├── README.md ├── mysql数据库 └── haha.sql ├── 关于系统.txt └── 项目源码 ├── ml-100k-data ├── MovieGenre3.csv ├── hhhh.csv ├── ratings.csv └── rrtotaltable.csv └── movierecommend ├── .idea ├── django_auth_example.iml ├── encodings.xml ├── misc.xml ├── modules.xml └── workspace.xml ├── __pycache__ └── models.cpython-36.pyc ├── django_auth_example ├── __init__.py ├── __pycache__ │ ├── __init__.cpython-36.pyc │ ├── settings.cpython-36.pyc │ ├── urls.cpython-36.pyc │ └── wsgi.cpython-36.pyc ├── settings.py ├── urls.py └── wsgi.py ├── manage.py ├── models.py ├── requirements.txt ├── templates ├── base.html ├── index.html └── users │ └── 3.jpg └── users ├── __init__.py ├── __pycache__ ├── __init__.cpython-36.pyc ├── admin.cpython-36.pyc ├── forms.cpython-36.pyc ├── models.cpython-36.pyc ├── urls.cpython-36.pyc └── views.cpython-36.pyc ├── admin.py ├── apps.py ├── forms.py ├── migrations ├── 0001_initial.py ├── 0002_auto_20211229_1513.py ├── __init__.py └── __pycache__ │ ├── 0001_initial.cpython-36.pyc │ ├── 0002_auto_20211229_1513.cpython-36.pyc │ └── __init__.cpython-36.pyc ├── models.py ├── static ├── css │ ├── Test.css │ ├── bootstrap.css │ ├── bootstrap.min.css │ ├── demo.css │ ├── firstPage.css │ ├── main.css │ └── star.css ├── img │ ├── DaoMeng.JPG │ ├── GaoYang.JPG │ ├── HuiHun.JPG │ ├── LostMan.JPG │ ├── Orphan.JPG │ ├── Seven.JPG │ ├── ZhaoHun.JPG │ ├── action │ │ ├── 103776.jpg │ │ ├── 105859.jpg │ │ ├── 113189.jpg │ │ ├── 1229238.jpg │ │ ├── 1298650.jpg │ │ ├── 145487.jpg │ │ ├── 2186715.jpg │ │ ├── 3540136.jpg │ │ ├── 3672840.jpg │ │ ├── 371746.jpg │ │ ├── 4276752.jpg │ │ ├── 4324274.jpg │ │ ├── 434409.jpg │ │ ├── 4600952.jpg │ │ ├── 499549.jpg │ │ ├── 5481184.jpg │ │ └── 77869.jpg │ ├── animation │ │ ├── 110357.jpg │ │ ├── 113198.jpg │ │ ├── 114709.jpg │ │ ├── 118829.jpg │ │ ├── 120794.jpg │ │ ├── 126029.jpg │ │ ├── 129167.jpg │ │ ├── 1323594.jpg │ │ ├── 230011.jpg │ │ ├── 245429.jpg │ │ ├── 266543.jpg │ │ ├── 29583.jpg │ │ ├── 3781476.jpg │ │ ├── 3919322.jpg │ │ ├── 396555.jpg │ │ ├── 441773.jpg │ │ ├── 4644382.jpg │ │ ├── 4692656.jpg │ │ └── 892782.jpg │ ├── cancel-custom-off.png │ ├── cancel-custom-on.png │ ├── cancel-off-big.png │ ├── cancel-on-big.png │ ├── comedy │ │ ├── 110201.jpg │ │ ├── 1109624.jpg │ │ ├── 1187043.jpg │ │ ├── 118799.jpg │ │ ├── 1372692.jpg │ │ ├── 1675434.jpg │ │ ├── 188766.jpg │ │ ├── 2245084.jpg │ │ ├── 2414370.jpg │ │ ├── 2459022.jpg │ │ ├── 356910.jpg │ │ ├── 362227.jpg │ │ ├── 373074.jpg │ │ ├── 3863552.jpg │ │ ├── 5061814.jpg │ │ ├── 5157018.jpg │ │ └── 5290882.jpg │ ├── crime │ │ ├── 1067920.jpg │ │ ├── 110413.jpg │ │ ├── 111161.jpg │ │ ├── 114369.jpg │ │ ├── 1160629.jpg │ │ ├── 137494.jpg │ │ ├── 1527788.jpg │ │ ├── 209144.jpg │ │ ├── 216165.jpg │ │ ├── 2165735.jpg │ │ ├── 2267998.jpg │ │ ├── 2820852.jpg │ │ ├── 2990738.jpg │ │ ├── 338564.jpg │ │ ├── 386651.jpg │ │ ├── 439884.jpg │ │ ├── 4701702.jpg │ │ └── 92263.jpg │ ├── drama │ │ ├── 1028532.jpg │ │ ├── 110081.jpg │ │ ├── 120382.jpg │ │ ├── 1285016.jpg │ │ ├── 1393746.jpg │ │ ├── 1410063.jpg │ │ ├── 166924.jpg │ │ ├── 1670345.jpg │ │ ├── 167404.jpg │ │ ├── 1707386.jpg │ │ ├── 2582802.jpg │ │ ├── 405094.jpg │ │ ├── 454876.jpg │ │ ├── 458352.jpg │ │ ├── 480249.jpg │ │ └── 73486.jpg │ ├── love │ │ ├── 1010048.jpg │ │ ├── 1055300.jpg │ │ ├── 106332.jpg │ │ ├── 109830.jpg │ │ ├── 1099212.jpg │ │ ├── 1194664.jpg │ │ ├── 120338.jpg │ │ ├── 1554523.jpg │ │ ├── 1859438.jpg │ │ ├── 2036416.jpg │ │ ├── 211915.jpg │ │ ├── 3043630.jpg │ │ ├── 428870.jpg │ │ ├── 808357.jpg │ │ ├── 817177.jpg │ │ ├── 93978.jpg │ │ └── 99487.jpg │ ├── science │ │ ├── 1190080.jpg │ │ ├── 1260502.jpg │ │ ├── 1305797.jpg │ │ ├── 133093.jpg │ │ ├── 1375666.jpg │ │ ├── 1454468.jpg │ │ ├── 1631867.jpg │ │ ├── 182789.jpg │ │ ├── 1877832.jpg │ │ ├── 2866360.jpg │ │ ├── 2872732.jpg │ │ ├── 289879.jpg │ │ ├── 76759.jpg │ │ ├── 816692.jpg │ │ ├── 848228.jpg │ │ ├── 910970.jpg │ │ └── 945513.jpg │ ├── shawshank.JPG │ ├── star-half-big.png │ ├── star-half.png │ ├── star-off-big.png │ ├── star-off.png │ ├── star-on-big.png │ ├── star-on.png │ ├── star.jpg │ ├── star.png │ └── thriller │ │ ├── 102926.jpg │ │ ├── 1148204.jpg │ │ ├── 1187064.jpg │ │ ├── 120804.jpg │ │ ├── 1259521.jpg │ │ ├── 1457767.jpg │ │ ├── 195714.jpg │ │ ├── 212985.jpg │ │ ├── 2281159.jpg │ │ ├── 2973516.jpg │ │ ├── 309698.jpg │ │ ├── 364385.jpg │ │ ├── 384537.jpg │ │ ├── 5700672.jpg │ │ ├── 63350.jpg │ │ ├── 81505.jpg │ │ └── 89371.jpg ├── js │ ├── GetText.js │ ├── Star.js │ ├── bootstrap.js │ ├── bootstrap.min.js │ ├── jquery-2.1.1.min.js │ ├── jquery-3.1.1.js │ ├── jquery.min.js │ ├── jquery.raty.js │ ├── jquery.raty.min.js │ ├── jquery.star-rating-svg.js │ ├── npm.js │ └── starScore.js ├── rrtotaltable.csv ├── users_resulttable.csv ├── users_resulttable2.csv └── users_resulttable2.csv.old ├── tests.py ├── urls.py └── views.py /README.md: -------------------------------------------------------------------------------- 1 | # Python_Collaborative_Filtering_Movie_Recommendations 2 | Python基于协同过滤算法的电影推荐视频网站设计 3 | 4 | 开发软件：Pycharm 开发环境: Python3.6 数据库：mysql5.6 5 | 6 | 本系统包含电影前端展示界面、电影评分板块、推荐算法的实现以及后端数据库的设 计.其中实现推荐算法是整个电影推荐系统的核心.系统采用由grouplens项目组从美国著名 电影网站movielens整理的ml-latest-small数据集，该数据集包含了671个用户对9000多部电 影的10万条评分数据.首先将该数据集包含的全部文件经过筛选重组之后存储到建好的数 据库中，并将数据集按一定比例划分为训练集和测试集，对训练集进行算法分析生成Top-N 个性化电影推荐列表，然后在测试集上对算法进行评测，至少包括准确率和召回率两种评 测指标. 7 | 8 | 协同过滤算法是推荐领域最出名也是应用最广泛的推荐算法.所以系统拟采用两种协 同过滤算法给出两种不同的推荐结果，一种是基于用户的协同过滤算法，另一种是基于物 品的协同过滤算法，用户可以根据两种推荐结果更加合理的选择合适的电影.系统采用了 改进之后的ItemCF-IUF和UserCF-IIF算法，对计算用户相似度和物品相似度的计算都做出 了改进.最后通过计算两种算法的准确率（Precision）、召回率(Recall)和流行度从而对系 统进行评测、并比较了两种算法各自的优势和劣势.实验证明，改进后的算法比原始的协 同过滤算法推荐效果要好，准确率更高. 9 | 10 | 整个系统涉及到的编程语言包含Python、Html5、JQuery、CSS3以及MySQL数据库编 程.用到的框架是Flask重量级web框架，通过该框架连接系统的前、后端.用户首先需要 填写用户名、密码以及邮箱注册系统，然后才能登陆推荐系统.进入首页后会看到8个电影 分类，包括恐怖片、动作片、剧情片等.用户需要给自己看过的电影进行评分，评分起止 为0.5-5.0分，共10个分段.每评价一部电影就要点击一下提交按钮，将所评分的电影的 imdbId号以及对应的评分存入数据库中.用户点击“推荐结果”按钮，系统就调用推荐算法 遍历数据库所存数据，得出推荐列表之后将结果反馈给浏览器，同时调取数据库所存电影 海报图片进行展示.用户点击自己登陆的昵称，会跳转页面显示自己已经评价过的电影. 11 | -------------------------------------------------------------------------------- /关于系统.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/wangjianlin1985/Python_Collaborative_Filtering_Movie_Recommendations/10222045b2ac700e2d3e0ff76dffc5c4ce1a8ef1/关于系统.txt -------------------------------------------------------------------------------- /项目源码/ml-100k-data/MovieGenre3.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/wangjianlin1985/Python_Collaborative_Filtering_Movie_Recommendations/10222045b2ac700e2d3e0ff76dffc5c4ce1a8ef1/项目源码/ml-100k-data/MovieGenre3.csv -------------------------------------------------------------------------------- /项目源码/movierecommend/.idea/django_auth_example.iml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 26 | 27 | 29 | -------------------------------------------------------------------------------- /项目源码/movierecommend/.idea/encodings.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | -------------------------------------------------------------------------------- /项目源码/movierecommend/.idea/misc.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | -------------------------------------------------------------------------------- /项目源码/movierecommend/.idea/modules.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | -------------------------------------------------------------------------------- /项目源码/movierecommend/.idea/workspace.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 20 | 21 | 22 | 23 | 24 | 32 | 33 | 34 | 35 | aptx4869 36 | login 37 | 38 | 39 | 40 | 75 | 76 | 77 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | 90 | 91 | 92 | 93 | 94 | 95 | 96 | 97 | 98 | 99 | 100 | 101 | 102 | 103 | 104 | 105 | 106 | 107 | 108 | 109 | 110 | 111 | 121 | 122 | 123 | 124 | 125 | 145 | 146 | 147 | 167 | 168 | 169 | 191 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 | 200 | 201 | 202 | 203 | 204 | 205 | 206 | 207 | 208 | 1523345153255 209 | 214 | 215 | 216 | 217 | 219 | 220 | 221 | 222 | 223 | 224 | 225 | 226 | 227 | 228 | 229 | 230 | 231 | 232 | 233 | 234 | 235 | 236 | 237 | 238 | 239 | 240 | 241 | 242 | 243 | 244 | 245 | 246 | 247 | 248 | 249 | 250 | 251 | 252 | 253 | 254 | 255 | 257 | 258 | 259 | 260 | 261 | 262 | 264 | 265 | 266 | 267 | 268 | 269 | 270 | 271 | 272 | 273 | 274 | 275 | 276 | 277 | 278 | user_sim_mat[user].items() 279 | Python 280 | EXPRESSION 281 | 282 | 283 | self.trainset 284 | Python 285 | EXPRESSION 286 | 287 | 288 | 289 | 290 | self.trainset 291 | Python 292 | EXPRESSION 293 | 294 | 295 | 296 | 297 | 298 | 299 | 300 | 301 | 302 | 303 | 304 | 305 | 306 | 307 | 308 | 309 | 310 | 311 | 312 | 313 | 314 | 315 | 316 | 317 | 318 | 319 | 320 | 321 | 322 | 323 | 324 | 325 | 326 | 327 | 328 | 329 | 330 | 331 | 332 | 333 | 334 | 335 | 336 | 337 | 338 | 339 | 340 | 341 | 342 | 343 | 344 | 345 | 346 | 347 | 348 | 349 | 350 | 351 | 352 | 353 | 354 | 355 | 356 | 357 | 358 | 359 | 360 | 361 | 362 | 363 | 364 | 365 | 366 | 367 | 368 | 369 | 370 | 371 | 372 | 373 | 374 | 375 | 376 | 377 | 378 | 379 | 380 | 381 | 382 | 383 | 384 | 385 | 386 | 387 | 388 | 389 | 390 | 391 | 392 | 393 | 394 | 395 | 396 | 397 | 398 | 399 | 400 | 401 | 402 | 403 | 404 | 405 | 406 | 407 | 408 | 409 | 410 | 411 | 412 | 413 | 414 | 415 | 416 | 417 | 418 | 419 | 420 | 421 | 422 | 423 | 424 | 425 | 426 | 427 | 428 | 429 | 430 | 431 | 432 | 433 | 434 | 435 | 436 | 437 | 438 | 439 | 440 | 441 | 442 | 443 | 444 | 445 | 446 | 447 | 448 | 449 | 450 | 451 | 452 | 453 | 454 | 455 | 456 | 457 | 458 | 459 | 460 | 461 | 462 | 463 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Django 1.11.1. 5 | 6 | For more information on this file, see 7 | https://docs.djangoproject.com/en/1.11/topics/settings/ 8 | 9 | For the full list of settings and their values, see 10 | https://docs.djangoproject.com/en/1.11/ref/settings/ 11 | """ 12 | 13 | import os 14 | 15 | # Build paths inside the project like this: os.path.join(BASE_DIR, ...) 16 | BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) 17 | 18 | 19 | # Quick-start development settings - unsuitable for production 20 | # See https://docs.djangoproject.com/en/1.11/howto/deployment/checklist/ 21 | 22 | # SECURITY WARNING: keep the secret key used in production secret! 23 | SECRET_KEY = '+h-pm!j*c$8!pyf!-^me8c&pjr4vl%b8zh_ms2wn7*bto%myg9' 24 | 25 | # SECURITY WARNING: don't run with debug turned on in production! 