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sneakers
Here are 46 public repositories matching this topic...
Browser automation tool for buying adidas shoes
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May 16, 2020 - JavaScript
Monitors off---white.com for new product releases and restocks
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Jan 26, 2019 - Python
Support proxies, keywords, multiple webhook url, avoid ban and more - current version: 1.5
monitor
monitoring
discord
shopify
streetwear
sneakers
monitoring-tool
sneakerbot
sneaker
footwear
restock
snkrs
sneakermonitor
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Jun 10, 2020 - JavaScript
App that scrapes the Footlocker website to construct URLs for upcoming sneaker releases and adds the shoe to your cart if it is available. Uses Python and Selenium Webdriver. *Chrome and Chromedriver must be installed and Chromedriver must be on main path
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Mar 20, 2017 - Python
An tool for Solebox, featuring account creation and checking orders.
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Apr 22, 2020 - Python
A twitter monitor that monitors users' tweets through Twitter streaming API.
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May 2, 2020 - Python
Using Selenium, Neha scraped data about 35 top selling sneakers of Nike and Adidas from stockx.com. She used this data to draw insights about sneaker resales.
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Feb 20, 2018 - Python
A background job scheduler for any queue backend
ruby
rails
sidekiq
schedule
queue
resque
scheduled-jobs
activejob
ruby-on-rails
periodic-jobs
rufus
sneakers
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May 4, 2020 - Ruby
Creates accounts on sneaker website UI AND 30 MORE SITES COMING THIS WEEK
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Jan 9, 2018 - Python
Adidas monitor :) able to monitor any pids
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Mar 15, 2020 - JavaScript
Autocheckout for https://store.sacai.jp/
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Nov 19, 2019 - Python
Advanced Sneakers adapter for ActiveJob
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Jun 30, 2020 - Ruby
Automation script for Air Dior - https://capsule.dior.com/
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Jun 26, 2020 - Python
A Shopify delay calculator, that calculates an optimal delay so your proxies won't get banned.
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Aug 19, 2019 - Python
A script which checks the stock of demandware sites (i.e. YeezySupply or Adidas)
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May 12, 2020 - Python
A basic monitor for the off---white.com website
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Nov 15, 2019 - Python
Sneaker price analysis and search recommendation
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Sep 5, 2019 - Jupyter Notebook
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What are some general characteristics of this market (in particular the venue du)?
Given our non-trivial holding time, we should devise our strategy according to key observations we have on our data.
We have observed:
Very few (model, size) trade regularly
Most can be characterized as having large spread, low volume and liquidity. Missing data on one side is often expected. It woul