ezspreadsheet 0.2.2

A simple API to store/load python objects to/from spreadsheets

EZ Spreadsheet

A simple API to store/load python objects to/from spreadsheets

Table of contents

• Goals
• Features
  • Object Serialization
  • Object Deserialization
  • Flexibility
  • Readability
• Installation
• Quick-start
• Additional Documentation

Goals

This project has a few goals:

1. Make OO projects easier to serialize
2. Make interfacing with spreadsheet files simple
3. Use as minimal syntax as possible to complete the above

Features

Below are a some of the features in ezspreadsheet.

Object serialization

The api lets you directly serialize object instances into spreadsheets:

from ezspreadsheet import Spreadsheet

class Animal():
    def __init__(self, name:str, conservation_status:str):
        self.name = name
        self.conservation_status = conservation_status

leopard_gecko = Animal('Leopard Gecko', 'Least Concern')

with Spreadsheet('animals.xlsx', Animal) as output_sheet: # to use .csv just change file extension
    output_sheet.store(leopard_gecko)

Object deserialization

The api lets you deserialize objects from spreadsheets back into instances (Note if you don't provide a class to build back into a dynamic namedtuple is generated):

from ezspreadsheet import Spreadsheet

class Animal():
    def __init__(self, name:str, conservation_status:str):
        self.name = name
        self.conservation_status = conservation_status

leopard_gecko = Animal('Leopard Gecko', 'Least Concern')

philippine_eagle = Animal('Philippine Eagle', 'Threatened')

# Store Data
with Spreadsheet('animals.xlsx', Animal) as output_sheet: # to use .csv just change file extension
    output_sheet.store(leopard_gecko, philippine_eagle)

# Retrieve data using the same class construtor
with Spreadsheet('animals.xlsx', Animal) as input_sheet: # to use .csv just change file extension
    animals, instances = input_sheet.load("animals")

print(instances) # prints: [<__main__.Animal object at 0x0000011BAB89A3A0>, <__main__.Animal object at 0x0000011BAD4289A0>]
# Note the class constructor is the same
print(Animal == animals) # Prints: True

# Retrieve namedtuple classes when no class constructor is available
with Spreadsheet('animals.xlsx') as input_sheet: # to use .csv just change file extension
    animals, instances = input_sheet.load("animals")

print(animals) # Prints: <class 'ezspreadsheet.animals'>
print(instances) # Prints: [animals(name='Leopard Gecko', conservation_status='Least Concern'), animals(name='Philippine Eagle', conservation_status='Threatened')]

# Note the class constructor is now different
print(Animal == animals) # Prints: False

Flexibility

There is syntactic flexibility to allow an arbitrary number of instance arguments, or simple Iterables (like lists and tuples):

from ezspreadsheet import Spreadsheet

class Animal():
    def __init__(self, name:str, conservation_status:str):
        self.name = name
        self.conservation_status = conservation_status

leopard_gecko = Animal('Leopard Gecko', 'Least Concern')

philippine_eagle = Animal('Philippine Eagle', 'Threatened')

# Direct instances
with Spreadsheet('animals.xlsx', Animal) as output_sheet: # to use .csv just change file extension
    output_sheet.store(leopard_gecko, philippine_eagle)

# Iterables
instances = []
instances.append(leopard_gecko)
instances.append(philippine_eagle)

with Spreadsheet('animals.xlsx', Animal) as output_sheet: # to use .csv just change file extension
    output_sheet.store(instances)

Readability

You can specify a readable variable in the Spreadsheet.store() method to allow Iterable instance attributes to be written in a readable format (note they will be deserialized as strings):

from ezspreadsheet import Spreadsheet
from dataclasses import dataclass

@dataclass
class User():
    Name:str
    Age:int
    Weight:int
    Family: list # Note that Iterables will be flattened to a string with newline seperators

jd = User("John Doe", 20, 75, ["Abby", "Mike", "Janice"])

# Store Data as readable
with Spreadsheet('users.xlsx', User) as output_sheet: # to use .csv just change file extension
    output_sheet.store(jd, readable=True)

