{"id":477757,"date":"2023-08-09T09:19:52","date_gmt":"2023-08-09T09:19:52","guid":{"rendered":""},"modified":"2023-09-05T11:15:22","modified_gmt":"2023-09-05T11:15:22","slug":"jupyter-notebook","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/jupyter-notebook\/","title":{"rendered":"s\u1ed5 ghi ch\u00e9p Jupyter"},"content":{"rendered":"

Jupyter Notebook l\u00e0 m\u00f4i tr\u01b0\u1eddng \u0111i\u1ec7n to\u00e1n t\u01b0\u01a1ng t\u00e1c \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng r\u1ed9ng r\u00e3i \u0111\u1ec3 ph\u00e2n t\u00edch d\u1eef li\u1ec7u, nghi\u00ean c\u1ee9u khoa h\u1ecdc, h\u1ecdc m\u00e1y v\u00e0 gi\u00e1o d\u1ee5c. N\u00f3 cung c\u1ea5p giao di\u1ec7n d\u1ef1a tr\u00ean web cho ph\u00e9p ng\u01b0\u1eddi d\u00f9ng t\u1ea1o v\u00e0 chia s\u1ebb t\u00e0i li\u1ec7u ch\u1ee9a m\u00e3 tr\u1ef1c ti\u1ebfp, h\u00ecnh \u1ea3nh tr\u1ef1c quan, v\u0103n b\u1ea3n gi\u1ea3i th\u00edch v\u00e0 ph\u01b0\u01a1ng tr\u00ecnh to\u00e1n h\u1ecdc. Jupyter Notebook l\u00e0 m\u1ed9t c\u00f4ng c\u1ee5 linh ho\u1ea1t cho ph\u00e9p ng\u01b0\u1eddi d\u00f9ng kh\u00e1m ph\u00e1 v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u m\u1ed9t c\u00e1ch t\u01b0\u01a1ng t\u00e1c, khi\u1ebfn n\u00f3 tr\u1edf th\u00e0nh t\u00e0i s\u1ea3n thi\u1ebft y\u1ebfu cho c\u00e1c nh\u00e0 nghi\u00ean c\u1ee9u, nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u c\u0169ng nh\u01b0 nh\u00e0 ph\u00e1t tri\u1ec3n.<\/p>\n

L\u1ecbch s\u1eed v\u1ec1 ngu\u1ed3n g\u1ed1c c\u1ee7a Jupyter Notebook v\u00e0 l\u1ea7n \u0111\u1ea7u ti\u00ean \u0111\u1ec1 c\u1eadp \u0111\u1ebfn n\u00f3<\/h2>\n

Ngu\u1ed3n g\u1ed1c c\u1ee7a Jupyter Notebook b\u1eaft ngu\u1ed3n t\u1eeb d\u1ef1 \u00e1n IPython, do Fernando P\u00e9rez kh\u1edfi x\u01b0\u1edbng v\u00e0o n\u0103m 2001. IPython \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n d\u01b0\u1edbi d\u1ea1ng shell t\u01b0\u01a1ng t\u00e1c cho Python, cung c\u1ea5p c\u00e1c ch\u1ee9c n\u0103ng v\u00e0 c\u1ea3i ti\u1ebfn b\u1ed5 sung so v\u1edbi shell Python ti\u00eau chu\u1ea9n. D\u1ea7n d\u1ea7n, IPython ph\u00e1t tri\u1ec3n th\u00e0nh m\u1ed9t d\u1ef1 \u00e1n to\u00e0n di\u1ec7n v\u1ec1 \u0111i\u1ec7n to\u00e1n t\u01b0\u01a1ng t\u00e1c v\u00e0 v\u00e0o n\u0103m 2014, d\u1ef1 \u00e1n Jupyter ra \u0111\u1eddi.<\/p>\n

C\u00e1i t\u00ean \u201cJupyter\u201d l\u00e0 s\u1ef1 k\u1ebft h\u1ee3p c\u1ee7a ba ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh c\u1ed1t l\u00f5i: Julia, Python v\u00e0 R. Nh\u1eefng ng\u00f4n ng\u1eef n\u00e0y h\u00ecnh th\u00e0nh n\u00ean tr\u1ecdng t\u00e2m ban \u0111\u1ea7u c\u1ee7a Jupyter, nh\u01b0ng n\u1ec1n t\u1ea3ng n\u00e0y \u0111\u00e3 nhanh ch\u00f3ng m\u1edf r\u1ed9ng h\u1ed7 tr\u1ee3 cho nhi\u1ec1u ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh kh\u00e1c nhau th\u00f4ng qua h\u1ea1t nh\u00e2n, khi\u1ebfn n\u00f3 tr\u1edf th\u00e0nh m\u1ed9t c\u00f4ng c\u1ee5 c\u00f3 gi\u00e1 tr\u1ecb cho l\u1eadp tr\u00ecnh \u0111a ng\u00f4n ng\u1eef.<\/p>\n

Th\u00f4ng tin chi ti\u1ebft v\u1ec1 Jupyter Notebook. M\u1edf r\u1ed9ng ch\u1ee7 \u0111\u1ec1 Notebook Jupyter.<\/h2>\n

Jupyter Notebook ho\u1ea1t \u0111\u1ed9ng tr\u00ean ki\u1ebfn tr\u00fac m\u00e1y kh\u00e1ch-m\u00e1y ch\u1ee7, trong \u0111\u00f3 m\u00e1y kh\u00e1ch th\u01b0\u1eddng l\u00e0 tr\u00ecnh duy\u1ec7t web v\u00e0 m\u00e1y ch\u1ee7 ch\u1ea1y tr\u00ean m\u00e1y c\u1ee5c b\u1ed9 ho\u1eb7c m\u00e1y ch\u1ee7 t\u1eeb xa. Th\u00e0nh ph\u1ea7n ph\u00eda m\u00e1y ch\u1ee7 ch\u1ecbu tr\u00e1ch nhi\u1ec7m th\u1ef1c thi m\u00e3 v\u00e0 hi\u1ec3n th\u1ecb s\u1ed5 ghi ch\u00e9p, trong khi th\u00e0nh ph\u1ea7n ph\u00eda m\u00e1y kh\u00e1ch cung c\u1ea5p giao di\u1ec7n t\u01b0\u01a1ng t\u00e1c \u0111\u1ec3 ng\u01b0\u1eddi d\u00f9ng l\u00e0m vi\u1ec7c.<\/p>\n

