KO
|
EN
gitlite — search
Search
#python
#java
#python3
#arduino
#golang
#machine-learning
#rust
#html
#flask
#javascript
#seismology
#nodejs
Crawler_Sofa_Score
★ 10
Open GitHub ↗
Crawler of the site sofascore.com
Download README (.md)
Explore Similar Repositories
spdx-tools-js
:
No description available.
jsbox-react-demo
:
JSBox Node.js demo that creates a React.js dev environment
nextjs-markdown-blog
:
NextJS Blog using Markdown files
FMXWndProcHook
:
FMX下TForm的WndProc HOOK
Video-Stream-With-React.Js
:
No description available.
// repository documentation
Was this content helpful?
★ 0
(0 ratings)
Select Rating:
★
★
★
★
★
Submit Feedback
Recent Feedback
×
Download README
Do you want to download the
README.md
file for
Crawler_Sofa_Score
?
Download (.md)
# Sofa Score Crawler Brazilian Football 2019 > The purpose of this crawler is access the site [Sofa Score](https://www.sofascore.com/tournament/football/brazil/brasileiro-serie-a/325) and extract the public data of the soccer players at brazilian league (Brasileirão Serie A and Brasileirão Serie B). The data contains: - **Attack** - Goals, Big chances missed, Successful dribbles, Total shots, Percent of Goal conversion - **Defence** - Tackles, Interceptions, Clearances, Errors lead to goal, Blocked shots - **Passing** - Big chances created, Assists, Accurate passes, Percent of Accurate passes, Key passes - **Goalkeeper** - Saves, Clean sheets, Penalties saved, Saved shots from inside the box, Runs out, Rating  ## Project Structure ``` ├── Crawler_Sofa_Score ├── Sofa_Score │ ├── spiders │ ├── __init__.py │ ├── sofa_scoure_2019A.py # spider to brasileirao 2019 serie A │ ├── sofa_scoure_2019B.py # spider to brasileirao 2019 serie B │ ├── _init__.py │ ├── items.py │ ├── middlewares.py │ ├── pipelines.py │ └── settings.py ├── README.md ├── requirements.txt ├── scrapy.cfg └── ... ``` ## How to run our spider Install the virtual environment and requirements: ``` python3 -m venv venv source venv/bin/activate pip3 install --upgrade pip pip3 install -r requirements.txt ``` To put our spider to work, run: ``` scrapy crawl brasileirao2019_serieA scrapy crawl brasileirao2019_serieB ```
