sfcparse 0.8.1

Simple File Configuration Parse. Easily import/export data!

sfcparse Module for Python

sfcparse = Simple File Configuration Parse

Current version 0.8.1

See "Updates" section on bottom for the latest version information

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Introduction

This module allows you to import and create custom python style save/config files for your program or script on a plain text file with any file extension. It can be used to easily export any data to a file as well. Also contains a feature for easily formatting data types for clean multiline output when exporting data to files.

Goal for the Project:

To provide an easy alternative to using .ini files in an attempt to make importing python data and saving any data to files for your projects simple. This also gives you the universal freedom to use any file extension or any made up file type you want.

Importing (Python only):

Imports stored variable names and their assigned values from any text file.

Returns a class with attributes from the file keeping python's natural recognition of data types, including comment lines being ignored.

Accepted Imported Data Types: str, int, float, bool, list, dict, tuple, set, nonetype, bytes

Exporting/Appending:

It simply sends string data to a file. It may be used for any string data file output.

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Tutorial Videos (New):

New tutorial training series on YouTube now available!

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Tutorial: Install & Usage

pip install sfcparse

Usage: Importing

Imports Pythonic Data Types from your Text File

Example test file Python data inside a file called settings.config.

# Comment for Single Line Data
saved_str = 'John Doe'
saved_int = 1024
saved_float = 128.75
saved_bool = False
saved_list = [1, 2, 3]
saved_dict = {'key1': 1, 'key2': 2}
saved_tuple = (1,2,3)
saved_set = { 1, 2, 3 }


# Comment for Multiline Data Sets
saved_data_multiline_dict = {
    'key1' : 'value 1',
    'key2' : 'value 2',
    'key3' : 'value 3'
}

saved_data_multiline_tuple = (
    1,
    2,
    3
)

Importing the above file into your python project and accessing the data

import sfcparse

settings_file = sfcparse.importfile('settings.config')

# Access any values imported
settings_file.saved_str
settings_file.saved_list
settings_file.saved_data_multiline_dict['key1']
...

That's it!

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Usage: Exporting - Single Line Values

Writes/Overwrites a New File

Exporting data to example file settings.config.

Note these are just examples to build your data to export.

import sfcparse

export_file = sfcparse.exportfile

# Single Line Values
string_to_save = 'John Doe'
number_to_save = 64
tuple_to_save = (1,2,3)


# Final Data to Export
data_to_save = f'''
# Comment Line
string_to_save = '{string_to_save}'
number_to_save = {number_to_save}
tuple_to_save = {tuple_to_save}
'''

export_file('settings.config', data_to_save)

This will be the expected output stored to the file

# Comment Line
string_to_save = 'John Doe'
number_to_save = 64
tuple_to_save = (1,2,3)

That's it!

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Usage: Exporting - Multiline Values

Writes/Overwrites a New File

Exporting data to example file settings.config.

Note these are just examples to build your data to export.

import sfcparse

export_file = sfcparse.exportfile

string_to_save = 'John Doe'
number_to_save = 64

# Multiline Values
dict_to_save = """{

    'key1' : 'value1',
    'key2' : 'value2'    
}
"""

list_to_save = """[

    1,
    2,
    3
]
"""

# Dict with Vars - NOTE: Must escape Curly Braces if using variables via f-string
dict_to_save_vars = f"""{{

    'key1' : '{string_to_save}',
    'key2' : {number_to_save}
}}
"""


# Final Data to Export
data_to_save = f'''
# Comment Line
dict_to_save = {dict_to_save}
list_to_save = {list_to_save}
dict_to_save_vars = {dict_to_save_vars}
'''

export_file('settings.config', data_to_save)

This will be the expected output stored to the file

# Comment Line
dict_to_save = {

    'key1' : 'value1',
    'key2' : 'value2'    
}

list_to_save = [  

    1,
    2,
    3
]

dict_to_save_vars = {

    'key1' : 'John Doe',
    'key2' : 64
}

Clean Format: You can also use "cleanformat" to easily organize your multiline output

data_to_save_clean = {'key1':'value1', 'key2':'value2', 'key3':'value3'}

clean_output = sfcparse.cleanformat(data_to_save_clean)

export_file('settings.config', f"data_to_save_clean = {clean_output}")

This will be the clean expected output stored to the file

data_to_save_clean = {
    'key1' : 'value1',
    'key2' : 'value2',
    'key3' : 'value3'
}

That's it!

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Usage: Appending:

Writes New Data to a File if it Exists

It is the same syntax as exporting, but here is an example using the same exported output from "Exporting - Single Line" settings.config.

Note these are just examples to build your data to append.

Also Single line appending may be more tedious than multiline, so it is recommended to build your data with multiple lines as shown!

import sfcparse

append_file = sfcparse.appendfile

data_to_append = ['item1', 'item2', 'item3']
data_to_append2 = [1,2,3]

# Single Line Appending
append_file('settings.config', f"data_to_append = {data_to_append}")

# Multiline Appending
final_save_data = f"""
data_to_append = {data_to_append}
data_to_append2 = {data_to_append2}
"""

append_file('settings.config', f"data_to_append = {final_save_data}")

This will be the expected output appended to the file if using the multiline append method

# Comment Line
string_to_save = 'John Doe'
number_to_save = 64
tuple_to_save = (1,2,3)
data_to_append = ['item1', 'item2', 'item3']
data_to_append2 = [1,2,3]

That's it!

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Module Performance

Importing

Imported a file 1000 times with 100 lines of data in 0.6s.

Lab Test Conducted:

from sfcparse import importfile
import time

file_to_import = 'data.test'
num_of_tests = 1000

# Performance Test
start_time = time.time()
for i in range(num_of_tests):
    importfile(file_to_import)
end_time = time.time()

elapsed_time = (end_time - start_time)

print(elapsed_time)

System: Tested on a 4th-Gen Intel Core i7-4790 at 3.6GHz

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Updates - sfcparse v0.8.0

API change:

• NEW: v0.8.0 - Compatible only on Python version 3.6+
• PREVIOUS: v0.7.7 - Compatible only on Python version 3.0+

Performance changes:

• cleanformat:
  • code improvement has a 23% performance gain
• importfile:
  • code improvement has a 10% performance gain

Feature Additions:

• cleanformat:
  • Has a new indentation level feature to add custom indent levels for exporting to a file NOTE: formatting performance will gain 5% boost if you set indent level to 0 (Default 1). Performance will decrease with more levels of indentation added.
  • Now supports nested data sets, but will not apply indentation to sub-level data sets
  • Now does not parse commas in values or keys and retains its original representation
• importfile:
  • Now supports importing nested data sets even when subsets are on multiple lines in the file
  • Comments can now be added after a value

General:

• Updated comments in module/functions

Known Limitations

Importing

• Does not support importing unpacked variables and values
• Does not support importing variables as values

Future Upgrades

Importing

• Add support for importing variables as values
• Add support for unpacked variables and values