C\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a Jupyter Notebook bao g\u1ed3m:<\/p>\n

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    T\u1ebf b\u00e0o<\/strong>: S\u1ed5 tay bao g\u1ed3m c\u00e1c \u00f4 ri\u00eang l\u1ebb, m\u1ed7i \u00f4 c\u00f3 kh\u1ea3 n\u0103ng ch\u1ee9a m\u00e3, v\u0103n b\u1ea3n ho\u1eb7c h\u00ecnh \u1ea3nh tr\u1ef1c quan. C\u00e1c \u00f4 c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c th\u1ef1c thi \u0111\u1ed9c l\u1eadp, cho ph\u00e9p ng\u01b0\u1eddi d\u00f9ng th\u1eed nghi\u1ec7m v\u00e0 s\u1eeda \u0111\u1ed5i m\u00e3 c\u1ee7a h\u1ecd nhi\u1ec1u l\u1ea7n.<\/p>\n<\/li>\n

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    Th\u1ef1c thi m\u00e3<\/strong>: Jupyter Notebook cho ph\u00e9p ng\u01b0\u1eddi d\u00f9ng th\u1ef1c thi m\u00e3 tr\u1ef1c ti\u1ebfp trong c\u00e1c \u00f4. C\u00e1c k\u1ebft qu\u1ea3, ch\u1eb3ng h\u1ea1n nh\u01b0 \u0111\u1ea7u ra v\u0103n b\u1ea3n, b\u1ea3ng ho\u1eb7c bi\u1ec3u \u0111\u1ed3, \u0111\u01b0\u1ee3c hi\u1ec3n th\u1ecb n\u1ed9i tuy\u1ebfn, t\u1ea1o \u0111i\u1ec1u ki\u1ec7n thu\u1eadn l\u1ee3i cho vi\u1ec7c kh\u00e1m ph\u00e1 v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u.<\/p>\n<\/li>\n

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    T\u00edch h\u1ee3p \u0111a ph\u01b0\u01a1ng ti\u1ec7n<\/strong>: Ng\u01b0\u1eddi d\u00f9ng c\u00f3 th\u1ec3 k\u1ebft h\u1ee3p nhi\u1ec1u lo\u1ea1i ph\u01b0\u01a1ng ti\u1ec7n kh\u00e1c nhau, ch\u1eb3ng h\u1ea1n nh\u01b0 h\u00ecnh \u1ea3nh, \u00e2m thanh v\u00e0 video, c\u00f9ng v\u1edbi h\u00ecnh \u1ea3nh tr\u1ef1c quan t\u01b0\u01a1ng t\u00e1c tr\u1ef1c ti\u1ebfp v\u00e0o s\u1ed5 ghi ch\u00e9p.<\/p>\n<\/li>\n

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    H\u1ed7 tr\u1ee3 gi\u1ea3m gi\u00e1<\/strong>: Jupyter h\u1ed7 tr\u1ee3 Markdown, cho ph\u00e9p ng\u01b0\u1eddi d\u00f9ng th\u00eam v\u0103n b\u1ea3n, ph\u01b0\u01a1ng tr\u00ecnh v\u00e0 t\u00e0i li\u1ec7u \u0111\u01b0\u1ee3c \u0111\u1ecbnh d\u1ea1ng v\u00e0o s\u1ed5 ghi ch\u00e9p. T\u00ednh n\u0103ng n\u00e0y khuy\u1ebfn kh\u00edch s\u1ef1 k\u1ebft h\u1ee3p gi\u1eefa m\u00e3 v\u00e0 v\u0103n b\u1ea3n gi\u1ea3i th\u00edch trong m\u1ed9t t\u00e0i li\u1ec7u duy nh\u1ea5t, khi\u1ebfn n\u00f3 tr\u1edf th\u00e0nh n\u1ec1n t\u1ea3ng l\u00fd t\u01b0\u1edfng cho nghi\u00ean c\u1ee9u c\u00f3 th\u1ec3 t\u00e1i t\u1ea1o.<\/p>\n<\/li>\n

  5. \n

    Widget<\/strong>: Jupyter h\u1ed7 tr\u1ee3 c\u00e1c ti\u1ec7n \u00edch t\u01b0\u01a1ng t\u00e1c cho ph\u00e9p ng\u01b0\u1eddi d\u00f9ng thao t\u00e1c c\u00e1c bi\u1ebfn v\u00e0 tham s\u1ed1, cung c\u1ea5p c\u00e1c c\u1eadp nh\u1eadt tr\u1ef1c quan h\u00f3a theo th\u1eddi gian th\u1ef1c v\u00e0 t\u1ea1o \u0111i\u1ec1u ki\u1ec7n thu\u1eadn l\u1ee3i cho vi\u1ec7c kh\u00e1m ph\u00e1 d\u1eef li\u1ec7u.<\/p>\n<\/li>\n

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    Xu\u1ea5t v\u00e0 chia s\u1ebb<\/strong>: S\u1ed5 ghi ch\u00e9p c\u00f3 th\u1ec3 d\u1ec5 d\u00e0ng \u0111\u01b0\u1ee3c xu\u1ea5t sang c\u00e1c \u0111\u1ecbnh d\u1ea1ng kh\u00e1c nhau nh\u01b0 HTML, PDF ho\u1eb7c slide, gi\u00fap thu\u1eadn ti\u1ec7n cho vi\u1ec7c chia s\u1ebb k\u1ebft qu\u1ea3 nghi\u00ean c\u1ee9u v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u v\u1edbi \u0111\u1ed3ng nghi\u1ec7p ho\u1eb7c c\u1ed9ng \u0111\u1ed3ng r\u1ed9ng l\u1edbn h\u01a1n.<\/p>\n<\/li>\n<\/ol>\n

