Python 实用宝典

Question 1

I’ve installed Anaconda and created two extra environments: py3k (which holds Python 3.3) and py34 (which holds Python 3.4). Besides those, I have a default environment named ‘root’ which the Anaconda installer created by default and which holds Python 2.7. This last one is the default, whenever I launch ‘ipython’ from the terminal it gives me version 2.7. In order to work with Python 3.4, I need to issue the commands (in the shell)

source activate py34
ipython

which change the default environment to Python 3.4. This works fine, but it’s annoying since most of the time I work on Python 3.4, instead of Python 2.7 (which I hold for teaching purposes, it’s a rather long story). Anyway, I’ll like to know how to change the default environment to Python 3.4, bearing in mind that I don’t want to reinstall everything from scratch.

Question 2

If you just want to change to another environment, use

source activate environment-name

(you can create environment-name with `conda create)

Typically it’s best to just create new environments. However, if you really want to change the Python version in the default environment, you can do so as follows:

First, make sure you have the latest version of conda by running

conda update conda

Then run

conda install python=3.5

This will attempt to update all your packages in your root environment to Python 3 versions. If it is not possible (e.g., because some package is not built for Python 3.5), it will give you an error message indicating which package(s) caused the issue.

If you installed packages with pip, you’ll have to reinstall them.

Question 3

Overview
Some people have multiple Anaconda environments with different versions of python for compatibility reasons. In this case, you should have a script that sets your default environment. With this method, you can preserve the versions of python you use in your environments.

The following assumes environment_name is the name of your environment

Mac / Linux:
Edit your bash profile so that the last line is source activate environment_name. In Mac OSX this is ~/.bash_profile, in other environments this may be ~/.bashrc

Example:
Here’s how i did it on Mac OSX

Open Terminal and type:

nano ~/.bash_profile
Go to end of file and type the following, where “p3.5” is my environment:

source activate p3.5
Exit File. Start a new terminal window.
Type the following to see what environment is active

conda info -e

The result shows that I’m using my p3.5 environment by default.

For Windows:
Create a command file (.cmd) with activate environment_name and follow these instructions to have it execute whenever you open a command prompt

Create a batch file command, e.g. “my_conda.cmd”, put it in the Application Data folder.
Configure it to be started automatically whenever you open cmd. This setting is in Registry:
key: HKCU\SOFTWARE\Microsoft\Command Processor
value: AutoRun
type: REG_EXPAND_SZ
data: “%AppData%\my_conda.cmd”

from this answer: https://superuser.com/a/302553/143794

Question 4

Under Linux there is an easier way to set the default environment by modifying ~/.bashrc or ~/.bash_profile At the end you’ll find something like

# added by Anaconda 2.1.0 installer
export PATH="~/anaconda/bin:$PATH"

Replace it with

# set python3 as default
export PATH="~/anaconda/envs/python3/bin:$PATH"

and thats all there is to it.

Question 5

For windows Anaconda comes with Anaconda Prompt which is a shortcut to cmd and can be used run conda commands without adding anaconda in PATH variable. Find the location of it, copy and rename the copy (say myenv_prompt). Right click myenv_prompt and select properties in the context menu.

The Target form of Properties window should already be filled with text, something like %windir%\system32\cmd.exe "/K" C:\Users\xxx\AppData\Local\Continuum\Miniconda3\Scripts\activate.bat C:\Users\xxx\AppData\Local\Continuum\Miniconda3\ There are three parts of this command 1)start …\cmd.exe 2)run …\acitvate.bat with environment 3)…\Miniconda3\

Change 3rd part to path of the environment (say myenv) you want as default i.e. fill the Target form something like %windir%\system32\cmd.exe "/K" C:\Users\xxx\AppData\Local\Continuum\Miniconda3\Scripts\activate.bat C:\Users\xxx\AppData\Local\Continuum\Miniconda3\envs\myenv

Now myenv_prompt will act as shortcut to start cmd with myenv as the default environment for python. This shortcut you can keep in start menu or pinned in taskbar.

