TerraHarmonize 0.1.4

A powerful and efficient package designed for the SatSure Sage GIS team, enabling precise and seamless POC matching and D1-D2 matching across all states.

TerraHarmonize 🌍 🚀 Seamless & Accurate POC and D1-D2 Matching for All States

This package was built for SatSure SAGE 🛰️ to effortlessly match client data with internal datasets for proof-of-concept (POC) validation. Whether you're working with geospatial surveys, land records, or administrative data, TerraHarmonize ensures precision, efficiency, and scalability across all states.

✨ Key Features: ✅ Fast & accurate POC matching 🏹 ✅ Handles diverse data formats 📊 ✅ Designed for scalability & performance ⚡

Installation

pip install TerraHarmonize

Examples

For changing regional character to English.

from TerraHarmonize import TextFormatters,SurveyMatching

>>> string = '12/अ/1'
>>> print(TextFormatters.regional_to_english_village(string,'Hi'))
    '12/A/1'

For getting the index of the best match.

from TerraHarmonize import TextFormatters,SurveyMatching

>>> string = '13/A1'
>>> comparing_list = ['13/A1','14/A/1','12/A/1','13/అ','13-అ/1']
    #correct matching is [0,3,4] index i.e. '13/A1','13/అ','13-అ/1' 
>>> print(SurveyMatching(string,comparing_list).poc_matching_simple(split_pattern= r"\/|\-"))
    [0]
>>> print(SurveyMatching(string,comparing_list).poc_matching(include='both',state='AP'))
    [0, 3, 4]

Adding / inbetween a number and an alphabet.

from TerraHarmonize import TextFormatters,SurveyMatching

>>> data = '13/1AA/BB1/E'
>>> updated_data = TextFormatters.normalize_alpha_num_slash(data,'En')
>>> print(updated_data)
    '13/1/AA/BB/1/E'

>>> data = {
            "district": ["District A", "District B", "District C"],
            "tehsil": ["Tehsil X", "Tehsil Y", "Tehsil Z"],
            "village": ["Village 1", "Village 2", "Village 3"],
            "survey_number_client": ["13/1/अ", "23/2A", "789/1"],
            "survey_number_satsure": [["13/1", "13/1/A", "13/2/1"], ["456A", "23/2", "23/2/अ"], ["324/1", "121/2"]],
            "survey_id": [["ID_1", "ID_2", "ID_3"], ["ID_4", "ID_5", "ID_6"], ["ID_7", "ID_8"]]
            }

>>> df = pd.DataFrame(data)
>>> matching = SurveyMatching.poc_matching_dataframe(df,'survey_number_client',
                                          'survey_number_satsure','survey_id',
                                          include='both',
                                          state='MH').fillna('missing')

📖 More Examples & Usage https://github.com/CM-SS155/TerraHarmonize-Docs