local reproduction details

Former-commit-id: 09d0c8a [formerly 0f9cadc]
Former-commit-id: 2f219096c8f123a204f154d68561ef9b4dfa7502

Author: michaeldorman

data/requirements.txt

@@ -0,0 +1,217 @@
+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: win-64
+affine=2.3.0=py_0
+anyio=2.2.0=py38haa244fe_0
+argon2-cffi=20.1.0=py38h294d835_2
+async_generator=1.10=py_0
+attrs=21.2.0=pyhd3eb1b0_0
+babel=2.9.1=pyh44b312d_0
+backcall=0.2.0=pyh9f0ad1d_0
+backports=1.0=py_2
+backports.functools_lru_cache=1.6.4=pyhd8ed1ab_0
+blas=1.0=mkl
+bleach=3.3.0=pyh44b312d_0
+branca=0.4.2=pyhd8ed1ab_0
+brotlipy=0.7.0=py38h2bbff1b_1003
+bzip2=1.0.8=he774522_0
+ca-certificates=2021.10.8=h5b45459_0
+cairo=1.16.0=hb19e0ff_1008
+certifi=2021.10.8=py38haa244fe_1
+cffi=1.14.3=py38hcd4344a_2
+cfitsio=3.470=he774522_6
+chardet=3.0.4=py38haa95532_1003
+click=7.1.2=pyhd3eb1b0_0
+click-plugins=1.1.1=py_0
+cligj=0.7.2=py38haa95532_0
+colorama=0.4.4=pyh9f0ad1d_0
+conda=4.11.0=py38haa244fe_0
+conda-package-handling=1.7.2=py38h76e460a_0
+console_shortcut=0.1.1=4
+cryptography=3.2.1=py38hcd4344a_1
+curl=7.78.0=h789b8ee_0
+cycler=0.10.0=py_2
+decorator=5.0.9=pyhd8ed1ab_0
+defusedxml=0.7.1=pyhd8ed1ab_0
+descartes=1.1.0=py_4
+entrypoints=0.3=pyhd8ed1ab_1003
+expat=2.4.1=h6c2663c_2
+fiona=1.8.20=py38h4bd599a_0
+folium=0.12.1.post1=pyhd8ed1ab_0
+fontconfig=2.13.1=h1989441_1005
+freetype=2.10.4=h546665d_1
+freexl=1.0.6=h2bbff1b_0
+gdal=3.2.2=py38hacca965_7
+geopandas=0.10.2=pyhd8ed1ab_0
+geopandas-base=0.10.2=pyha770c72_0
+geos=3.9.1=h39d44d4_2
+geotiff=1.6.0=ha8a8a2d_6
+gettext=0.19.8.1=h1a89ca6_1005
+hdf4=4.2.15=h0e5069d_3
+hdf5=1.10.6=nompi_h5268f04_1114
+icc_rt=2019.0.0=h0cc432a_1
+icu=68.1=h0e60522_0
+idna=2.10=py_0
+importlib-metadata=4.5.0=py38haa244fe_0
+intel-openmp=2021.2.0=haa95532_616
+ipykernel=5.5.5=py38h43734a8_0
+ipython=7.24.1=py38h43734a8_0
+ipython_genutils=0.2.0=py_1
+jbig=2.1=h8d14728_2003
+jedi=0.18.0=py38haa244fe_2
+jinja2=3.0.1=pyhd8ed1ab_0
+joblib=1.1.0=pyhd8ed1ab_0
+jpeg=9d=h8ffe710_0
+json5=0.9.5=pyh9f0ad1d_0
+jsonschema=3.2.0=pyhd8ed1ab_3
+jupyter_client=6.1.12=pyhd8ed1ab_0
+jupyter_core=4.7.1=py38haa244fe_0
+jupyter_server=1.4.1=py38haa95532_0
+jupyterlab=3.1.1=pyhd8ed1ab_0
+jupyterlab_pygments=0.1.2=pyh9f0ad1d_0
+jupyterlab_server=2.6.0=pyhd8ed1ab_0
+kealib=1.4.14=h96bfa42_2
+kiwisolver=1.3.1=py38hbd9d945_1
+krb5=1.19.2=hbae68bd_0
+lcms2=2.12=h2a16943_0
+lerc=2.2.1=h0e60522_0
+libblas=3.9.0=1_h8933c1f_netlib
+libboost=1.67.0=hd9e427e_4
+libcblas=3.9.0=5_hd5c7e75_netlib
+libclang=11.1.0=default_h5c34c98_1
+libcurl=7.78.0=h789b8ee_0
+libdeflate=1.7=h8ffe710_5
+libffi=3.3=h0e60522_2
+libgdal=3.2.2=ha6cada3_7
+libglib=2.68.3=h1e62bf3_0
+libiconv=1.16=he774522_0
+libkml=1.3.0=he5f2a48_4
+liblapack=3.9.0=5_hd5c7e75_netlib
+libnetcdf=4.8.0=nompi_hf689e7d_103
+libpng=1.6.37=h2a8f88b_0
+libpq=13.3=hfcc5ef8_0
+librttopo=1.1.0=hb340de5_6
+libsodium=1.0.18=h8d14728_1
+libspatialindex=1.9.3=h6c2663c_0
+libspatialite=5.0.1=h762a7f4_5
+libssh2=1.9.0=h7a1dbc1_1
+libtiff=4.3.0=h0c97f57_1
+libwebp-base=1.2.0=h8ffe710_2
+libxml2=2.9.12=hf5bbc77_0
+libzip=1.8.0=hfed4ece_0
+lz4-c=1.9.3=h8ffe710_0
+m2w64-expat=2.1.1=2
+m2w64-gcc-libgfortran=5.3.0=6
+m2w64-gcc-libs=5.3.0=7
