Introducing the New CyberGISX Python 3 0.9.4 Kernel¶
Authors: Alex Michels
Last Updated: July 25th, 2023
This notebook introduces the brand new Python 3-0.9.4 Kernel!
Summary:¶
- Tag notebooks that rely on the "Python 3" kernel. The unversioned "Python 3" kernel will be updated to use the latest 0.9.4 kernel on release. Please save the notebooks with the "Python 3-0.9.0" kernel if you would like to preserve current behavior. Due to updated package versions and new packages, we cannot guaranttee that all notebooks that work with the "Python 3-0.9.0" kernel will work with the Python 3-0.9.4 kernel.
- Python 3-0.9.4 has updated and new packages. The kernel has lots of updates and new packages like census, gtfspy, and pyrosm!
- Java now loaded in Python 3 0.9.4 Kernel. The "Python 3-0.9.4" kernel now uses our new
cybergisx-0.9.0metamodule which loads Java into the environment. This was required for a variety of packages.
Tag notebooks that rely on the "Python 3" kernel.¶
The unversioned "Python 3" kernel will be updated to use the latest 0.9.4 kernel on release. This is done so that our "Python 3" kernel is always using our latest version. We feel this is important so that new users can jump right in and not get confused with our versioned kernel system. By the "unversioned" Python 3 kernel, we are referring to the kernel in the image below:
Please save the notebooks with the "Python 3-0.9.0" kernel if you would like to preserve current behavior. You can tell which kernel a notebook is using by checking the top-right corner. Notebooks using the Python 3 kernel will look like:
To change the notebook to use the "Python 3-0.9.0" kernel, simply click the kernel name in the top-right (the area circled in the image above) to bring up a "Select Kernel" dropdown menu. Then, select "Python3-0.9.0" and save the notebook.
Due to updated package versions and new packages, we cannot guaranttee that all notebooks that work with the "Python 3-0.9.0" will work with the "Python 3-0.9.4" kernel. There are a variety of updated and new packages which we will discuss further in the next section, so some code may work with both kernels and other code may not.
Python 3-0.9.4 has updated and new packages¶
The Python 3-0.9.4 kernel has a variety of new and updated packages! A few of the new packages:
- census
- dgl & dglgo
- googlemaps
- gtfspy
- movingpandas
- plotnine
- r5py
- spatial_access
- torch & torch_geometric
- urbanpy
A few of the notable updates/upgrades are:
- geopandas 0.10.2 -> 0.13.2
- osmnx 1.1.2 -> 1.2.2
- pandas 1.3.5-> 2.0.0
- scikit-learn 1.0.2 -> 1.2.2
For a full read-out of the kernel we can use conda:
In [1]:
!conda list -p /cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.4
