Conda: Difference between revisions
No edit summary |
|||
| Line 4: | Line 4: | ||
[http://conda.pydata.org Conda] is a cross-language package and environment manager. It can be used to install NSIS itself and various plugins and header files. | [http://conda.pydata.org Conda] is a cross-language package and environment manager. It can be used to install NSIS itself and various plugins and header files. | ||
== Why use Conda for building NSIS installers? == | == Why use Conda for building NSIS installers? == | ||
| Line 10: | Line 11: | ||
Conda typically runs scripts in isolated environments. Configuring continuous integration or build servers is straightforward. | Conda typically runs scripts in isolated environments. Configuring continuous integration or build servers is straightforward. | ||
== How to use Conda == | == How to use Conda == | ||
| Line 17: | Line 19: | ||
# Using 'conda execute' | # Using 'conda execute' | ||
# Creating conda environments manually | # Creating conda environments manually | ||
=== Option 1: Using conda execute === | === Option 1: Using conda execute === | ||
| Line 43: | Line 46: | ||
Install [http://conda.pydata.org/miniconda.html miniconda] and [https://anaconda.org/conda-forge/conda-execute conda execute] first. | Install [http://conda.pydata.org/miniconda.html miniconda] and [https://anaconda.org/conda-forge/conda-execute conda execute] first. | ||
=== Option 2: Creating conda environments manually === | === Option 2: Creating conda environments manually === | ||
| Line 53: | Line 57: | ||
This only requires [http://conda.pydata.org/miniconda.html miniconda]. | This only requires [http://conda.pydata.org/miniconda.html miniconda]. | ||
== Creating Conda packages for NSIS plugins == | |||
It’s quite simple to create a "conda recipe" to build packages for NSIS plugins or header files. Just have a look at the examples at [https://github.com/faph/NSIS-Conda-Recipes this GitHub repo] and create a pull request with a new recipe. We will build the recipe and publish it on the anaconda.org NSIS channel. | |||
Alternatively, raise a GitHub issue and someone may be willing to create a recipe. | |||
[[Category:Development Environments]] | [[Category:Development Environments]] | ||
Revision as of 18:49, 19 October 2015
| Author: Faph (talk, contrib) |
What is Conda?
Conda is a cross-language package and environment manager. It can be used to install NSIS itself and various plugins and header files.
Why use Conda for building NSIS installers?
Conda is particularly good at managing packages and installing required packages and its dependencies. NSIS plugins and macro header files can be distributed as conda packages. A repository of NSIS conda packages is available at the anaconda.org NSIS channel.
Conda typically runs scripts in isolated environments. Configuring continuous integration or build servers is straightforward.
How to use Conda
There are two possible approaches for building NSIS installers with conda:
- Using 'conda execute'
- Creating conda environments manually
Option 1: Using conda execute
Add this to the top of an NSIS source file:
# conda execute # env: # - nsis # - plugin1 # - plugin2 # - ... # channels: # - nsis # run_with: makensis ; NSIS source as usual ...
Then compile the file like this:
conda execute yourinstaller.nsi
This will create a temporary isolated conda environment with NSIS and the listed plugins installed. You don't need to have NSIS installed first! Then it simply runs makensis as usual.
Install miniconda and conda execute first.
Option 2: Creating conda environments manually
Create a permanent NSIS environment like this:
conda create --name nsisenv --channel nsis nsis plugin1 plugin2 ...
Then run makensis within that environment to compile an NSIS source file.
This only requires miniconda.
Creating Conda packages for NSIS plugins
It’s quite simple to create a "conda recipe" to build packages for NSIS plugins or header files. Just have a look at the examples at this GitHub repo and create a pull request with a new recipe. We will build the recipe and publish it on the anaconda.org NSIS channel.
Alternatively, raise a GitHub issue and someone may be willing to create a recipe.