# Retrieve namedtuple classes when no class constructor is available
with Spreadsheet('users.xlsx') as input_sheet: # to use .csv just change file extension
    users, instances = input_sheet.load("users")

print(instances[0].Family) # Prints: - Abby\n- Mike\n- Janice

# Store Data as not readable
with Spreadsheet('users.xlsx', User) as output_sheet: # to use .csv just change file extension
    output_sheet.store(jd)

# Retrieve namedtuple classes when no class constructor is available
with Spreadsheet('users.xlsx') as input_sheet: # to use .csv just change file extension
    users, instances = input_sheet.load("users")

print(instances[0].Family) # Prints: ['Abby', 'Mike', 'Janice']

Installation

From PyPi

1. Run pip install ezspreadsheet or sudo pip3 install ezspreadsheet

From source

1. Clone this repo: (https://github.com/Descent098/ezspreadsheet)
2. Run pip install . or sudo pip3 install .in the root directory

Quick-start

Note that syntax does not change between .xlsx and .csv files, you can replace .xlsx with .csv and below examples will work

Store some animal instances in a spreadsheet called 'animals.xlsx', then read back the data

from ezspreadsheet import Spreadsheet

class Animal():
    def __init__(self, name:str, conservation_status:str):
        self.name = name
        self.conservation_status = conservation_status

leopard_gecko = Animal('Leopard Gecko', 'Least Concern')

philippine_eagle = Animal('Philippine Eagle', 'Threatened')

# Store
with Spreadsheet('animals.xlsx', Animal) as output_sheet: # to use .csv just change file extension
    output_sheet.store(leopard_gecko, philippine_eagle)

# Load
with Spreadsheet('animals.xlsx', Animal) as input_sheet: # to use .csv just change file extension
    _, instances = output_sheet.load("animals")

print(instances) # prints: [<__main__.Animal object at 0x0000011BAB89A3A0>, <__main__.Animal object at 0x0000011BAD4289A0>]

Store a list of instances into a spreadsheet called 'users.xlsx'

from ezspreadsheet import Spreadsheet

import random
import string
from dataclasses import dataclass

@dataclass
class User():
    Name:str
    Age:int
    Weight:int
    Family: list # Note that Iterables will be flattened to a string with newline seperators

instances = []
ranstring = lambda: ''.join(random.choices(string.ascii_uppercase, k=10)) # Generates a random 10 character string
for i in range(1000):
    instances.append(User(ranstring(), random.randint(12,100), random.randint(75,400), [ranstring(), ranstring(), ranstring()]))

with Spreadsheet('users.xlsx', User) as output_sheet: # to use .csv just change file extension
    output_sheet.store(instances)

Differences between xlsx and csv

Please note there are some differnces between .xlsx files and .csv files:

1. .xlsx files are significantly faster because they isntantiate cell objects and are C-level optimized instead of just doing plain text generation. If you need to save thousands of objects, I would recommend using .xlsx files.
2. When passing readable=True to Spreadsheet.store() the formatting for .xlsx files allows for newlines, so iterables are broken by newlines \n. CSV readers use newlines to read csv files (even when told not to), so they are broken by tabs \t in .csv files instead.

Additional Documentation

Additional documentation can be found at https://kieranwood.ca/ezspreadsheet

For details on how contributing to the project, please see CONTRIBUTING.md, for details on upcoming changes see our roadmap.

For most recent changes see CHANGELOG.md.

Changelog

0.2.2; November 24th 2020

• Updated links to include docs and source code urls

0.2.1; November 24th 2020

• Updated description to match name change

0.2.0; November 24th 2020

• Added deserialization methods for xlsx files
• Added serialization and deserialization methods for CSV files
• Changed name from ezexcel to ezspreadsheet
• Split Xlxs processing to internal class and converted Spreadsheet class to dispatching class

0.1.1; September 25th 2020

Fixed logo loading on PyPi

Bug fixes

• Fixed loading issue with logo on PyPi

0.1.0; September 25th

Initial release of EZ Excel

Features

• Ability to provide a class to instantiate a Spreadsheet
• Ability to pass instances in an iterable of class to Spreadsheet to be serialized
• Automatically flatten Iterable attributes within instances to endline delimited strings
• Added testing suite for all existing functionality

Documentation improvements

• Wrote all existing documentation :)