Anaconda
Anaconda 有幾種不同的應用場合或意義: anaconda.com Platform; anaconda.org Cloud; Channel; mini-conda Environment vs Channel miniconda
$ conda update --all
$ conda update -n base conda $ conda create --name kotti_py364 python=3.6.4 # # To activate this environment, use: # > source activate kotti_py364 # # To deactivate an active environment, use: # > source deactivate #
$ conda info --envs # conda environments: # base * C:\Users\marr\Anaconda3 $ conda install -c conda-forge --name base selenium
$ conda create --name myapp_27 python=2.7 flask sqlalchemy $ conda env list $ source activate myapp_27 $ source deactivate
$ python -V Python 3.6.1 $ conda create --name py361env (其實預設是產生 Python 3.5.4 環境) Solving environment: done ## Package Plan ## environment location: /Users/marr/anaconda3/envs/py361env Proceed ([y]/n)? Preparing transaction: done Verifying transaction: done Executing transaction: done # # To activate this environment, use: # > source activate py361env # # To deactivate an active environment, use: # > source deactivate # $ conda env list # conda environments: # base * /Users/marr/anaconda3 py361env /Users/marr/anaconda3/envs/py361env $ source activate py361env $ conda install -c esri arcgis To initialize this nbextension in the browser every time the notebook (or other app) loads: jupyter nbextension enable arcgis --py --sys-prefix Enabling notebook extension arcgis/mapview... - Validating: OK $ git clone git@github.com/Esri/arcgis-python-api.git (samples folder)
virtualenv for beginner Managing Channels Intel Distribution for Python
conda 類似於 pipenv (= pip + virtualenv),結合套件管理與虛擬環境,但好處是 conda 支援 Python 之外的多樣語言,例如 R 也可以用 conda安裝;conda比較麻煩的地方是,用 pip 裝的套件不受 conda 管轄 (可以匯出/列表但是更新/安裝/移除要用 pip),還有套件數較 pip 略少 (雖然也很多了)。如果你覺得要背兩套系統太麻煩,其實可以試試 pipenv (PyPi 官方推薦的)
pip pipenv site-packages base 不要動 再開一個 env
virtualenv Linux vs Windows 差別: 在 Windows 執行 venv 時可帶 --symlinks 參數 執行 python -m venv --help 就能看到說明了。
conda 安裝結果的執行效率較好 Windows Menu 設定
Jupyter Notebook Ubuntu Install
How a Notebook is Changing Science: image video Magic Bash: 50:44-59:59 Install a Second Kernel: 1:55:00-1:58:00 JupyterHub with Kubernates: 2:45:00-3:19:00 One Button Workflow nbflow: 3:26-12:50
Cell Magic Extensions Jupyter Public Server Jupyter BinderHub
$ sudo apt-get install python-dev build-essentials $ sudo pip install --upgrade jupyter $ jupyter notebook --no-browser $ jupyter notebook --no-browser --ip=*
Jupyter Protocol Notebook as Document: from Structure to Application
Tips for Data Science Extensions - Diagram Editor: Draw.io ShareLaTeX
Datalab
Colaboratory Get Ready with Jupyter Notebooks Against Large Datasets
Node.js
Installing Node.js and NPM python-virtualenv
# To install this package with conda run one of the following: $ conda install -c conda-forge nodejs # Or $ conda install -c conda-forge/label/gcc7 nodejs
Tensorflow
conda create --name=tensorflow --python=3.5 anaconda activate tensorflow pip install tensorflow keras
pip install selenium from selenium import webdriver
https://medium.com/datainpoint/python-essentials-conda-quickstart-1f1e9ecd1025 VisualCode + npm + tensorflow.js