From f911164a8e97f17af506dde584e2c268c5e56fc7 Mon Sep 17 00:00:00 2001
From: Zeitsperre <10819524+Zeitsperre@users.noreply.github.com>
Date: Mon, 18 Dec 2023 13:54:05 -0500
Subject: [PATCH] safer Python calls
---
CONTRIBUTING.rst | 2 +-
docs/explanation.rst | 5 -----
docs/installation.rst | 14 +++++++-------
3 files changed, 8 insertions(+), 13 deletions(-)
diff --git a/CONTRIBUTING.rst b/CONTRIBUTING.rst
index 3a6380280..fd5233f55 100644
--- a/CONTRIBUTING.rst
+++ b/CONTRIBUTING.rst
@@ -123,7 +123,7 @@ Ready to contribute? Here's how to set up `xclim` for local development.
3. Create a development environment. We recommend using ``conda``::
$ conda create -n xclim python=3.9 --file=environment.yml
- $ pip install -e .[dev]
+ $ python -m pip install -e ".[dev]"
4. Create a branch for local development::
diff --git a/docs/explanation.rst b/docs/explanation.rst
index 5232cf825..2f6488f32 100644
--- a/docs/explanation.rst
+++ b/docs/explanation.rst
@@ -5,11 +5,6 @@ Why use xclim?
Purpose
=======
-.. important::
-
- The content of this section is actively being developed in the forthcoming paper submission to JOSS.
- This section will be updated and finalized when the wording has been agreed upon in :pull:`250`
-
`xclim` aims to position itself as a climate services tool for any researchers interested in using Climate and Forecast Conventions (`CF-Conventions `_) compliant datasets to perform climate analyses. This tool is optimized for working with Big Data in the climate science domain and can function as an independent library for one-off analyses in *Jupyter Notebooks* or as a backend engine for performing climate data analyses via **Web Processing Services** (`WPS `_; e.g. `Finch `_). It was primarily developed targeting Earth and Environmental Science audiences and researchers, originally for calculating climate indicators for the Canadian government web service `ClimateData.ca `_.
The primary domains that `xclim` is built for are in calculating climate indicators, performing statistical correction / bias adjustment of climate model output variables or simulations, and in performing climate model simulation ensemble statistics.
diff --git a/docs/installation.rst b/docs/installation.rst
index 722121b85..d24a30631 100644
--- a/docs/installation.rst
+++ b/docs/installation.rst
@@ -11,7 +11,7 @@ To install `xclim` via `pip`, run this command in your terminal:
.. code-block:: shell
- $ pip install xclim
+ $ python -m pip install xclim
If you don't have `pip`_ installed, this `Python installation guide`_ can guide you through the process.
@@ -55,7 +55,7 @@ Both of these libraries are available on PyPI and conda-forge:
.. code-block:: shell
- $ pip install flox clisops
+ $ python -m pip install flox clisops
# Or, alternatively:
$ conda install -c conda-forge flox clisops
@@ -70,7 +70,7 @@ For convenience, these libraries can be installed alongside `xclim` using the fo
.. code-block:: shell
- $ pip install -r requirements_upstream.txt
+ $ python -m pip install -r requirements_upstream.txt
Or, alternatively:
@@ -105,13 +105,13 @@ Afterwards, `SBCK` can be installed from PyPI using `pip`:
.. code-block:: shell
- $ pip install SBCK
+ $ python -m pip install SBCK
Another experimental function :py:indicator:`xclim.sdba.property.first_eof` makes use of the `eofs`_ library, which is available on both PyPI and conda-forge:
.. code-block:: shell
- $ pip install eofs
+ $ python -m pip install eofs
# or alternatively,
$ conda install -c conda-forge eofs
@@ -145,7 +145,7 @@ Once you have extracted a copy of the source, you can install it with pip:
.. code-block:: shell
- $ pip install -e ".[dev]"
+ $ python -m pip install -e ".[dev]"
Alternatively, you can also install a local development copy via `flit`_:
@@ -166,4 +166,4 @@ To create a conda environment including `xclim`'s dependencies and several optio
$ conda env create -n my_xclim_env python=3.8 --file=environment.yml
$ conda activate my_xclim_env
- (my_xclim_env) $ pip install -e .
+ (my_xclim_env) $ python -m pip install -e .