Metadata-Version: 2.4
Name: gpycraft
Version: 1.0.3
Summary: A Python package for manipulating google sheets directly on any coding platform and perform CRUD process easily. Sheets can be stored and retrieved in firebase storage
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: firebase-admin
Requires-Dist: gspread
Requires-Dist: oauth2client
Requires-Dist: pandas
Requires-Dist: PyYAML
Requires-Dist: tqdm
Requires-Dist: xlsxwriter
Requires-Dist: openpyxl
Dynamic: description
Dynamic: description-content-type
Dynamic: license-file
Dynamic: requires-dist
Dynamic: summary

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<h1 align="center" style="color: red; font-family: 'MedievalSharp'; font-size: 22px;">GPYCRAFT</h1>




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This python module makes it possible to manipulate google sheets or any sheets stored in firebase storage. It allows for manipulation and display sheet data in a convenient way for analysis. It supports creation of API to google sheet

Before Starting it is neccessary to have credentials.json file found in Google cloud platform and make sure the google sheet link is shareable




# Read data from Google Sheets
data = db.read_sheet(key='column_name', number_of_rows=5, start_index=1, end_index=10)
key: The column name to filter data by.
number_of_rows: The number of rows to retrieve.
start_index and end_index: The range of rows to retrieve.
Converting Data to Pandas DataFrame
in_pd Method
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# Convert data to Pandas DataFrame
df = db.in_pd()
Converting Data to JSON
in_json Method
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# Convert data to JSON
json_data = db.in_json(target_key='column_name', num_rows=5, start_index=1, end_index=10)
target_key: The specific key to include in the JSON output.
num_rows: The number of rows to include in the JSON output.
start_index and end_index: The range of rows to include in the JSON output.
FireStoreUpload Class
Initialization
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from googlepycraft.fireStore.firestoreupload import FireStoreUpload
Initialize the FireStoreUpload class with the path to your Firebase service account credentials JSON file and the name of your Firebase Storage bucket.

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uploader = FireStoreUpload(credentials_path='path/to/firebase_credentials.json', storage_bucket='your_storage_bucket_name')
Uploading Files to Firebase Storage
upload_file Method
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# Upload a file to Firebase Storage
uploader.upload_file(local_file_path='path/to/local/file.txt')
local_file_path: The local path of the file to be uploaded.
Example Usage
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# Example usage of gsheetsdb
db = gsheetsdb(credentials_path='path/to/credentials.json', sheet_url='https://docs.google.com/spreadsheets/d/your_spreadsheet_id/edit')
data = db.read_sheet(key='column_name', number_of_rows=5, start_index=1, end_index=10)
df = db.in_pd()
json_data = db.in_json(target_key='column_name', num_rows=5, start_index=1, end_index=10)

# Example usage of FireStoreUpload
uploader = FireStoreUpload(credentials_path='path/to/firebase_credentials.json', storage_bucket='your_storage_bucket_name')
uploader.upload_file(local_file_path='path/to/local/file.txt')

Note: Make sure to replace placeholders such as path/to/credentials.json, your_spreadsheet_id, your_storage_bucket_name, etc., with your actual file paths and identifiers.
