How to Read a JSON File in Python

What you’ll build or solve

You’ll read a JSON file from disk and turn it into Python data like dicts and lists.

When this approach works best

Reading a JSON file works well when you:

• Load app settings like feature flags, UI preferences, or environment-specific config.
• Process exported data, like a list of users, products, or events saved as JSON.
• Build small utilities that read structured input for reporting or automation.

Skip this approach if the file is extremely large, and you only need a tiny slice of it. A streaming parser or a different storage format may fit better.

Prerequisites

• Python 3 installed
• You know what JSON looks like, objects and arrays
• Your file contains valid JSON, double quotes, no trailing commas, no comments

Step-by-step instructions

1) Load JSON from a file

Use the built-in json module.

Option A (most common): json.load() reads from a file object

Option B: json.loads() parses a string

importjson
frompathlibimportPath

# Option A: Load directly from a file object
withopen("data.json","r",encoding="utf-8")asf:
data=json.load(f)

# Option B: Load from a string you already have
text=Path("data.json").read_text(encoding="utf-8")
data=json.loads(text)

What to look for: json.load() reads from a file object, json.loads() parses a string.

If you’re dealing with folders and want portable paths across operating systems, see Example 2.

2) Access the data safely

First, confirm what you loaded. JSON at the top level is usually a dict or a list.

ifisinstance(data,dict):
print("Top-level keys:",list(data.keys()))
elifisinstance(data,list):
print("Top-level list length:",len(data))

Then access values in a way that matches the shape.

If data is a dict:

project=data.get("project","unknown")
max_retries=data.get("max_retries",0)

print(project,max_retries)

If you need a nested value but some keys may be missing, chain .get() with a default dict:

metrics=data.get("metrics", {})
signups=metrics.get("signups",0)

print(signups)

3) Handle JSON errors

Two errors show up most often:

• FileNotFoundError when the path is wrong
• json.JSONDecodeError when the file is not valid JSON

importjson
fromjsonimportJSONDecodeError
frompathlibimportPath

path=Path("data.json")

try:
withpath.open("r",encoding="utf-8")asf:
data=json.load(f)
exceptFileNotFoundError:
print(f"File not found:{path.resolve()}")
exceptJSONDecodeErrorase:
print("Invalid JSON.")
print(f"Line{e.lineno}, column{e.colno}:{e.msg}")
else:
print("Loaded JSON successfully.")

What to look for: The line and column in JSONDecodeError usually point to a missing quote, extra comma, or another formatting issue.

Examples you can copy

Example 1: Read a simple config file

config.json:

{
  "debug":false,
  "base_url":"https://example.com",
  "max_retries":3
}

Python:

importjson
frompathlibimportPath

config=json.loads(Path("config.json").read_text(encoding="utf-8"))

debug=config.get("debug",False)
base_url=config.get("base_url","https://example.com")
max_retries=config.get("max_retries",0)

print(debug)
print(base_url)
print(max_retries)

Example 2: Read JSON from a file in a subfolder

This helps when your script and your JSON file live in different folders.

importjson
frompathlibimportPath

# Folder structure example:
# project/
#   app.py
#   data/
#     users.json

path=Path(__file__).parent/"data"/"users.json"

withpath.open("r",encoding="utf-8")asf:
users=json.load(f)

print(len(users))

What to look for: Path(__file__).parent anchors the path to the script’s location, not your current terminal folder.

Example 3: Read a list of records and loop through it

users.json:

[
  {"name":"Amina", "role":"admin"},
  {"name":"Luka", "role":"editor"},
  {"name":"Noor", "role":"viewer"}
]

Python:

importjson

withopen("users.json","r",encoding="utf-8")asf:
users=json.load(f)

foruserinusers:
print(f'{user["name"]} ->{user["role"]}')

Example 4: Read nested JSON and pull out a few values

report.json:

{
  "run_id":"2026-02-16T10:15:00Z",
  "metrics": {
    "signups":128,
    "paid_conversions":14
  },
  "top_sources": ["search","referral","email"]
}

Python:

importjson
frompathlibimportPath

report=json.loads(Path("report.json").read_text(encoding="utf-8"))

run_id=report["run_id"]
signups=report["metrics"]["signups"]
top_source=report["top_sources"][0]

print(run_id)
print(signups)
print(top_source)

Common mistakes and how to fix them

Mistake 1: Reading the file as text and treating it like a dict

What you might do:

withopen("data.json","r",encoding="utf-8")asf:
data=f.read()

print(data["project"])

Why it breaks: f.read() returns a string, so data["project"] does not make sense.

Correct approach:

importjson

withopen("data.json","r",encoding="utf-8")asf:
data=json.load(f)

print(data["project"])

Mistake 2: Using JSON-like syntax that JSON doesn’t allow

What you might write (invalid JSON):

{ 'project': 'demo', 'max_retries':3, }

Why it breaks: JSON requires double quotes, and trailing commas are not allowed.

Correct JSON:

{
  "project":"demo",
  "max_retries":3
}

Then load it:

importjson

withopen("data.json","r",encoding="utf-8")asf:
data=json.load(f)

print(data)

Troubleshooting

If you see FileNotFoundError, print the resolved path and confirm the file exists there:

frompathlibimportPath
print(Path("data.json").resolve())

If you see json.JSONDecodeError, go to the line and column shown, then look for a missing quote, an extra comma, or a comment.

If you see UnicodeDecodeError, the file may not be UTF-8. Try a different encoding that matches the source:

frompathlibimportPath
text=Path("data.json").read_text(encoding="cp1252")

If you see KeyError, print the keys you actually have, then update your key name or use .get() with a default:

print(list(data.keys()))

If you see TypeError: list indices must be integers, your top-level JSON is a list, not a dict. Loop through it or use an index like data[0].

Quick recap

• Load the file with json.load() or read text and parse with json.loads().
• Check if the top-level data is a dict or a list before accessing values.
• Use .get() and default values when keys might be missing.
• Catch FileNotFoundError for bad paths and JSONDecodeError for invalid JSON.
• Use the error’s line and column to locate formatting problems quickly.