0%

anaconda tutorial on ubuntu 16.04

Guide

  • ubuntu 16.04
  • conda 4.6.14
  • python 3.7.3 (default)
  • python 3.5.6 (env)

Install Conda

download Anaconda3-2019.03-Linux-x86_64.sh from here

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
bash ./Anaconda3-2019.03-Linux-x86_64.sh

[/home/kezunlin/anaconda3] >>>
PREFIX=/home/kezunlin/anaconda3
installing: python-3.7.3-h0371630_0 ...
Python 3.7.3
...
installing: scikit-image-0.14.2-py37he6710b0_0 ...
installing: scikit-learn-0.20.3-py37hd81dba3_0 ...
installing: astropy-3.1.2-py37h7b6447c_0 ...
installing: statsmodels-0.9.0-py37h035aef0_0 ...
installing: seaborn-0.9.0-py37_0 ...
installing: anaconda-2019.03-py37_0 ...
installation finished.
Do you wish the installer to initialize Anaconda3
by running conda init? [yes|no]

If you'd prefer that conda's base environment not be activated on startup,
set the auto_activate_base parameter to false:

conda config --set auto_activate_base false

Thank you for installing Anaconda3!

conda config –set auto_activate_base false

check version

1
2
3
4
5
6
7
conda --version
conda 4.6.11

conda update conda

conda --version
conda 4.6.14

Managing Environments

create new env

When you begin using conda, you already have a default environment named base. You don’t want to put programs into your base environment, though. Create separate environments to keep your programs isolated from each other.

1
2
3
4
5
6
7
8
(base) kezunlin@ke:~$ conda --version
conda 4.6.14

(base) kezunlin@ke:~$ conda create --name snowflakes biopython
(base) kezunlin@ke:~$ conda activate snowflakes
(snowflakes) kezunlin@ke:~$
(snowflakes) kezunlin@ke:~$ conda deactivate
(base) kezunlin@ke:~$

conda activate only works on conda 4.6 and later versions.

list envs

1
2
3
4
5
conda info --envs
# conda environments:
#
base * /home/kezunlin/anaconda3
snowflakes /home/kezunlin/anaconda3/envs/snowflakes

~/.conda/environments.txt

1
2
3
/home/kezunlin/anaconda3
/home/kezunlin/anaconda3/envs/snowflakes
/home/kezunlin/anaconda3/envs/py35

Managing Python

When you create a new environment, conda installs the same Python version you used when you downloaded and installed Anaconda. If you want to use a different version of Python, for example Python 3.5, simply create a new environment and specify the version of Python that you want.

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
conda create --name snakes python=3.5
conda activate py35

conda info --envs
# conda environments:
#
base /home/kezunlin/anaconda3
py35 * /home/kezunlin/anaconda3/envs/py35
snowflakes /home/kezunlin/anaconda3/envs/snowflakes

(base) kezunlin@ke:~$ python --version
Python 3.7.3
(base) kezunlin@ke:~$ conda activate py35
(py35) kezunlin@ke:~$ python --version
Python 3.5.6 :: Anaconda, Inc.

Managing packages

list packages

1
2
3
4
5
6
7
8
9
(base) kezunlin@ke:~$ conda activate py35
(py35) kezunlin@ke:~$
(py35) kezunlin@ke:~$ conda list
# packages in environment at /home/kezunlin/anaconda3/envs/py35:
#
# Name Version Build Channel
ca-certificates 2019.1.23 0
certifi 2018.8.24 py35_1
libedit 3.1.20181209 hc058e9b_0
1
2
3
4
5
6
7
8
9
10
conda search beautifulsoup4

...
beautifulsoup4 4.6.3 py27_0 pkgs/main
beautifulsoup4 4.6.3 py35_0 pkgs/main
beautifulsoup4 4.6.3 py36_0 pkgs/main
beautifulsoup4 4.6.3 py37_0 pkgs/main
beautifulsoup4 4.7.1 py27_1 pkgs/main
beautifulsoup4 4.7.1 py36_1 pkgs/main
beautifulsoup4 4.7.1 py37_1 pkgs/main

install

1
conda install beautifulsoup4

conda config

1
2
conda config --set show_channel_urls yes
conda config --show

Tools

Jupyter notebook

install jupyter

1
2
3
conda create -n py35 python=3.5
conda activate py35
conda install jupyter

install kernel

1
2
python -m ipykernel install --user --name=py35
Installed kernelspec py35 in /home/kezunlin/.local/share/jupyter/kernels/py35

jupyter depends on notebook and ipykernel
also see tensorflow jupyter notebook kenel

run jupyter

1
jupyter notebook

now we can see py35 kernel appears.

py35 kernel

tensorflow-gpu/keras

1
2
conda activate py35
conda install tensorflow-gpu keras

test

1
2
3
>>>import tensorflow as tf
>>>import keras as K
Using TensorFlow backend.

.keras/keras.json

1
2
3
4
5
6
{
"epsilon": 1e-07,
"floatx": "float32",
"image_data_format": "channels_last",
"backend": "tensorflow"
}

pytorch

see pytorch tutorial on ubuntu 16.04

Reference

History

  • 20190524: created.