first release
This commit is contained in:
commit
542a7820f5
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DB_HOST=DB_HOST
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USERS=USERS
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PASSW=PASSW
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DATABASE=DATABASE
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SPREADSHEET_ID=SPREADSHEET_ID
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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.pybuilder/
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/#use-with-ide
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.pdm.toml
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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.idea/
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creds_service_acc.json
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import os
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import gspread
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from oauth2client.service_account import ServiceAccountCredentials
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from dotenv import load_dotenv
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load_dotenv()
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# SET UP GOOGLE SPREADSHEET
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SPREADSHEET_ID = os.getenv('SPREADSHEET_ID')
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SCOPES = [
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'https://www.googleapis.com/auth/spreadsheets',
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'https://www.googleapis.com/auth/drive'
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]
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CREDENTIALS = ServiceAccountCredentials.from_json_keyfile_name('creds_service_acc.json', SCOPES)
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client = gspread.authorize(CREDENTIALS)
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# Open the spreadsheet using the correct spreadsheet key
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spreadsheet = client.open_by_key(SPREADSHEET_ID)
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import os
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from dotenv import load_dotenv
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from peewee import *
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load_dotenv()
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DATABASE = os.getenv("DATABASE")
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DB_HOST = os.getenv("DB_HOST")
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USERS = os.getenv("USERS")
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PASSW = os.getenv("PASSW")
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db = MySQLDatabase(
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database=DATABASE, user=USERS, password=PASSW, host=DB_HOST, port=3306
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)
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class Price(Model):
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sku = CharField()
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Название_позиции_укр = CharField(null=True)
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РРЦ = IntegerField(null=True)
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Количество = IntegerField(null=True)
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Цена_Prom_розница = IntegerField(null=True)
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Скидка_в_процент_Prom_розница = IntegerField(null=True)
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Время_скидки_Prom_розница = CharField(null=True)
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Минимальный_объем_заказа = IntegerField(null=True)
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Цена_Prom_Оптовыей_сайт = IntegerField(null=True)
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Минимальный_заказ_опт = IntegerField(null=True)
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Скидка_в_процент_Prom_опт = IntegerField(null=True)
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Время_скидки_Prom_опт = CharField(null=True)
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Уникальный_идентификатор_prom_розн = IntegerField(null=True)
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Цена_розн_розетка_r = IntegerField(null=True)
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Цена_старая_розетка = IntegerField(null=True)
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Цена_розн_эпицентр_e = IntegerField(null=True)
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Цена_розн_алло_a = IntegerField(null=True)
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Цена_опенкарт_дроп_os = IntegerField(null=True)
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Цена_опенкарт_опт_os = IntegerField(null=True)
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Цена_опенкарт_крупнопт_os = IntegerField(null=True)
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Уникальный_идентификатор_prom_опт = IntegerField(null=True)
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ID_KCRM = IntegerField(null=True)
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Уникальный_идентификатор_Rozetka = IntegerField(null=True)
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Уникальный_идентификатор_OS = IntegerField(null=True)
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Штрих_code = IntegerField(null=True)
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Дата_скидки_OC = DateField(null=True)
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Скидка_дроп_процент = IntegerField(null=True)
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Скидка_опт_процент = IntegerField(null=True)
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Скидка_Крупный_опт_процент = IntegerField(null=True)
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Цена_опенкарт_дроп_pro_os = IntegerField(null=True)
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Цена_опенкарт_крупнопт_ТОВ_os = IntegerField(null=True)
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Скидка_дропPRO_процент = IntegerField(null=True)
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class Meta:
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database = db
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# Connect to the database and create tables
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db.create_tables([Price])
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from dev_xlsx import spreadsheet
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from models import Price
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def fetch_data_from_database():
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# Query the database for the data
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data = {}
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for price in Price.select():
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data[price.sku] = price.Количество # Assuming 'sku' is the key
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return data
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def update_spreadsheet_with_new_values(new_values):
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# Open the first worksheet
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worksheet = spreadsheet.get_worksheet(0)
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# Get all values from the worksheet
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values = worksheet.get_all_values()
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headers = values[0]