    C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a Jupyter Notebook. C\u00e1ch ho\u1ea1t \u0111\u1ed9ng c\u1ee7a Notebook Jupyter.<\/h2>\n

    C\u00e1c t\u1ec7p Notebook Jupyter \u0111\u01b0\u1ee3c l\u01b0u v\u1edbi ph\u1ea7n m\u1edf r\u1ed9ng .ipynb v\u00e0 ch\u1ee9a c\u1ea5u tr\u00fac d\u1ef1a tr\u00ean JSON. S\u1ed5 ghi ch\u00e9p bao g\u1ed3m nhi\u1ec1u \u00f4, m\u1ed7i \u00f4 \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh l\u00e0 m\u00e3, \u0111\u00e1nh d\u1ea5u ho\u1eb7c v\u0103n b\u1ea3n th\u00f4. Khi m\u1edf s\u1ed5 ghi ch\u00e9p, m\u00e1y ch\u1ee7 Jupyter s\u1ebd \u0111\u1ecdc t\u1ec7p, th\u1ef1c thi c\u00e1c \u00f4 m\u00e3 v\u00e0 hi\u1ec3n th\u1ecb \u0111\u1ea7u ra. Sau \u0111\u00f3, s\u1ed5 ghi ch\u00e9p \u0111\u01b0\u1ee3c hi\u1ec3n th\u1ecb s\u1ebd \u0111\u01b0\u1ee3c hi\u1ec3n th\u1ecb trong tr\u00ecnh duy\u1ec7t web c\u1ee7a ng\u01b0\u1eddi d\u00f9ng.<\/p>\n

    M\u00e1y ch\u1ee7 Jupyter qu\u1ea3n l\u00fd m\u00f4i tr\u01b0\u1eddng th\u1ef1c thi c\u1ee7a s\u1ed5 ghi ch\u00e9p v\u00e0 giao ti\u1ebfp v\u1edbi nhi\u1ec1u h\u1ea1t nh\u00e2n kh\u00e1c nhau. H\u1ea1t nh\u00e2n l\u00e0 c\u00e1c qu\u00e1 tr\u00ecnh th\u1ef1c thi m\u00e3 b\u1eb1ng ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh t\u01b0\u01a1ng \u1ee9ng c\u1ee7a ch\u00fang v\u00e0 g\u1eedi \u0111\u1ea7u ra tr\u1edf l\u1ea1i m\u00e1y ch\u1ee7 Jupyter. M\u1ed7i s\u1ed5 ghi ch\u00e9p \u0111\u01b0\u1ee3c li\u00ean k\u1ebft v\u1edbi m\u1ed9t h\u1ea1t nh\u00e2n c\u1ee5 th\u1ec3, cho ph\u00e9p ng\u01b0\u1eddi d\u00f9ng l\u00e0m vi\u1ec7c b\u1eb1ng c\u00e1c ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh kh\u00e1c nhau trong c\u00f9ng m\u1ed9t m\u00f4i tr\u01b0\u1eddng Jupyter.<\/p>\n

    Ph\u00e2n t\u00edch c\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a Jupyter Notebook<\/h2>\n

    C\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a Jupyter Notebook g\u00f3p ph\u1ea7n t\u1ea1o n\u00ean s\u1ef1 ph\u1ed5 bi\u1ebfn v\u00e0 linh ho\u1ea1t c\u1ee7a n\u00f3:<\/p>\n

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      Kh\u00e1m ph\u00e1 d\u1eef li\u1ec7u t\u01b0\u01a1ng t\u00e1c<\/strong>: Kh\u1ea3 n\u0103ng th\u1ef1c thi m\u00e3 t\u1eebng b\u01b0\u1edbc c\u1ee7a Jupyter Notebook khuy\u1ebfn kh\u00edch vi\u1ec7c kh\u00e1m ph\u00e1 d\u1eef li\u1ec7u t\u01b0\u01a1ng t\u00e1c, gi\u00fap b\u1ea1n d\u1ec5 d\u00e0ng h\u00ecnh dung v\u00e0 hi\u1ec3u c\u00e1c b\u1ed9 d\u1eef li\u1ec7u ph\u1ee9c t\u1ea1p.<\/p>\n<\/li>\n

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      Nghi\u00ean c\u1ee9u t\u00e1i s\u1ea3n xu\u1ea5t<\/strong>: S\u1ef1 k\u1ebft h\u1ee3p gi\u1eefa m\u00e3, t\u00e0i li\u1ec7u v\u00e0 h\u00ecnh \u1ea3nh h\u00f3a trong m\u1ed9t s\u1ed5 tay duy nh\u1ea5t th\u00fac \u0111\u1ea9y kh\u1ea3 n\u0103ng t\u00e1i t\u1ea1o, cho ph\u00e9p c\u00e1c nh\u00e0 nghi\u00ean c\u1ee9u chia s\u1ebb c\u00e1c ph\u00e2n t\u00edch v\u00e0 ph\u01b0\u01a1ng ph\u00e1p c\u1ee7a h\u1ecd m\u1ed9t c\u00e1ch d\u1ec5 d\u00e0ng.<\/p>\n<\/li>\n

    3. \n

      C\u00f4ng c\u1ee5 gi\u00e1o d\u1ee5c<\/strong>: Jupyter Notebook \u0111\u00f3ng vai tr\u00f2 nh\u01b0 m\u1ed9t c\u00f4ng c\u1ee5 gi\u00e1o d\u1ee5c tuy\u1ec7t v\u1eddi \u0111\u1ec3 d\u1ea1y l\u1eadp tr\u00ecnh, khoa h\u1ecdc d\u1eef li\u1ec7u v\u00e0 c\u00e1c m\u00f4n k\u1ef9 thu\u1eadt kh\u00e1c do t\u00ednh ch\u1ea5t t\u01b0\u01a1ng t\u00e1c v\u00e0 kh\u1ea3 n\u0103ng k\u1ebft h\u1ee3p m\u00e3 v\u1edbi c\u00e1c gi\u1ea3i th\u00edch.<\/p>\n<\/li>\n

