice	0
Carol	1

Why this tool exists

JMESPath doesn't natively support CSV. This tool bridges the gap.

AWS CLI users often search for "jmespath create csv" because they need spreadsheet-friendly results. Instead of chaining jq, sed, and manual scripts, write one JMESPath query, preview the CSV, and download immediately.

Back to JMESPath tester

Traditional path ❌

Run AWS CLI to get JSON
Install jq and craft filters
Pipe and debug shell quoting
Manually save CSV
Hope spreadsheets open correctly

Our path ✅

Paste AWS CLI JSON
Write JMESPath query
Preview CSV columns
Click "Export to CSV"
Open in Excel/Sheets instantly

10 AWS CLI scenarios ready to try

Realistic JSON outputs plus JMESPath expressions you can load directly into the converter. Click “Try this example” to prefill the tool and export CSV.

🖥️

EC2 instance inventory

aws ec2 describe-instances --region us-east-1

Flattens Reservations and Instances, then projects only the columns needed for reporting.

View JSON output

{
  "Reservations": [
    {
      "ReservationId": "r-0123abcd",
      "Instances": [
        {
          "InstanceId": "i-0abc1234def567890",
          "InstanceType": "t3.micro",
          "LaunchTime": "2024-12-05T14:03:21+00:00",
          "PrivateIpAddress": "10.0.1.12",
          "State": { "Name": "running" },
          "Tags": [
            { "Key": "Name", "Value": "app-server-1" },
            { "Key": "Env", "Value": "prod" }
          ]
        },
        {
          "InstanceId": "i-0ffedcba987654321",
          "InstanceType": "m6g.large",
          "LaunchTime": "2024-11-01T09:14:10+00:00",
          "PrivateIpAddress": "10.0.2.7",
          "State": { "Name": "stopped" },
          "Tags": [
            { "Key": "Name", "Value": "batch-worker" },
            { "Key": "Env", "Value": "staging" }
          ]
        }
      ]
    }
  ]
}

JMESPath

Reservations[].Instances[].{InstanceId: InstanceId, Type: InstanceType, State: State.Name, LaunchTime: LaunchTime, PrivateIP: PrivateIpAddress}

CSV preview

InstanceId	Type	State	LaunchTime	PrivateIP
i-0abc1234def567890	t3.micro	running	2024-12-05T14:03:21+00:00	10.0.1.12
i-0ffedcba987654321	m6g.large	stopped	2024-11-01T09:14:10+00:00	10.0.2.7

🪣

S3 bucket list

aws s3api list-buckets

Lists bucket names with creation dates. Region can be joined from a separate call.

View JSON output

{
  "Buckets": [
    { "Name": "data-lake-prod", "CreationDate": "2023-08-15T12:00:00.000Z" },
    { "Name": "cdn-assets", "CreationDate": "2022-04-03T09:22:10.000Z" },
    { "Name": "backup-logs", "CreationDate": "2024-01-19T18:44:29.000Z" }
  ],
  "Owner": { "DisplayName": "example-account", "ID": "123456789012" }
}

JMESPath

Buckets[].{Name: Name, CreationDate: CreationDate}

CSV preview

Name	CreationDate
data-lake-prod	2023-08-15T12:00:00.000Z
cdn-assets	2022-04-03T09:22:10.000Z
backup-logs	2024-01-19T18:44:29.000Z

Lambda functions

aws lambda list-functions --region us-west-2

Creates a concise inventory ready for operations reviews.