26 | DEBUG = True 27 | 28 | ALLOWED_HOSTS = [] 29 | 30 | AUTH_USER_MODEL = 'users.User' #自己加的 使用user下的User模型 31 | LOGIN_REDIRECT_URL = '/' #自己添加，实现登录之后跳转到首页 32 | 33 | 34 | 35 | 36 | # Application definition 37 | 38 | INSTALLED_APPS = [ 39 | 'django.contrib.admin', 40 | 'django.contrib.auth', 41 | 'django.contrib.contenttypes', 42 | 'django.contrib.sessions', 43 | 'django.contrib.messages', 44 | 'django.contrib.staticfiles', 45 | 'users', 46 | ] 47 | 48 | MIDDLEWARE = [ 49 | 'django.middleware.security.SecurityMiddleware', 50 | 'django.contrib.sessions.middleware.SessionMiddleware', 51 | 'django.middleware.common.CommonMiddleware', 52 | 'django.middleware.csrf.CsrfViewMiddleware', 53 | 'django.contrib.auth.middleware.AuthenticationMiddleware', 54 | 'django.contrib.messages.middleware.MessageMiddleware', 55 | 'django.middleware.clickjacking.XFrameOptionsMiddleware', 56 | ] 57 | 58 | ROOT_URLCONF = 'django_auth_example.urls' 59 | 60 | TEMPLATES = [ 61 | { 62 | 'BACKEND': 'django.template.backends.django.DjangoTemplates', 63 | 'DIRS': [os.path.join(BASE_DIR, 'templates')], 64 | 'APP_DIRS': True, 65 | 'OPTIONS': { 66 | 'context_processors': [ 67 | 'django.template.context_processors.debug', 68 | 'django.template.context_processors.request', 69 | 'django.contrib.auth.context_processors.auth', 70 | 'django.contrib.messages.context_processors.messages', 71 | ], 72 | }, 73 | }, 74 | ] 75 | 76 | WSGI_APPLICATION = 'django_auth_example.wsgi.application' 77 | 78 | 79 | # Database 80 | # https://docs.djangoproject.com/en/1.11/ref/settings/#databases 81 | 82 | DATABASES = { 83 | 'default': { 84 | 'ENGINE': 'django.db.backends.mysql', 85 | #'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), 86 | 'NAME': 'haha', 87 | 'USER': 'root', 88 | 'PASSWORD': '123456', 89 | 'HOST': '127.0.0.1', 90 | 'PORT': '3306', 91 | } 92 | } 93 | 94 | 95 | # Password validation 96 | # https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators 97 | 98 | AUTH_PASSWORD_VALIDATORS = [ 99 | { 100 | 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', 101 | }, 102 | { 103 | 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', 104 | }, 105 | { 106 | 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', 107 | }, 108 | { 109 | 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', 110 | }, 111 | ] 112 | 113 | 114 | # Internationalization 115 | # https://docs.djangoproject.com/en/1.11/topics/i18n/ 116 | 117 | LANGUAGE_CODE = 'zh-hans' 118 | 119 | TIME_ZONE = 'Asia/Shanghai' 120 | 121 | USE_I18N = True 122 | 123 | USE_L10N = True 124 | 125 | USE_TZ = True 126 | 127 | 128 | # Static files (CSS, JavaScript, Images) 129 | # https://docs.djangoproject.com/en/1.11/howto/static-files/ 130 | 131 | STATIC_URL = '/static/' 132 | 133 | STATICFILES_DIRS = ( 134 | os.path.join(BASE_DIR, 'static').replace('\\', '/'), 135 | ) 136 | -------------------------------------------------------------------------------- /项目源码/movierecommend/django_auth_example/urls.py: -------------------------------------------------------------------------------- 1 | """django_auth_example URL Configuration 2 | 3 | The `urlpatterns` list routes URLs to views. For more information please see: 4 | https://docs.djangoproject.com/en/1.11/topics/http/urls/ 5 | Examples: 6 | Function views 7 | 1. Add an import: from my_app import views 8 | 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home') 9 | Class-based views 10 | 1. Add an import: from other_app.views import Home 11 | 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home') 12 | Including another URLconf 13 | 1. Import the include() function: from django.conf.urls import url, include 14 | 2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls')) 15 | """ 16 | from django.conf.urls import url, include 17 | from django.contrib import admin 18 | from users import views 19 | from users.views import insert 20 | urlpatterns = [ 21 | url(r'^admin/', admin.site.urls), 22 | # 别忘记在顶部引入 include 函数 23 | url(r'^users/', include('users.urls')), 24 | url(r'^users/', include('django.contrib.auth.urls')), 25 | url(r'^$', views.index, name='index'), 26 | url(r'^insert/$', insert), 27 | url(r'^users/recommend1/$', views.recommend1), 28 | url(r'^users/recommend2/$', views.recommend2), 29 | url(r'^users/recommend1/users/recommend1/recommend2/$', views.recommend2), 30 | # url(r'^users/showmessage/$', views.showmessage), 31 | ] 32 | -------------------------------------------------------------------------------- /项目源码/movierecommend/django_auth_example/wsgi.py: -------------------------------------------------------------------------------- 1 | """ 2 | WSGI config for django_auth_example project. 3 | 4 | It exposes the WSGI callable as a module-level variable named ``application``. 5 | 6 | For more information on this file, see 7 | https://docs.djangoproject.com/en/1.11/howto/deployment/wsgi/ 8 | """ 9 | 10 | import os 11 | 12 | from django.core.wsgi import get_wsgi_application 13 | 14 | os.environ.setdefault("DJANGO_SETTINGS_MODULE", "django_auth_example.settings") 15 | 16 | application = get_wsgi_application() 17 | -------------------------------------------------------------------------------- /项目源码/movierecommend/manage.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | import os 3 | import sys 4 | 5 | if __name__ == "__main__": 6 | os.environ.setdefault("DJANGO_SETTINGS_MODULE", "django_auth_example.settings") 7 | try: 8 | from django.core.management import execute_from_command_line 9 | except ImportError: 10 | # The above import may fail for some other reason. Ensure that the 11 | # issue is really that Django is missing to avoid masking other 12 | # exceptions on Python 2. 13 | try: 14 | import django 15 | except ImportError: 16 | raise ImportError( 17 | "Couldn't import Django. Are you sure it's installed and " 18 | "available on your PYTHONPATH environment variable? Did you " 19 | "forget to activate a virtual environment?" 20 | ) 21 | raise 22 | execute_from_command_line(sys.argv) 23 | -------------------------------------------------------------------------------- /项目源码/movierecommend/requirements.txt: -------------------------------------------------------------------------------- 1 | Django==2.2 2 | django-tinymce==2.6.0 3 | mysqlclient==2.0.1 4 | numpy==1.19.1 5 | pandas==1.1.0 6 | Pillow==7.2.0 7 | PyMySQL==1.0.2 8 | python-dateutil==2.8.1 9 | pytz==2020.1 10 | six==1.15.0 11 | sqlparse==0.3.1 12 | -------------------------------------------------------------------------------- /项目源码/movierecommend/templates/base.html: -------------------------------------------------------------------------------- 1 |  2 | {% load staticfiles %} 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | {% block title %}{% endblock %} -- a django blog 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 28 | 29 | 30 | 31 | 32 | 33 |
34 | 35 | 36 | 55 | 56 | 57 |
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59 |
60 | {% block content %}{% endblock %} 61 |
62 |
63 | {% block rightside %}{% endblock %} 64 |
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-*- coding: utf-8 -*- 2 | # Generated by Django 1.11.7 on 2018-05-07 05:14 3 | from __future__ import unicode_literals 4 | 5 | import django.contrib.auth.models 6 | import django.contrib.auth.validators 7 | from django.db import migrations, models 8 | import django.utils.timezone 9 | 10 | 11 | class Migration(migrations.Migration): 12 | 13 | initial = True 14 | 15 | dependencies = [ 16 | ('auth', '0008_alter_user_username_max_length'), 17 | ] 18 | 19 | operations = [ 20 | migrations.CreateModel( 21 | name='User', 22 | fields=[ 23 | ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), 24 | ('password', models.CharField(max_length=128, verbose_name='password')), 25 | ('last_login', models.DateTimeField(blank=True, null=True, verbose_name='last login')), 26 | ('is_superuser', models.BooleanField(default=False, help_text='Designates that this user has all permissions without explicitly assigning them.', verbose_name='superuser status')), 27 | ('username', models.CharField(error_messages={'unique': 'A user with that username already exists.'}, help_text='Required. 150 characters or fewer. Letters, digits and @/./+/-/_ only.', max_length=150, unique=True, validators=[django.contrib.auth.validators.UnicodeUsernameValidator()], verbose_name='username')), 28 | ('first_name', models.CharField(blank=True, max_length=30, verbose_name='first name')), 29 | ('last_name', models.CharField(blank=True, max_length=30, verbose_name='last name')), 30 | ('email', models.EmailField(blank=True, max_length=254, verbose_name='email address')), 31 | ('is_staff', models.BooleanField(default=False, help_text='Designates whether the user can log into this admin site.', verbose_name='staff status')), 32 | ('is_active', models.BooleanField(default=True, help_text='Designates whether this user should be treated as active. Unselect this instead of deleting accounts.', verbose_name='active')), 33 | ('date_joined', models.DateTimeField(default=django.utils.timezone.now, verbose_name='date joined')), 34 | ('nickname', models.CharField(blank=True, max_length=50)), 35 | ('groups', models.ManyToManyField(blank=True, help_text='The groups this user belongs to. A user will get all permissions granted to each of their groups.', related_name='user_set', related_query_name='user', to='auth.Group', verbose_name='groups')), 36 | ('user_permissions', models.ManyToManyField(blank=True, help_text='Specific permissions for this user.', related_name='user_set', related_query_name='user', to='auth.Permission', verbose_name='user permissions')), 37 | ], 38 | options={ 39 | 'verbose_name': 'user', 40 | 'verbose_name_plural': 'users', 41 | 'abstract': False, 42 | }, 43 | managers=[ 44 | ('objects', django.contrib.auth.models.UserManager()), 45 | ], 46 | ), 47 | migrations.CreateModel( 48 | name='Insertposter', 49 | fields=[ 50 | ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), 51 | ('userId', models.IntegerField(null=True)), 52 | ('title', models.CharField(blank=True, max_length=200)), 53 | ('poster', models.CharField(blank=True, max_length=500, null=True)), 54 | ], 55 | ), 56 | migrations.CreateModel( 57 | name='Resulttable', 58 | fields=[ 59 | ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), 60 | ('userId', models.IntegerField(null=True)), 61 | ('imdbId', models.IntegerField()), 62 | ('rating', models.DecimalField(blank=True, decimal_places=1, max_digits=3, null=True)), 63 | ], 64 | ), 65 | ] 66 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/migrations/0002_auto_20211229_1513.py: -------------------------------------------------------------------------------- 1 | # Generated by Django 2.2 on 2021-12-29 07:13 2 | 3 | from django.db import migrations, models 4 | 5 | 6 | class Migration(migrations.Migration): 7 | 8 | dependencies = [ 9 | ('users', '0001_initial'), 10 | ] 11 | 12 | operations = [ 13 | migrations.AlterField( 14 | model_name='user', 15 | name='last_name', 16 | field=models.CharField(blank=True, max_length=150, verbose_name='last name'), 17 | ), 18 | ] 19 | 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-------------------------------------------------------------------------------- 1 | from django.db import models 2 | 3 | # Create your models here. 4 | from django.db import models 5 | from django.contrib.auth.models import AbstractUser 6 | 7 | class User(AbstractUser): 8 | nickname = models.CharField(max_length=50, blank=True) 9 | 10 | class Meta(AbstractUser.Meta): 11 | pass 12 | 13 | 14 | # class MYBOOK(models.Model): 15 | # name = models.CharField(max_length=200) 16 | # price = models.FloatField() 17 | # 18 | # def __str__(self): 19 | # return self.name+':'+str(self.price) 20 | 21 | # class Resulttable(models.Model): 22 | # # movieId = models.IntegerField(null=True) # Field name made lowercase. 23 | # userId = models.IntegerField(null=True) # Field name made lowercase. 24 | # rating = models.DecimalField(max_digits=3, decimal_places=1, blank=True, null=True) 25 | # imdbId = models.IntegerField() # Field name made lowercase. 26 | # title = models.CharField(max_length=50, blank=True, null=True) 27 | # 28 | # # class Meta: 29 | # # managed = False 30 | # # db_table = 'resulttable' 31 | # 32 | # def __str__(self): 33 | # return self.userId+':'+self.rating 34 | 35 | 36 | class Resulttable(models.Model): 37 | # movieId = models.IntegerField(null=True) # Field name made lowercase. 38 | userId = models.IntegerField(null=True) # Field name made lowercase. 39 | imdbId = models.IntegerField() # Field name made lowercase. 