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      S\u1ef1 h\u1ee3p t\u00e1c<\/strong>: S\u1ed5 tay Jupyter c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c chia s\u1ebb v\u00e0 c\u1ed9ng t\u00e1c d\u1ec5 d\u00e0ng, th\u00fac \u0111\u1ea9y tinh th\u1ea7n \u0111\u1ed3ng \u0111\u1ed9i v\u00e0 trao \u0111\u1ed5i ki\u1ebfn th\u1ee9c gi\u1eefa c\u00e1c nh\u00e0 nghi\u00ean c\u1ee9u v\u00e0 nh\u00e0 ph\u00e1t tri\u1ec3n.<\/p>\n<\/li>\n<\/ol>\n

      C\u00e1c lo\u1ea1i s\u1ed5 tay Jupyter<\/h2>\n

      Jupyter Notebook h\u1ed7 tr\u1ee3 nhi\u1ec1u h\u1ea1t nh\u00e2n, cho ph\u00e9p ng\u01b0\u1eddi d\u00f9ng l\u00e0m vi\u1ec7c v\u1edbi c\u00e1c ng\u00f4n ng\u1eef v\u00e0 c\u00f4ng ngh\u1ec7 l\u1eadp tr\u00ecnh kh\u00e1c nhau. D\u01b0\u1edbi \u0111\u00e2y l\u00e0 m\u1ed9t s\u1ed1 lo\u1ea1i Notebook Jupyter ph\u1ed5 bi\u1ebfn c\u00f9ng v\u1edbi c\u00e1c h\u1ea1t nh\u00e2n li\u00ean quan c\u1ee7a ch\u00fang:<\/p>\n\n\n\n\n\n\n\n\n\n
      Ki\u1ec3u<\/th>\nh\u1ea1t nh\u00e2n<\/th>\nS\u1ef1 mi\u00eau t\u1ea3<\/th>\n<\/tr>\n<\/thead>\n
      S\u1ed5 tay Python<\/td>\nIPython (nh\u00e2n Python)<\/td>\nLo\u1ea1i Notebook Jupyter m\u1eb7c \u0111\u1ecbnh cho l\u1eadp tr\u00ecnh Python.<\/td>\n<\/tr>\n
      M\u00e1y t\u00ednh x\u00e1ch tay R<\/td>\nH\u1ea1t nh\u00e2n IR (h\u1ea1t nh\u00e2n R)<\/td>\n\u0110\u01b0\u1ee3c thi\u1ebft k\u1ebf \u0111\u1ec3 ph\u00e2n t\u00edch v\u00e0 th\u1ed1ng k\u00ea d\u1eef li\u1ec7u b\u1eb1ng R.<\/td>\n<\/tr>\n
      s\u1ed5 tay Julia<\/td>\nIJulia (h\u1ea1t nh\u00e2n Julia)<\/td>\nTh\u00edch h\u1ee3p cho t\u00ednh to\u00e1n khoa h\u1ecdc v\u1edbi ng\u00f4n ng\u1eef Julia.<\/td>\n<\/tr>\n
      S\u1ed5 tay Ruby<\/td>\nIRuby (h\u1ea1t nh\u00e2n Ruby)<\/td>\nCho ph\u00e9p l\u1eadp tr\u00ecnh Ruby t\u01b0\u01a1ng t\u00e1c.<\/td>\n<\/tr>\n
      S\u1ed5 tay JavaScript<\/td>\nIJavascript (h\u1ea1t nh\u00e2n Node.js)<\/td>\nD\u00e0nh cho ph\u00e1t tri\u1ec3n web v\u00e0 c\u00e1c d\u1ef1 \u00e1n d\u1ef1a tr\u00ean JavaScript.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      C\u00e1c c\u00e1ch s\u1eed d\u1ee5ng Jupyter Notebook, c\u00e1c v\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p li\u00ean quan \u0111\u1ebfn vi\u1ec7c s\u1eed d\u1ee5ng.<\/h2>\n

      C\u00e1c tr\u01b0\u1eddng h\u1ee3p s\u1eed d\u1ee5ng c\u1ee7a Jupyter Notebook<\/h3>\n
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      1. \n

        Ph\u00e2n t\u00edch v\u00e0 tr\u1ef1c quan h\u00f3a d\u1eef li\u1ec7u<\/strong>: Jupyter Notebook \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng r\u1ed9ng r\u00e3i \u0111\u1ec3 ph\u00e2n t\u00edch, kh\u00e1m ph\u00e1 v\u00e0 tr\u1ef1c quan h\u00f3a d\u1eef li\u1ec7u do t\u00ednh ch\u1ea5t t\u01b0\u01a1ng t\u00e1c v\u00e0 kh\u1ea3 n\u0103ng tr\u1ef1c quan h\u00f3a c\u1ee7a n\u00f3.<\/p>\n<\/li>\n

      2. \n

        H\u1ecdc m\u00e1y v\u00e0 AI<\/strong>: C\u00e1c nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u v\u00e0 ng\u01b0\u1eddi th\u1ef1c h\u00e0nh h\u1ecdc m\u00e1y s\u1eed d\u1ee5ng Jupyter Notebook \u0111\u1ec3 ph\u00e1t tri\u1ec3n, \u0111\u00e0o t\u1ea1o v\u00e0 th\u1eed nghi\u1ec7m c\u00e1c m\u00f4 h\u00ecnh h\u1ecdc m\u00e1y.<\/p>\n<\/li>\n

