Skip to main content

JSON to excel convertor

Project description

JSON to excel converter

A package that converts json to CSV, excel or other table formats

Sample output

Simple json

[
  {
    "col1": "val1",
    "col2": "val2" 
  }
]

the generated CSV/excel is:

col1          col2
==================
val1          val2

Nested json

[
  {
    "col1": "val1",
    "col2": {
      "col21": "val21",
      "col22": "val22"
    }
  }
]

the generated CSV/excel is (in excel, col2 spans two cells horizontally):

col1          col2
              col21         col22
=================================
val1          val21         val22

json with array property

[
  {
    "col1": "val1",
    "col2": [
      {
        "col21": "val21"
      },
      {
        "col21": "val22"
      }
    ]
  }
]

the generated CSV/excel is (in excel, col2 spans two cells horizontally):

col1          col2         
              col21         col21
=================================
val1          val21         val22

Installation

pip install json-excel-converter[extra]

where extra is:

  • xlsxwriter to use the xlsxwriter

Usage

Simple usage

from json_excel_converter import Converter 
from json_excel_converter.xlsx import Writer

data = [
    {'a': [1], 'b': 'hello'},
    {'a': [1, 2, 3], 'b': 'world'}
]

conv = Converter()
conv.convert(data, Writer(file='/tmp/test.xlsx'))

Streaming usage with restarts

from json_excel_converter import Converter, LinearizationError 
from json_excel_converter.csv import Writer

conv = Converter()
writer = Writer(file='/tmp/test.csv')
while True:
    try:
        data = get_streaming_data()     # custom function to get iterator of data
        conv.convert_streaming(data, writer)
        break
    except LinearizationError:
        pass

Arrays

When the first row is processed, the library guesses the columns layout. In case of arrays, a column (or more columns if the array contains json objects) is created for each of the items in the array, as shown in the example above.

On subsequent rows the array might contain more items. The library reacts by adjusting the number of columns in the layout and raising LinearizationError as previous rows might be already output.

Converter.convert_streaming just raises this exception - it is the responsibility of caller to take the right action.

Converter.convert captures this error and restarts the processing. In case of CSV this means truncating the output file to 0 bytes and processing the data again. XLSX writer caches all the data before writing them to excel so the restart just means discarding the cache.

If you know the size of the array in advance, you should pass it in options. Then no processing restarts are required and LinearizationError is not raised.

from json_excel_converter import Converter, Options
from json_excel_converter.xlsx import Writer

data = [
   {'a': [1]},
   {'a': [1, 2, 3]}
]
options = Options()
options['a'].cardinality = 3

conv = Converter(options=options)
writer = Writer(file='/tmp/test.xlsx')
conv.convert(data, writer)
# or
conv.convert_streaming(data, writer)    # no exception occurs here

XLSX Formatting

Cell format

XLSX writer enables you to format the header and data by passing an array of header_formatters or data_formatters. Take these from json_excel_converter.xlsx.formats package or create your own.

from json_excel_converter import Converter

from json_excel_converter.xlsx import Writer
from json_excel_converter.xlsx.formats import LastUnderlined, Bold, \
    Centered, Format

data = [
    {'a': 'Hello'},
    {'a': 'World'}
]

w = Writer('/tmp/test3.xlsx',
           header_formats=(
               Centered, Bold, LastUnderlined,
               Format({
                   'font_color': 'red'
               })),
           data_formats=(
               Format({
                   'font_color': 'green'
               }),)
           )

conv = Converter()
conv.convert(data, w)

See https://xlsxwriter.readthedocs.io/format.html for details on formats in xlsxwriter

Column widths

Pass the required column widths to writer:

w = Writer('/tmp/test3.xlsx', column_widths={
    'a': 20
})

Width of nested data can be specified as well:

data = [
    {'a': {'b': 1, 'c': 2}}
]

w = Writer('/tmp/test3.xlsx', column_widths={
    'a.b': 20,
    'a.c': 30,
})

To set the default column width, pass it as DEFAULT_COLUMN_WIDTH property:

w = Writer('/tmp/test3.xlsx', column_widths={
    DEFAULT_COLUMN_WIDTH: 20
})

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

json_excel_converter-1.0.1.tar.gz (15.7 kB view details)

Uploaded Source

Built Distribution

json_excel_converter-1.0.1-py3-none-any.whl (15.6 kB view details)

Uploaded Python 3

File details

Details for the file json_excel_converter-1.0.1.tar.gz.

File metadata

  • Download URL: json_excel_converter-1.0.1.tar.gz
  • Upload date:
  • Size: 15.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.0.5 CPython/3.7.1 Linux/4.15.0-1028-gcp

File hashes

Hashes for json_excel_converter-1.0.1.tar.gz
Algorithm Hash digest
SHA256 31a1fcc3bb5902f582e2657b0e7b8fd89d50c8ba6fe078527e2412360cb98f01
MD5 094fbfa5b30e6dcdd5d76d3b1068801f
BLAKE2b-256 9f6bf306a73b9752a4782131765553eb7d450c485cdbd81feaaec07cf81640e8

See more details on using hashes here.

File details

Details for the file json_excel_converter-1.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for json_excel_converter-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 55129fbd456175184bbff29ee5a70900f27e31e068827a25e0139c6dccd0c41e
MD5 9acec89911902ff1503cfb087b16c875
BLAKE2b-256 9d724b3dea40e83184a570ea0c4f0ecd6b030dd1b6806427d0461896e4e670fd

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page