40 | rating = models.DecimalField(max_digits=3, decimal_places=1, blank=True, null=True) 41 | # title = models.CharField(max_length=50, blank=True, null=True) 42 | 43 | # class Meta: 44 | # managed = False 45 | # db_table = 'resulttable' 46 | 47 | def __str__(self): 48 | return self.userId+':'+self.rating 49 | 50 | 51 | class Insertposter(models.Model): 52 | userId = models.IntegerField(null=True) 53 | title = models.CharField(max_length=200,blank=True,null = False) 54 | poster = models.CharField(max_length=500, blank=True, null=True) 55 | 56 | def __str__(self): 57 | return self.userId + ':' + self.poster 58 | 59 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/css/Test.css: -------------------------------------------------------------------------------- 1 | h2{ 2 | text-align:center; 3 | #color:#00ff00; 4 | font-family:"Times New Roman", Times, serif; 5 | } 6 | 7 | 8 | /*.pic,.BiaoQian{*/ 9 | /*float:left;*/ 10 | /*margin-top: 70px;*/ 11 | /*}*/ 12 | 13 | /*.pic{*/ 14 | /*margin-left:200px;*/ 15 | /*#border: 1px solid #00FF00;*/ 16 | /*margin-right:50px;*/ 17 | /*width:320px;*/ 18 | /*height:400px;*/ 19 | /*}*/ 20 | 21 | /*.BiaoQian{*/ 22 | /*#border: 1px solid #000000;*/ 23 | /*width:700px;*/ 24 | /*height:500px;*/ 25 | /*}*/ 26 | 27 | 28 | /*.content {*/ 29 | /*width:100%;*/ 30 | /*overflow: hidden;*/ 31 | 32 | /*}*/ 33 | 34 | 35 | /*.tags_list ul*/ 36 | /*{*/ 37 | /*list-style-type:none;*/ 38 | /*margin-left:50px;*/ 39 | /*width:35%;*/ 40 | /*margin-top: 15px;*/ 41 | /*}*/ 42 | 43 | 44 | /*li {*/ 45 | /*list-style: none;*/ 46 | /*display: inline-block;*/ 47 | /*#width: 33.3%;*/ 48 | /*text-align: center;*/ 49 | /*overflow: hidden;*/ 50 | /*vertical-align: bottom;*/ 51 | /*}*/ 52 | 53 | 54 | /*.img-box {*/ 55 | /*height: 300px;*/ 56 | /*overflow: hidden;*/ 57 | /*padding-right: 25px;*/ 58 | /*padding-left: 35px;*/ 59 | /*}*/ 60 | /*.img-box img {*/ 61 | /*position: relative;*/ 62 | /*width: 100%;*/ 63 | /*top: 50%;*/ 64 | /*transform: translateY(-60%);*/ 65 | /*}*/ 66 | 67 | 68 | 69 | 70 | /*.star_bg {*/ 71 | /*width: 120px; height: 20px;*/ 72 | /*background: url(../img/star.jpg) repeat-x;*/ 73 | /*position: relative;*/ 74 | /*overflow: hidden;*/ 75 | /*}*/ 76 | /*.star {*/ 77 | /*height: 100%; width: 24px;*/ 78 | /*line-height: 6em;*/ 79 | /*position: absolute;*/ 80 | /*z-index: 3;*/ 81 | /*}*/ 82 | /*.star:hover {*/ 83 | /*background: url(../img/star.jpg) repeat-x 0 -20px!important;*/ 84 | /*left: 0; z-index: 2;*/ 85 | /*}*/ 86 | /*.star_1 { left: 0; }*/ 87 | 88 | /*/* 幕后的英雄，单选按钮 */ 89 | 90 | /*.score_1:checked ~ .star_1 { width: 24px; }*/ 91 | /*.score_2:checked ~ .star_2 { width: 48px; }*/ 92 | /*.score_3:checked ~ .star_3 { width: 72px; }*/ 93 | /*.score_4:checked ~ .star_4 { width: 96px; }*/ 94 | /*.score_5:checked ~ .star_5 { width: 120px; }*/ 95 | 96 | /*.star_bg:hover .star { background-image: none; }*/ 97 | 98 | 99 | 100 | .figure_title>a { 101 | display: block; 102 | } 103 | 104 | 105 | #user { 106 | padding-left: 10px; 107 | margin-top: 20px 108 | } 109 | 110 | .figures_lists { 111 | margin-left: 0; 112 | padding: 0; 113 | list-style-type: none; 114 | } 115 | 116 | 117 | 118 | .list_item { 119 | display: inline-block; 120 | /*float: left;*/ 121 | vertical-align: top; 122 | margin-bottom: 20px; 123 | position: relative; 124 | padding-right: 25px; 125 | padding-left: 25px; 126 | } 127 | 128 | .label_title { 129 | position: absolute; 130 | top: 0; 131 | left: 0; 132 | background-color: #1CBF11; 133 | border-radius: 10px; 134 | } 135 | .label_font { 136 | color: #fff; 137 | padding: 0 5px; 138 | } 139 | #my-content { 140 | margin: 25px auto; 141 | padding: 0 10px; 142 | } 143 | #my-content:first-child { 144 | padding: 0; 145 | } 146 | 147 | .figure img { 148 | width: 80%; 149 | } 150 | .new_image { 151 | position: absolute; 152 | top: 0; 153 | left: 0; 154 | } 155 | /*@media 设备类型 and|only|not (设备特性) {样式代码}*/ 156 | @media handheld and (max-device-width: 768px) { 157 | .nav>li { 158 | display: inline-table; 159 | margin-right: 10px; 160 | } 161 | .container { 162 | padding-left: 0; 163 | padding-right: 0; 164 | margin: 0 10px; 165 | } 166 | .list_item { 167 | width: 32%; 168 | } 169 | } 170 | 171 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/css/demo.css: -------------------------------------------------------------------------------- 1 | .evaluate{ 2 | padding-left: 30px; 3 | } 4 | #title{ 5 | color:red; 6 | } 7 | 8 | 9 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/css/firstPage.css: -------------------------------------------------------------------------------- 1 | h2{ 2 | text-align:center; 3 | #color:#00ff00; 4 | font-family:"Times New Roman", Times, serif; 5 | } 6 | 7 | 8 | .pic,.BiaoQian{ 9 | float:left; 10 | margin-top: 70px; 11 | } 12 | 13 | .pic{ 14 | margin-left:200px; 15 | #border: 1px solid #00FF00; 16 | margin-right:50px; 17 | width:320px; 18 | height:400px; 19 | } 20 | 21 | .BiaoQian{ 22 | #border: 1px solid #000000; 23 | width:700px; 24 | height:500px; 25 | } 26 | 27 | 28 | .content { 29 | width:100%; 30 | overflow: hidden; 31 | 32 | } 33 | 34 | 35 | .tags_list ul 36 | { 37 | list-style-type:none; 38 | margin-left:50px; 39 | width:35%; 40 | margin-top: 15px; 41 | } 42 | 43 | 44 | li { 45 | list-style: none; 46 | display: inline-block; 47 | #width: 33.3%; 48 | text-align: center; 49 | overflow: hidden; 50 | vertical-align: bottom; 51 | } 52 | 53 | 54 | .img-box { 55 | height: 300px; 56 | overflow: hidden; 57 | padding-right: 25px; 58 | padding-left: 35px; 59 | } 60 | .img-box img { 61 | position: relative; 62 | width: 100%; 63 | top: 50%; 64 | transform: translateY(-60%); 65 | } 66 | 67 | #user { 68 | padding-left: 10px; 69 | margin-top: 20px 70 | } 71 | 72 | .figures_lists { 73 | margin-left: 0; 74 | padding: 0; 75 | list-style-type: none; 76 | } 77 | .list_item { 78 | display: inline-block; 79 | /*float: left;*/ 80 | vertical-align: top; 81 | margin-bottom: 20px; 82 | position: relative; 83 | } 84 | .label_title { 85 | position: absolute; 86 | top: 0; 87 | left: 0; 88 | background-color: #1CBF11; 89 | border-radius: 10px; 90 | } 91 | .label_font { 92 | color: #fff; 93 | padding: 0 5px; 94 | } 95 | #my-content { 96 | margin: 25px auto; 97 | padding: 0 10px; 98 | } 99 | #my-content:first-child { 100 | padding: 0; 101 | } 102 | 103 | 104 | .figure_title>a { 105 | display: block; 106 | } 107 | .figure img { 108 | width: 80%; 109 | } 110 | .new_image { 111 | position: absolute; 112 | top: 0; 113 | left: 0; 114 | } 115 | /*@media 设备类型 and|only|not (设备特性) {样式代码}*/ 116 | @media handheld and (max-device-width: 768px) { 117 | .nav>li { 118 | display: inline-table; 119 | margin-right: 10px; 120 | } 121 | .container { 122 | padding-left: 0; 123 | padding-right: 0; 124 | margin: 0 10px; 125 | } 126 | .list_item { 127 | width: 32%; 128 | } 129 | } 130 | 131 | 132 | 133 | /*.container_{*/ 134 | /*position:absolute;*/ 135 | /*}*/ 136 | .btn .zhuxiao{ 137 | position: absolute; 138 | right: 0px; 139 | } 140 | 141 | /*.login_{*/ 142 | /*position: absolute;*/ 143 | /*}*/ 144 | 145 | 146 | 147 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/css/main.css: -------------------------------------------------------------------------------- 1 | h2{ 2 | text-align:center; 3 | #color:#00ff00; 4 | font-family:"Times New Roman", Times, serif; 5 | } 6 | 7 | 8 | .pic,.BiaoQian{ 9 | float:left; 10 | margin-top: 70px; 11 | } 12 | 13 | .pic{ 14 | margin-left:200px; 15 | #border: 1px solid #00FF00; 16 | margin-right:50px; 17 | width:320px; 18 | height:400px; 19 | } 20 | 21 | .BiaoQian{ 22 | #border: 1px solid #000000; 23 | width:700px; 24 | height:500px; 25 | } 26 | 27 | 28 | .content { 29 | width:100%; 30 | overflow: hidden; 31 | 32 | } 33 | 34 | 35 | .tags_list ul 36 | { 37 | list-style-type:none; 38 | margin-left:50px; 39 | width:35%; 40 | margin-top: 15px; 41 | } 42 | 43 | 44 | li { 45 | list-style: none; 46 | display: inline-block; 47 | #width: 33.3%; 48 | text-align: center; 49 | overflow: hidden; 50 | vertical-align: bottom; 51 | } 52 | 53 | 54 | .img-box { 55 | height: 300px; 56 | overflow: hidden; 57 | padding-right: 25px; 58 | padding-left: 35px; 59 | } 60 | .img-box img { 61 | position: relative; 62 | width: 100%; 63 | top: 50%; 64 | transform: translateY(-60%); 65 | } 66 | 67 | #user { 68 | padding-left: 10px; 69 | margin-top: 20px 70 | } 71 | 72 | .figures_lists { 73 | margin-left: 0; 74 | padding: 0; 75 | list-style-type: none; 76 | } 77 | .list_item { 78 | display: inline-block; 79 | /*float: left;*/ 80 | vertical-align: top; 81 | margin-bottom: 20px; 82 | position: relative; 83 | } 84 | .label_title { 85 | position: absolute; 86 | top: 0; 87 | left: 0; 88 | background-color: #1CBF11; 89 | border-radius: 10px; 90 | } 91 | .label_font { 92 | color: #fff; 93 | padding: 0 5px; 94 | } 95 | #my-content { 96 | margin: 25px auto; 97 | padding: 0 10px; 98 | } 99 | #my-content:first-child { 100 | padding: 0; 101 | } 102 | 103 | 104 | .figure_title>a { 105 | display: block; 106 | } 107 | .figure img { 108 | width: 80%; 109 | } 110 | .new_image { 111 | position: absolute; 112 | top: 0; 113 | left: 0; 114 | } 115 | /*@media 设备类型 and|only|not (设备特性) {样式代码}*/ 116 | @media handheld and (max-device-width: 768px) { 117 | .nav>li { 118 | display: inline-table; 119 | margin-right: 10px; 120 | } 121 | .container { 122 | padding-left: 0; 123 | padding-right: 0; 124 | margin: 0 10px; 125 | } 126 | .list_item { 127 | width: 32%; 128 | } 129 | } 130 | 131 | 132 | 133 | .container_{ 134 | position:absolute; 135 | } 136 | 137 | 138 | 139 | 140 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/css/star.css: -------------------------------------------------------------------------------- 1 | /*.content{*/ 2 | /*width: 600px;*/ 3 | /*margin:0 auto;*/ 4 | /*padding-top:20px;*/ 5 | /*}*/ 6 | /* 重置文本格式元素 */ 7 | a { 8 | text-decoration: none; 9 | cursor: pointer; 10 | color:#333333; 11 | font-size:14px; 12 | } 13 | a:hover { 14 | text-decoration: none; 15 | } 16 | .clearfix::after{ 17 | display:block; 18 | content:''; 19 | height:0; 20 | overflow:hidden; 21 | clear:both; 22 | } 23 | 24 | .block .star_score{ 25 | float:left; 26 | } 27 | 28 | .star_score { 29 | background-image: url("../img/starky.png"); 30 | width:160px; 31 | height:21px; 32 | position:relative; 33 | } 34 | 35 | /*分数动态*/ 36 | .star_score a{ 37 | height:21px; 38 | display:block; 39 | text-indent:-999em; 40 | position:absolute; 41 | left:0; 42 | } -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/img/DaoMeng.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/wangjianlin1985/Python_Collaborative_Filtering_Movie_Recommendations/10222045b2ac700e2d3e0ff76dffc5c4ce1a8ef1/项目源码/movierecommend/users/static/img/DaoMeng.JPG -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/img/GaoYang.JPG: -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- 1 | /*! 2 | * jQuery Raty - A Star Rating Plugin 3 | * 4 | * The MIT License 5 | * 6 | * author: Washington Botelho 7 | * github: wbotelhos/raty 8 | * version: 2.8.0 9 | * 10 | */ 11 | 12 | (function($) { 13 | 'use strict'; 14 | 15 | var methods = { 16 | init: function(options) { 17 | return this.each(function() { 18 | this.self = $(this); 19 | 20 | methods.destroy.call(this.self); 21 | 22 | this.opt = $.extend(true, {}, $.fn.raty.defaults, options, this.self.data()); 23 | 24 | methods._adjustCallback.call(this); 25 | methods._adjustNumber.call(this); 26 | methods._adjustHints.call(this); 27 | 28 | this.opt.score = methods._adjustedScore.call(this, this.opt.score); 29 | 30 | if (this.opt.starType !== 'img') { 31 | methods._adjustStarType.call(this); 32 | } 33 | 34 | methods._adjustPath.call(this); 35 | methods._createStars.call(this); 36 | 37 | if (this.opt.cancel) { 38 | methods._createCancel.call(this); 39 | } 40 | 41 | if (this.opt.precision) { 42 | methods._adjustPrecision.call(this); 43 | } 44 | 45 | methods._createScore.call(this); 46 | methods._apply.call(this, this.opt.score); 47 | methods._setTitle.call(this, this.opt.score); 48 | methods._target.call(this, this.opt.score); 49 | 50 | if (this.opt.readOnly) { 51 | methods._lock.call(this); 52 | } else { 53 | this.style.cursor = 'pointer'; 54 | 55 | methods._binds.call(this); 56 | } 57 | }); 58 | }, 59 | 60 | _adjustCallback: function() { 61 | var options = ['number', 'readOnly', 'score', 'scoreName', 'target', 'path']; 62 | 63 | for (var i = 0; i < options.length; i++) { 64 | if (typeof this.opt[options[i]] === 'function') { 65 | this.opt[options[i]] = this.opt[options[i]].call(this); 66 | } 67 | } 68 | }, 69 | 70 | _adjustedScore: function(score) { 71 | if (!score) { 72 | return score; 73 | } 74 | 75 | return methods._between(score, 0, this.opt.number); 76 | }, 77 | 78 | _adjustHints: function() { 79 | if (!this.opt.hints) { 80 | this.opt.hints = []; 81 | } 82 | 83 | if (!this.opt.halfShow && !this.opt.half) { 84 | return; 85 | } 86 | 87 | var steps = this.opt.precision ? 