Awesome

Introduction

This project crawls job&company data from job-seeking websites, cleans the data, modelizes, converts, and stores it in the database. then use Echarts and Bootstrap to build a front-end page to display the IT job statistics, to show the newest requirements and trends of the IT job market.

Demo

You can input the keyword you are interested in into the search box, such as "Python", then click the search button, and the statistics of this keyword will show.

• The first chart Years of Working(工作年限要求) is about the experience requirement of the Python, according to the data, the "3 ~ 5 years" is the most frequent requirement, then the following is 1 ~ 3 years (Chart Source Code)

• The second chart Salary Range(薪水分布) is about the salary of the Python, according to the data, the "11k ~ 20k" is the most frequent salary provided, then the following is 21k ~ 35k (Chart Source Code)

and we also got charts:

• Education Requirement Data Chart
• City Job Count Chart
• Job Count Change Chart
• Company Finance Stage Chart

Python Charts Example:

Quick Start

This tutorial is based on Linux - Ubuntu, for other systems, please find the corresponding command

• Clone the project

git clone git@github.com:JustForFunnnn/webspider.git

• Install MySQL, Redis, Python3

# install Redis
apt-get install redis-server

# run Redis in background
nohup redis-server &

# install Python3
apt-get install python3

# install MySQL
apt-get install mysql-server

# start MySQL
sudo service mysql start

• Config database and table

# create database
CREATE DATABASE `spider` CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;

We still need to create the tables, copy the table definition SQL from tests/schema.sql and run it in MySQL

• Build project

# after a successful build, some executable jobs will be generated under the path env/bin 
make

• Run unit-test

make test

• Run code style check

make flake8

• Start web service

env/bin/web

• Stat crawler

# run task scheduler/dispatcher
env/bin/celery_beat
# run celery worker for job data
env/bin/celery_lg_jobs_data_worker
# run celery worker for job count
env/bin/celery_lg_jobs_count_worker

• Other jobs

# start crawl job count immediately
env/bin/crawl_lg_jobs_count
# start crawl job data immediately
env/bin/crawl_lg_data
# start celery monitoring
env/bin/celery_flower

• Clean

# clean the existing build result
make clean