      3. \n

        Nghi\u00ean c\u1ee9u v\u00e0 H\u1ecdc thu\u1eadt<\/strong>: S\u1ef1 t\u00edch h\u1ee3p m\u00e3, ph\u01b0\u01a1ng tr\u00ecnh v\u00e0 tr\u1ef1c quan h\u00f3a c\u1ee7a Jupyter Notebook l\u00e0m cho n\u00f3 tr\u1edf th\u00e0nh m\u1ed9t n\u1ec1n t\u1ea3ng tuy\u1ec7t v\u1eddi \u0111\u1ec3 th\u1ef1c hi\u1ec7n v\u00e0 tr\u00ecnh b\u00e0y nghi\u00ean c\u1ee9u trong c\u00e1c l\u0129nh v\u1ef1c h\u1ecdc thu\u1eadt kh\u00e1c nhau.<\/p>\n<\/li>\n

      4. \n

        Gi\u00e1o d\u1ee5c v\u00e0 H\u1ecdc t\u1eadp<\/strong>: Jupyter Notebook \u0111\u00f3ng vai tr\u00f2 nh\u01b0 m\u1ed9t c\u00f4ng c\u1ee5 gi\u00e1o d\u1ee5c \u0111\u1ec3 gi\u1ea3ng d\u1ea1y l\u1eadp tr\u00ecnh, khoa h\u1ecdc d\u1eef li\u1ec7u v\u00e0 c\u00e1c m\u00f4n k\u1ef9 thu\u1eadt kh\u00e1c.<\/p>\n<\/li>\n<\/ol>\n

        C\u00e1c v\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p th\u01b0\u1eddng g\u1eb7p<\/h3>\n
          \n
        1. \n

          S\u1ef1 c\u1ed1 h\u1ea1t nh\u00e2n<\/strong>: \u0110\u00f4i khi, kernel c\u00f3 th\u1ec3 b\u1ecb l\u1ed7i do l\u1ed7i m\u00e3 ho\u1eb7c kh\u00f4ng \u0111\u1ee7 t\u00e0i nguy\u00ean. \u0110\u1ec3 gi\u1ea3i quy\u1ebft v\u1ea5n \u0111\u1ec1 n\u00e0y, ng\u01b0\u1eddi d\u00f9ng c\u00f3 th\u1ec3 kh\u1edfi \u0111\u1ed9ng l\u1ea1i kernel v\u00e0 ch\u1ea1y l\u1ea1i m\u00e3.<\/p>\n<\/li>\n

        2. \n

          K\u00edch th\u01b0\u1edbc m\u00e1y t\u00ednh x\u00e1ch tay l\u1edbn<\/strong>: M\u00e1y t\u00ednh x\u00e1ch tay c\u1ef1c l\u1edbn c\u00f3 th\u1ec3 t\u1ea3i v\u00e0 x\u1eed l\u00fd ch\u1eadm. Ng\u01b0\u1eddi d\u00f9ng c\u00f3 th\u1ec3 chia c\u00e1c s\u1ed5 ghi ch\u00e9p l\u1edbn th\u00e0nh c\u00e1c s\u1ed5 nh\u1ecf h\u01a1n ho\u1eb7c x\u00f3a \u0111\u1ea7u ra \u0111\u1ec3 gi\u1ea3m k\u00edch th\u01b0\u1edbc t\u1ec7p.<\/p>\n<\/li>\n

        3. \n

          Qu\u1ea3n l\u00fd ph\u1ee5 thu\u1ed9c<\/strong>: Khi l\u00e0m vi\u1ec7c v\u1edbi c\u00e1c d\u1ef1 \u00e1n ph\u1ee9c t\u1ea1p, vi\u1ec7c qu\u1ea3n l\u00fd c\u00e1c ph\u1ea7n ph\u1ee5 thu\u1ed9c c\u00f3 th\u1ec3 g\u1eb7p kh\u00f3 kh\u0103n. C\u00f4ng c\u1ee5 nh\u01b0 virtualenv<\/code> (d\u00e0nh cho Python) v\u00e0 vi\u1ec7c ch\u1ee9a b\u1eb1ng Docker c\u00f3 th\u1ec3 gi\u00fap qu\u1ea3n l\u00fd c\u00e1c ph\u1ea7n ph\u1ee5 thu\u1ed9c m\u1ed9t c\u00e1ch hi\u1ec7u qu\u1ea3.<\/p>\n<\/li>\n

        4. \n

          B\u1ea3o m\u1eadt d\u1eef li\u1ec7u<\/strong>: N\u1ebfu c\u00f3 li\u00ean quan \u0111\u1ebfn d\u1eef li\u1ec7u nh\u1ea1y c\u1ea3m, ng\u01b0\u1eddi d\u00f9ng n\u00ean th\u1eadn tr\u1ecdng khi chia s\u1ebb s\u1ed5 ghi ch\u00e9p v\u00e0 c\u00e2n nh\u1eafc vi\u1ec7c b\u1ea3o m\u1eadt s\u1ed5 ghi ch\u00e9p b\u1eb1ng m\u1eadt kh\u1ea9u ho\u1eb7c m\u00e3 h\u00f3a.<\/p>\n<\/li>\n<\/ol>\n

          C\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh v\u00e0 c\u00e1c so s\u00e1nh kh\u00e1c v\u1edbi c\u00e1c thu\u1eadt ng\u1eef t\u01b0\u01a1ng t\u1ef1 d\u01b0\u1edbi d\u1ea1ng b\u1ea3ng v\u00e0 danh s\u00e1ch.<\/h2>\n

