wbmon

Wildberries marketplace prices monitor with publishing into Google Sheets.
Sample of deployed and real-time running Google Sheets with results is below. Or see this spreadsheet itself.

Features
Built with
How to run
How to deploy 24/7
Contributing

Features

Scheduling of parsed intervals with power of cron scheduler: see in APScheduler's doc
Saving fields: timestamp, link, brand name, goods name, seller, id, customer price, seller price
Reading list of links from Google Sheet or from file
Publishing parsed results to Google Sheet and to file
Detailed logging: sample
Up-to-date parsing conditions 👍

Built with

Online-services

Wildberries - Online-marketplace, one of three leading in CIS, since 2004**|** No API used
Google Sheets - Spreadsheet application offered by Google, since 2006 | proprietary
Google Cloud APIs and services - you'll need create project in it to connect pygsheets and Google Sheets. Since 2018 | proprietary

Software

Python - Language to work quickly and integrate systems more effectively, since 1991 | GPL compatible
APScheduler - Advanced Python scheduler coming with python-telegram-bot, since 2009 | MIT
selenium python script to get price from WB html page with, since 2008 | Apache 2
pygsheets - library to access google spreadsheets through the Google Sheets API v4, since 2016 | MIT
python-dotenv - Read key-value pairs from a .env file and set them as envir-t variables, since 2014 | BSD

How to run

Before running app these bare steps required:

Create project in Google Cloud Console to authorize pygsheets. Google account is required
Install dependencies
Finish authentification flow by following URL, given Google and pasting answer code
Prepare list of your links into one of two sources: Google Sheet or text file

1. Create project in Google Cloud Console

In order to authorize pygsheets and have ability to publish parsed results to Google Sheets, please follow pygsheet instruction, following method OAuth Credentials
Doing that, on stage 7 choose Desktop app. Keep Publishing status to Testing
Download credentials and put it in the app folder with name client_secret.json. The name controlled by OAUTH_CREDENTIALS_FILE setting

2. Installing dependencies

Create project folder and clone the project:

$ cd /projects/project-folder/
$ git clone https://github.com/baidakovil/wbmon .

(Optional, recommended) Create dedicated virtual environment to use the bot and
activate it. I use virtualenv, some venv. Path and name are to your discretion.
```
$ cd /virtual-environments-folder/
$ virtualenv env_name
$ source env_name/bin/activate
```
With virtual env activated, cd into project folder and install dependencies:
```
$ cd /project-folder/
$ python3 -m pip install -r requirements.txt
```

3. Prepare links to parse

If you want to store links in Google Sheets, create spreadsheet with name links in Google Account that you will authorize in next step. Then, paste links in column A, starting from cell A1 down to A2 and below. Example of links file
Simplest way: create file links.txt in project folder, where each line will consist URL started with https:// www.wildberries.... When program will not find links spreadsheet, it will read this file.

Notice: links and links.txt are defined by LINKS_SPREADSHEET_NAME and LINKS_FILE in config.py
Notice: you can use different Google accounts to create project in 1 (User1) and to store spreadsheets (User2). How to: add user User2 in the section Test users at Google Cloud Console, and choose User2 in the next, 4 step.

4. Finish authorization

With virtual environment activated, run the program:
```
$ cd /project-folder/
$ python main.py
```

Look into console: you will be prompted with message

Please go to this URL and finish the authentication flow: https://accounts.google.com/o/oauth2/auth?response_type=code&client_id=...

Open link in browser, authorize your Google account, copy code and paste it to console. You'll see sheets.googleapis.com-python.json file in project folder. This step should be passed once for given client_secret.json file.

Notice: with Publishing status set to Testing, token will expire after 7 days. Unfortunately, I could not manage authorization after setting Publishing status to Production, though this documented to be OK. Hope you'll be more lucky, if you need more than 7 days of continuous work.

How to deploy 24/7

There is nothing special about the deployment of this application compared to other python applications. I do it with systemd, in the way as described in manual deployment section of my favourite Green Grass Bot project. For this type of deployment I have attach sample file scripts/wbmon.service-example and deployment.yml workflow in .github folder. It works well.

What matters when deploying

Look at config

Many things are defined by settings in the config.py file. It is well-documented, so read it all. With .env file you can control two modes: test and working. For test mode be enabled, .env file should consist exactly TEST='false' string. Notice, there are 3 sections in config.py:

COMMON SETTINGS — settings with values, similar for test and working modes
TEST CONFIG — setting values for test mode
WORKING CONFIG — setting values for working mode

Ask questions

If you stuck with things, please feel free to contact me

Contributing

Please feel free to open pull requests. If you're planning on implementing something big (i.e. not fixing a typo, a small bug fix, minor refactor, etc) then please open an issue first.

baidakovil/wbmon