View JSON output

{
  "Functions": [
    {
      "FunctionName": "image-resize",
      "Runtime": "python3.11",
      "MemorySize": 512,
      "Timeout": 15,
      "LastModified": "2024-12-10T08:11:54.123+0000"
    },
    {
      "FunctionName": "webhook-handler",
      "Runtime": "nodejs20.x",
      "MemorySize": 256,
      "Timeout": 10,
      "LastModified": "2024-11-28T17:01:02.987+0000"
    }
  ]
}

JMESPath

Functions[].{FunctionName: FunctionName, Runtime: Runtime, MemoryMB: MemorySize, TimeoutSec: Timeout, LastModified: LastModified}

CSV preview

FunctionName	Runtime	MemoryMB	TimeoutSec	LastModified
image-resize	python3.11	512	15	2024-12-10T08:11:54.123+0000
webhook-handler	nodejs20.x	256	10	2024-11-28T17:01:02.987+0000

👤

IAM users

aws iam list-users

Highlights account age and password usage for security audits.

View JSON output

{
  "Users": [
    {
      "UserName": "alice",
      "CreateDate": "2022-07-12T10:05:33Z",
      "PasswordLastUsed": "2024-12-14T06:20:01Z"
    },
    {
      "UserName": "bob",
      "CreateDate": "2023-02-03T18:40:11Z",
      "PasswordLastUsed": null
    }
  ]
}

JMESPath

Users[].{UserName: UserName, CreateDate: CreateDate, PasswordLastUsed: PasswordLastUsed}

CSV preview

UserName	CreateDate	PasswordLastUsed
alice	2022-07-12T10:05:33Z	2024-12-14T06:20:01Z
bob	2023-02-03T18:40:11Z

🗄️

RDS instances

aws rds describe-db-instances --region us-east-1

Summarizes database fleet status and sizes for capacity tracking.

View JSON output

{
  "DBInstances": [
    {
      "DBInstanceIdentifier": "orders-db",
      "DBInstanceClass": "db.r6g.large",
      "Engine": "aurora-postgresql",
      "DBInstanceStatus": "available",
      "AllocatedStorage": 100
    },
    {
      "DBInstanceIdentifier": "analytics-db",
      "DBInstanceClass": "db.r6g.2xlarge",
      "Engine": "aurora-mysql",
      "DBInstanceStatus": "modifying",
      "AllocatedStorage": 500
    }
  ]
}

JMESPath

DBInstances[].{DBInstanceIdentifier: DBInstanceIdentifier, Engine: Engine, Status: DBInstanceStatus, Class: DBInstanceClass, AllocatedStorage: AllocatedStorage}

CSV preview

DBInstanceIdentifier	Engine	Status	Class	AllocatedStorage
orders-db	aurora-postgresql	available	db.r6g.large	100
analytics-db	aurora-mysql	modifying	db.r6g.2xlarge	500

🧱

CloudFormation stacks

aws cloudformation list-stacks --stack-status-filter CREATE_COMPLETE UPDATE_COMPLETE

Produces a clean list of stacks and their states for governance.

View JSON output

{
  "StackSummaries": [
    {
      "StackName": "networking",
      "CreationTime": "2023-06-01T12:00:00Z",
      "StackStatus": "CREATE_COMPLETE"
    },
    {
      "StackName": "payments",
      "CreationTime": "2024-02-10T08:30:00Z",
      "StackStatus": "UPDATE_COMPLETE"
    }
  ]
}

JMESPath

StackSummaries[].{StackName: StackName, Status: StackStatus, CreationTime: CreationTime}

CSV preview

StackName	Status	CreationTime
networking	CREATE_COMPLETE	2023-06-01T12:00:00Z
payments	UPDATE_COMPLETE	2024-02-10T08:30:00Z

📦

ECS tasks

aws ecs list-tasks --cluster prod-cluster && aws ecs describe-tasks --cluster prod-cluster --tasks <ids>

Extracts the essentials for task health dashboards.