          M\u00e1y t\u00ednh x\u00e1ch tay Jupyter so v\u1edbi JupyterLab<\/h3>\n

          JupyterLab l\u00e0 m\u00f4i tr\u01b0\u1eddng ph\u00e1t tri\u1ec3n t\u01b0\u01a1ng t\u00e1c ti\u00ean ti\u1ebfn \u0111\u01b0\u1ee3c x\u00e2y d\u1ef1ng d\u1ef1a tr\u00ean ki\u1ebfn tr\u00fac Jupyter. \u0110\u00e2y l\u00e0 so s\u00e1nh gi\u1eefa Jupyter Notebook v\u00e0 JupyterLab:<\/p>\n\n\n\n\n\n\n\n\n\n\n
          Di\u1ec7n m\u1ea1o<\/th>\nM\u00e1y t\u00ednh x\u00e1ch tay Jupyter<\/th>\nJupyterLab<\/th>\n<\/tr>\n<\/thead>\n
          Giao di\u1ec7n ng\u01b0\u1eddi d\u00f9ng<\/td>\nGiao di\u1ec7n t\u00e0i li\u1ec7u \u0111\u01a1n<\/td>\nGiao di\u1ec7n \u0111a t\u00e0i li\u1ec7u<\/td>\n<\/tr>\n
          Ch\u1ec9nh s\u1eeda theo th\u1ebb<\/td>\nKh\u00f4ng \u0111\u01b0\u1ee3c h\u1ed7 tr\u1ee3<\/td>\n\u0110\u01b0\u1ee3c h\u1ed7 tr\u1ee3, cho ph\u00e9p m\u1edf nhi\u1ec1u file<\/td>\n<\/tr>\n
          Kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng<\/td>\nTi\u1ec7n \u00edch m\u1edf r\u1ed9ng b\u1ecb gi\u1edbi h\u1ea1n<\/td>\nKh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng cao th\u00f4ng qua c\u00e1c plugin<\/td>\n<\/tr>\n
          Qu\u1ea3n l\u00fd kh\u00f4ng gian l\u00e0m vi\u1ec7c<\/td>\nGiao di\u1ec7n \u0111\u01a1n gi\u1ea3n<\/td>\nQu\u1ea3n l\u00fd b\u1ed1 tr\u00ed kh\u00f4ng gian l\u00e0m vi\u1ec7c linh ho\u1ea1t<\/td>\n<\/tr>\n
          Thi\u1ebft b\u1ecb \u0111\u1ea7u cu\u1ed1i t\u00edch h\u1ee3p<\/td>\nKh\u00f4ng t\u00edch h\u1ee3p s\u1eb5n<\/td>\nThi\u1ebft b\u1ecb \u0111\u1ea7u cu\u1ed1i t\u00edch h\u1ee3p \u0111\u1ec3 th\u1ef1c thi m\u00e3<\/td>\n<\/tr>\n
          B\u1ea3ng \u0111i\u1ec1u khi\u1ec3n m\u00e3<\/td>\nKh\u00f4ng t\u00edch h\u1ee3p s\u1eb5n<\/td>\nB\u1ea3ng \u0111i\u1ec1u khi\u1ec3n m\u00e3 t\u00edch h\u1ee3p cho c\u00f4ng vi\u1ec7c t\u01b0\u01a1ng t\u00e1c<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

          Notebook Jupyter so v\u1edbi R Markdown<\/h3>\n

          R Markdown l\u00e0 \u0111\u1ecbnh d\u1ea1ng t\u00e0i li\u1ec7u cho ph\u00e9p k\u1ebft h\u1ee3p m\u00e3 R, v\u0103n b\u1ea3n v\u00e0 h\u00ecnh \u1ea3nh tr\u1ef1c quan trong m\u1ed9t t\u00e0i li\u1ec7u duy nh\u1ea5t. \u0110\u00e2y l\u00e0 so s\u00e1nh gi\u1eefa Jupyter Notebook v\u00e0 R Markdown:<\/p>\n\n\n\n\n\n\n\n\n\n
          Di\u1ec7n m\u1ea1o<\/th>\nM\u00e1y t\u00ednh x\u00e1ch tay Jupyter<\/th>\nGi\u1ea3m gi\u00e1 R<\/th>\n<\/tr>\n<\/thead>\n
          Ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh<\/td>\nH\u1ed7 tr\u1ee3 nhi\u1ec1u ng\u00f4n ng\u1eef<\/td>\nCh\u1ee7 y\u1ebfu t\u1eadp trung v\u00e0o l\u1eadp tr\u00ecnh R<\/td>\n<\/tr>\n
          T\u01b0\u01a1ng t\u00e1c<\/td>\nTh\u1ef1c thi m\u00e3 t\u01b0\u01a1ng t\u00e1c<\/td>\nT\u00ednh t\u01b0\u01a1ng t\u00e1c h\u1ea1n ch\u1ebf trong vi\u1ec7c th\u1ef1c thi m\u00e3<\/td>\n<\/tr>\n
          \u0110\u00e1nh gi\u00e1 m\u00e3<\/td>\nTh\u1ef1c thi \u00f4 ri\u00eang l\u1ebb<\/td>\nTh\u1ef1c thi m\u00e3 tu\u1ea7n t\u1ef1 xuy\u00ean su\u1ed1t<\/td>\n<\/tr>\n
          T\u00ednh linh ho\u1ea1t \u0111\u1ea7u ra<\/td>\nT\u00f9y ch\u1ecdn \u0111\u1ea7u ra linh ho\u1ea1t h\u01a1n<\/td>\n\u0110\u1ecbnh d\u1ea1ng \u0111\u1ea7u ra h\u1ea1n ch\u1ebf<\/td>\n<\/tr>\n
          Tr\u1ef1c quan h\u00f3a<\/td>\nH\u1ed7 tr\u1ee3 tr\u1ef1c quan phong ph\u00fa<\/td>\nH\u1ed7 tr\u1ee3 phong ph\u00fa cho tr\u1ef1c quan h\u00f3a ggplot2<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

          Quan \u0111i\u1ec3m v\u00e0 c\u00f4ng ngh\u1ec7 c\u1ee7a t\u01b0\u01a1ng lai li\u00ean quan \u0111\u1ebfn Jupyter Notebook<\/h2>\n