One advantage of this method is that you can create a few shortcuts each having different environment as default environment. Also you can set the default folder by filling Start in form of the Properties window

Hope this helps

PS:It is not required to find Anaconda Prompt and can be done by changing target of any shortcut. But you will require to know path of cmd.exe and activate.bat

Question 6

Change permanent

conda install python={version}

Change Temporarily

View your environments

run conda info --envs on your terminal window or an Anconda Prompt

If It doesn’t show environment that you want to install

run conda create -n py36 python=3.6 anaconda for python 3.6 change version as your prefer

Activating an environment (use Anaconda prompt)

run activate envnme envnme you can find by this commandconda info --envs as a example when you run conda info --envs it show

base * C:\Users\DulangaHeshan\Anaconda3 py36 C:\Users\DulangaHeshan\Anaconda3\envs\py36

then run activate py36

to check run python --version

In Windows, it is good practice to deactivate one environment before activating another. https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html?highlight=deactivate%20environment

Question 7

The correct answer (as of Dec 2018) is… you can’t. Upgrading conda install python=3.6 may work, but it might not if you have packages that are necessary, but cannot be uninstalled.

Anaconda uses a default environment named base and you cannot create a new (e.g. python 3.6) environment with the same name. This is intentional. If you want your base Anaconda to be python 3.6, the right way to do this is to install Anaconda for python 3.6. As a package manager, the goal of Anaconda is to make different environments encapsulated, hence why you must source activate into them and why you can’t just quietly switch the base package at will as this could lead to many issues on production systems.

Question 8

I wasn’t satisfied with any of the answers presented here, since activating an environment takes a few seconds on my platform (for whatever reason)

I modified my path variable so that the environment I want as default has priority over the actual default.

In my case I used the following commands to accomplish that for the environment “py35”:

setx PATH "%userprofile%\Anaconda3\envs\py35\;%PATH%"
setx PATH "%userprofile%\Anaconda3\envs\py35\Scripts;%PATH%"

to find out where your environment is stored, activate it and enter where python. I’m not sure yet if this approach has any downsides. Since it also changes the default path of the conda executable. If that should be the case, please comment.

Question 9

I got this when installing a library using anaconda. My version went from Python 3.* to 2.7 and a lot of my stuff stopped working. The best solution I found was to first see the most recent version available:

conda search python

Then update to the version you want:

conda install python=3.*.*

Source: http://chris35wills.github.io/conda_python_version/

Other helpful commands:

conda info
python --version

Question 10

Create a shortcut of anaconda prompt onto desktop or taskbar, and then in the properties of that shortcut make sure u modify the last path in “Target:” to the path of ur environment:

C:\Users\BenBouali\Anaconda3\ WILL CHANGE INTO C:\Users\BenBouali\Anaconda3\envs\tensorflow-gpu

preview

and this way u can use that shortcut to open a certain environment when clicking it, you can add it to ur path too and now you’ll be able to run it from windows run box by just typing in the name of the shortcut.

Question 11

On Windows, create a batch file with the following line in it:

start cmd /k "C:\Anaconda3\Scripts\activate.bat C:\Anaconda3 & activate env"

The first path contained in quotes is the path to the activate.bat file in the Anaconda installation. The path on your system might be different. The name following the activate command of course should be your desired environment name.

Then run the batch file when you need to open an Anaconda prompt.

Question 12

Load your “base” environment — as OP’s py34 — when you load your terminal/shell.

If you use Bash, put the line:

conda activate py34

in your .bash_profile (or .bashrc):

$ echo 'conda activate py34' >> ~/.bash_profile

Every time you run a new terminal, conda environment py34 will be loaded.

Question 13

I’m on Windows 8, using Anaconda 1.7.5 64bit.

I created a new Anaconda environment with

conda create -p ./test python=2.7 pip

from C:\Pr\TEMP\venv\.

This worked well (there is a folder with a new python distribution). conda tells me to type

activate C:\PR\TEMP\venv\test

to activate the environment, however this returns:

No environment named "C:\PR\temp\venv\test" exists in C:\PR\Anaconda\envs

How can I activate the environment? What am I doing wrong?

Question 14

If this happens you would need to set the PATH for your environment (so that it gets the right Python from the environment and Scripts\ on Windows).

Imagine you have created an environment called py33 by using:

conda create -n py33 python=3.3 anaconda

Here the folders are created by default in Anaconda\envs, so you need to set the PATH as:

set PATH=C:\Anaconda\envs\py33\Scripts;C:\Anaconda\envs\py33;%PATH%

Now it should work in the command window:

activate py33

The line above is the Windows equivalent to the code that normally appears in the tutorials for Mac and Linux:

$ source activate py33

More info: https://groups.google.com/a/continuum.io/forum/#!topic/anaconda/8T8i11gO39U

Does `anaconda` create a separate PYTHONPATH variable for each new environment?

