@@ -34,10 +34,10 @@ https://github.com/SciTools/iris.
3434
3535Iris makes use of a range of other libraries and python modules. These
3636dependencies must be in place before you can successfully install
37- Iris. Once you have satisfied the requirements detailed below,
38- extract the iris source package, cd to the new directory, and enter ::
37+ Iris. Once you have satisfied the requirements detailed in the
38+ ``requirements`` directory, go to the root of Iris' and run ::
3939
40- python setup.py install
40+ pip install .
4141
4242
4343In-place build - an alternative for developers
@@ -46,118 +46,18 @@ We are very keen to encourage contributions to Iris. For this type of
4646development activity an in-place build can be useful. Once you've cloned
4747the Iris git repository you can perform an in-place build with::
4848
49- python setup.py develop
50-
51-
52- Build and runtime requirements
53- ==============================
54- These are external packages which you will need to have installed before
55- installing and running Iris.
56-
57- Many of these packages are available in Linux package managers
58- such as aptitude and yum. For example, it may be possible to install
59- Numpy using::
60-
61- apt-get install python-numpy
62-
63- If you are installing dependencies with a package manager on Linux,
64- you may need to install the development packages (look for a "-dev"
65- postfix) in addition to the core packages.
66-
67-
68- python 2.7 or 3.5+ (http://www.python.org/)
69- Iris requires Python 2.7 or Python 3.5+.
70-
71- numpy (http://numpy.scipy.org/)
72- Python package for scientific computing including a powerful N-dimensional
73- array object.
74-
75- scipy (http://www.scipy.org/)
76- Python package for scientific computing.
77-
78- cartopy v0.11.0 or later (http://github.com/SciTools/cartopy/)
79- Python package which provides cartographic tools for python.
80-
81- dask v0.15.0 or later (https://dask.pydata.org/)
82- Python package for parallel computing.
83-
84- PyKE v1.1.1 or later (http://pyke.sourceforge.net/)
85- Python knowledge-based inference engine.
86-
87- netcdf4-python (http://netcdf4-python.googlecode.com/)
88- Python interface to the netCDF version 4 C library.
89- (It is strongly recommended to ensure your installation uses a
90- thread-safe build of HDF5 to avoid segmentation faults when using
91- lazy evaluation.)
92-
93- cf_units v2.0 or later (https://github.com/SciTools/cf_units)
94- CF data units handling, using udunits.
95-
96- setuptools v36.0 or later (http://pypi.python.org/pypi/setuptools/)
97- Python package for installing/removing python packages.
98-
99-
100- The full list of packages may be found in the repository at
101- ``requirements/core.txt``.
102-
103-
104- Optional
105- ''''''''
106- These are optional packages which you may want to install to enable
107- additonal Iris functionality such as plotting and
108- loading/saving GRIB. These packages are required for the full Iris test
109- suite to run.
110-
111- gdal (https://pypi.python.org/pypi/GDAL/)
112- Python package for the Geospatial Data Abstraction Library (GDAL).
113-
114- graphviz (http://www.graphviz.org/)
115- Graph visualisation software.
116-
117- iris-grib (https://github.com/scitools/iris-grib)
118- Iris interface to ECMWF's GRIB API
119-
120- matplotlib (https://matplotlib.org)
121- Python package for 2D plotting.
122-
123- mock (http://pypi.python.org/pypi/mock/)
124- Python mocking and patching package for testing. Note that this package
125- is only required to support the Iris unit tests.
126-
127- nose (https://nose.readthedocs.io/en/latest/)
128- Python package for software testing. Iris is not compatible with nose2.
129-
130- pep8 (https://pypi.python.org/pypi/pep8)
131- Python package for software testing.
132-
133- pandas (http://pandas.pydata.org)
134- Python package providing high-performance, easy-to-use data structures and
135- data analysis tools.
136-
137- PythonImagingLibrary (http://effbot.org/zone/pil-index.htm)
138- Python package for image processing.
139-
140- pyugrid (https://github.com/pyugrid/pyugrid)
141- A Python API to utilize data written using the unstructured grid
142- UGRID conventions.
143-
144- shapely (https://github.com/Toblerity/Shapely)
145- Python package for the manipulation and analysis of planar geometric
146- objects.
147-
148- mo_pack (https://github.com/SciTools/mo_pack)
149- A Python wrapper to libmo_unpack, giving WGDOS packing and unpacking.
49+ pip install -e .
15050
15151
15252Generating conda requirements
15353'''''''''''''''''''''''''''''
15454
15555Requirements for Iris are stored in the ``requirements`` directory in the root of the source repository.
156- It is possible to generate a requirements file suitable for conda use with::
56+ It is possible to generate a requirements file suitable for use with conda ::
15757
15858 python requirements/gen_conda_requirements.py > conda_requirements.txt
15959
160- This may be installed with::
60+ This may then be installed with::
16161
16262 conda create -n my_iris_env --file conda_requirements.txt
16363
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