{"id":282592,"date":"2022-09-29T04:00:00","date_gmt":"2022-09-29T03:00:00","guid":{"rendered":"https:\/\/blog.jetbrains.com\/datalore\/2022\/07\/14\/how-to-get-the-best-autocomplete-in-jupyter-notebooks-and-more\/"},"modified":"2022-09-28T07:17:34","modified_gmt":"2022-09-28T06:17:34","slug":"how-to-get-the-best-autocomplete-in-jupyter-notebooks-and-more","status":"publish","type":"datalore","link":"https:\/\/blog.jetbrains.com\/zh-hans\/datalore\/2022\/09\/29\/how-to-get-the-best-autocomplete-in-jupyter-notebooks-and-more\/","title":{"rendered":"\u5982\u4f55\u5728 Jupyter Notebook \u4e2d\u83b7\u5f97\u6700\u4f73\u81ea\u52a8\u8865\u5168\u7b49\u529f\u80fd"},"content":{"rendered":"\n

\u5728\u6ca1\u6709\u4efb\u4f55\u7f16\u7801\u8f85\u52a9\u7684\u201c\u7eaf\u6587\u672c\u201d\u98ce\u683c Jupyter Notebook \u4e2d\u7f16\u5199\u4ee3\u7801\u53ef\u80fd\u4f1a\u8ba9\u4eba\u611f\u5230\u4e0d\u77e5\u6240\u63aa\uff0c\u52bf\u5fc5\u4f1a\u5f71\u54cd\u6570\u636e\u79d1\u5b66\u5bb6\u7684\u5de5\u4f5c\u6548\u7387\u3002\u5728\u8fd9\u7bc7\u535a\u6587\u4e2d\uff0c\u6211\u4eec\u5c06\u4ecb\u7ecd 2 \u79cd\u65b9\u5f0f\u6765\u5f25\u8865\u8fd9\u79cd\u4e0d\u8db3\uff0c\u5e76\u5728\u60a8\u7684 Jupyter Notebook \u4e2d\u8bbf\u95ee\u81ea\u52a8\u8865\u5168\u548c\u5176\u4ed6\u7f16\u7801\u8f85\u52a9\u529f\u80fd\u3002<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u542f\u7528\u81ea\u52a8\u8865\u5168\u529f\u80fd<\/h2>\n\n\n\n

\u8981\u5728 Jupyter Notebook<\/strong> \u6216 JupyterLab<\/strong> \u4e2d\u542f\u7528\u4ee3\u7801\u81ea\u52a8\u8865\u5168\u529f\u80fd\uff0c\u53ea\u9700\u5728\u7f16\u5199\u4ee3\u7801\u65f6\u6309 Tab \u952e\u5373\u53ef\u3002Jupyter \u5c06\u63d0\u4f9b\u4e00\u4e9b\u8865\u5168\u9009\u9879\u5efa\u8bae\u3002\u4f7f\u7528\u65b9\u5411\u952e\u5bfc\u822a\u5230\u6240\u9700\u9009\u9879\uff0c\u7136\u540e\u6309 Enter \u952e\u9009\u62e9\u8be5\u5efa\u8bae\u3002<\/p>\n\n\n\n

\"\"
\u5728 Jupyter Notebook \u4e2d\u6309 Tab \u952e\u53ef\u4ee5\u542f\u7528\u4ee3\u7801\u81ea\u52a8\u8865\u5168<\/figcaption><\/figure>\n\n\n\n

\u5f88\u9057\u61be\uff0cJupyter \u4e0d\u652f\u6301\u81ea\u52a8\u8c03\u7528\u4ee3\u7801\u8865\u5168\u9009\u9879\uff0c\u8fd9\u610f\u5473\u7740\u60a8\u59cb\u7ec8\u9700\u8981\u6309 Tab \u952e\u3002<\/p>\n\n\n\n

\u4e3a\u907f\u514d\u8fd9\u79cd\u60c5\u51b5\uff0c\u60a8\u53ef\u4ee5\u8003\u8651\u5c1d\u8bd5 Datalore<\/a><\/strong> \u2013 \u4e00\u6b3e\u53ef\u4ee5\u5728\u7ebf\u514d\u8d39\u4f7f\u7528\u7684\u534f\u4f5c\u5f0f\u6570\u636e\u79d1\u5b66\u5e73\u53f0\u3002<\/p>\n\n\n\n

\"\"
Datalore \u4e2d\u7684\u4ee3\u7801\u8865\u5168<\/figcaption><\/figure>\n\n\n\n