Question 15

Use cmd instead of Powershell! I spent 2 hours before I switched to cmd and then it worked!

create Environment:

conda create -n your_environment_name

see list of conda environments:

conda env list

activate your environment:

conda activate your_environment_name

That’s all folks

Question 16

Note that the command for activating an environment has changed in Conda version 4.4. The recommended way of activating an environment is now conda activate myenv instead of source activate myenv. To enable the new syntax, you should modify your .bashrc file. The line that currently reads something like

export PATH="<path_to_your_conda_install>/bin:$PATH"

Should be changed to

. <path_to_your_conda_install>/etc/profile.d/conda.sh

This only adds the conda command to the path, but does not yet activate the base environment (which was previously called root). To do also that, add another line

conda activate base

after the first command. See all the details in Anaconda’s blog post from December 2017. (I think that this page is currently missing a newline between the two lines, it says .../conda.shconda activate base).

(This answer is valid for Linux, but it might be relevant for Windows and Mac as well)

Question 17

All the former answers seem to be outdated.

conda activate was introduced in conda 4.4 and 4.6.

conda activate: The logic and mechanisms underlying environment activation have been reworked. With conda 4.4, conda activate and conda deactivate are now the preferred commands for activating and deactivating environments. You’ll find they are much more snappy than the source activate and source deactivate commands from previous conda versions. The conda activate command also has advantages of (1) being universal across all OSes, shells, and platforms, and (2) not having path collisions with scripts from other packages like python virtualenv’s activate script.

Examples

conda create -n venv-name python=3.6
conda activate -n venv-name
conda deactivate

These new sub-commands are available in “Aanconda Prompt” and “Anaconda Powershell Prompt” automatically. To use conda activate in every shell (normal cmd.exe and powershell), check expose conda command in every shell on Windows.

References

Question 18

As you can see from the error message the paths, that you specified, are wrong. Try it like this:

activate ..\..\temp\venv\test

However, when I needed to install Anaconda, I downloaded it from here and installed it to the default paths (C:\Anaconda), than I put this path to the environment variables, so now Anacondas interpreter is used as default. If you are using PyCharm, for example, you can specify the interpreter there directly.

Question 19

Below is how it worked for me

C:\Windows\system32>set CONDA_ENVS_PATH=d:\your\location
C:\Windows\system32>conda info

Shows new environment path

C:\Windows\system32>conda create -n YourNewEnvironment –clone=root

Clones default root environment

C:\Windows\system32>activate YourNewEnvironment

Deactivating environment “d:\YourDefaultAnaconda3″… Activating environment “d:\your\location\YourNewEnvironment”…

[YourNewEnvironment] C:\Windows\system32>conda info -e

conda environments: #

YourNewEnvironment
* d:\your\location\YourNewEnvironment

root d:\YourDefaultAnaconda3

Question 20

I’ve tried to activate env from Jenkins job (in bash) with conda activate base and it failed, so after many tries, this one worked for me (CentOS 7) :

source /opt/anaconda2/bin/activate base

Question 21

let’s assume your environment name is ‘demo’ and you are using anaconda and want to create a virtual environment:

(if you want python3)

    conda create -n demo python=3

(if you want python2)

    conda create -n demo python=2

After running above command you have to activate the environment by bellow command:

    source activate demo

Question 22

For me, using Anaconda Prompt instead of cmd or PowerShell is the key.

In Anaconda Prompt, all I need to do is activate XXX

Question 23

I was having the same, a fix seems to have been made in the source.

Question 24

just as @Simba has rightly answered alot has changed in the conda env since 4.6. Conda activate (env-name) overthrew source activate (env-name) for good but not without it own challenges. conda activate oftentimes force your environment to base and make u see something like . Therefore throwing loads of error back at you. This can also be because auto_activate_base is set to True.

You can check this by using the following command

conda config --set auto_activate_base False

source ~/.bashrc.

And To reactivate use this

conda config --set auto_activate_base True

source ~/.bashrc

Question 25

Window: conda activate environment_name

Mac: conda activate environment_name

Question 26

I’ve installed and have been using the Anaconda Python distribution, and I have started using the Anaconda (Conda) environment. I can use the standard conda install... command to put packages from the distribution into my environments, but to use anything outside (i.e. Flask-WTF, flask-sqlalchemy, and alembic) I need to use pip install in the active environment. However, when I look at the contents of the environment, either in the directory, or using conda list these pip installed packages don’t show up.