10 : 2; 88 | 89 | for (var i = 0; i < this.opt.number; i++) { 90 | var group = this.opt.hints[i]; 91 | 92 | if (Object.prototype.toString.call(group) !== '[object Array]') { 93 | group = [group]; 94 | } 95 | 96 | this.opt.hints[i] = []; 97 | 98 | for (var j = 0; j < steps; j++) { 99 | var 100 | hint = group[j], 101 | last = group[group.length - 1]; 102 | 103 | if (last === undefined) { 104 | last = null; 105 | } 106 | 107 | this.opt.hints[i][j] = hint === undefined ? last : hint; 108 | } 109 | } 110 | }, 111 | 112 | _adjustNumber: function() { 113 | this.opt.number = methods._between(this.opt.number, 1, this.opt.numberMax); 114 | }, 115 | 116 | _adjustPath: function() { 117 | this.opt.path = this.opt.path || ''; 118 | 119 | if (this.opt.path && this.opt.path.charAt(this.opt.path.length - 1) !== '/') { 120 | this.opt.path += '/'; 121 | } 122 | }, 123 | 124 | _adjustPrecision: function() { 125 | this.opt.half = true; 126 | }, 127 | 128 | _adjustStarType: function() { 129 | var replaces = ['cancelOff', 'cancelOn', 'starHalf', 'starOff', 'starOn']; 130 | 131 | this.opt.path = ''; 132 | 133 | for (var i = 0; i < replaces.length; i++) { 134 | this.opt[replaces[i]] = this.opt[replaces[i]].replace('.', '-'); 135 | } 136 | }, 137 | 138 | _apply: function(score) { 139 | methods._fill.call(this, score); 140 | 141 | if (score) { 142 | if (score > 0) { 143 | this.score.val(score); 144 | } 145 | 146 | methods._roundStars.call(this, score); 147 | } 148 | }, 149 | 150 | _between: function(value, min, max) { 151 | return Math.min(Math.max(parseFloat(value), min), max); 152 | }, 153 | 154 | _binds: function() { 155 | if (this.cancel) { 156 | methods._bindOverCancel.call(this); 157 | methods._bindClickCancel.call(this); 158 | methods._bindOutCancel.call(this); 159 | } 160 | 161 | methods._bindOver.call(this); 162 | methods._bindClick.call(this); 163 | methods._bindOut.call(this); 164 | }, 165 | 166 | _bindClick: function() { 167 | var that = this; 168 | 169 | that.stars.on('click.raty', function(evt) { 170 | var 171 | execute = true, 172 | score = (that.opt.half || that.opt.precision) ? that.self.data('score') : (this.alt || $(this).data('alt')); 173 | 174 | if (that.opt.click) { 175 | execute = that.opt.click.call(that, +score, evt); 176 | } 177 | 178 | if (execute || execute === undefined) { 179 | if (that.opt.half && !that.opt.precision) { 180 | score = methods._roundHalfScore.call(that, score); 181 | } 182 | 183 | methods._apply.call(that, score); 184 | } 185 | }); 186 | }, 187 | 188 | _bindClickCancel: function() { 189 | var that = this; 190 | 191 | that.cancel.on('click.raty', function(evt) { 192 | that.score.removeAttr('value'); 193 | 194 | if (that.opt.click) { 195 | that.opt.click.call(that, null, evt); 196 | } 197 | }); 198 | }, 199 | 200 | _bindOut: function() { 201 | var that = this; 202 | 203 | that.self.on('mouseleave.raty', function(evt) { 204 | var score = +that.score.val() || undefined; 205 | 206 | methods._apply.call(that, score); 207 | methods._target.call(that, score, evt); 208 | methods._resetTitle.call(that); 209 | 210 | if (that.opt.mouseout) { 211 | that.opt.mouseout.call(that, score, evt); 212 | } 213 | }); 214 | }, 215 | 216 | _bindOutCancel: function() { 217 | var that = this; 218 | 219 | that.cancel.on('mouseleave.raty', function(evt) { 220 | var icon = that.opt.cancelOff; 221 | 222 | if (that.opt.starType !== 'img') { 223 | icon = that.opt.cancelClass + ' ' + icon; 224 | } 225 | 226 | methods._setIcon.call(that, this, icon); 227 | 228 | if (that.opt.mouseout) { 229 | var score = +that.score.val() || undefined; 230 | 231 | that.opt.mouseout.call(that, score, evt); 232 | } 233 | }); 234 | }, 235 | 236 | _bindOver: function() { 237 | var 238 | that = this, 239 | action = that.opt.half ? 'mousemove.raty' : 'mouseover.raty'; 240 | 241 | that.stars.on(action, function(evt) { 242 | var score = methods._getScoreByPosition.call(that, evt, this); 243 | 244 | methods._fill.call(that, score); 245 | 246 | if (that.opt.half) { 247 | methods._roundStars.call(that, score, evt); 248 | methods._setTitle.call(that, score, evt); 249 | 250 | that.self.data('score', score); 251 | } 252 | 253 | methods._target.call(that, score, evt); 254 | 255 | if (that.opt.mouseover) { 256 | that.opt.mouseover.call(that, score, evt); 257 | } 258 | }); 259 | }, 260 | 261 | _bindOverCancel: function() { 262 | var that = this; 263 | 264 | that.cancel.on('mouseover.raty', function(evt) { 265 | var 266 | starOff = that.opt.path + that.opt.starOff, 267 | icon = that.opt.cancelOn; 268 | 269 | if (that.opt.starType === 'img') { 270 | that.stars.attr('src', starOff); 271 | } else { 272 | icon = that.opt.cancelClass + ' ' + icon; 273 | 274 | that.stars.attr('class', starOff); 275 | } 276 | 277 | methods._setIcon.call(that, this, icon); 278 | methods._target.call(that, null, evt); 279 | 280 | if (that.opt.mouseover) { 281 | that.opt.mouseover.call(that, null); 282 | } 283 | }); 284 | }, 285 | 286 | _buildScoreField: function() { 287 | return $('', { name: this.opt.scoreName, type: 'hidden' }).appendTo(this); 288 | }, 289 | 290 | _createCancel: function() { 291 | var 292 | icon = this.opt.path + this.opt.cancelOff, 293 | cancel = $('<' + this.opt.starType + ' />', { title: this.opt.cancelHint, 'class': this.opt.cancelClass }); 294 | 295 | if (this.opt.starType === 'img') { 296 | cancel.attr({ src: icon, alt: 'x' }); 297 | } else { 298 | // TODO: use $.data 299 | cancel.attr('data-alt', 'x').addClass(icon); 300 | } 301 | 302 | if (this.opt.cancelPlace === 'left') { 303 | this.self.prepend(' ').prepend(cancel); 304 | } else { 305 | this.self.append(' ').append(cancel); 306 | } 307 | 308 | this.cancel = cancel; 309 | }, 310 | 311 | _createScore: function() { 312 | var score = $(this.opt.targetScore); 313 | 314 | this.score = score.length ? score : methods._buildScoreField.call(this); 315 | }, 316 | 317 | _createStars: function() { 318 | for (var i = 1; i <= this.opt.number; i++) { 319 | var 320 | name = methods._nameForIndex.call(this, i), 321 | attrs = { alt: i, src: this.opt.path + this.opt[name] }; 322 | 323 | if (this.opt.starType !== 'img') { 324 | attrs = { 'data-alt': i, 'class': attrs.src }; // TODO: use $.data. 325 | } 326 | 327 | attrs.title = methods._getHint.call(this, i); 328 | 329 | $('<' + this.opt.starType + ' />', attrs).appendTo(this); 330 | 331 | if (this.opt.space) { 332 | this.self.append(i < this.opt.number ? ' ' : ''); 333 | } 334 | } 335 | 336 | this.stars = this.self.children(this.opt.starType); 337 | }, 338 | 339 | _error: function(message) { 340 | $(this).text(message); 341 | 342 | $.error(message); 343 | }, 344 | 345 | _fill: function(score) { 346 | var hash = 0; 347 | 348 | for (var i = 1; i <= this.stars.length; i++) { 349 | var 350 | icon, 351 | star = this.stars[i - 1], 352 | turnOn = methods._turnOn.call(this, i, score); 353 | 354 | if (this.opt.iconRange && this.opt.iconRange.length > hash) { 355 | var irange = this.opt.iconRange[hash]; 356 | 357 | icon = methods._getRangeIcon.call(this, irange, turnOn); 358 | 359 | if (i <= irange.range) { 360 | methods._setIcon.call(this, star, icon); 361 | } 362 | 363 | if (i === irange.range) { 364 | hash++; 365 | } 366 | } else { 367 | icon = this.opt[turnOn ? 'starOn' : 'starOff']; 368 | 369 | methods._setIcon.call(this, star, icon); 370 | } 371 | } 372 | }, 373 | 374 | _getFirstDecimal: function(number) { 375 | var 376 | decimal = number.toString().split('.')[1], 377 | result = 0; 378 | 379 | if (decimal) { 380 | result = parseInt(decimal.charAt(0), 10); 381 | 382 | if (decimal.slice(1, 5) === '9999') { 383 | result++; 384 | } 385 | } 386 | 387 | return result; 388 | }, 389 | 390 | _getRangeIcon: function(irange, turnOn) { 391 | return turnOn ? irange.on || this.opt.starOn : irange.off || this.opt.starOff; 392 | }, 393 | 394 | _getScoreByPosition: function(evt, icon) { 395 | var score = parseInt(icon.alt || icon.getAttribute('data-alt'), 10); 396 | 397 | if (this.opt.half) { 398 | var 399 | size = methods._getWidth.call(this), 400 | percent = parseFloat((evt.pageX - $(icon).offset().left) / size); 401 | 402 | score = score - 1 + percent; 403 | } 404 | 405 | return score; 406 | }, 407 | 408 | _getHint: function(score, evt) { 409 | if (score !== 0 && !score) { 410 | return this.opt.noRatedMsg; 411 | } 412 | 413 | var 414 | decimal = methods._getFirstDecimal.call(this, score), 415 | integer = Math.ceil(score), 416 | group = this.opt.hints[(integer || 1) - 1], 417 | hint = group, 418 | set = !evt || this.move; 419 | 420 | if (this.opt.precision) { 421 | if (set) { 422 | decimal = decimal === 0 ? 9 : decimal - 1; 423 | } 424 | 425 | hint = group[decimal]; 426 | } else if (this.opt.halfShow || this.opt.half) { 427 | decimal = set && decimal === 0 ? 1 : decimal > 5 ? 1 : 0; 428 | 429 | hint = group[decimal]; 430 | } 431 | 432 | return hint === '' ? '' : hint || score; 433 | }, 434 | 435 | _getWidth: function() { 436 | var width = this.stars[0].width || parseFloat(this.stars.eq(0).css('font-size')); 437 | 438 | if (!width) { 439 | methods._error.call(this, 'Could not get the icon width!'); 440 | } 441 | 442 | return width; 443 | }, 444 | 445 | _lock: function() { 446 | var hint = methods._getHint.call(this, this.score.val()); 447 | 448 | this.style.cursor = ''; 449 | this.title = hint; 450 | 451 | this.score.prop('readonly', true); 452 | this.stars.prop('title', hint); 453 | 454 | if (this.cancel) { 455 | this.cancel.hide(); 456 | } 457 | 458 | this.self.data('readonly', true); 459 | }, 460 | 461 | _nameForIndex: function(i) { 462 | return this.opt.score && this.opt.score >= i ? 'starOn' : 'starOff'; 463 | }, 464 | 465 | _resetTitle: function() { 466 | for (var i = 0; i < this.opt.number; i++) { 467 | this.stars[i].title = methods._getHint.call(this, i + 1); 468 | } 469 | }, 470 | 471 | _roundHalfScore: function(score) { 472 | var 473 | integer = parseInt(score, 10), 474 | decimal = methods._getFirstDecimal.call(this, score); 475 | 476 | if (decimal !== 0) { 477 | decimal = decimal > 5 ? 1 : 0.5; 478 | } 479 | 480 | return integer + decimal; 481 | }, 482 | 483 | _roundStars: function(score, evt) { 484 | var 485 | decimal = (score % 1).toFixed(2), 486 | name ; 487 | 488 | if (evt || this.move) { 489 | name = decimal > 0.5 ? 'starOn' : 'starHalf'; 490 | } else if (decimal > this.opt.round.down) { // Up: [x.76 .. x.99] 491 | name = 'starOn'; 492 | 493 | if (this.opt.halfShow && decimal < this.opt.round.up) { // Half: [x.26 .. x.75] 494 | name = 'starHalf'; 495 | } else if (decimal < this.opt.round.full) { // Down: [x.00 .. x.5] 496 | name = 'starOff'; 497 | } 498 | } 499 | 500 | if (name) { 501 | var 502 | icon = this.opt[name], 503 | star = this.stars[Math.ceil(score) - 1]; 504 | 505 | methods._setIcon.call(this, star, icon); 506 | } // Full down: [x.00 .. x.25] 507 | }, 508 | 509 | _setIcon: function(star, icon) { 510 | star[this.opt.starType === 'img' ? 