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 .