Using pip freeze and pip list just lists every package I’ve ever installed.

Is there a way to keep track of what is in each of my Anaconda envs (both pip and conda installed)?

Question 27

conda-env now does this automatically (if pip was installed with conda).

You can see how this works by using the export tool used for migrating an environment:

conda env export -n <env-name> > environment.yml

The file will list both conda packages and pip packages:

name: stats
channels:
  - javascript
dependencies:
  - python=3.4
  - bokeh=0.9.2
  - numpy=1.9.*
  - nodejs=0.10.*
  - flask
  - pip:
    - Flask-Testing

If you’re looking to follow through with exporting the environment, move environment.yml to the new host machine and run:

conda env create -f path/to/environment.yml

Question 28

conda will only keep track of the packages it installed. And pip will give you the packages that were either installed using the pip installer itself or they used setuptools in their setup.py so conda build generated the egg information. So you have basically three options.

You can take the union of the conda list and pip freeze and manage packages that were installed using conda (that show in the conda list) with the conda package manager and the ones that are installed with pip (that show in pip freeze but not in conda list) with pip.
Install in your environment only the python, pip and distribute packages and manage everything with pip. (This is not that trivial if you’re on Windows…)
Build your own conda packages, and manage everything with conda.

I would personally recommend the third option since it’s very easy to build conda packages. There is a git repository of example recipes on the continuum’s github account. But it usually boils down to:

 conda skeleton pypi PACKAGE
 conda build PACKAGE

or just:

conda pipbuild PACKAGE

Also when you have built them once, you can upload them to https://binstar.org/ and just install from there.

Then you’ll have everything managed using conda.

Question 29

There is a branch of conda (new-pypi-install) that adds better integration with pip and PyPI. In particular conda list will also show pip installed packages and conda install will first try to find a conda package and failing that will use pip to install the package.

This branch is scheduled to be merged later this week so that version 2.1 of conda will have better pip-integration with conda.

Question 30

I followed @Viktor Kerkez’s answer and have had mixed success. I found that sometimes this recipe of

conda skeleton pypi PACKAGE

conda build PACKAGE

would look like everything worked but I could not successfully import PACKAGE. Recently I asked about this on the Anaconda user group and heard from @Travis Oliphant himself on the best way to use conda to build and manage packages that do not ship with Anaconda. You can read this thread here, but I’ll describe the approach below to hopefully make the answers to the OP’s question more complete…

Example: I am going to install the excellent prettyplotlib package on Windows using conda 2.2.5.

1a) conda build --build-recipe prettyplotlib

You’ll see the build messages all look good until the final TEST section of the build. I saw this error

File “C:\Anaconda\conda-bld\test-tmp_dir\run_test.py”, line 23 import None SyntaxError: cannot assign to None TESTS FAILED: prettyplotlib-0.1.3-py27_0

1b) Go into /conda-recipes/prettyplotlib and edit the meta.yaml file. Presently, the packages being set up like in step 1a result in yaml files that have an error in the test section. For example, here is how mine looked for prettyplotlib

test:   # Python imports   imports:
    - 
    - prettyplotlib
    - prettyplotlib

Edit this section to remove the blank line preceded by the – and also remove the redundant prettyplotlib line. At the time of this writing I have found that I need to edit most meta.yaml files like this for external packages I am installing with conda, meaning that there is a blank import line causing the error along with a redundant import of the given package.

1c) Rerun the command from 1a, which should complete with out error this time. At the end of the build you’ll be asked if you want to upload the build to binstar. I entered No and then saw this message:

If you want to upload this package to binstar.org later, type:

$ binstar upload C:\Anaconda\conda-bld\win-64\prettyplotlib-0.1.3-py27_0.tar.bz2

That tar.bz2 file is the build that you now need to actually install.

2) conda install C:\Anaconda\conda-bld\win-64\prettyplotlib-0.1.3-py27_0.tar.bz2

Following these steps I have successfully used conda to install a number of packages that do not come with Anaconda. Previously, I had installed some of these using pip, so I did pip uninstall PACKAGE prior to installing PACKAGE with conda. Using conda, I can now manage (almost) all of my packages with a single approach rather than having a mix of stuff installed with conda, pip, easy_install, and python setup.py install.