Datalore<\/a> \u5c06\u81ea\u52a8<\/strong>\u8c03\u7528\u4ee3\u7801\u8865\u5168\u9009\u9879\uff0c\u5e76\u5728\u6307\u5b9a\u65b9\u6cd5\u5f62\u53c2\u65f6\u4e3a\u60a8\u63d0\u4f9b\u4e0a\u4e0b\u6587\u5e2e\u52a9<\/strong>\u3002\u5b83\u8fd8\u5305\u542b\u4e00\u4e9b\u5fae\u5c0f\u5374\u91cd\u8981\u7684\u529f\u80fd\uff0c\u4f8b\u5982\u5c06\u6587\u672c\u5149\u6807\u7f6e\u4e8e\u5706\u62ec\u53f7\u5185\uff0c\u4f7f\u60a8\u7684\u4ee3\u7801\u4e0d\u6613\u51fa\u9519\u3002<\/p>\n\n\n\n

Notebook \u73af\u5883\u5df2\u7ecf\u4e3a\u60a8\u9884\u88c5\u4e86\u70ed\u95e8\u6570\u636e\u79d1\u5b66\u8f6f\u4ef6\u5305\uff0c\u56e0\u6b64\u60a8\u53ef\u4ee5\u7acb\u5373\u5f00\u59cb\u5728 Datalore \u4e2d\u7f16\u5199\u4ee3\u7801\u3002<\/p>\n\n\n\n

\n \n \u8bd5\u7528 Datalore\n <\/a>\n<\/p>\n\n\n\n

\u83b7\u5f97\u6b63\u786e\u7684 Python \u4ee3\u7801\u7f29\u8fdb<\/h2>\n\n\n\n

\u5728 Python \u4e2d\uff0c\u7f29\u8fdb\u975e\u5e38\u91cd\u8981\u3002\u6211\u4eec\u770b\u4e00\u4e0b\u7b80\u5355\u7684 if<\/em> \u5b50\u53e5\u7684\u7f29\u8fdb\u662f\u5982\u4f55\u5de5\u4f5c\u7684\u3002<\/p>\n\n\n\n

\u5728\u4e0b\u9762\u7684\u793a\u4f8b\u4e2d\uff0cJupyterLab \u4f7f\u7528\u4e86\u9519\u8bef\u7684\u7f29\u8fdb\uff0c\u5bfc\u81f4\u6267\u884c\u5355\u5143\u65f6\u51fa\u9519\uff1a<\/p>\n\n\n\n

\"\"
Python \u4e2d\u7f29\u8fdb\u7684\u91cd\u8981\u6027<\/figcaption><\/figure>\n\n\n\n

Datalore<\/a><\/strong> \u4f1a\u81ea\u52a8\u66f4\u6b63\u7f29\u8fdb\uff0c\u786e\u4fdd\u60a8\u7684\u4ee3\u7801\u5728\u6267\u884c\u65f6\u4e0d\u4f1a\u51fa\u9519\u3002<\/p>\n\n\n\n

\"\"
Datalore \u4e2d\u7684\u81ea\u52a8 Python \u7f29\u8fdb<\/figcaption><\/figure>\n\n\n\n

\u83b7\u5f97\u4e0a\u4e0b\u6587\u5e2e\u52a9<\/h2>\n\n\n\n

\u5728 JupyterLab<\/strong> \u4e2d\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7\u9009\u62e9\u51fd\u6570\u5e76\u4f7f\u7528\u4e0a\u4e0b\u6587\u83dc\u5355\u6765\u83b7\u5f97\u4e0a\u4e0b\u6587\u5e2e\u52a9\u3002\u5f53\u60a8\u5c06\u9f20\u6807\u60ac\u505c\u5728\u4efb\u4f55\u51fd\u6570\/\u65b9\u6cd5\u4e0a\u65b9\u65f6\uff0cDatalore \u4f1a\u4e3a\u60a8\u63d0\u4f9b\u4e0a\u4e0b\u6587\u5e2e\u52a9\uff0c\u5b83\u8fd8\u4f1a\u5728\u60a8\u8f93\u5165\u4ee3\u7801\u65f6\u5b9e\u65f6\u63d0\u4f9b\u65b9\u6cd5\u5f62\u53c2\u5efa\u8bae\u3002<\/p>\n\n\n\n

\"\"\/
Jupyter \u4e0e Datalore \u4e2d\u7684\u4e0a\u4e0b\u6587\u6587\u6863\u5bf9\u6bd4<\/figcaption><\/figure>\n\n\n\n

Datalore \u4e2d\u7684\u5176\u4ed6\u4ee3\u7801\u7f16\u8f91\u529f\u80fd<\/h2>\n\n\n\n