View JSON output

{
  "tasks": [
    {
      "taskArn": "arn:aws:ecs:us-east-1:123456789012:task/prod-cluster/1111",
      "lastStatus": "RUNNING",
      "clusterArn": "arn:aws:ecs:us-east-1:123456789012:cluster/prod-cluster"
    },
    {
      "taskArn": "arn:aws:ecs:us-east-1:123456789012:task/prod-cluster/2222",
      "lastStatus": "PENDING",
      "clusterArn": "arn:aws:ecs:us-east-1:123456789012:cluster/prod-cluster"
    }
  ]
}

JMESPath

tasks[].{TaskArn: taskArn, ClusterArn: clusterArn, LastStatus: lastStatus}

CSV preview

TaskArn	ClusterArn	LastStatus
arn:aws:ecs:us-east-1:123456789012:task/prod-cluster/1111	arn:aws:ecs:us-east-1:123456789012:cluster/prod-cluster	RUNNING
arn:aws:ecs:us-east-1:123456789012:task/prod-cluster/2222	arn:aws:ecs:us-east-1:123456789012:cluster/prod-cluster	PENDING

🌐

VPC list

aws ec2 describe-vpcs

Adds tag-based names to the VPC list to make reports readable.

View JSON output

{
  "Vpcs": [
    {
      "VpcId": "vpc-0abc1234",
      "CidrBlock": "10.0.0.0/16",
      "State": "available",
      "Tags": [{ "Key": "Name", "Value": "core" }]
    },
    {
      "VpcId": "vpc-0def5678",
      "CidrBlock": "172.31.0.0/16",
      "State": "available",
      "Tags": [{ "Key": "Name", "Value": "shared-services" }]
    }
  ]
}

JMESPath

Vpcs[].{VpcId: VpcId, CidrBlock: CidrBlock, State: State, Name: Tags[?Key=='Name'].Value | [0]}

CSV preview

VpcId	CidrBlock	State	Name
vpc-0abc1234	10.0.0.0/16	available	core
vpc-0def5678	172.31.0.0/16	available	shared-services

🛡️

Security groups

aws ec2 describe-security-groups --region us-west-2

Surfaces inbound rules in a compact structure to scan open access quickly.

View JSON output

{
  "SecurityGroups": [
    {
      "GroupId": "sg-0123abcd",
      "GroupName": "web-frontend",
      "VpcId": "vpc-0abc1234",
      "IpPermissions": [
        {
          "IpProtocol": "tcp",
          "FromPort": 443,
          "ToPort": 443,
          "IpRanges": [{ "CidrIp": "0.0.0.0/0" }]
        }
      ]
    },
    {
      "GroupId": "sg-0fedcba9",
      "GroupName": "db",
      "VpcId": "vpc-0abc1234",
      "IpPermissions": [
        {
          "IpProtocol": "tcp",
          "FromPort": 5432,
          "ToPort": 5432,
          "IpRanges": [{ "CidrIp": "10.0.0.0/16" }]
        }
      ]
    }
  ]
}

JMESPath

SecurityGroups[].{GroupId: GroupId, GroupName: GroupName, VpcId: VpcId, InboundRules: IpPermissions[].{Protocol: IpProtocol, FromPort: FromPort, ToPort: ToPort, Source: IpRanges[].CidrIp | [0]}}

CSV preview

GroupId	GroupName	VpcId	InboundRules
sg-0123abcd	web-frontend	vpc-0abc1234	[{"Protocol":"tcp","FromPort":443,"ToPort":443,"Source":"0.0.0.0/0"}]
sg-0fedcba9	db	vpc-0abc1234	[{"Protocol":"tcp","FromPort":5432,"ToPort":5432,"Source":"10.0.0.0/16"}]

⏰

CloudWatch alarms

aws cloudwatch describe-alarms --state-value ALARM

Creates an actionable list of active alarms for on-call handoffs.