For context, I think this recent blog post by @Travis Oliphant will be helpful for people like me who do not appreciate everything that goes into robust Python packaging but certainly appreciate when stuff “just works”. conda seems like a great way forward…

Question 31

This is why I wrote Picky: http://picky.readthedocs.io/

It’s a python package that tracks packages installed with either pip or conda in either virtualenvs and conda envs.

Question 32

I think what’s missing here is that when you do:

>pip install .

to install a local package with a setup.py, it installs a package that is visible to all the conda envs that use the same version of python. Note I am using the conda version of pip!

e.g., if I’m using python2.7 it puts the local package here:

/usr/local/anaconda/lib/python2.7/site-packages

If I then later create a new conda env with python=2.7 (= the default):

>conda create --name new

>source activate new

And then do:

(new)>conda list    // empty - conda is not aware of any packages yet

However, if I do:

(new)>pip list      // the local package installed above is present

So in this case, conda does not know about the pip package, but the package is available to python.

However, If I instead install the local package (again using pip) after I’ve created (and activated) the new conda env, now conda sees it:

(new)>conda list   // sees that the package is there and was installed by pip

So I think the interaction between conda and pip has some issues – ie, using pip to install a local package from within one conda env makes that package available (but not seen via conda list) to all other conda envs of the same python version.

Question 33

conda env export lists all conda and pip packages in an environment. conda-env must be installed in the conda root (conda install -c conda conda-env).

To write an environment.yml file describing the current environment:

conda env export > environment.yml

References:

Question 34

I usually prefix the ‘bin/pip’ folder for the specific environment you want to install the package before the ‘pip’ command. For instance, if you would like to install pymc3 in the environment py34, you should use this command:

~/anaconda/envs/py34/bin/pip install git+https://github.com/pymc-devs/pymc3

You basically just need to find the right path to your environment ‘bin/pip’ folder and put it before the install command.

Question 35

My which pip shows the following path:

$ which pip
/home/kmario23/anaconda3/bin/pip

So, whatever package I install using pip install <package-name> will have to be reflected in the list of packages when the list is exported using:

$ conda list --export > conda_list.txt

But, I don’t. So, instead I used the following command as suggested by several others:

# get environment name by
$ conda-env list

# get list of all installed packages by (conda, pip, etc.,)
$ conda-env export -n <my-environment-name> > all_packages.yml
# if you haven't created any specific env, then just use 'root'

Now, I can see all the packages in my all-packages.yml file.

Question 36

You can start by installing the below given command in the conda environment:

conda install pip

Followed by installing all pip packages you need in the environment.

After installing all the conda and pip packages to export the environment use:

conda env export -n <env-name> > environment.yml

This will create the required file in the folder

Question 37

I want to remove a certain environment created with conda. How can I achieve that? Let’s say I have an active testenv environment. I tried, by following documentation, with:

$ conda env remove

CondaEnvironmentError: cannot remove current environment. deactivate and run conda remove again

I then deactivate it:

$ source deactivate

I try running again the command to remove it and I still get the same error. What is going wrong here?

Question 38

You probably didn’t fully deactivate the Conda environment – remember, the command you need to use with Conda is conda deactivate (for older versions, use source deactivate). So it may be wise to start a new shell and activate the environment in that before you try. Then deactivate it.

You can use the command

conda env remove -n ENV_NAME

to remove the environment with that name. (--name is equivalent to -n)

Note that you can also place environments anywhere you want using -p /path/to/env instead of -n ENV_NAME when both creating and deleting environments, if you choose. They don’t have to live in your conda installation.

UPDATE, 30 Jan 2019: From Conda 4.6 onwards the conda activate command becomes the new official way to activate an environment across all platforms. The changes are described in this Anaconda blog post

Question 39

After making sure your environment is not active, type:

$ conda env remove --name ENVIRONMENT

Question 40

Official documentation way worked for me:

conda remove --name myenv --all

Or just conda env remove --name myenv.

To verify that the environment was removed, in your terminal window or an Anaconda Prompt, run:

conda info --envs

The environments list that displays should not show the removed environment.

You anaconda3 enviroments folder might list an empty folder of deleted environment in your anaconda3 installation folder, like:

/opt/anaconda3/envs

Question 41

There’re 3 ways to achieve this in total. Assuming you have a environment named myenv,

conda env remove --name myenv, -n is shortcut for --name.
conda remove --name myenv --all.