'src' : 'className'] = this.opt.path + icon; 511 | }, 512 | 513 | _setTarget: function(target, score) { 514 | if (score) { 515 | score = this.opt.targetFormat.toString().replace('{score}', score); 516 | } 517 | 518 | if (target.is(':input')) { 519 | target.val(score); 520 | } else { 521 | target.html(score); 522 | } 523 | }, 524 | 525 | _setTitle: function(score, evt) { 526 | if (score) { 527 | var 528 | integer = parseInt(Math.ceil(score), 10), 529 | star = this.stars[integer - 1]; 530 | 531 | star.title = methods._getHint.call(this, score, evt); 532 | } 533 | }, 534 | 535 | _target: function(score, evt) { 536 | if (this.opt.target) { 537 | var target = $(this.opt.target); 538 | 539 | if (!target.length) { 540 | methods._error.call(this, 'Target selector invalid or missing!'); 541 | } 542 | 543 | var mouseover = evt && evt.type === 'mouseover'; 544 | 545 | if (score === undefined) { 546 | score = this.opt.targetText; 547 | } else if (score === null) { 548 | score = mouseover ? this.opt.cancelHint : this.opt.targetText; 549 | } else { 550 | if (this.opt.targetType === 'hint') { 551 | score = methods._getHint.call(this, score, evt); 552 | } else if (this.opt.precision) { 553 | score = parseFloat(score).toFixed(1); 554 | } 555 | 556 | var mousemove = evt && evt.type === 'mousemove'; 557 | 558 | if (!mouseover && !mousemove && !this.opt.targetKeep) { 559 | score = this.opt.targetText; 560 | } 561 | } 562 | 563 | methods._setTarget.call(this, target, score); 564 | } 565 | }, 566 | 567 | _turnOn: function(i, score) { 568 | return this.opt.single ? (i === score) : (i <= score); 569 | }, 570 | 571 | _unlock: function() { 572 | this.style.cursor = 'pointer'; 573 | this.removeAttribute('title'); 574 | 575 | this.score.removeAttr('readonly'); 576 | 577 | this.self.data('readonly', false); 578 | 579 | for (var i = 0; i < this.opt.number; i++) { 580 | this.stars[i].title = methods._getHint.call(this, i + 1); 581 | } 582 | 583 | if (this.cancel) { 584 | this.cancel.css('display', ''); 585 | } 586 | }, 587 | 588 | cancel: function(click) { 589 | return this.each(function() { 590 | var self = $(this); 591 | 592 | if (self.data('readonly') !== true) { 593 | methods[click ? 'click' : 'score'].call(self, null); 594 | 595 | this.score.removeAttr('value'); 596 | } 597 | }); 598 | }, 599 | 600 | click: function(score) { 601 | return this.each(function() { 602 | if ($(this).data('readonly') !== true) { 603 | score = methods._adjustedScore.call(this, score); 604 | 605 | methods._apply.call(this, score); 606 | 607 | if (this.opt.click) { 608 | this.opt.click.call(this, score, $.Event('click')); 609 | } 610 | 611 | methods._target.call(this, score); 612 | } 613 | }); 614 | }, 615 | 616 | destroy: function() { 617 | return this.each(function() { 618 | var 619 | self = $(this), 620 | raw = self.data('raw'); 621 | 622 | if (raw) { 623 | self.off('.raty').empty().css({ cursor: raw.style.cursor }).removeData('readonly'); 624 | } else { 625 | self.data('raw', self.clone()[0]); 626 | } 627 | }); 628 | }, 629 | 630 | getScore: function() { 631 | var 632 | score = [], 633 | value ; 634 | 635 | this.each(function() { 636 | value = this.score.val(); 637 | 638 | score.push(value ? +value : undefined); 639 | }); 640 | 641 | return (score.length > 1) ? score : score[0]; 642 | }, 643 | 644 | move: function(score) { 645 | return this.each(function() { 646 | var 647 | integer = parseInt(score, 10), 648 | decimal = methods._getFirstDecimal.call(this, score); 649 | 650 | if (integer >= this.opt.number) { 651 | integer = this.opt.number - 1; 652 | decimal = 10; 653 | } 654 | 655 | var 656 | width = methods._getWidth.call(this), 657 | steps = width / 10, 658 | star = $(this.stars[integer]), 659 | percent = star.offset().left + steps * decimal, 660 | evt = $.Event('mousemove', { pageX: percent }); 661 | 662 | this.move = true; 663 | 664 | star.trigger(evt); 665 | 666 | this.move = false; 667 | }); 668 | }, 669 | 670 | readOnly: function(readonly) { 671 | return this.each(function() { 672 | var self = $(this); 673 | 674 | if (self.data('readonly') !== readonly) { 675 | if (readonly) { 676 | self.off('.raty').children(this.opt.starType).off('.raty'); 677 | 678 | methods._lock.call(this); 679 | } else { 680 | methods._binds.call(this); 681 | methods._unlock.call(this); 682 | } 683 | 684 | self.data('readonly', readonly); 685 | } 686 | }); 687 | }, 688 | 689 | reload: function() { 690 | return methods.set.call(this, {}); 691 | }, 692 | 693 | score: function() { 694 | var self = $(this); 695 | 696 | return arguments.length ? methods.setScore.apply(self, arguments) : methods.getScore.call(self); 697 | }, 698 | 699 | set: function(options) { 700 | return this.each(function() { 701 | $(this).raty($.extend({}, this.opt, options)); 702 | }); 703 | }, 704 | 705 | setScore: function(score) { 706 | return this.each(function() { 707 | if ($(this).data('readonly') !== true) { 708 | score = methods._adjustedScore.call(this, score); 709 | 710 | methods._apply.call(this, score); 711 | methods._target.call(this, score); 712 | } 713 | }); 714 | } 715 | }; 716 | 717 | $.fn.raty = function(method) { 718 | if (methods[method]) { 719 | return methods[method].apply(this, Array.prototype.slice.call(arguments, 1)); 720 | } else if (typeof method === 'object' || !method) { 721 | return methods.init.apply(this, arguments); 722 | } else { 723 | $.error('Method ' + method + ' does not exist!'); 724 | } 725 | }; 726 | 727 | $.fn.raty.defaults = { 728 | cancel: false, 729 | cancelClass: 'raty-cancel', 730 | cancelHint: 'Cancel this rating!', 731 | cancelOff: 'cancel-off.png', 732 | cancelOn: 'cancel-on.png', 733 | cancelPlace: 'left', 734 | click: undefined, 735 | half: false, 736 | halfShow: true, 737 | hints: ['bad', 'poor', 'regular', 'good', 'gorgeous'], 738 | iconRange: undefined, 739 | mouseout: undefined, 740 | mouseover: undefined, 741 | noRatedMsg: 'Not rated yet!', 742 | number: 5, 743 | numberMax: 20, 744 | path: undefined, 745 | precision: false, 746 | readOnly: false, 747 | round: { down: 0.25, full: 0.6, up: 0.76 }, 748 | score: undefined, 749 | scoreName: 'score', 750 | single: false, 751 | space: true, 752 | starHalf: 'star-half.png', 753 | starOff: 'star-off.png', 754 | starOn: 'star-on.png', 755 | starType: 'img', 756 | target: undefined, 757 | targetFormat: '{score}', 758 | targetKeep: false, 759 | targetScore: undefined, 760 | targetText: '', 761 | targetType: 'hint' 762 | }; 763 | })(jQuery); 764 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/js/jquery.raty.min.js: -------------------------------------------------------------------------------- 1 | /*! 2 | * jQuery Raty - A Star Rating Plugin 3 | * 4 | * Licensed under The MIT License 5 | * 6 | * @version 2.5.2 7 | * @author Washington Botelho 8 | * @documentation wbotelhos.com/raty 9 | * 10 | */ 11 | 12 | ;(function(b){var a={init:function(c){return this.each(function(){a.destroy.call(this);this.opt=b.extend(true,{},b.fn.raty.defaults,c);var e=b(this),g=["number","readOnly","score","scoreName"];a._callback.call(this,g);if(this.opt.precision){a._adjustPrecision.call(this);}this.opt.number=a._between(this.opt.number,0,this.opt.numberMax);this.opt.path=this.opt.path||"";if(this.opt.path&&this.opt.path.slice(this.opt.path.length-1,this.opt.path.length)!=="/"){this.opt.path+="/";}this.stars=a._createStars.call(this);this.score=a._createScore.call(this);a._apply.call(this,this.opt.score);var f=this.opt.space?4:0,d=this.opt.width||(this.opt.number*this.opt.size+this.opt.number*f);if(this.opt.cancel){this.cancel=a._createCancel.call(this);d+=(this.opt.size+f);}if(this.opt.readOnly){a._lock.call(this);}else{e.css("cursor","pointer");a._binds.call(this);}if(this.opt.width!==false){e.css("width",d);}a._target.call(this,this.opt.score);e.data({settings:this.opt,raty:true});});},_adjustPrecision:function(){this.opt.targetType="score";this.opt.half=true;},_apply:function(c){if(c&&c>0){c=a._between(c,0,this.opt.number);this.score.val(c);}a._fill.call(this,c);if(c){a._roundStars.call(this,c);}},_between:function(e,d,c){return Math.min(Math.max(parseFloat(e),d),c);},_binds:function(){if(this.cancel){a._bindCancel.call(this);}a._bindClick.call(this);a._bindOut.call(this);a._bindOver.call(this);},_bindCancel:function(){a._bindClickCancel.call(this);a._bindOutCancel.call(this);a._bindOverCancel.call(this);},_bindClick:function(){var c=this,d=b(c);c.stars.on("click.raty",function(e){c.score.val((c.opt.half||c.opt.precision)?d.data("score"):this.alt);if(c.opt.click){c.opt.click.call(c,parseFloat(c.score.val()),e);}});},_bindClickCancel:function(){var c=this;c.cancel.on("click.raty",function(d){c.score.removeAttr("value");if(c.opt.click){c.opt.click.call(c,null,d);}});},_bindOut:function(){var c=this;b(this).on("mouseleave.raty",function(d){var e=parseFloat(c.score.val())||undefined;a._apply.call(c,e);a._target.call(c,e,d);if(c.opt.mouseout){c.opt.mouseout.call(c,e,d);}});},_bindOutCancel:function(){var c=this;c.cancel.on("mouseleave.raty",function(d){b(this).attr("src",c.opt.path+c.opt.cancelOff);if(c.opt.mouseout){c.opt.mouseout.call(c,c.score.val()||null,d);}});},_bindOverCancel:function(){var c=this;c.cancel.on("mouseover.raty",function(d){b(this).attr("src",c.opt.path+c.opt.cancelOn);c.stars.attr("src",c.opt.path+c.opt.starOff);a._target.call(c,null,d);if(c.opt.mouseover){c.opt.mouseover.call(c,null);}});},_bindOver:function(){var c=this,d=b(c),e=c.opt.half?"mousemove.raty":"mouseover.raty";c.stars.on(e,function(g){var h=parseInt(this.alt,10);if(c.opt.half){var f=parseFloat((g.pageX-b(this).offset().left)/c.opt.size),j=(f>0.5)?1:0.5;h=h-1+j;a._fill.call(c,h);if(c.opt.precision){h=h-j+f;}a._roundStars.call(c,h);d.data("score",h);}else{a._fill.call(c,h);}a._target.call(c,h,g);if(c.opt.mouseover){c.opt.mouseover.call(c,h,g);}});},_callback:function(c){for(i in c){if(typeof this.opt[c[i]]==="function"){this.opt[c[i]]=this.opt[c[i]].call(this);}}},_createCancel:function(){var e=b(this),c=this.opt.path+this.opt.cancelOff,d=b("",{src:c,alt:"x",title:this.opt.cancelHint,"class":"raty-cancel"});if(this.opt.cancelPlace=="left"){e.prepend(" ").prepend(d);}else{e.append(" ").append(d);}return d;},_createScore:function(){return b("",{type:"hidden",name:this.opt.scoreName}).appendTo(this);},_createStars:function(){var e=b(this);for(var c=1;c<=this.opt.number;c++){var f=a._getHint.call(this,c),d=(this.opt.score&&this.opt.score>=c)?"starOn":"starOff";d=this.opt.path+this.opt[d];b("",{src:d,alt:c,title:f}).appendTo(this);if(this.opt.space){e.append((ce){var j=m.opt.iconRange[e],h=j.on||m.opt.starOn,c=j.off||m.opt.starOff,k=l?h:c;if(f<=j.range){g.attr("src",m.opt.path+k);}if(f==j.range){e++;}}else{var k=l?"starOn":"starOff";g.attr("src",this.opt.path+this.opt[k]);}}},_getHint:function(d){var c=this.opt.hints[d-1];return(c==="")?"":(c||d);},_lock:function(){var d=parseInt(this.score.val(),10),c=d?a._getHint.call(this,d):this.opt.noRatedMsg;b(this).data("readonly",true).css("cursor","").attr("title",c);this.score.attr("readonly","readonly");this.stars.attr("title",c);if(this.cancel){this.cancel.hide();}},_roundStars:function(e){var d=(e-Math.floor(e)).toFixed(2);if(d>this.opt.round.down){var c="starOn";if(this.opt.halfShow&&d1)?d:d[0];},readOnly:function(c){return this.each(function(){var d=b(this);if(d.data("readonly")!==c){if(c){d.off(".raty").children("img").off(".raty");a._lock.call(this);}else{a._binds.call(this);a._unlock.call(this);}d.data("readonly",c);}});},reload:function(){return a.set.call(this,{});},score:function(){return arguments.length?a.setScore.apply(this,arguments):a.getScore.call(this);},set:function(c){return this.each(function(){var e=b(this),f=e.data("settings"),d=b.extend({},f,c);e.raty(d);});},setScore:function(c){return b(this).each(function(){if(b(this).data("readonly")!