+m2w64-gcc-libs-core=5.3.0=7
+m2w64-gettext=0.19.7=2
+m2w64-gmp=6.1.0=2
+m2w64-libiconv=1.14=6
+m2w64-libwinpthread-git=5.0.0.4634.697f757=2
+m2w64-xz=5.2.2=2
+mapclassify=2.4.3=pyhd8ed1ab_0
+markupsafe=2.0.1=py38h294d835_0
+matplotlib=3.4.2=py38haa244fe_0
+matplotlib-base=3.4.2=py38heae8d8c_0
+matplotlib-inline=0.1.2=pyhd8ed1ab_2
+menuinst=1.4.16=py38he774522_1
+mistune=0.8.4=py38h294d835_1003
+mkl=2021.2.0=haa95532_296
+mkl-service=2.3.0=py38h2bbff1b_1
+mkl_fft=1.3.0=py38h277e83a_2
+mkl_random=1.2.1=py38hf11a4ad_2
+msys2-conda-epoch=20160418=1
+munch=2.5.0=py_0
+nbclassic=0.2.6=pyhd3eb1b0_0
+nbclient=0.5.3=pyhd8ed1ab_0
+nbconvert=6.1.0=py38haa244fe_0
+nbformat=5.1.3=pyhd8ed1ab_0
+nest-asyncio=1.5.1=pyhd8ed1ab_0
+networkx=2.6.3=pyhd8ed1ab_1
+notebook=6.4.0=pyha770c72_0
+numpy=1.20.2=py38ha4e8547_0
+numpy-base=1.20.2=py38hc2deb75_0
+olefile=0.46=pyh9f0ad1d_1
+openjpeg=2.4.0=hb211442_1
+openssl=1.1.1l=h8ffe710_0
+packaging=20.9=pyh44b312d_0
+pandas=1.2.4=py38hd77b12b_0
+pandoc=2.14.0.3=h8ffe710_0
+pandocfilters=1.4.2=py_1
+parso=0.8.2=pyhd8ed1ab_0
+pcre=8.44=ha925a31_0
+pickleshare=0.7.5=py_1003
+pillow=8.3.1=py38h794f750_0
+pip=20.2.4=py38haa95532_0
+pixman=0.40.0=h8ffe710_0
+poppler=21.03.0=h9ff6ed8_0
+poppler-data=0.4.10=0
+postgresql=13.3=h1c22c4f_0
+powershell_shortcut=0.0.1=3
+proj=8.0.1=h1cfcee9_0
+prometheus_client=0.11.0=pyhd8ed1ab_0
+prompt-toolkit=3.0.19=pyha770c72_0
+pycosat=0.6.3=py38h2bbff1b_0
+pycparser=2.20=py_2
+pygeos=0.10.2=py38h127f298_0
+pygments=2.9.0=pyhd8ed1ab_0
+pyopenssl=19.1.0=pyhd3eb1b0_1
+pyparsing=2.4.7=pyh9f0ad1d_0
+pyproj=3.1.0=py38h5f73dae_3
+pyqt=5.12.3=py38haa244fe_7
+pyqt-impl=5.12.3=py38h885f38d_7
+pyqt5-sip=4.19.18=py38h885f38d_7
+pyqtchart=5.12=py38h885f38d_7
+pyqtwebengine=5.12.1=py38h885f38d_7
+pyrsistent=0.17.3=py38h294d835_2
+pysocks=1.7.1=py38haa95532_0
+python=3.8.5=h5fd99cc_1
+python-dateutil=2.8.1=pyhd3eb1b0_0
+python_abi=3.8=2_cp38
+pytz=2021.1=pyhd3eb1b0_0
+pywin32=227=py38he774522_1
+pywinpty=0.5.7=py38_0
+pyzmq=22.1.0=py38h09162b1_0
+qt=5.12.9=h5909a2a_4
+rasterio=1.2.6=py38hbd91096_1
+rasterstats=0.16.0=pyhd8ed1ab_0
+requests=2.24.0=py_0
+richdem=0.3.4=py38h7f85c0c_3
+rtree=0.9.7=py38h2eaa2aa_1
+ruamel_yaml=0.15.87=py38he774522_1
+scikit-learn=1.0.1=py38hb60ee80_2
+scipy=1.7.0=py38he847743_0
+send2trash=1.7.1=pyhd8ed1ab_0
+setuptools=50.3.1=py38haa95532_1
+shapely=1.7.1=py38h13ff51f_5
+simplejson=3.17.3=py38h294d835_0
+six=1.15.0=py38haa95532_0
+sniffio=1.2.0=py38haa244fe_1
+snuggs=1.4.7=py_0
+sqlite=3.36.0=h8ffe710_0
+tbb=2018.0.5=he980bc4_0
+terminado=0.9.4=py38haa95532_0
+testpath=0.5.0=pyhd8ed1ab_0
+threadpoolctl=3.0.0=pyh8a188c0_0
+tiledb=2.3.2=h78dabda_0
+tk=8.6.10=he774522_0
+tornado=6.1=py38h294d835_1
+tqdm=4.51.0=pyhd3eb1b0_0
+traitlets=5.0.5=py_0
+urllib3=1.25.11=py_0
+vc=14.1=h0510ff6_4
+vs2015_runtime=14.16.27012=hf0eaf9b_3
+wcwidth=0.2.5=pyh9f0ad1d_2
+webencodings=0.5.1=py_1
+wheel=0.35.1=pyhd3eb1b0_0
+win_inet_pton=1.1.0=py38haa95532_0
+wincertstore=0.2=py38_0
+winpty=0.4.3=4
+xerces-c=3.2.3=ha925a31_0
+xyzservices=2021.11.0=pyhd8ed1ab_0
+xz=5.2.5=h62dcd97_0
+yaml=0.2.5=he774522_0
+zeromq=4.3.4=h0e60522_0
+zipp=3.4.1=pyhd8ed1ab_0
+zlib=1.2.11=h62dcd97_4
+zstd=1.5.0=h6255e5f_0