Delete the env folder directly. (Not recommended)

# list environments and their locations
conda env list
# or
# conda info --envs

# delete the folder listed
rm -rf /Users/username/.local/share/conda/envs/myenv

If you wanna delete the environment without a prompt to let you check again. Use -y, shortcut for --yes. (For global use check silent prompt in conda)

conda env remove -n myenv -y
conda remove -n myenv --all -y

References

conda env --help
conda remove --help

Question 42

You may try the following: Open anaconda command prompt and type

conda remove --name myenv --all

This will remove the entire environment.

Further reading: docs.conda.io > Manage Environments

Question 43

First you have to deactivate your environment before removing it. You can remove conda environment by using the following command

Suppose your environment name is “sample_env” , you can remove this environment by using

source deactivate    
conda remove -n sample_env --all

‘–all’ will be used to remove all the dependencies

Question 44

Environments created with the --prefix or -p flag must be removed with the -p flag (not -n).

For example: conda remove -p </filepath/myenvironment> --all, in which </filepath/myenvironment> is substituted with a complete or relative path to the environment.

Question 45

My environment name is: test

conda remove -n test --all

Question 46

Use source deactivate to deactivate the environment before removing it, replace ENV_NAME with the environment you wish to remove:

source deactivate
conda env remove -n ENV_NAME

Question 47

First deactivate the environment and come back to the base environment. From the base, you should be able to run the command conda env remove -n <envname>. This will give you the message

Remove all packages in environment C:\Users\<username>\AppData\Local\Continuum\anaconda3\envs\{envname}:

Question 48

if you are in base:

(base) HP-Compaq-Elite-8300-CMT:~$

remove env_name by:

conda env remove -n env_name

if you are already in env_name environment :

(env_name) HP-Compaq-Elite-8300-CMT:~$

deactivate then remove by :

conda deactivate env_name

conda env remove -n env_name

Question 49

This worked for me:

conda env remove --name tensorflow

Question 50

To remove complete conda environment :

conda remove --name YOUR_CONDA_ENV_NAME --all

Question 51

Because you can only deactivate the active environment, so conda deactivate does not need nor accept arguments. The error message is very explicit here.

Just call conda deactivate https://github.com/conda/conda/issues/7296#issuecomment-389504269

Question 52

Is there a way (using conda update) that I can list outdated packages and select or bulk update (compatible) packages in Anaconda?

It doesn’t make much sense updating the packages individually as there are hundreds of them.

Question 53

You want conda update --all.

conda search --outdated will show outdated packages, and conda update --all will update them (note that the latter will not update you from Python 2 to Python 3, but the former will show Python as being outdated if you do use Python 2).

Question 54

Before you proceed to conda update --all command, first update conda with conda update conda command if you haven’t update it for a long time. It happent to me (Python 2.7.13 on Anaconda 64 bits).

Question 55

the Conda Package Manager is almost ready for beta testing, but it will not be fully integrated until the release of Spyder 2.4 (https://github.com/spyder-ide/spyder/wiki/Roadmap). As soon as we have it ready for testing we will post something on the mailing list (https://groups.google.com/forum/#!forum/spyderlib). Be sure to subscribe

Cheers!

Question 56

# list packages that can be updated
conda search --outdated

# update all packages prompted(by asking the user yes/no)
conda update --all

# update all packages unprompted
conda update --all -y

Question 57

I recently discovered Conda after I was having trouble installing SciPy, specifically on a Heroku app that I am developing.

With Conda you create environments, very similar to what virtualenv does. My questions are:

If I use Conda will it replace the need for virtualenv? If not, how do I use the two together? Do I install virtualenv in Conda, or Conda in virtualenv?
Do I still need to use pip? If so, will I still be able to install packages with pip in an isolated environment?

Question 58

Conda replaces virtualenv. In my opinion it is better. It is not limited to Python but can be used for other languages too. In my experience it provides a much smoother experience, especially for scientific packages. The first time I got MayaVi properly installed on Mac was with conda.
You can still use pip. In fact, conda installs pip in each new environment. It knows about pip-installed packages.

For example:

conda list

lists all installed packages in your current environment. Conda-installed packages show up like this:

sphinx_rtd_theme          0.1.7                    py35_0    defaults

and the ones installed via pip have the <pip> marker:

wxpython-common           3.0.0.0                   <pip>

Question 59

Short answer is, you only need conda.