\u5feb\u901f\u4fee\u590d<\/strong><\/p>\n\n\n\n

Datalore<\/a> \u63d0\u4f9b\u4e86\u591a\u79cd\u5feb\u901f\u4fee\u590d\uff0c\u4f8b\u5982 import \u4f18\u5316\uff0c\u53ef\u4ee5\u5e2e\u52a9\u60a8\u7684\u4ee3\u7801\u770b\u8d77\u6765\u66f4\u52a0\u4e13\u4e1a\u7b80\u6d01\u3002<\/p>\n\n\n\n

\"\"
Datalore \u4e2d\u7684 import \u4f18\u5316<\/figcaption><\/figure>\n\n\n\n

\u91cd\u6784<\/strong><\/p>\n\n\n\n

Datalore<\/a> \u652f\u6301\u4f7f\u7528\u4e0a\u4e0b\u6587\u83dc\u5355\u91cd\u547d\u540d\u53d8\u91cf\u548c\u51fd\u6570\u3002\u5b83\u5c06\u4ec5\u91cd\u547d\u540d\u53d8\u91cf\u6216\u51fd\u6570\uff0c\u800c\u76f8\u540c\u540d\u79f0\u7684\u6587\u672c\u8f93\u5165\u5c06\u4fdd\u6301\u4e0d\u53d8\u3002\u5728 JupyterLab \u4e2d\uff0c\u7ecf\u5178\u7684\u201c\u67e5\u627e\u5e76\u66ff\u6362\u201d\u529f\u80fd\u7684\u884c\u4e3a\u6709\u6240\u4e0d\u540c\uff1a\u5b83\u5c06\u66ff\u6362\u6240\u6709\u6761\u76ee\uff0c\u5c31\u50cf\u5728\u6587\u672c\u6587\u4ef6\u4e2d\u4e00\u6837\u3002<\/p>\n\n\n\n

\"\"\/
Datalore \u4e2d\u7684\u201c\u91cd\u547d\u540d\u201d\u91cd\u6784<\/figcaption><\/figure>\n\n\n\n

\u5728\u6267\u884c\u4ee3\u7801\u4e4b\u524d\u9ad8\u4eae\u663e\u793a\u9519\u8bef<\/strong><\/p>\n\n\n\n

\u4efb\u4f55\u4eba\u90fd\u4e0d\u60f3\u5728 Notebook \u4e2d\u770b\u5230\u7ea2\u8272\u7684\u9519\u8bef\u4fe1\u606f\u3002Datalore<\/a> \u5728\u6267\u884c\u5355\u5143\u4e4b\u524d\u5c06\u9ad8\u4eae\u663e\u793a\u9519\u8bef\uff0c\u8ba9\u60a8\u63d0\u524d\u4e86\u89e3\u4efb\u4f55\u6f5c\u5728\u95ee\u9898\u3002<\/p>\n\n\n\n

\"\"
Datalore \u4e2d\u7684\u9519\u8bef\u9ad8\u4eae\u663e\u793a<\/figcaption><\/figure>\n\n\n\n

SQL\u3001R\u3001Scala \u548c Kotlin \u4ee3\u7801\u81ea\u52a8\u8865\u5168<\/strong><\/p>\n\n\n\n

\u9664\u4e86 Python\uff0cDatalore<\/a> \u8fd8\u63d0\u4f9b\u4e86\u9488\u5bf9 SQL\u3001R\u3001Scala \u548c Kotlin \u7684\u4ee3\u7801\u8865\u5168\u548c\u8bed\u6cd5\u9ad8\u4eae\u663e\u793a\u529f\u80fd\u3002<\/p>\n\n\n\n

