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The main Anaconda distribution is pretty large . MiniConda downloads what you need to do to start. Choose the Miniconda that matches the main software you want to integrate with. (You can install both if you want.)
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(> 3 GB). MiniConda is a smaller version that just includes the Python standard library to start.
You can download and install either one, depending on whether you want to spend the time and disk space. Miniconda most efficient, as you can always download down anything in the conda distibution you want later.
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Anaconda first run
Open the Anaconda prompt window (Search in Windows and start the shortcut "Anaconda Prompt") and enter "python" in the command window:
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(D:\Users\cpricejwpowell\Miniconda2) C:\Users\cprice>pythonjwpowell>python Python 2.7.13 |Continuum Analytics, Inc.| (default, May 11 2017, 14:07:41) [MSC v.1500 32 bit (Intel)] on win32 Type "help", "copyright", "credits" or "license" for more information. Anaconda is brought to you by Continuum Analytics. Please check out: http://continuum.io/thanks and https://anaconda.org >>> |
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mkdir %USERPROFILE%\.certificates copy %USERPROFILE%\Downloads\DOIRootCADOIRootCA2.crtcer %USERPROFILE%\.certificates conda config --set ssl_verify %USERPROFILE%\.certificates\DOIRootCADOIRootCA2.crtcer |
If you plan to use the pip utility to download and install packages not included in the Conda distribution, set up a certificate for pip:
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mkdir %APPDATA%\pip pushd %APPDATA%\pip (echo [global] >& pip.ini echo cert=%USERPROFILE%\.certificates\DOIRootCADOIRootCA2.certcer) >>> %APPDATA%\pip\pip.ini popd |
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(Or you can just look at the list below under B.)
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# pyversions.py - report ArcGIS Python modue versions # Example output: # C:\ArcGIS\Pro\bin\ArcGISPro.exe # Python 3.5.2 # matplotlib 1.5.3 # numpy 1.11.2 # scipy |Continuum Analytics, Inc.| (default, Jul 5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)] # matplotlib 1.5.3 # numpy 1.11.2 # scipy 0.18.1 import sys import os ff = "{} {}" try: print(sys.executable) print(ff.format("Python", sys.version.split("|")[0])) import matplotlib print(ff.format("matplotlib", matplotlib.__version__)) import numpy print(ff.format("numpy", numpy.__version__)) import scipy print(ff.format("scipy", scipy.__version__)) except: raisepass |
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Open an Anaconda command window and load the virtual environment.
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C:\Users\cprice> conda info --envs
# conda environments:
#
arc1041 D:\Users\cprice\Miniconda2\envs\arc1041
root * D:\Users\cprice\Miniconda2
D:\Users\cprice>activate arc1041
Activating environment "arc1041"...
[arc1022] D:\Users\cprice> conda list
# packages in environment at D:\Users\cprice\Miniconda2\envs\arc1041:
#
dateutil 2.4.1 py27_0
matplotlib 1.3.0 np17py27_0
numpy 1.7.1 py27_3
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You can add more packages using conda install, but make sure you specify version numbers for these that won't change the Python modules required to stay compatible with ArcGIS's Python stack.
Let's add the Jupyter notebook and the Spyder IDE which are both popular additions to your toolbox.
Specifying the list of module versions (ARCLIST) here ensures the environment will still work with ArcGIS 10.4.1.
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set ARCLIST=python=2.7.10 numpy=1.9.2 matplotlib=1.4.3 scipy=0.16.0 pandas pyparsing xlrd xlwt
conda install -n arc1041 %ARCLIST% jupyter spyder
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The following NEW packages will be INSTALLED:
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You can search for more packages available in conda with conda search.
You're not limited to adding only packages to which conda has access to your new environment. Here's an example on how to install a commonly desired GIS-related package (shapely) into a conda virtual environment using the python pip utility:
http://deparkes.co.uk/2015/01/29/install-shapely-on-anaconda/
This can most easily be done (personal opinion) with a Python usercustomize.py startup script
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###########################################
# Edit here match your setup
# These paths must match your Anaconda setup exactly.
# Anaconda home folders
conda_arcmap_home = r"D:\Users\cprice\Miniconda2"
conda_arcmap64_home = r"D:\Users\cprice\Miniconda3x64"
conda_arcpro_home = r"D:\Users\cprice\Miniconda3x64"
# anaconda environments set up to match Desktop and Pro
conda_arcmap_env = "arc1041"
conda_arcmap64_env = "arc1041x64"
conda_arcpro_env = "arcpro13"
# Pro path must be included here - registry read not working
pro_path = r"C:\ArcGIS\Pro" + "\\"
pro_exe = os.path.join(pro_path, "bin\\ArcGISPro.exe")
# change to false after testing done
debug = True
# do not edit below this line
########################################### |
python -m site --user-site
C:\Users\username\AppData\Roaming\Python\Python27\site-packages (ArcGIS Desktop)
C:\Users\username\AppData\Roaming\Python\Python34\site-packages (ArcGIS Pro, Python35 for Pro 2.0)
ArcGIS
Windows 10 won’t show a start menu item if the name of an item/shortcut within the new group matches a shortcut name in another group and has the same target (e.g. both ‘Anaconda2 (32-bit)’ and ‘Anaconda2 (64-bit)’ have a shortcut named ‘Anaconda Prompt’ with a target of cmd.exe which confuses Windows 10). So, when Miniconda2 32-bit (and/or 64-bit) is installed edit the ‘Properties’ of ‘Anaconda Prompt’ -> General tab -> rename to ‘Anaconda Prompt 32-bit’. Also, rename each shortcut that is created for environments for 32-bit or 64-bit similarly for consistency. For example, if you created a new virtual environment in Anaconda 32-bit named arc1041 then you would rename the shortcut from ‘Anaconda Prompt (arc1041)’ to ‘Anaconda Prompt 32-bit (arc1041).
