safer Python calls

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::
 

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 <https://cfconventions.org/>`_) 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 <https://www.ogc.org/standard/wps/>`_; e.g. `Finch <https://github.com/bird-house/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 <https://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.

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 .