          Jupyter Notebook \u0111\u00e3 tr\u1edf th\u00e0nh m\u1ed9t c\u00f4ng c\u1ee5 thi\u1ebft y\u1ebfu trong l\u0129nh v\u1ef1c khoa h\u1ecdc d\u1eef li\u1ec7u, nghi\u00ean c\u1ee9u v\u00e0 gi\u00e1o d\u1ee5c. B\u1ea3n ch\u1ea5t t\u01b0\u01a1ng t\u00e1c v\u00e0 h\u1ee3p t\u00e1c c\u1ee7a n\u00f3 \u0111\u00e3 d\u1eabn \u0111\u1ebfn vi\u1ec7c \u00e1p d\u1ee5ng r\u1ed9ng r\u00e3i trong nhi\u1ec1u l\u0129nh v\u1ef1c kh\u00e1c nhau. T\u01b0\u01a1ng lai c\u1ee7a Jupyter Notebook c\u00f3 th\u1ec3 s\u1ebd li\u00ean t\u1ee5c c\u1ea3i ti\u1ebfn, t\u00edch h\u1ee3p v\u1edbi c\u00e1c c\u00f4ng ngh\u1ec7 m\u1edbi n\u1ed5i v\u00e0 h\u1ed7 tr\u1ee3 m\u1edf r\u1ed9ng cho nhi\u1ec1u ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh h\u01a1n.<\/p>\n

          Nh\u1eefng ph\u00e1t tri\u1ec3n c\u00f3 th\u1ec3 c\u00f3 trong t\u01b0\u01a1ng lai bao g\u1ed3m:<\/p>\n

            \n
          1. \n

            C\u1ea3i thi\u1ec7n s\u1ef1 h\u1ee3p t\u00e1c<\/strong>: N\u1ed7 l\u1ef1c n\u00e2ng cao c\u00e1c t\u00ednh n\u0103ng c\u1ed9ng t\u00e1c, cho ph\u00e9p c\u1ed9ng t\u00e1c theo th\u1eddi gian th\u1ef1c tr\u00ean s\u1ed5 ghi ch\u00e9p gi\u1eefa nhi\u1ec1u ng\u01b0\u1eddi d\u00f9ng.<\/p>\n<\/li>\n

          2. \n

            Gi\u1ea3i ph\u00e1p d\u1ef1a tr\u00ean \u0111\u00e1m m\u00e2y<\/strong>: Nhi\u1ec1u d\u1ecbch v\u1ee5 d\u1ef1a tr\u00ean \u0111\u00e1m m\u00e2y h\u01a1n d\u00e0nh cho S\u1ed5 ghi ch\u00e9p Jupyter, cho ph\u00e9p ng\u01b0\u1eddi d\u00f9ng truy c\u1eadp v\u00e0 l\u00e0m vi\u1ec7c tr\u00ean s\u1ed5 ghi ch\u00e9p c\u1ee7a h\u1ecd t\u1eeb m\u1ecdi n\u01a1i.<\/p>\n<\/li>\n

          3. \n

            T\u00edch h\u1ee3p v\u1edbi AI v\u00e0 Machine Learning<\/strong>: T\u00edch h\u1ee3p c\u00e1c kh\u1ea3 n\u0103ng AI \u0111\u1ec3 h\u1ed7 tr\u1ee3 ho\u00e0n thi\u1ec7n m\u00e3, g\u1ee1 l\u1ed7i v\u00e0 \u0111\u1ec1 xu\u1ea5t th\u00f4ng minh.<\/p>\n<\/li>\n

          4. \n

            B\u1ea3o m\u1eadt v\u00e0 quy\u1ec1n ri\u00eang t\u01b0 n\u00e2ng cao<\/strong>: C\u00e1c bi\u1ec7n ph\u00e1p b\u1ea3o m\u1eadt ch\u1eb7t ch\u1ebd h\u01a1n \u0111\u1ec3 \u0111\u1ea3m b\u1ea3o quy\u1ec1n ri\u00eang t\u01b0 v\u00e0 b\u1ea3o v\u1ec7 d\u1eef li\u1ec7u khi chia s\u1ebb s\u1ed5 ghi ch\u00e9p.<\/p>\n<\/li>\n<\/ol>\n

            C\u00e1ch s\u1eed d\u1ee5ng ho\u1eb7c li\u00ean k\u1ebft m\u00e1y ch\u1ee7 proxy v\u1edbi Jupyter Notebook<\/h2>\n

            C\u00e1c m\u00e1y ch\u1ee7 proxy, gi\u1ed1ng nh\u01b0 c\u00e1c m\u00e1y ch\u1ee7 do OneProxy (oneproxy.pro) cung c\u1ea5p, c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng c\u00f9ng v\u1edbi Jupyter Notebook \u0111\u1ec3 t\u0103ng c\u01b0\u1eddng b\u1ea3o m\u1eadt, quy\u1ec1n ri\u00eang t\u01b0 v\u00e0 ki\u1ec3m so\u00e1t truy c\u1eadp. M\u00e1y ch\u1ee7 proxy \u0111\u00f3ng vai tr\u00f2 trung gian gi\u1eefa ng\u01b0\u1eddi d\u00f9ng v\u00e0 internet, chuy\u1ec3n ti\u1ebfp y\u00eau c\u1ea7u v\u00e0 ph\u1ea3n h\u1ed3i, gi\u00fap \u0111\u1ea1t \u0111\u01b0\u1ee3c nh\u1eefng \u0111i\u1ec1u sau:<\/p>\n

              \n
            1. \n

              Ki\u1ec3m so\u00e1t truy c\u1eadp<\/strong>: M\u00e1y ch\u1ee7 proxy c\u00f3 th\u1ec3 h\u1ea1n ch\u1ebf quy\u1ec1n truy c\u1eadp v\u00e0o c\u00e1c phi\u00ean b\u1ea3n Jupyter Notebook, ch\u1ec9 cho ph\u00e9p nh\u1eefng ng\u01b0\u1eddi d\u00f9ng \u0111\u01b0\u1ee3c \u1ee7y quy\u1ec1n t\u01b0\u01a1ng t\u00e1c v\u1edbi s\u1ed5 ghi ch\u00e9p.<\/p>\n<\/li>\n