\u603b\u7ed3<\/h2>\n\n\n\n
<\/td>JupyterLab<\/strong><\/td>Datalore<\/a><\/strong><\/td><\/tr>
Python \u4ee3\u7801\u81ea\u52a8\u8865\u5168<\/td>\u901a\u8fc7\u6309 Tab \u624b\u52a8\u8c03\u7528\uff1b\u53ef\u4ee5\u901a\u8fc7 Jupyter \u63d2\u4ef6\u548c\u6269\u5c55\u7a0b\u5e8f\u63d0\u4f9b\u81ea\u52a8\u8c03\u7528<\/td>\u5f00\u7bb1\u81ea\u52a8\u8c03\u7528<\/td><\/tr>
SQL\u3001R\u3001Scala \u548c Kotlin \u4ee3\u7801\u81ea\u52a8\u8865\u5168<\/td>⛔️<\/td>✅<\/td><\/tr>
\u4e0a\u4e0b\u6587\u5e2e\u52a9<\/td>\u5728\u5355\u72ec\u7684\u9009\u9879\u5361\u4e2d<\/td>\u60ac\u505c\u65f6<\/td><\/tr>
\u5feb\u901f\u4fee\u590d\uff08\u4f8b\u5982\uff0c\u79fb\u9664\u672a\u4f7f\u7528\u7684 import\uff09<\/td>⛔️<\/td>✅<\/td><\/tr>
\u91cd\u6784\uff08\u4f8b\u5982\uff0c\u91cd\u547d\u540d\u53d8\u91cf\uff09<\/td>⛔️<\/td>✅<\/td><\/tr>
\u952e\u5165\u4ee3\u7801\u65f6\u7684\u65b9\u6cd5\u89c4\u8303<\/td>⛔️<\/td>✅<\/td><\/tr>
\u9519\u8bef\u9ad8\u4eae\u663e\u793a<\/td>⛔️<\/td>✅<\/td><\/tr>
\u4ee3\u7801\u7f29\u8fdb<\/td>\u6709\u65f6\u4e0d\u51c6\u786e\uff08\u8bf7\u53c2\u89c1\u4e0a\u65b9\u793a\u4f8b\uff09<\/td>✅<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6211\u4eec\u5e0c\u671b\u8fd9\u4e9b\u63d0\u793a\u80fd\u5e2e\u52a9\u60a8\u4eab\u53d7\u5230\u66f4\u597d\u7684\u4ee3\u7801\u7f16\u8f91\u4f53\u9a8c\uff0c\u8ba9\u60a8\u5728\u5206\u4eab\u5de5\u4f5c\u65f6\u66f4\u52a0\u81ea\u4fe1\u3002<\/p>\n\n\n\n

\n \n \u8bd5\u7528 Datalore\n <\/a>\n<\/p>\n\n\n\n

\u5982\u4f55\u8bd5\u7528 Datalore<\/h2>\n\n\n\n

\u5982\u679c\u60a8\u60f3\u81ea\u5df1\u4f7f\u7528 Datalore\uff0c\u8bf7\u5728\u7ebf\u6ce8\u518c\u4ee5\u83b7\u53d6 Datalore Community \u6216 Datalore Professional<\/a>\u3002\u60a8\u8fd8\u53ef\u4ee5\u901a\u8fc7 Enterprise \u65b9\u6848<\/a>\u5728\u60a8\u7684\u79c1\u6709\u4e91\u6216\u672c\u5730\u90e8\u7f72\u73af\u5883\u4e2d\u6258\u7ba1 Datalore\uff0c\u4f9b\u60a8\u7684\u56e2\u961f\u8bd5\u7528\u3002<\/p>\n\n\n\n

\u4eca\u5929\u7684\u6587\u7ae0\u5c31\u5230\u8fd9\u91cc\uff01\u8bf7\u5173\u6ce8\u6211\u4eec\u7684\u535a\u5ba2<\/a>\u4ee5\u83b7\u53d6\u5b9e\u7528\u63d0\u793a\uff0c\u4ee5\u53ca\u5fae\u4fe1\u516c\u4f17\u53f7\uff08ID: JetBrainsChina\uff09\/\u5fae\u535a<\/a>\/B\u7ad9<\/a>\u83b7\u53d6\u6700\u65b0\u52a8\u6001\uff01<\/p>\n\n\n\n

\u795d\u60a8\u6109\u5feb\u6295\u8eab\u6570\u636e\u79d1\u5b66\uff01<\/p>\n\n\n\n

Datalore \u56e2\u961f<\/p>\n\n\n\n

<\/h2>\n\n\n\n

\u672c\u535a\u6587\u82f1\u6587\u539f\u4f5c\u8005\uff1a<\/p>\n\n\n

\n
\n
\n
\n \"\"\n <\/div>\n
\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n","protected":false},"author":1297,"featured_media":264674,"comment_status":"closed","ping_status":"closed","template":"","categories":[947,1401,89],"tags":[603,7057],"cross-post-tag":[],"acf":[],"_links":{"self":[{"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/datalore\/282592"}],"collection":[{"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/datalore"}],"about":[{"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/types\/datalore"}],"author":[{"embeddable":true,"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/users\/1297"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/comments?post=282592"}],"version-history":[{"count":10,"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/datalore\/282592\/revisions"}],"predecessor-version":[{"id":282626,"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/datalore\/282592\/revisions\/282626"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/media\/264674"}],"wp:attachment":[{"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/media?parent=282592"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/categories?post=282592"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/tags?post=282592"},{"taxonomy":"cross-post-tag","embeddable":true,"href":"https:\/\/blog.jetbrains.com\/zh-hans\/wp-json\/wp\/v2\/cross-post-tag?post=282592"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}