# packages in environment at /cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.4: # # Name Version Build Channel _libgcc_mutex 0.1 conda_forge conda-forge _openmp_mutex 4.5 2_kmp_llvm conda-forge _tflow_select 2.3.0 mkl defaults abseil-cpp 20210324.2 h9c3ff4c_0 conda-forge absl-py 1.4.0 pyhd8ed1ab_0 conda-forge access 1.1.9 pypi_0 pypi affine 2.4.0 pyhd8ed1ab_0 conda-forge aiobotocore 2.5.0 pyhd8ed1ab_0 conda-forge aiohttp 3.8.4 py38h01eb140_1 conda-forge aioitertools 0.11.0 pyhd8ed1ab_0 conda-forge aiosignal 1.3.1 pyhd8ed1ab_0 conda-forge alabaster 0.7.13 pypi_0 pypi alsa-lib 1.2.3.2 h166bdaf_0 conda-forge amply 0.1.5 pyhd8ed1ab_0 conda-forge annotated-types 0.6.0 pypi_0 pypi anyio 3.6.1 pypi_0 pypi anyjson 0.3.3 py38h578d9bd_1003 conda-forge appdirs 1.4.4 pyh9f0ad1d_0 conda-forge arcgis 1.9.1 py38_2328 Esri argon2-cffi 21.3.0 pyhd8ed1ab_0 conda-forge argon2-cffi-bindings 21.2.0 py38h0a891b7_3 conda-forge argparse 1.4.0 pypi_0 pypi arpack 3.7.0 hdefa2d7_2 conda-forge arrow 1.2.3 pyhd8ed1ab_0 conda-forge arrow-cpp 6.0.1 py38h87e2ab4_3_cpu conda-forge astor 0.8.1 pyh9f0ad1d_0 conda-forge asttokens 2.2.1 pyhd8ed1ab_0 conda-forge astunparse 1.6.3 pyhd8ed1ab_0 conda-forge async-lru 2.0.4 pypi_0 pypi async-timeout 4.0.2 pyhd8ed1ab_0 conda-forge at-spi2-atk 2.38.0 h0630a04_3 conda-forge at-spi2-core 2.40.3 h0630a04_0 conda-forge atk-1.0 2.36.0 h3371d22_4 conda-forge atlas 0.27.0 pypi_0 pypi attrs 23.1.0 pyh71513ae_1 conda-forge autopep8 2.0.4 pypi_0 pypi aws-c-auth 0.6.8 hfef2836_0 conda-forge aws-c-cal 0.5.12 h70efedd_7 conda-forge aws-c-common 0.6.17 h7f98852_0 conda-forge aws-c-compression 0.2.14 h7c7754b_7 conda-forge aws-c-event-stream 0.2.7 hb80ed28_31 conda-forge aws-c-http 0.6.10 h58a30cf_2 conda-forge aws-c-io 0.10.13 he836878_5 conda-forge aws-c-mqtt 0.7.9 h042a236_0 conda-forge aws-c-s3 0.1.27 h4f4cd48_12 conda-forge aws-c-sdkutils 0.1.1 h7c7754b_4 conda-forge aws-checksums 0.1.12 h7c7754b_6 conda-forge aws-crt-cpp 0.17.9 hc7d31a4_1 conda-forge aws-requests-auth 0.4.3 py_0 defaults aws-sdk-cpp 1.9.154 h77f1c7e_0 conda-forge babel 2.12.1 pyhd8ed1ab_1 conda-forge backcall 0.2.0 pyh9f0ad1d_0 conda-forge backports 1.1 pyhd3eb1b0_0 defaults backports.functools_lru_cache 1.6.4 pyhd8ed1ab_0 conda-forge backports.zoneinfo 0.2.1 py38h0a891b7_7 conda-forge bcrypt 3.2.2 py38h0a891b7_1 conda-forge beautifulsoup4 4.12.2 pyha770c72_0 conda-forge black 21.12b0 pyhd8ed1ab_0 conda-forge blas 2.117 openblas conda-forge blas-devel 3.9.0 17_linux64_openblas conda-forge bleach 6.0.0 pyhd8ed1ab_0 conda-forge blinker 1.6.2 pyhd8ed1ab_0 conda-forge blis 0.7.11 pypi_0 pypi blosc 1.21.4 h0f2a231_0 conda-forge blosc2 2.0.0 pypi_0 pypi bokeh 3.1.1 pyhd8ed1ab_0 conda-forge boost 1.74.0 py38h2b96118_5 conda-forge boost-cpp 1.74.0 h312852a_4 conda-forge boto3 1.26.76 pyhd8ed1ab_0 conda-forge botocore 1.29.76 pyhd8ed1ab_0 conda-forge branca 0.6.0 pyhd8ed1ab_0 conda-forge brotli 1.0.9 h166bdaf_8 conda-forge brotli-bin 1.0.9 h166bdaf_8 conda-forge brotli-python 1.0.9 py38hfa26641_8 conda-forge brotlipy 0.7.0 py38h0a891b7_1005 conda-forge brunsli 0.1 h9c3ff4c_0 conda-forge bs4 4.12.2 hd8ed1ab_0 conda-forge bzip2 1.0.8 h7f98852_4 conda-forge c-ares 1.19.1 hd590300_0 conda-forge c-blosc2 2.9.2 hb4ffafa_0 conda-forge ca-certificates 2023.08.22 h06a4308_0 defaults cachetools 5.3.0 pyhd8ed1ab_0 conda-forge cairo 1.16.0 h6cf1ce9_1008 conda-forge cairomm 1.14.4 ha770c72_1 conda-forge cairomm-1.0 1.14.4 