data/zion.gpkg

@@ -38,13 +38,34 @@ We aim to make this web version of the book as easy as possible. See the source
 
 ### Reproduce the book locally
 
-To reproduce the book locally, run the following commands:
+First, download the book sample data into your working directory, and place them in a sub-directory named `"data"` inside that working directory.
 
-```bash
-# Todo add content
+For Windows, follow these steps:
+
+* Install [miniconda](https://docs.conda.io/en/latest/miniconda.html)
+* Open the Anaconda Prompt as Administrator, navigate to the above-mentioned working directory, and then run:
+
+```sh
+conda install -c conda-forge --file data/requirements.txt
+```
+
+* Open the Jupyter Notebook of any of chapters using a command such as:
 
+```sh
+jupyter notebook 02-spatial-data.ipynb
 ```
 
+For Linux, use your preferred package manager to install the packages used in the book (`geopandas`, `rasterio`, etc.) as specified in each chapter, as well as the Jupyter Notebook interface. For example, using `pip` to install the Jupyter Notebook package is as follows:
+
+```sh
+pip install jupyter-book
+```
+
+Then, navigate to the above-mentioned working directory, and open the Jupyter Notebook of any of chapters using a command such as:
+
+```sh
+jupyter notebook 02-spatial-data.ipynb
+```
 
 ### Reproduce the book in a Docker container with VSCode IDE