View JSON output

{
  "MetricAlarms": [
    {
      "AlarmName": "HighCPU",
      "StateValue": "ALARM",
      "MetricName": "CPUUtilization",
      "Namespace": "AWS/EC2"
    },
    {
      "AlarmName": "5xxErrors",
      "StateValue": "ALARM",
      "MetricName": "5XXError",
      "Namespace": "AWS/ApplicationELB"
    }
  ]
}

JMESPath

MetricAlarms[].{AlarmName: AlarmName, StateValue: StateValue, MetricName: MetricName, Namespace: Namespace}

CSV preview

AlarmName	StateValue	MetricName	Namespace
HighCPU	ALARM	CPUUtilization	AWS/EC2
5xxErrors	ALARM	5XXError	AWS/ApplicationELB

How to create CSV from JSON using JMESPath

Paste your JSON data. Use AWS CLI output, API responses, or any structured JSON.
Write your JMESPath query. Use filters, projections, and functions to shape columns.
Export to CSV. Adjust delimiter, encoding, and quotes. Preview the first rows before download.

Do's

Use multi-select hashes like {Name: name, Age: age}
Filter early to reduce CSV size
Rename keys for human-friendly headers
Validate JSON before exporting

Don'ts

Avoid deeply nested objects—flatten first
Avoid massive arrays without filtering
Don't mix inconsistent shapes in one projection
Don't include secrets or tokens in exports

Automate it

Python (pip install jmespath pandas)

import json
import jmespath
import pandas as pd

with open("input.json") as f:
    data = json.load(f)

expr = jmespath.compile("Reservations[].Instances[].{Id: InstanceId, Type: InstanceType}")
rows = expr.search(data)
df = pd.json_normalize(rows)
df.to_csv("jmespath-result.csv", index=False, encoding="utf-8-sig")

Bash (npm i -g jmespath)

#!/usr/bin/env bash
set -euo pipefail

aws ec2 describe-instances --region us-east-1 \
  | jp 'Reservations[].Instances[].{Id: InstanceId, State: State.Name}' \
  | jq -r '(.[0] | keys_unsorted) as $cols | $cols, (.[] | [.[]]) | @csv' \
  > jmespath-result.csv

echo "Saved jmespath-result.csv"

Which method to choose?

Method	Steps	Pros	Cons
JMESPath + this CSV tool	Paste JSON → Write expression → Export CSV	No installs, works with AWS CLI output, reusable expressions	Browser-based; huge files may need pre-filtering
jq	Install jq → Learn filters → Use @csv	Powerful CLI, streams large data	Requires shell proficiency; harder for teams to share recipes
Python pandas	Install pandas → Load JSON → Normalize → Export CSV	Very flexible, good for complex transforms	Heavier dependency, more code to maintain
Generic online converters	Upload JSON → Download CSV	Quick for trivial data	No JMESPath filtering, privacy concerns, limited formatting

FAQ

▶Can I use this for large JSON files?

Yes, but for very large payloads you should filter first with JMESPath to reduce size before exporting. The tool runs in-browser.

▶How do I handle nested arrays in CSV?

Flatten with projections like people[].skills[] or use multi-select hashes {Name: name, Skill: skills[0]} to produce consistent columns.

▶Can I automate this process?

Yes. Use the Python or Bash examples below to run JMESPath and export CSV in scripts or CI pipelines.

▶Is the CSV format compatible with Excel?

Choose UTF-8 with BOM for the broadest compatibility. Tab or comma delimiters both open in Excel and Google Sheets.

▶What if my JSON has inconsistent structure?

Define explicit projections to normalized keys, e.g., {Name: name, Region: region || 'unknown'}. Missing fields will be blank.

▶Can I export multiple files at once?

Use the automation snippets to iterate through inputs and write multiple CSV files; the online tool downloads one file at a time.

▶Does JMESPath natively support CSV?

No. JMESPath is a query language only. This tool bridges the gap so you can convert JSON to CSV without extra scripts.

▶How do I avoid leaking secrets?

Remove sensitive fields in your expression, e.g., {Id: id, Name: name} to exclude tokens or ARNs before download. Everything runs locally in your browser.

Ready to convert your JSON to CSV?

Use JMESPath to shape your data, then export to CSV instantly. Built for AWS CLI, API responses, and spreadsheet workflows.

Start converting →Try JMESPath tester