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# Find the index of 'Количество' column
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quantity_index = headers.index('Количество')
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# Update values in the spreadsheet
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for row in values[1:]: # Skip the header row
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sku = row[0] # Assuming SKU is the first column
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if sku in new_values and row[quantity_index] != str(new_values[sku]): # Compare as strings
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worksheet.update_cell(values.index(row) + 1, quantity_index + 1, str(new_values[sku])) # Adjust to 1-based index
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if __name__ == "__main__":
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# Fetch data from the database
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data_from_database = fetch_data_from_database()
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# Compare values and update the spreadsheet
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update_spreadsheet_with_new_values(data_from_database)
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import pandas as pd
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from dev_xlsx import spreadsheet
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from models import Price, db
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def spreadsheet_transform():
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try:
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# Select the first worksheet
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worksheet = spreadsheet.get_worksheet(0)
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# Get all values from the worksheet
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values = worksheet.get_all_values()
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# Convert values to DataFrame
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df = pd.DataFrame(values[1:], columns=values[0])
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except Exception as e:
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print(f"Error retrieving data from Google Spreadsheet: {e}")
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return
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column_mapping = {
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"": "sku",
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"Название_позиции_укр": "Название_позиции_укр",
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"РРЦ": "РРЦ",
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"Количество": "Количество",
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"Цена Prom розница": "Цена_Prom_розница",
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"Скидка в % Prom розница": "Скидка_в_процент_Prom_розница",
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"Время скидки Prom розница": "Время_скидки_Prom_розница",
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"Минимальный_объем_заказа": "Минимальный_объем_заказа",
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"Цена Prom Оптовыей сайт": "Цена_Prom_Оптовыей_сайт",
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"Минимальный_заказ_опт": "Минимальный_заказ_опт",
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"Скидка в % Prom опт": "Скидка_в_процент_Prom_опт",
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"Время скидки Prom опт": "Время_скидки_Prom_опт",
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"Уникальный_идентификатор prom розн": "Уникальный_идентификатор_prom_розн",
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"Цена_розн_розетка_r": "Цена_розн_розетка_r",
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"Цена старая розетка": "Цена_старая_розетка",
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"Цена_розн_эпицентр_e": "Цена_розн_эпицентр_e",
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"Цена_розн_алло_a": "Цена_розн_алло_a",
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"Цена_опенкарт_дроп_os": "Цена_опенкарт_дроп_os",
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"Цена_опенкарт_опт_os": "Цена_опенкарт_опт_os",
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"Цена_опенкарт_крупнопт_os": "Цена_опенкарт_крупнопт_os",
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"Уникальный_идентификатор prom опт": "Уникальный_идентификатор_prom_опт",
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"ID KCRM": "ID_KCRM",
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"Уникальный_идентификатор Rozetka": "Уникальный_идентификатор_Rozetka",
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"Уникальный_идентификатор OS": "Уникальный_идентификатор_OS",
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"Штрих code": "Штрих_code",
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"Дата скидки OC": "Дата_скидки_OC",
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"Скидка дроп %": "Скидка_дроп_процент",
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"Скидка опт %": "Скидка_опт_процент",
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"Скидка Крупный опт % ": "Скидка_Крупный_опт_процент",
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"Цена_опенкарт_дроп_pro_os": "Цена_опенкарт_дроп_pro_os",
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"Цена_опенкарт_крупнопт-ТОВ_os": "Цена_опенкарт_крупнопт_ТОВ_os",
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"Скидка дропPRO %": "Скидка_дропPRO_процент"
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}
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# Iterate over rows and save to the database
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try:
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# Iterate over rows and save to the database
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for index, row in df.iterrows():
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# Create a dictionary to store mapped data
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mapped_data = {}
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for column_name, field_name in column_mapping.items():
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# Map DataFrame column to model field
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mapped_data[field_name] = row[column_name]
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try:
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# Create a Price object using mapped data
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Price.create(**mapped_data)
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except Exception as e:
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print(f"Error inserting row {index}: {e}")
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print("Data inserted successfully.")
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except Exception as e:
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print(f"Error inserting data into the database: {e}")
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finally:
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# Close the database connection
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db.close()
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# run script when you want to update all db
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if __name__ == "__main__":
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spreadsheet_transform()
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Reference in New Issue