==true){a._apply.call(this,c);a._target.call(this,c);}});}};b.fn.raty=function(c){if(a[c]){return a[c].apply(this,Array.prototype.slice.call(arguments,1));}else{if(typeof c==="object"||!c){return a.init.apply(this,arguments);}else{b.error("Method "+c+" does not exist!");}}};b.fn.raty.defaults={cancel:false,cancelHint:"Cancel this rating!",cancelOff:"cancel-off.png",cancelOn:"cancel-on.png",cancelPlace:"left",click:undefined,half:false,halfShow:true,hints:["bad","poor","regular","good","gorgeous"],iconRange:undefined,mouseout:undefined,mouseover:undefined,noRatedMsg:"Not rated yet!",number:5,numberMax:20,path:"",precision:false,readOnly:false,round:{down:0.25,full:0.6,up:0.76},score:undefined,scoreName:"score",single:false,size:16,space:true,starHalf:"star-half.png",starOff:"star-off.png",starOn:"star-on.png",target:undefined,targetFormat:"{score}",targetKeep:false,targetText:"",targetType:"hint",width:undefined};})(jQuery); 13 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/js/jquery.star-rating-svg.js: -------------------------------------------------------------------------------- 1 | /* 2 | * jQuery StarRatingSvg v0.9.5 3 | * 4 | * http://github.com/nashio/star-rating-svg 5 | * Author: Ignacio Chavez 6 | * Licensed under MIT 7 | */ 8 | 9 | ;(function ( $, window, document, undefined ) { 10 | 11 | 'use strict'; 12 | 13 | // Create the defaults once 14 | var pluginName = 'starRating'; 15 | var defaults = { 16 | totalStars: 5, 17 | useFullStars: false, 18 | emptyColor: 'lightgray', 19 | hoverColor: 'orange', 20 | activeColor: 'gold', 21 | useGradient: true, 22 | readonly: false, 23 | disableAfterRate: true, 24 | starGradient: { 25 | start: '#FEF7CD', 26 | end: '#FF9511' 27 | }, 28 | strokeWidth: 0, 29 | strokeColor: 'black', 30 | initialRating: 0, 31 | starSize: 40 32 | }; 33 | 34 | // The actual plugin constructor 35 | var Plugin = function( element, options ) { 36 | var _rating; 37 | this.element = element; 38 | this.$el = $(element); 39 | this.settings = $.extend( {}, defaults, options ); 40 | 41 | // grab rating if defined on the element 42 | _rating = this.$el.data('rating') || this.settings.initialRating; 43 | this._state = { 44 | // round to the nearest half 45 | rating: (Math.round( _rating * 2 ) / 2).toFixed(1) 46 | }; 47 | 48 | // create unique id for stars 49 | this._uid = Math.floor( Math.random() * 999 ); 50 | 51 | // override gradient if not used 52 | if( !options.starGradient && !this.settings.useGradient ){ 53 | this.settings.starGradient.start = this.settings.starGradient.end = this.settings.activeColor; 54 | } 55 | 56 | this._defaults = defaults; 57 | this._name = pluginName; 58 | this.init(); 59 | }; 60 | 61 | var methods = { 62 | init: function () { 63 | this.renderMarkup(); 64 | this.addListeners(); 65 | this.initRating(); 66 | }, 67 | 68 | addListeners: function(){ 69 | if( this.settings.readOnly ){ return; } 70 | this.$stars.on('mouseover', this.hoverRating.bind(this)); 71 | this.$stars.on('mouseout', this.restoreState.bind(this)); 72 | this.$stars.on('click', this.applyRating.bind(this)); 73 | }, 74 | 75 | // apply styles to hovered stars 76 | hoverRating: function(e){ 77 | this.paintStars(this.getIndex(e), 'hovered'); 78 | }, 79 | 80 | // clicked on a rate, apply style and state 81 | applyRating: function(e){ 82 | var index = this.getIndex(e); 83 | var rating = index + 1; 84 | 85 | // paint selected and remove hovered color 86 | this.paintStars(index, 'active'); 87 | this.executeCallback( rating, this.$el ); 88 | this._state.rating = rating; 89 | 90 | if(this.settings.disableAfterRate){ 91 | this.$stars.off(); 92 | } 93 | }, 94 | 95 | restoreState: function(){ 96 | var rating = this._state.rating || -1; 97 | this.paintStars(rating - 1, 'active'); 98 | }, 99 | 100 | getIndex: function(e){ 101 | var $target = $(e.currentTarget); 102 | var width = $target.width(); 103 | var side = ( e.offsetX < (width / 2) && !this.settings.useFullStars) ? 'left' : 'right'; 104 | 105 | // get index for half or whole star 106 | var index = $target.index() - ((side === 'left') ? 0.5 : 0); 107 | 108 | // pointer is way to the left, rating should be none 109 | index = ( index < 0 && (e.offsetX < width / 5) ) ? -1 : index; 110 | return index; 111 | }, 112 | 113 | initRating: function(){ 114 | this.paintStars(this._state.rating - 1, 'active'); 115 | }, 116 | 117 | paintStars: function(endIndex, stateClass){ 118 | var $polygonLeft; 119 | var $polygonRight; 120 | var leftClass; 121 | var rightClass; 122 | 123 | $.each(this.$stars, function(index, star){ 124 | $polygonLeft = $(star).find('polygon[data-side="left"]'); 125 | $polygonRight = $(star).find('polygon[data-side="right"]'); 126 | leftClass = rightClass = (index <= endIndex) ? stateClass : 'empty'; 127 | 128 | // has another half rating, add half star 129 | leftClass = ( index - endIndex === 0.5 ) ? stateClass : leftClass; 130 | 131 | $polygonLeft.attr('class', 'svg-' + leftClass + '-' + this._uid); 132 | $polygonRight.attr('class', 'svg-' + rightClass + '-' + this._uid); 133 | 134 | }.bind(this)); 135 | }, 136 | 137 | renderMarkup: function () { 138 | // inject an svg manually to have control over attributes 139 | var star = '
' + 140 | this.getLinearGradient(this._uid + '_SVGID_1_', this.settings.emptyColor, this.settings.emptyColor) + 141 | this.getLinearGradient(this._uid + '_SVGID_2_', this.settings.hoverColor, this.settings.hoverColor) + 142 | this.getLinearGradient(this._uid + '_SVGID_3_', this.settings.starGradient.start, this.settings.starGradient.end) + 143 | '' + 144 | '' + 145 | '
'; 146 | 147 | // inject svg markup 148 | var starsMarkup = ''; 149 | for( var i = 0; i < this.settings.totalStars; i++){ 150 | starsMarkup += star; 151 | } 152 | this.$el.append(starsMarkup); 153 | this.$stars = this.$el.find('.jq-star'); 154 | }, 155 | 156 | getLinearGradient: function(id, startColor, endColor){ 157 | return ' '; 158 | }, 159 | 160 | executeCallback: function(rating, $el){ 161 | var callback = this.settings.callback; 162 | if( $.isFunction( callback ) ){ 163 | callback(rating, $el); 164 | } 165 | } 166 | 167 | }; 168 | 169 | var publicMethods = { 170 | 171 | unload: function(){ 172 | var _name = 'plugin_' + pluginName; 173 | var $el = $(this); 174 | var $star = $el.data(_name).$star; 175 | $el.removeData(_name); 176 | $star.off(); 177 | } 178 | 179 | }; 180 | 181 | 182 | // Avoid Plugin.prototype conflicts 183 | $.extend(Plugin.prototype, methods); 184 | 185 | $.fn[ pluginName ] = function ( options ) { 186 | 187 | // if options is a public method 188 | if( !$.isPlainObject(options) ){ 189 | if( publicMethods.hasOwnProperty(options) ){ 190 | publicMethods[options].apply(this); 191 | return; 192 | } 193 | } 194 | 195 | return this.each(function() { 196 | // preventing against multiple instantiations 197 | if ( !$.data( this, 'plugin_' + pluginName ) ) { 198 | $.data( this, 'plugin_' + pluginName, new Plugin( this, options ) ); 199 | } 200 | }); 201 | }; 202 | 203 | })( jQuery, window, document ); 204 | 205 | 206 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/js/npm.js: -------------------------------------------------------------------------------- 1 | // This file is autogenerated via the `commonjs` Grunt task. You can require() this file in a CommonJS environment. 2 | require('../../js/transition.js') 3 | require('../../js/alert.js') 4 | require('../../js/button.js') 5 | require('../../js/carousel.js') 6 | require('../../js/collapse.js') 7 | require('../../js/dropdown.js') 8 | require('../../js/modal.js') 9 | require('../../js/tooltip.js') 10 | require('../../js/popover.js') 11 | require('../../js/scrollspy.js') 12 | require('../../js/tab.js') 13 | require('../../js/affix.js') -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/js/starScore.js: -------------------------------------------------------------------------------- 1 | function scoreFun(object,opts){ 2 | // 默认属性 3 | var defaults={ 4 | fen_d:6, // 每个a的宽度 5 | ScoreGrade:10, // a的个数 6 | types:["喜欢", 7 | "还行", 8 | "不喜欢"], 9 | nameScore:"fenshu", 10 | parent:"star_score"}; 11 | options=$.extend({},defaults,opts); 12 | var countScore=object.find("."+options.nameScore); // 找到名为“fenshu”的类 13 | var startParent=object.find("."+options.parent); // 找到名为“star_score”的类 14 | var now_cli; 15 | var fen_cli; 16 | var atu; 17 | var fen_d=options.fen_d; // 每个a的宽度 18 | var len=options.ScoreGrade; // 把a的个数赋值给len 19 | startParent.width(fen_d*len); //包含a的div盒子的宽度 20 | var preA=(5/len); 21 | for(var i=0;i"); // 不整体刷新页面的情况下，可以使用void(0) 23 | newSpan.css({"left":0,"width":fen_d*(i+1),"z-index":len-i}); // 设置a的宽度、层级 24 | newSpan.appendTo(startParent) 25 | } // 把a放到类名为“star_score”的div里 26 | startParent.find("a").each( // each（）方法 27 | function(index,element){ 28 | $(this).click(function(){ // 点击事件 29 | now_cli=index; // 当前a的索引值 30 | show(index,$(this)) // 调用show方法 31 | }); 32 | $(this).mouseenter(function(){ /* mouseenter事件(与 mouseover 事件不同，只有在鼠标指针穿过被选元素时， 33 | 才会触发 mouseenter 事件。如果鼠标指针穿过任何子元素，同样会触发 mouseover 事件。) */ 34 | show(index,$(this)) 35 | }); 36 | $(this).mouseleave(function(){ // mouseleave事件 37 | if(now_cli>=0){ 38 | var scor=preA*(parseInt(now_cli)+1); // 评分 39 | startParent.find("a").removeClass("clibg"); // 清除a的“clibg”类 40 | startParent.find("a").eq(now_cli).addClass("clibg"); // eq()选择器，选取索引值为“now_cli”的a，给它加上“clibg”类 41 | var ww=fen_d*(parseInt(now_cli)+1); // 当前a的宽度 42 | startParent.find("a").eq(now_cli).css({"width":ww,"left":"0"}); // 给索引值为“now_cli”的a加上宽度“ww”和left值 43 | if(countScore){ 44 | countScore.text(scor) 45 | } 46 | }else{ 47 | startParent.find("a").removeClass("clibg"); 48 | if(countScore){ 49 | countScore.text("") 50 | } 51 | } 52 | }) 53 | }); 54 | 55 | // show方法 56 | function show(num,obj){ 57 | var n=parseInt(num)+1; 58 | var lefta=num*fen_d; 59 | var ww=fen_d*n; 60 | var scor=preA*n; // 评分 61 | object.find("a").removeClass("clibg"); // 清除所有a的“clibg”类 62 | obj.addClass("clibg"); // 给当前a添加“clibg”类 63 | obj.css({"width":ww,"left":"0"}); // 给当前a添加宽度“ww”和left值 64 | countScore.text(scor); // 显示评分 65 | } 66 | }; -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/users_resulttable.csv: -------------------------------------------------------------------------------- 1 | 1001,1372692,5.0 2 | 1001,1187043,4.5 3 | 1002,1372692,4.0 4 | 1002,2186715,3.5 5 | 1002,1229238,4.0 6 | 1002,3540136,4.5 7 | 1001,2414370,4.5 8 | 1001,1187043,4.0 9 | 1001,4600952,3.5 10 | 1002,4644382,3.5 11 | 1002,113198,4.0 12 | 1002,111161,4.0 13 | 1003,1187043,4.5 14 | 1003,188766,5.0 15 | 1003,5290882,4.5 16 | 1003,105859,5.0 17 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/static/users_resulttable2.csv: -------------------------------------------------------------------------------- 1 | 1001,1372692,5.0 2 | 1001,1187043,4.5 3 | 1002,1372692,4.0 4 | 1002,2186715,3.5 5 | 1002,1229238,4.0 6 | 1002,3540136,4.5 7 | 1001,2414370,4.5 8 | 1001,1187043,4.0 9 | 1001,4600952,3.5 10 | 1002,4644382,3.5 11 | 1002,113198,4.0 12 | 1002,111161,4.0 13 | 1003,1187043,4.5 14 | 1003,188766,5.0 15 | 1003,5290882,4.5 16 | 1003,105859,5.0 17 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/tests.py: -------------------------------------------------------------------------------- 1 | from django.test import TestCase 2 | 3 | # Create your tests here. 4 | -------------------------------------------------------------------------------- /项目源码/movierecommend/users/urls.py: -------------------------------------------------------------------------------- 1 | from django.conf.urls import url 2 | from . import views 3 | 4 | app_name = 'users' 5 | urlpatterns = [ 6 | url(r'^register/', views.register, name='register'), 7 | url(r'^showmessage/', views.showmessage, name='showmessage'), 8 | 9 | ] -------------------------------------------------------------------------------- /项目源码/movierecommend/users/views.py: -------------------------------------------------------------------------------- 1 | from django.shortcuts import render, redirect,HttpResponseRedirect 2 | from .forms import RegisterForm 3 | from users.models import Resulttable,Insertposter 4 | from django.db import models 5 | 6 | def register(request): 7 | # 只有当请求为 POST 时，才表示用户提交了注册信息 8 | if request.method == 'POST': 9 | form = RegisterForm(request.POST) 10 | 11 | # 验证数据的合法性 12 | if form.is_valid(): 13 | # 如果提交数据合法，调用表单的 save 方法将用户数据保存到数据库 14 | form.save() 15 | 16 | # 注册成功，跳转回首页 17 | return redirect('/') 18 | else: 19 | # 请求不是 POST，表明用户正在访问注册页面，展示一个空的注册表单给用户 20 | form = RegisterForm() 21 | 22 | # 渲染模板 23 | # 如果用户正在访问注册页面，则渲染的是一个空的注册表单 24 | # 如果用户通过表单提交注册信息，但是数据验证不合法，则渲染的是一个带有错误信息的表单 25 | return render(request, 'users/register.html', context={'form': form}) 26 | 27 | def index(request): 28 | return render(request, 'users/..