2.4. Read JSON

File paths works also with URLs
File can be compressed with .gz, .bz2, .zip, .xz

2.4.1. Compressed

If the extension is .gz, .bz2, .zip, and .xz, the corresponding compression method is automatically selected

>>> df = pd.read_json('sample_file.zip', compression='zip')  
>>> df = pd.read_json('sample_file.gz', compression='infer')  

2.4.2. Assignments

# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author

# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -v myfile.py`

# %% About
# - Name: Pandas Read JSON
# - Difficulty: easy
# - Lines: 1
# - Minutes: 3

# %% English
# 1. Read data from `DATA` as `result: pd.DataFrame`
# 2. Run doctests - all must succeed

# %% Polish
# 1. Wczytaj dane z DATA jako `result: pd.DataFrame`
# 2. Uruchom doctesty - wszystkie muszą się powieść

# %% Tests
"""
>>> import sys; sys.tracebacklimit = 0
>>> assert sys.version_info >= (3, 9), \
'Python 3.9+ required'

>>> assert result is not Ellipsis, \
'Assign result to variable: `result`'
>>> assert type(result) is pd.DataFrame, \
'Variable `result` must be a `pd.DataFrame` type'

>>> result.loc[[0,10,20]]
    sepal_length  sepal_width  petal_length  petal_width     species
0            5.1          3.5           1.4          0.2      setosa
10           7.0          3.2           4.7          1.4  versicolor
20           6.3          3.3           6.0          2.5   virginica
"""

import pandas as pd


DATA = 'https://python3.info/_static/iris.json'


# Read DATA from JSON
# type: pd.DataFrame
result = ...

# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author

# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -v myfile.py`

# %% About
# - Name: Pandas Read JSON OpenAPI
# - Difficulty: medium
# - Lines: 3
# - Minutes: 5

# %% English
# 1. Import `requests` module
# 2. Define `resp` with result of `requests.get()` for `DATA`
# 3. Define `data` with conversion of `resp` from JSON to Python dict by calling `.json()` on `resp`
# 4. Define `result: pd.DataFrame` from value for key `paths` in `data` dict
# 5. Run doctests - all must succeed

# %% Polish
# 1. Zaimportuj moduł `requests`
# 2. Zdefiniuj `resp` z resultatem `requests.get()` dla `DATA`
# 3. Zdefiniuj `data` z przekształceniem `resp` z JSON do Python dict wywołując `.json()` na `resp`
# 4. Zdefiniuj `result: pd.DataFrame` dla wartości z klucza `paths` w słowniku `data`
# 5. Uruchom doctesty - wszystkie muszą się powieść

# %% Hints
# - `pd.DataFrame(data)`

# %% Tests
"""
>>> import sys; sys.tracebacklimit = 0
>>> assert sys.version_info >= (3, 9), \
'Python 3.9+ required'

>>> assert result is not Ellipsis, \
'Assign result to variable: `result`'
>>> assert type(result) is pd.DataFrame, \
'Variable `result` must be a `pd.DataFrame` type'

>>> list(result.index)
['put', 'post', 'get', 'delete']

>>> list(result.columns)  # doctest: +NORMALIZE_WHITESPACE
['/pet', '/pet/findByStatus', '/pet/findByTags', '/pet/{petId}', '/pet/{petId}/uploadImage',
 '/store/inventory', '/store/order', '/store/order/{orderId}',
 '/user', '/user/createWithList', '/user/login', '/user/logout', '/user/{username}']
"""

import pandas as pd
import requests

DATA = 'https://python3.info/_static/openapi.json'


# Define `resp` with result of `requests.get()` for `DATA`
# type: requests.models.Response
resp = ...

# Define `data` with conversion of `resp` from JSON to Python dict by calling `.json()` on `resp`
# type: dict
data = ...

# Define `result: pd.DataFrame` from value for key `paths` in `data` dict
# type: pd.DataFrame
result = ...