Skip to main content

No project description provided

Project description

Introduction

A package to read/write xlsx worksheet like dictionary, based on openpyxl.

Installation

  • from pip
pip install pyxlsx
  • download package and run setup.py
python setup.py install

Usage

  • Create a new xlsx file and write to it
from pyxlsx import new_xlsx

with new_xlsx(filename) as wb:
    ws = wb.create_sheet('sheet1')
    # some operations

# or
wb = new_xlsx()
ws = wb.creat_sheet('sheet1')  # create a new sheet with name 'sheet1'
# some operations
wb.save(filename)
  • Open an existing xlsx file
from pyxlsx import open_xlsx

with open_xlsx(filename) as wb:
    ws1 = wb.active  # get active sheet
    ws2 = wb['sheet2']
    # some operations

# or
wb = open_xlsx(filename)
ws = wb['sheet2']
# some operations
wb.save()
# to save as another file
wb.save(another_filename)
  • Append rows to a worksheet
ws = wb['sheet1']
ws.append(
    ["", "", "str('Unknown')", "float(4.5)", "int(500)"]
)
# keys can only be of type str
content1 = {
    'id': '001',
    'productName': 'pork',
    'productType': 'meat',
    'price': 2.5,
    'weight': 1000,
}
content2 = {
    'id': '002',
    'productName': 'beef',
    'productType': 'meat',
    'price': 4.5,
    'weight': 1000,
    'origin': 'Australia'
}
# header is auto-generated from keys of the dict the first time append_by_header is called.
ws.append_by_header(content1)  
# new header name will be append to header if append_header is True (default value)
ws.append_by_header(content2)  
# below is the result of writing operation
A B C D E F
1 str('Unknown') float(30) int(0)
2 id productName productType price weight origin
3 001 pork meat 2.5 1000
4 002 beef meat 4.5 1000 Australia
  • Read from / write to a worksheet by row Note: if there are duplicate header names, only the first would be used.
ws = wb['sheet1']
assert ws.header is None
ws.header_row = 2  # set the second row as worksheet header row
assert ws.header is not None

for row in ws.content_rows:  # starting from row just below header row
    print(row[1])  # row cell value can accessed by column number, if key is of type int
    print(row['productName'])  # row cell value can be accessed by header name, if key is of type of str
    print(row['price'])  
    if row['productName'] == 'pork':
        row[1] = '003'  # change pork id to '003'
        row['price'] = 3.5  # change pork price to 3.5
# output as below
# '001'
# 'pork'
# 2.5
# '002'
# 'beef'
# 4.5
  • Read from a worksheet by column
ws = wb['sheet1']
ws.header_row = 2
# get a full column
column_cells = ws['B']
for c in column_cells:
    print(c.data)  # 'pork', 'beef'

# get a content column (containing only cells below header) by header name, 
# if key is of type str
name_column = ws.get_content_column('productName')
for c in name_column:
    print(c.data)  # 'pork', 'beef'

# get a content column by column number,
# if key is of type int
name_column = ws.get_content_column(2)
for c in name_column:
    print(c.data)  # 'pork', 'beef'
  • Read cell directly from Worksheet, Header, ContentRow
ws = wb['sheet1']
ws.header_row = 2
# access a cell by coordinate (row, column)
cell = ws.cell(2, 2)
print(cell.data)  # 'productName'

# access a cell by header name if key is of type str
cell = ws.header.cell('productName')
print(cell.data)  # 'productName'
# access a cell by column number
cell = ws.header.cell(1)
print(cell.data)  # 'id'

for row in ws.content_rows:
    cell = row.cell(1)  # '001', '002'
    print(cell.data)
    cell = row.cell('productName')
    print(cell.data)  # 'pork', 'beef'
  • Read adjacent cells of a certain cell
cell = ws.cell(2, 2)
print(cell.top.data)  # "str('Unknown')"
print(cell.left.data)  # 'id'
print(cell.right.data)  # 'productType'
print(cell.bottom.data)  # 'pork'

for c in cell.vertical:
    print(c.data)  # 'productName', 'pork', 'beef'

for c in cell.horizontal:
    print(c.data)  # 'productName', 'productType', 'price', 'weigth', 'origin'

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

pyxlsx-1.1.3.tar.gz (13.4 kB view details)

Uploaded Source

Built Distribution

pyxlsx-1.1.3-py3-none-any.whl (16.9 kB view details)

Uploaded Python 3

File details

Details for the file pyxlsx-1.1.3.tar.gz.

File metadata

  • Download URL: pyxlsx-1.1.3.tar.gz
  • Upload date:
  • Size: 13.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/49.2.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for pyxlsx-1.1.3.tar.gz
Algorithm Hash digest
SHA256 2e8dfdabb92651896c64ccfd1900dc0edfa1f93ed830834a7d70ccf685f1d3db
MD5 59e6031f18ef7843b85ca1547c7c09fa
BLAKE2b-256 fa8dad6f4e0290c90827e7d4fa69f459b5cd4527ce72509bc2a29fa68259c426

See more details on using hashes here.

File details

Details for the file pyxlsx-1.1.3-py3-none-any.whl.

File metadata

  • Download URL: pyxlsx-1.1.3-py3-none-any.whl
  • Upload date:
  • Size: 16.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/49.2.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for pyxlsx-1.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 b9197184249c7246a7b90941eb42507b98a35746a6599e5404f22f90c576cc0c
MD5 db5391a65597fcc8bbe55d9950079d18
BLAKE2b-256 1565b71814ad490c2f3b63c641b9b452fb478b916f761feb9edf90610649190b

See more details on using hashes here.

Supported by

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