Conda effectively combines the functionality of pip and virtualenv in a single package, so you do not need virtualenv if you are using conda.
You would be surprised how many packages conda supports. If it is not enough, you can use pip under conda.

Here is a link to the conda page comparing conda, pip and virtualenv:

https://docs.conda.io/projects/conda/en/latest/commands.html#conda-vs-pip-vs-virtualenv-commands.

Question 60

Virtual Environments and pip

I will add that creating and removing conda environments is simple with Anaconda.

> conda create --name <envname> python=<version> <optional dependencies>

> conda remove --name <envname> --all

In an activated environment, install packages via conda or pip:

(envname)> conda install <package>

(envname)> pip install <package>

These environments are strongly tied to conda’s pip-like package management, so it is simple to create environments and install both Python and non-Python packages.

Jupyter

In addition, installing ipykernel in an environment adds a new listing in the Kernels dropdown menu of Jupyter notebooks, extending reproducible environments to notebooks. As of Anaconda 4.1, nbextensions were added, adding extensions to notebooks more easily.

Reliability

In my experience, conda is faster and more reliable at installing large libraries such as numpy and pandas. Moreover, if you wish to transfer your the preserved state of an environment, you can do so by sharing or cloning an env.

Question 61

Installing Conda will enable you to create and remove python environments as you wish, therefore providing you with same functionality as virtualenv would.

In case of both distributions you would be able to create an isolated filesystem tree, where you can install and remove python packages (probably, with pip) as you wish. Which might come in handy if you want to have different versions of same library for different use cases or you just want to try some distribution and remove it afterwards conserving your disk space.

Differences:

License agreement. While virtualenv comes under most liberal MIT license, Conda uses 3 clause BSD license.

Conda provides you with their own package control system. This package control system often provides precompiled versions (for most popular systems) of popular non-python software, which can easy ones way getting some machine learning packages working. Namely you don’t have to compile optimized C/C++ code for you system. While it is a great relief for most of us, it might affect performance of such libraries.

Unlike virtualenv, Conda duplicating some system libraries at least on Linux system. This libraries can get out of sync leading to inconsistent behavior of your programs.

Verdict:

Conda is great and should be your default choice while starting your way with machine learning. It will save you some time messing with gcc and numerous packages. Yet, Conda does not replace virtualenv. It introduces some additional complexity which might not always be desired. It comes under different license. You might want to avoid using conda on a distributed environments or on HPC hardware.

Question 62

I use both and (as of Jan, 2020) they have some superficial differences that lend themselves to different usages for me. By default Conda prefers to manage a list of environments for you in a central location, whereas virtualenv makes a folder in the current directory. The former (centralized) makes sense if you are e.g. doing machine learning and just have a couple of broad environments that you use across many projects and want to jump into them from anywhere. The latter (per project folder) makes sense if you are doing little one-off projects that have completely different sets of lib requirements that really belong more to the project itself.

The empty environment that Conda creates is about 122MB whereas the virtualenv’s is about 12MB, so that’s another reason you may prefer not to scatter Conda environments around everywhere.

Finally, another superficial indication that Conda prefers its centralized envs is that (again, by default) if you do create a Conda env in your own project folder and activate it the name prefix that appears in your shell is the (way too long) absolute path to the folder. You can fix that by giving it a name, but virtualenv does the right thing by default.

I expect this info to become stale rapidly as the two package managers vie for dominance, but these are the trade-offs as of today :)

Question 63

Another new option and my current preferred method of getting an environment up and running is Pipenv

It is currently the officially recommended Python packaging tool from Python.org

Question 64

Yes, conda is a lot easier to install than virtualenv, and pretty much replaces the latter.

问题：如何更改默认的Anaconda python环境

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问题：如何激活Anaconda环境

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问题：如何在Anaconda（Conda）环境中跟踪点子安装的软件包？

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问题：删除Conda环境

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参考资料

References

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问题：使用Conda进行批量包装更新

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问题：康达能否取代对virtualenv的需求？

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差异：

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Differences:

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问题：如何更新Anaconda？

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95％的人实际想要什么

更新单个软件包

仅更新标准Anaconda发行版中的软件包

为什么更新Anaconda软件包几乎总是一个坏主意

利用conda环境

pip，PyPI和setuptools？

Anaconda或Anaconda Enterprise的商业用途