關于國賽環境使用的一些研究……
1 - 關于Python環境的
使用Anaconda2管理Python環境
1.1 - 安裝
官網下載下傳安裝包下載下傳。
1.2 - 建立Python環境
localhost:template mac$ conda create --name python36 python=3.6
Solving environment: done
## Package Plan ##
environment location: /anaconda2/envs/python36
added / updated specs:
- python=3.6
.........
裝Python2或者3都行,随意。
1.3 - 檢視Python環境 conda info -e
localhost:template mac$ conda info -e
# conda environments:
#
face_recognition /Users/mac/.conda/envs/face_recognition
test2 /Users/mac/.conda/envs/test2
base * /anaconda2
python27 /anaconda2/envs/python27
python36 /anaconda2/envs/python36
帶 * 号的是目前的環境。
1.4 - 激活Python環境
activate python34 # for Windows
source activate python34 # for Linux & Mac
效果如下:
localhost:template mac$ source activate python36
(python36) localhost:template mac$
1.5 - 檢視目前環境安裝的庫 conda list
1.6 - 在目前環境安裝庫 conda install lib_name
(python36) localhost:template mac$ conda install requests
Solving environment: done
## Package Plan ##
environment location: /anaconda2/envs/python36
added / updated specs:
- requests
The following packages will be downloaded:
package | build
---------------------------|-----------------
requests-2.14.2 | py36_0 720 KB https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
The following NEW packages will be INSTALLED:
requests: 2.14.2-py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
Proceed ([y]/n)? y
Downloading and Extracting Packages
requests-2.14.2 | 720 KB | ############################################################################# | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
1.7 -退出目前環境
deactivate python34 # for Windows
source deactivate python34 # for Linux & Mac
2 - 關于docker
安裝不提了,直接寫怎麼使用官方complete
2.1 - 下載下傳環境 git clone
2.2 - 部署環境
舉例,終端進入deploy檔案夾,輸入
docker-compose up -d
localhost:ciscn2018-template mac$ cd CISCN-2018-web-for-players/
localhost:CISCN-2018-web-for-players mac$ ls
README.md checker template
localhost:CISCN-2018-web-for-players mac$ cd template/
localhost:template mac$ ls
README.md deploy writeup.md
localhost:template mac$ cd deploy/
localhost:deploy mac$ ls
Dockerfile requirement.pip www
docker-compose.yml start_sshop.sh
localhost:deploy mac$ docker-compose up -d
Starting deploy_sshop_1 ... done
2.3 - 檢視容器狀态 docker ps
localhost:deploy mac$ docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
036006fd2513 deploy_sshop "/sbin/my_init" 7 hours ago Up 9 minutes 0.0.0.0:22->22/tcp, 0.0.0.0:80->8233/tcp deploy_sshop_1
2.4 - 打開容器bash
docker run -t -i deploy_sshop /bin/bash
//docker run 運作
// -t -i 背景,打開讀寫
//deploy_sshop 容器名稱或者ID
///bin/bash 應用bash
2.5 - 檔案傳輸
docker cp <containerId>:/file/path/within/container /host/path/target
2.6 - 退出容器 exit
直接輸入 exit 就好。
2.7 - 檢視容器作業系統
�� ��������������cat /etc/os-release //linux
2.8 - 列出鏡像
docker image ls
2.9 - 檢視鏡像、容器、資料卷所占空間
docker system df
3 - checker.py 使用
3.1 - 運作環境Python2*
輸入參數四個:
python ./checker.py 0.0.0.0 80 _xrsf
3.2 - 需要下載下傳兩個依賴包:
conda install requests
conda install pyquery