Open an Anaconda command window and load the virtual environment.
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C:\Users\jwpowell> conda info --envs
# conda environments:
#
arc1041 D:\Users\jwpowell\Miniconda2\envs\arc1041
root * D:\Users\jwpowell\Miniconda2
D:\Users\jwpowell>activate arc1041
Activating environment "arc1041"...
[arc1022] D:\Users\jwpowell> conda list
# packages in environment at D:\Users\jwpowell\Miniconda2\envs\arc1041:
#
dateutil 2.4.1 py27_0
matplotlib 1.3.0 np17py27_0
numpy 1.7.1 py27_3
... |
You can add more packages using conda install, but make sure you specify version numbers for these that won't change the Python modules required to stay compatible with ArcGIS's Python stack.
Let's add the Jupyter notebook and the Spyder IDE which are both popular additions to your toolbox.
Specifying the list of module versions (ARCLIST) here ensures the environment will still work with ArcGIS 10.4.1.
Code Block | ||||
---|---|---|---|---|
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set ARCLIST=python=2.7.10 numpy=1.9.2 matplotlib=1.4.3 scipy=0.16.0 pandas pyparsing xlrd xlwt
conda install -n arc1041 %ARCLIST% jupyter spyder
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The following NEW packages will be INSTALLED:
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Conda does provide a method for pinning dependencies to an environment so you don't have to specify them each time (as: ARCLIST above). You need to list these packages in a filed called pinned in the conda-meta folder.
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C:\Users\jwpowell> activate arc1041
(arc1041) C:\Users\jwpowell>(echo python ==2.7.10 & echo numpy ==1.9.2 & echo matplotlib ==1.4.3 & echo scipy ==0.16.0) > %CONDA_PREFIX%\conda-meta\pinned
(arc1041) C:\Users\jwpowell>type %CONDA_PREFIX%\conda-meta\pinned
python ==2.7.10
numpy ==1.9.2
matplotlib ==1.4.3
scipy ==0.16.0 |
Now that this has been set up, conda install -n arc1041 scipy-0.18.1 will generate an error, and conda install six will update six to the highest version compatible with the pinned modules.
You can search for more packages available in conda with conda search. There's a nice list on the Anaconda website that describes them all.
You're not limited to adding only packages to which conda has access to your new environment. Here's an example on how to install a commonly desired GIS-related package (shapely) into a conda virtual environment using the python pip utility:
http://deparkes.co.uk/2015/01/29/install-shapely-on-anaconda/
This can most easily be done (personal opinion) with a Python usercustomize.py startup script
Code Block | ||||
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###########################################
# Edit here match your setup
# These paths must match your Anaconda setup exactly.
# Anaconda home folders
conda_arcmap_home = r"D:\Users\jwpowell\Miniconda2"
conda_arcmap64_home = r"D:\Users\jwpowell\Miniconda3x64"
conda_arcpro_home = r"D:\Users\jwpowell\Miniconda3x64"
# anaconda environments set up to match Desktop and Pro
conda_arcmap_env = "arc1041"
conda_arcmap64_env = "arc1041x64"
conda_arcpro_env = "arcpro13"
# ArcGIS Pro install folder
default_pro_path = r"C:\ArcGIS\Pro"
# change to false after testing done
debug = True
# do not edit below this line
########################################### |
Create a user-specific site packages folder and place the script in the folder with the name usercustomize.py.
The user site-packages folder path can be found with: python -m site --user-site
Usually: C:\Users\username\AppData\Roaming\Python\Python27\site-packages (ArcGIS Desktop)
C:\Users\username\AppData\Roaming\Python\Python34\site-packages (ArcGIS Pro, Python35 for Pro 2.0)
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:: Python 2.7
mkdir %APPDATA%\Python\Python27\site-packages
copy usercustomize.py %APPDATA%\Python\Python27\site-packages
:: Python 3.4
mkdir %APPDATA%\Python\Python34\site-packages
copy usercustomize.py %APPDATA%\Python\Python34\site-packages |
ArcGIS
print ("\n".join(sys.path)) -- you should see the Anaconda site-packages near the end of the list
Anaconda
activate arc1041 (or whichever environment in the list)
python
import arcpy
print ("\n".join(sys.path)) -- you should see the AnacondaArcGIS site-packages near the end of the list
Anaconda
activate arc1041 (or whichever environment in the list)
import arcpy
print ("\n".join(sys.path)) -- you should see the ArcGIS site-packages near the end of the list
http://www.continuum.io/blog/conda
How to do a separate Python installation with ArcGIS? (GIS Stack Exchange)
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How to do a separate Python installation with ArcGIS? (GIS Stack Exchange)
Using ArcPy with Anaconda (PyMorton)
Many thanks to Parker Norton for his reviews and excellent additions to this document!
Justin Mayers has posted a batch script to install and set up set up MiniConda and environments to interact compatibly with Esri desktop software (ArcMap and Pro).
USGS BWTST supports an Anaconda3 SCCM package. This could be installed and linked to Pro using the information in this document.
ArcGIS Pro 2.x and later sets up an Anaconda install of its own. This environment could also be leveraged in various ways as time goes on.