//index.html') 29 | # 为啥？ 30 | 31 | def check(request): 32 | return render((request, 'users/..//index.html')) 33 | # def showregist(request): 34 | # pass 35 | 36 | 37 | def showmessage(request): 38 | usermovieid = [] 39 | usermovietitle = [] 40 | data=Resulttable.objects.filter(userId=1001) 41 | for row in data: 42 | usermovieid.append(row.imdbId) 43 | 44 | try: 45 | conn = get_conn() 46 | cur = conn.cursor() 47 | #Insertposter.objects.filter(userId=USERID).delete() 48 | for i in usermovieid: 49 | cur.execute('select * from moviegenre3 where imdbId = %s',i) 50 | rr = cur.fetchall() 51 | for imdbId,title,poster in rr: 52 | usermovietitle.append(title) 53 | print(title) 54 | 55 | # print(poster_result) 56 | finally: 57 | conn.close() 58 | return render(request, 'users/message.html', locals()) 59 | 60 | 61 | # USERID = 1002 62 | def recommend1(request): 63 | USERID = int(request.GET["userIdd"]) + 1000 64 | Insertposter.objects.filter(userId=USERID).delete() 65 | #selectMysql() 66 | read_mysql_to_csv('users/static/users_resulttable.csv',USERID) #追加数据，提高速率 67 | ratingfile = os.path.join('users/static', 'users_resulttable.csv') 68 | usercf = UserBasedCF() 69 | #userid = '1001' 70 | userid = str(USERID)#得到了当前用户的id 71 | print(userid) 72 | usercf.generate_dataset(ratingfile) 73 | usercf.calc_user_sim() 74 | usercf.recommend(userid) #得到imdbId号 75 | 76 | #先删除所有数据 77 | 78 | 79 | try: 80 | conn = get_conn() 81 | cur = conn.cursor() 82 | #Insertposter.objects.filter(userId=USERID).delete() 83 | for i in matrix: 84 | cur.execute('select * from moviegenre3 where imdbId = %s',i) 85 | rr = cur.fetchall() 86 | for imdbId,title,poster in rr: 87 | #print(value) #value才是真正的海报链接 88 | if(Insertposter.objects.filter(title=title)): 89 | continue 90 | else: 91 | Insertposter.objects.create(userId=USERID, title=title, poster=poster) 92 | 93 | # print(poster_result) 94 | finally: 95 | conn.close() 96 | #results = Insertposter.objects.all() #从这里传递给html= Insertposter.objects.all() # 从这里传递给html 97 | results = Insertposter.objects.filter(userId=USERID) 98 | return render(request,'users/movieRecommend.html', locals()) 99 | # return render(request, 'users/..//index.html', locals()) 100 | 101 | 102 | def recommend2(request): 103 | USERID = int(request.GET["userIddd"]) + 1000 104 | #USERID = 1001 105 | Insertposter.objects.filter(userId=USERID).delete() 106 | #selectMysql() 107 | #read_mysql_to_csv2('users/static/users_resulttable2.csv',USERID) #追加数据，提高速率 108 | read_mysql_to_csv2('users/static/users_resulttable2.csv') # 追加数据，提高速率 109 | ratingfile2 = os.path.join('users/static', 'users_resulttable2.csv') 110 | itemcf = ItemBasedCF() 111 | #userid = '1001' 112 | userid = str(USERID)#得到了当前用户的id 113 | print(userid) 114 | itemcf.generate_dataset(ratingfile2) 115 | itemcf.calc_movie_sim() 116 | itemcf.recommend(userid) #得到imdbId号 117 | 118 | #先删除所有数据 119 | 120 | 121 | try: 122 | conn = get_conn() 123 | cur = conn.cursor() 124 | #Insertposter.objects.filter(userId=USERID).delete() 125 | for i in matrix2: 126 | cur.execute('select * from moviegenre3 where imdbId = %s',i) 127 | rr = cur.fetchall() 128 | for imdbId,title,poster in rr: 129 | #print(value) #value才是真正的海报链接 130 | if(Insertposter.objects.filter(title=title)): 131 | continue 132 | else: 133 | Insertposter.objects.create(userId=USERID, title=title, poster=poster) 134 | 135 | # print(poster_result) 136 | finally: 137 | conn.close() 138 | results = Insertposter.objects.filter(userId=USERID) #从这里传递给html= Insertposter.objects.all() # 从这里传递给html 139 | 140 | return render(request, 'users/movieRecommend2.html',locals()) 141 | # return HttpResponseRedirect('movieRecommend.html', locals()) 142 | 143 | 144 | 145 | 146 | 147 | 148 | def insert(request): 149 | # MOVIEID = int(request.GET["movieId"]) 150 | global USERID 151 | USERID = int(request.GET["userId"])+1000 152 | # USERID = {{}} 153 | RATING = float(request.GET["rating"]) 154 | IMDBID = int(request.GET["imdbId"]) 155 | 156 | Resulttable.objects.create(userId=USERID, rating=RATING,imdbId=IMDBID) 157 | #print(USERID) 158 | # return HttpResponseRedirect('/') 159 | return render(request, 'index.html',{'userId':USERID,'rating':RATING,'imdbId':IMDBID}) 160 | 161 | 162 | 163 | import sys 164 | import random 165 | import os,math 166 | from operator import itemgetter 167 | import pymysql 168 | import csv 169 | from django.http import HttpResponse 170 | import codecs 171 | 172 | 173 | def get_conn(): 174 | conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='123456', db='haha', charset='utf8') 175 | return conn 176 | 177 | def query_all(cur, sql, args): 178 | cur.execute(sql, args) 179 | return cur.fetchall() 180 | 181 | def read_mysql_to_csv(filename,user): 182 | with codecs.open(filename=filename, mode='w', encoding='utf-8') as f: 183 | write = csv.writer(f, dialect='excel') 184 | conn = get_conn() 185 | cur = conn.cursor() 186 | cur.execute('select * from users_resulttable') 187 | #sql = ('select * from users_resulttable WHERE userId = 1001') 188 | rr = cur.fetchall() 189 | #results = query_all(cur=cur, sql=sql, args=None) 190 | for result in rr: 191 | #print(result) 192 | #write.writerow(result[:-1]) 193 | write.writerow(result[1:]) 194 | 195 | 196 | #def read_mysql_to_csv2(filename,user): 197 | def read_mysql_to_csv2(filename): 198 | #with codecs.open(filename=filename, mode='a', encoding='utf-8') as f: 199 | with codecs.open(filename=filename, mode='w', encoding='utf-8') as f: 200 | write = csv.writer(f, dialect='excel') 201 | conn = get_conn() 202 | cur = conn.cursor() 203 | cur.execute('select * from users_resulttable') 204 | #sql = ('select * from users_resulttable WHERE userId = 1001') 205 | sql = ('select * from users_resulttable') 206 | rr = cur.fetchall() 207 | results = query_all(cur=cur, sql=sql, args=None) 208 | for result in results: 209 | #print(result) 210 | #write.writerow(result[:-1]) 211 | write.writerow(result[1:]) 212 | 213 | 214 | 215 | 216 | 217 | # if __name__ == '__main__': 218 | # # main() 219 | # read_mysql_to_csv('../users/static/users_resulttable.csv') 220 | # 221 | 222 | 223 | import sys 224 | import random 225 | import math 226 | import os 227 | from operator import itemgetter 228 | 229 | random.seed(0) 230 | user_sim_mat = {} 231 | matrix = [] #全局变量 232 | matrix2 = [] 233 | 234 | class UserBasedCF(object): 235 | ''' TopN recommendation - User Based Collaborative Filtering ''' 236 | 237 | def __init__(self): 238 | self.trainset = {} # 训练集 239 | self.testset = {} # 测试集 240 | self.initialset = {} # 存储要推荐的用户的信息 241 | self.n_sim_user = 10 242 | self.n_rec_movie = 5 243 | 244 | self.movie_popular = {} 245 | self.movie_count = 0 # 总电影数量 246 | 247 | print('Similar user number = %d' % self.n_sim_user, file=sys.stderr) 248 | print('recommended movie number = %d' % 249 | self.n_rec_movie, file=sys.stderr) 250 | 251 | @staticmethod 252 | def loadfile(filename): 253 | ''' load a file, return a generator. ''' 254 | fp = open(filename, 'r', encoding='UTF-8') 255 | for i, line in enumerate(fp): 256 | yield line.strip('\r\n') 257 | # if i % 100000 == 0: 258 | # print ('loading %s(%s)' % (filename, i), file=sys.stderr) 259 | fp.close() 260 | print('load %s success' % filename, file=sys.stderr) 261 | 262 | def initial_dataset(self, filename1): 263 | initialset_len = 0 264 | for lines in self.loadfile(filename1): 265 | users, movies, ratings = lines.split(',') 266 | self.initialset.setdefault(users, {}) 267 | self.initialset[users][movies] = (ratings) 268 | initialset_len += 1 269 | 270 | def generate_dataset(self, filename2, pivot=1.0): 271 | ''' load rating data and split it to training set and test set ''' 272 | trainset_len = 0 273 | testset_len = 0 274 | 275 | for line in self.loadfile(filename2): 276 | # user, movie, rating, _ = line.split('::') 277 | user, movie, rating = line.split(',') 278 | # split the data by pivot 279 | if random.random() < pivot: # pivot=0.7应该表示训练集：测试集=7：3 280 | self.trainset.setdefault(user, {}) 281 | self.trainset[user][movie] = (rating) # trainset[user][movie]可以获取用户对电影的评分 都是整数 282 | trainset_len += 1 283 | else: 284 | self.testset.setdefault(user, {}) 285 | self.testset[user][movie] = (rating) 286 | testset_len += 1 287 | 288 | print('split training set and test set succ', file=sys.stderr) 289 | print('train set = %s' % trainset_len, file=sys.stderr) 290 | print('test set = %s' % testset_len, file=sys.stderr) 291 | 292 | def calc_user_sim(self): 293 | movie2users = dict() 294 | 295 | for user, movies in self.trainset.items(): 296 | for movie in movies: 297 | # inverse table for item-users 298 | if movie not in movie2users: 299 | movie2users[movie] = set() 300 | movie2users[movie].add(user) # 看这个电影的用户id 301 | # print(movie) #输出的是movieId 302 | # print(movie2users[movie]) #输出的是{'userId'...} 303 | # print(movie2users) #movieId:{'userId','userId'...} 304 | 305 | # count item popularity at the same time 306 | if movie not in self.movie_popular: 307 | self.movie_popular[movie] = 0 308 | self.movie_popular[movie] += 1 309 | # print ('build movie-users inverse table succ', file=sys.stderr) 310 | 311 | # save the total movie number, which will be used in evaluation 312 | self.movie_count = len(movie2users) 313 | print('total movie number = %d' % self.movie_count, file=sys.stderr) 314 | 315 | # count co-rated items between users 计算用户之间共同评分的物品 316 | usersim_mat = user_sim_mat 317 | # print ('building user co-rated movies matrix...', file=sys.stderr) 318 | 319 | for movie, users in movie2users.items(): # 通过.items()遍历movie2users这个字典里的所有键、值 320 | for u in users: 321 | for v in users: 322 | if u == v: 323 | continue 324 | usersim_mat.setdefault(u, {}) 325 | usersim_mat[u].setdefault(v, 0) 326 | usersim_mat[u][v] += 1 / math.log(1 + len(users)) # usersim_mat二维矩阵应该存的是用户u和用户v之间共同评分的电影数目 327 | # print ('build user co-rated movies matrix succ', file=sys.stderr) 328 | 329 | # calculate similarity matrix 330 | # print ('calculating user similarity matrix...', file=sys.stderr) 331 | simfactor_count = 0 332 | PRINT_STEP = 20000 333 | 334 | for u, related_users in usersim_mat.items(): 335 | for v, count in related_users.items(): 336 | usersim_mat[u][v] = count / math.sqrt( 337 | len(self.trainset[u]) * len(self.trainset[v])) 338 | simfactor_count += 1 339 | 340 | 341 | def recommend(self, user): 342 | ''' Find K similar users and recommend N movies. ''' 343 | matrix.clear() #每次都要清空 344 | K = self.n_sim_user # 这里等于20 345 | N = self.n_rec_movie # 这里等于10 346 | rank = dict() # 用户对电影的兴趣度 347 | # print(self.initialset[user]) 348 | watched_movies = self.trainset[user] # user用户已经看过的电影 只包括训练集里的 349 | # 这里之后不能是训练集 350 | # watched_movies = self.initialset[user] 351 | for similar_user, similarity_factor in sorted(user_sim_mat[user].items(), 352 | key=itemgetter(1), reverse=True)[ 353 | 0:K]: # itemgetter(1)表示对第2个域(相似度)排序 reverse=TRUE表示降序 354 | for imdbid in self.trainset[similar_user]: # similar_user是items里面的键，就是所有用户 similarity_factor是值，就是对应的相似度 355 | if imdbid in watched_movies: 356 | continue # 如果该电影用户已经看过，则跳过 357 | # predict the user's "interest" for each movie 358 | rank.setdefault(imdbid, 0) # 没有值就为0 359 | rank[imdbid] += similarity_factor #rank[movie]就是各个电影的相似度 360 | # 这里是把和各个用户的相似度加起来，而各个用户的相似度只是基于看过的公共电影数目除以这两个用户看过的电影数量积 361 | #print(rank[movie]) 362 | # return the N best movies 363 | # rank_ = dict() 364 | rank_ = sorted(rank.items(), key=itemgetter(1), reverse=True)[0:N] #类型是list不是字典了 365 | for key,value in rank_: 366 | matrix.append(key) #matrix为存储推荐的imdbId号的数组 367 | #print(key) #得到了推荐的电影的imdbid号 368 | print(matrix) 369 | #return sorted(rank.items(), key=itemgetter(1), reverse=True)[0:N] 370 | return matrix 371 | 372 | 373 | 374 | 375 | 376 | 377 | 378 | # class UserBasedCF(object): 379 | # ''' TopN recommendation - User Based Collaborative Filtering ''' 