            2. \n

              \u1ea9n danh<\/strong>: Ng\u01b0\u1eddi d\u00f9ng c\u00f3 th\u1ec3 s\u1eed d\u1ee5ng m\u00e1y ch\u1ee7 proxy \u0111\u1ec3 che gi\u1ea5u \u0111\u1ecba ch\u1ec9 IP th\u1ef1c c\u1ee7a h\u1ecd khi truy c\u1eadp Jupyter Notebook, b\u1ed5 sung th\u00eam m\u1ed9t l\u1edbp \u1ea9n danh v\u00e0 quy\u1ec1n ri\u00eang t\u01b0.<\/p>\n<\/li>\n

            3. \n

              C\u00e2n b\u1eb1ng t\u1ea3i<\/strong>: \u0110\u1ed1i v\u1edbi c\u00e1c t\u1ed5 ch\u1ee9c c\u00f3 nhi\u1ec1u phi\u00ean b\u1ea3n Jupyter Notebook, m\u00e1y ch\u1ee7 proxy c\u00f3 th\u1ec3 ph\u00e2n ph\u1ed1i c\u00e1c y\u00eau c\u1ea7u \u0111\u1ebfn gi\u1eefa c\u00e1c m\u00e1y ch\u1ee7 kh\u00e1c nhau, t\u1ed1i \u01b0u h\u00f3a vi\u1ec7c s\u1eed d\u1ee5ng t\u00e0i nguy\u00ean.<\/p>\n<\/li>\n

            4. \n

              An ninh v\u00e0 Gi\u00e1m s\u00e1t<\/strong>: M\u00e1y ch\u1ee7 proxy c\u00f3 th\u1ec3 cung c\u1ea5p c\u00e1c bi\u1ec7n ph\u00e1p b\u1ea3o m\u1eadt b\u1ed5 sung, ch\u1eb3ng h\u1ea1n nh\u01b0 l\u1ecdc l\u01b0u l\u01b0\u1ee3ng \u0111\u1ed9c h\u1ea1i v\u00e0 gi\u00e1m s\u00e1t nh\u1eadt k\u00fd truy c\u1eadp.<\/p>\n<\/li>\n<\/ol>\n

              Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n

              \u0110\u1ec3 bi\u1ebft th\u00eam th\u00f4ng tin v\u1ec1 Jupyter Notebook, b\u1ea1n c\u00f3 th\u1ec3 tham kh\u1ea3o c\u00e1c t\u00e0i nguy\u00ean sau:<\/p>\n

                \n
              1. D\u1ef1 \u00e1n Jupyter<\/a><\/li>\n
              2. T\u00e0i li\u1ec7u Jupyter<\/a><\/li>\n
              3. T\u00e0i li\u1ec7u JupyterLab<\/a><\/li>\n
              4. Gi\u1ea3m gi\u00e1 R<\/a><\/li>\n<\/ol>","protected":false},"featured_media":468721,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-477757","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about Jupyter Notebook: A Comprehensive Guide<\/mark>","faq_items":[{"question":"What is Jupyter Notebook?","answer":"

                Jupyter Notebook is an interactive computing environment used for data analysis, scientific research, machine learning, and education. It provides a web-based interface where users can create documents containing live code, visualizations, and explanatory text.<\/p>"},{"question":"How did Jupyter Notebook originate?","answer":"

                Jupyter Notebook originated from the IPython project initiated by Fernando P\u00e9rez in 2001. The project evolved into Jupyter in 2014, derived from the combination of Julia, Python, and R, which were the primary focus languages at the time.<\/p>"},{"question":"What are the key features of Jupyter Notebook?","answer":"

                Jupyter Notebook offers several key features, including support for multiple programming languages, code execution within cells, interactive widgets, rich media integration, and markdown support for adding formatted text and equations.<\/p>"},{"question":"How does Jupyter Notebook work internally?","answer":"

                Jupyter Notebook operates on a client-server architecture. The client, usually a web browser, communicates with the server running on the local machine or a remote server. The server manages the notebook's execution environment and interacts with kernels, which execute code in their respective programming languages.<\/p>"},{"question":"What types of Jupyter Notebooks are available?","answer":"

                Jupyter Notebooks support various kernels for different programming languages. Some popular types include Python Notebook (IPython kernel), R Notebook (IRkernel), Julia Notebook (IJulia), Ruby Notebook (IRuby), and JavaScript Notebook (IJavascript).<\/p>"},{"question":"How can Jupyter Notebook be used?","answer":"

                Jupyter Notebook finds applications in data analysis, visualization, machine learning, research, and education. It serves as a valuable tool for interactive exploration and documentation of code and results.<\/p>"},{"question":"What are common issues users may face with Jupyter Notebook?","answer":"

                Users may encounter problems such as kernel crashes, large notebook sizes, dependency management, and data security concerns. Restarting the kernel, breaking notebooks into smaller parts, using virtual environments, and securing sensitive data are potential solutions.<\/p>"},{"question":"How does Jupyter Notebook compare to JupyterLab?","answer":"

                Jupyter Notebook and JupyterLab are both interactive computing environments, but JupyterLab offers a more advanced multi-document interface, tabbed editing, and better extensibility through plugins.<\/p>"},{"question":"What does the future hold for Jupyter Notebook?","answer":"

                The future of Jupyter Notebook includes improved collaboration features, cloud-based solutions, integration with AI, and enhanced security and privacy measures.<\/p>"},{"question":"How can proxy servers be used with Jupyter Notebook?","answer":"

                Proxy servers, like those provided by OneProxy, can enhance security, privacy, and access control when using Jupyter Notebook. They can restrict access, provide anonymity, load balancing, and additional security measures.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/477757","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/477757\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media\/468721"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=477757"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}