380 | # 381 | # def __init__(self): 382 | # self.trainset = {} # 训练集 383 | # self.testset = {} # 测试集 384 | # self.initialset = {} # 存储要推荐的用户的信息 385 | # self.n_sim_user = 50 386 | # self.n_rec_movie = 10 387 | # 388 | # self.movie_popular = {} 389 | # self.movie_count = 0 # 总电影数量 390 | # 391 | # print('Similar user number = %d' % self.n_sim_user, file=sys.stderr) 392 | # print('recommended movie number = %d' % 393 | # self.n_rec_movie, file=sys.stderr) 394 | # 395 | # @staticmethod 396 | # def loadfile(filename): 397 | # ''' load a file, return a generator. ''' 398 | # fp = open(filename, 'r', encoding='UTF-8') 399 | # for i, line in enumerate(fp): 400 | # yield line.strip('\r\n') 401 | # # if i % 100000 == 0: 402 | # # print ('loading %s(%s)' % (filename, i), file=sys.stderr) 403 | # fp.close() 404 | # print('load %s success' % filename, file=sys.stderr) 405 | # 406 | # def initial_dataset(self, filename1): 407 | # initialset_len = 0 408 | # for lines in self.loadfile(filename1): 409 | # users, movies, ratings = lines.split(',') 410 | # self.initialset.setdefault(users, {}) 411 | # self.initialset[users][movies] = (ratings) 412 | # initialset_len += 1 413 | # 414 | # def generate_dataset(self, filename2, pivot=0.7): 415 | # ''' load rating data and split it to training set and test set ''' 416 | # trainset_len = 0 417 | # testset_len = 0 418 | # 419 | # for line in self.loadfile(filename2): 420 | # # user, movie, rating, _ = line.split('::') 421 | # user, movie, rating = line.split(',') 422 | # # split the data by pivot 423 | # if random.random() < pivot: # pivot=0.7应该表示训练集：测试集=7：3 424 | # self.trainset.setdefault(user, {}) 425 | # self.trainset[user][movie] = (rating) # trainset[user][movie]可以获取用户对电影的评分 都是整数 426 | # trainset_len += 1 427 | # else: 428 | # self.testset.setdefault(user, {}) 429 | # self.testset[user][movie] = (rating) 430 | # testset_len += 1 431 | # 432 | # print('split training set and test set succ', file=sys.stderr) 433 | # print('train set = %s' % trainset_len, file=sys.stderr) 434 | # print('test set = %s' % testset_len, file=sys.stderr) 435 | # 436 | # def calc_user_sim(self): 437 | # ''' calculate user similarity matrix ''' 438 | # # build inverse table for item-users 439 | # # key=movieID, value=list of userIDs who have seen this movie 440 | # # print ('building movie-users inverse table...', file=sys.stderr) 441 | # movie2users = dict() 442 | # 443 | # for user, movies in self.trainset.items(): 444 | # for movie in movies: 445 | # # inverse table for item-users 446 | # if movie not in movie2users: 447 | # movie2users[movie] = set() 448 | # movie2users[movie].add(user) # 看这个电影的用户id 449 | # # print(movie) #输出的是movieId 450 | # # print(movie2users[movie]) #输出的是{'userId'...} 451 | # # print(movie2users) #movieId:{'userId','userId'...} 452 | # 453 | # # count item popularity at the same time 454 | # if movie not in self.movie_popular: 455 | # self.movie_popular[movie] = 0 456 | # self.movie_popular[movie] += 1 457 | # # print ('build movie-users inverse table succ', file=sys.stderr) 458 | # 459 | # # save the total movie number, which will be used in evaluation 460 | # self.movie_count = len(movie2users) 461 | # print('total movie number = %d' % self.movie_count, file=sys.stderr) 462 | # 463 | # # count co-rated items between users 计算用户之间共同评分的物品 464 | # usersim_mat = user_sim_mat 465 | # # print ('building user co-rated movies matrix...', file=sys.stderr) 466 | # 467 | # for movie, users in movie2users.items(): # 通过.items()遍历movie2users这个字典里的所有键、值 468 | # for u in users: 469 | # for v in users: 470 | # if u == v: 471 | # continue 472 | # usersim_mat.setdefault(u, {}) 473 | # usersim_mat[u].setdefault(v, 0) 474 | # usersim_mat[u][v] += 1 / math.log(1 + len(users)) # usersim_mat二维矩阵应该存的是用户u和用户v之间共同评分的电影数目 475 | # # print ('build user co-rated movies matrix succ', file=sys.stderr) 476 | # 477 | # # calculate similarity matrix 478 | # # print ('calculating user similarity matrix...', file=sys.stderr) 479 | # simfactor_count = 0 480 | # PRINT_STEP = 20000 481 | # 482 | # for u, related_users in usersim_mat.items(): 483 | # for v, count in related_users.items(): 484 | # usersim_mat[u][v] = count / math.sqrt( 485 | # len(self.trainset[u]) * len(self.trainset[v])) 486 | # simfactor_count += 1 487 | # # if simfactor_count % PRINT_STEP == 0: 488 | # # print ('calculating user similarity factor(%d)' % 489 | # # simfactor_count, file=sys.stderr) 490 | # 491 | # # print ('calculate user similarity matrix(similarity factor) succ', 492 | # # file=sys.stderr) 493 | # # print ('Total similarity factor number = %d' % 494 | # # simfactor_count, file=sys.stderr) 495 | # 496 | # 497 | # def recommend(self, user): 498 | # ''' Find K similar users and recommend N movies. ''' 499 | # matrix.clear() #每次都要清空 500 | # K = self.n_sim_user # 这里等于20 501 | # N = self.n_rec_movie # 这里等于10 502 | # rank = dict() # 用户对电影的兴趣度 503 | # # print(self.initialset[user]) 504 | # # print(self.trainset[user]) 505 | # watched_movies = self.trainset[user] # user用户已经看过的电影 只包括训练集里的 506 | # # 这里之后不能是训练集 507 | # # watched_movies = self.initialset[user] 508 | # for similar_user, similarity_factor in sorted(user_sim_mat[user].items(), 509 | # key=itemgetter(1), reverse=True)[ 510 | # 0:K]: # itemgetter(1)表示对第2个域(相似度)排序 reverse=TRUE表示降序 511 | # for imdbid in self.trainset[similar_user]: # similar_user是items里面的键，就是所有用户 similarity_factor是值，就是对应的相似度 512 | # if imdbid in watched_movies: 513 | # continue # 如果该电影用户已经看过，则跳过 514 | # # predict the user's "interest" for each movie 515 | # rank.setdefault(imdbid, 0) # 没有值就为0 516 | # rank[imdbid] += similarity_factor #rank[movie]就是各个电影的相似度 517 | # # 这里是把和各个用户的相似度加起来，而各个用户的相似度只是基于看过的公共电影数目除以这两个用户看过的电影数量积 518 | # #print(rank[movie]) 519 | # # return the N best movies 520 | # # rank_ = dict() 521 | # rank_ = sorted(rank.items(), key=itemgetter(1), reverse=True)[0:N] #类型是list不是字典了 522 | # for key,value in rank_: 523 | # matrix.append(key) #matrix为存储推荐的imdbId号的数组 524 | # #print(key) #得到了推荐的电影的imdbid号 525 | # print(matrix) 526 | # #return sorted(rank.items(), key=itemgetter(1), reverse=True)[0:N] 527 | # return matrix 528 | 529 | 530 | class ItemBasedCF(object): 531 | ''' TopN recommendation - Item Based Collaborative Filtering ''' 532 | 533 | def __init__(self): 534 | self.trainset = {} 535 | self.testset = {} 536 | 537 | self.n_sim_movie = 10 538 | self.n_rec_movie = 5 539 | 540 | self.movie_sim_mat = {} 541 | self.movie_popular = {} 542 | self.movie_count = 0 543 | 544 | # print('Similar movie number = %d' % self.n_sim_movie, file=sys.stderr) 545 | # print('Recommended movie number = %d' % 546 | # self.n_rec_movie, file=sys.stderr) 547 | 548 | @staticmethod 549 | def loadfile(filename): 550 | ''' load a file, return a generator. ''' 551 | # data1=np.loadtxt(filename,delimiter=',',dtype=float) 552 | fp = open(filename, 'r', encoding='UTF-8') 553 | for i, line in enumerate(fp): 554 | yield line.strip('\r\n') 555 | # if i % 100000 == 0: 556 | # print ('loading %s(%s)' % (filename, i), file=sys.stderr) 557 | fp.close() 558 | print('load %s succ' % filename, file=sys.stderr) 559 | 560 | def generate_dataset(self, filename, pivot=1.0): 561 | ''' load rating data and split it to training set and test set ''' 562 | trainset_len = 0 563 | testset_len = 0 564 | 565 | for line in self.loadfile(filename): 566 | user, movie, rating = line.split(',') 567 | # user, movie, rating = np.loadtxt(filename,delimiter=',') 568 | rating = float(rating) 569 | # print(type(rating)) 570 | 571 | # split the data by pivot 572 | if random.random() < pivot: 573 | self.trainset.setdefault(user, {}) 574 | 575 | self.trainset[user][movie] = float(rating) 576 | trainset_len += 1 577 | else: 578 | self.testset.setdefault(user, {}) 579 | 580 | self.testset[user][movie] = float(rating) 581 | testset_len += 1 582 | 583 | # print('split training set and test set succ', file=sys.stderr) 584 | print('train set = %s' % trainset_len, file=sys.stderr) 585 | # print('test set = %s' % testset_len, file=sys.stderr) 586 | 587 | def calc_movie_sim(self): 588 | ''' calculate movie similarity matrix ''' 589 | print('counting movies number and popularity...', file=sys.stderr) 590 | 591 | for user, movies in self.trainset.items(): 592 | for movie in movies: 593 | # count item popularity 594 | if movie not in self.movie_popular: 595 | self.movie_popular[movie] = 0 596 | self.movie_popular[movie] += 1 597 | 598 | # print('count movies number and popularity succ', file=sys.stderr) 599 | 600 | # save the total number of movies 601 | self.movie_count = len(self.movie_popular) 602 | print('total movie number = %d' % self.movie_count, file=sys.stderr) 603 | 604 | # count co-rated users between items 605 | itemsim_mat = self.movie_sim_mat 606 | # print('building co-rated users matrix...', file=sys.stderr) 607 | 608 | for user, movies in self.trainset.items(): 609 | for m1 in movies: 610 | for m2 in movies: 611 | if m1 == m2: 612 | continue 613 | itemsim_mat.setdefault(m1, {}) 614 | itemsim_mat[m1].setdefault(m2, 0) 615 | itemsim_mat[m1][m2] += 1 / math.log(1 + len(movies) * 1.0) 616 | 617 | #print('build co-rated users matrix succ', file=sys.stderr) 618 | 619 | # calculate similarity matrix 620 | #print('calculating movie similarity matrix...', file=sys.stderr) 621 | simfactor_count = 0 622 | PRINT_STEP = 2000000 623 | 624 | for m1, related_movies in itemsim_mat.items(): 625 | for m2, count in related_movies.items(): 626 | itemsim_mat[m1][m2] = count / math.sqrt( 627 | self.movie_popular[m1] * self.movie_popular[m2]) 628 | simfactor_count += 1 629 | if simfactor_count % PRINT_STEP == 0: 630 | print('calculating movie similarity factor(%d)' % 631 | simfactor_count, file=sys.stderr) 632 | 633 | #print('calculate movie similarity matrix(similarity factor) succ', 634 | # file=sys.stderr) 635 | #print('Total similarity factor number = %d' % 636 | #simfactor_count, file=sys.stderr) 637 | 638 | def recommend(self, user): 639 | ''' Find K similar movies and recommend N movies. ''' 640 | K = self.n_sim_movie 641 | N = self.n_rec_movie 642 | matrix2.clear() 643 | rank = {} 644 | watched_movies = self.trainset[user] 645 | 646 | for movie, rating in watched_movies.items(): 647 | for related_movie, similarity_factor in sorted(self.movie_sim_mat[movie].items(), 648 | key=itemgetter(1), reverse=True)[:K]: 649 | if related_movie in watched_movies: 650 | continue 651 | rank.setdefault(related_movie, 0) 652 | rank[related_movie] += similarity_factor * rating 653 | # return the N best movies 654 | #print(sorted(rank.items(), key=itemgetter(1), reverse=True)[:N]) 655 | rank_ = sorted(rank.items(), key=itemgetter(1), reverse=True)[:N] 656 | for key,value in rank_: 657 | matrix2.append(key) #matrix为存储推荐的imdbId号的数组 658 | #print(key) #得到了推荐的电影的imdbid号 659 | print(matrix2) 660 | #return sorted(rank.items(), key=itemgetter(1), reverse=True)[:N] 661 | return matrix2 662 | 663 | 664 | 665 | 666 | 667 | # 668 | if __name__ == '__main__': 669 | # ratingfile = os.path.join('ml-1m', 'ratings.dat') 670 | # ratingfile1 = os.path.join('ml-100k', 'insertusers.csv') 671 | ratingfile2 = os.path.join('static', 'users_resulttable.csv') # 一共671个用户 672 | #ratingfile2 = os.path.join('static', 'rrtotaltable.csv') 673 | 674 | usercf = UserBasedCF() 675 | userId = '1' 676 | # usercf.initial_dataset(ratingfile1) 677 | usercf.generate_dataset(ratingfile2) 678 | usercf.calc_user_sim() 679 | # usercf.evaluate() 680 | usercf.recommend(userId) # 给用户5推荐了10部电影 输出的是‘movieId’,兴趣度 109444、110148都是用户2已经看过并且评分为4的电影。 681 | # print(sorted(user_sim_mat['2'].items(),key=itemgetter(1), reverse=True)[0:20]) #输出的是{'useId':{'另一个userId':相似度,'其他userId':'相似度...'}}... 682 | #这里输的userId,是要从另一张储存登录用户的userid# 这里输的userId,是要从另一张储存登录用户的userid 683 | 684 | 685 | 686 | 687 | 688 | --------------------------------------------------------------------------------