h09cb3b9_0 conda-forge cartopy 0.20.0 py38hc951a7f_0 conda-forge catalogue 2.0.10 pypi_0 pypi cchardet 2.1.7 pypi_0 pypi cenpy 1.0.1 pyhd8ed1ab_0 conda-forge census 0.8.20 pypi_0 pypi certifi 2023.7.22 pyhd8ed1ab_0 conda-forge cffi 1.15.1 py38h4a40e3a_3 conda-forge cfitsio 3.470 hb418390_7 conda-forge cftime 1.6.2 py38h26c90d9_1 conda-forge chapyter 0.3.1 pypi_0 pypi charls 2.2.0 h9c3ff4c_0 conda-forge charset-normalizer 3.1.0 pyhd8ed1ab_0 conda-forge click 8.1.5 pypi_0 pypi click-plugins 1.1.1 py_0 defaults cligj 0.7.2 pyhd8ed1ab_1 conda-forge cloudpathlib 0.15.1 pypi_0 pypi cloudpickle 2.2.1 pyhd8ed1ab_0 conda-forge coin-or-cbc 2.10.10 h9002f0b_0 conda-forge coin-or-cgl 0.60.7 h516709c_0 conda-forge coin-or-clp 1.17.8 h1ee7a9c_0 conda-forge coin-or-osi 0.108.8 ha2443b9_0 conda-forge coin-or-utils 2.11.9 hee58242_0 conda-forge coincbc 2.10.10 0_metapackage conda-forge colorama 0.4.6 pyhd8ed1ab_0 conda-forge colorcet 3.0.1 pyhd8ed1ab_0 conda-forge colorspacious 1.1.2 pyh24bf2e0_0 conda-forge colour 0.1.5 py_0 conda-forge comm 0.1.3 pyhd8ed1ab_0 conda-forge confection 0.1.3 pypi_0 pypi configargparse 1.5.3 pyhd8ed1ab_0 conda-forge contextily 1.3.0 pyhd8ed1ab_0 conda-forge contourpy 1.1.0 py38h7f3f72f_0 conda-forge coverage 7.2.7 py38h01eb140_0 conda-forge cryptography 39.0.1 py38h9ce1e76_0 defaults curl 7.88.1 h5eee18b_0 defaults cybergis-compute-client 0.2.5 pypi_0 pypi cycler 0.11.0 pyhd8ed1ab_0 conda-forge cykhash 2.0.1 py38h8dc9893_1 conda-forge cymem 2.0.8 pypi_0 pypi cython 0.29.35 py38h17151c0_0 conda-forge cytoolz 0.12.0 py38h0a891b7_1 conda-forge dash 2.10.2 pyhd8ed1ab_0 conda-forge dash-bootstrap-components 1.4.1 pyhd8ed1ab_0 conda-forge dask 2023.5.0 pypi_0 pypi dataclasses 0.8 pyhc8e2a94_3 conda-forge datashader 0.15.0 pyhd8ed1ab_0 conda-forge datashape 0.5.4 py_1 conda-forge dbus 1.13.18 hb2f20db_0 defaults debugpy 1.6.7 py38h8dc9893_0 conda-forge decorator 5.1.1 pyhd8ed1ab_0 conda-forge defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge deprecation 2.1.0 pyh9f0ad1d_0 conda-forge descartes 1.1.0 py_4 defaults dgl 1.1.2 pypi_0 pypi dglgo 0.0.2 pypi_0 pypi dill 0.3.6 pyhd8ed1ab_1 conda-forge disjoint-set 0.7.3 pypi_0 pypi diskcache 5.6.1 pypi_0 pypi distributed 2023.5.0 pypi_0 pypi dnspython 2.3.0 pyhd8ed1ab_0 conda-forge docutils 0.20.1 py38h578d9bd_0 conda-forge draco 1.5.6 hf52228f_0 conda-forge earthpy 0.9.4 pyhd8ed1ab_0 conda-forge entrypoints 0.4 pyhd8ed1ab_0 conda-forge epoxy 1.5.10 h166bdaf_1 conda-forge esda 2.4.3 pyhd8ed1ab_0 conda-forge et_xmlfile 1.1.0 pyhd8ed1ab_0 conda-forge exceptiongroup 1.1.1 pyhd8ed1ab_0 conda-forge executing 1.2.0 pyhd8ed1ab_0 conda-forge exiv2 0.27.5 h848de5d_0 conda-forge expat 2.5.0 hcb278e6_1 conda-forge fastjsonschema 2.16.1 pypi_0 pypi filelock 3.12.2 pyhd8ed1ab_0 conda-forge findspark 2.0.1 pyhd8ed1ab_0 conda-forge fiona 1.8.20 py38hbb147eb_1 conda-forge flake8 6.0.0 pyhd8ed1ab_0 conda-forge flask 2.0.3 pyhd8ed1ab_0 conda-forge flask-compress 1.13 pyhd8ed1ab_0 conda-forge flask_cors 3.0.10 pyhd3deb0d_0 conda-forge flask_json 0.3.4 py_0 conda-forge flit-core 3.9.0 pyhd8ed1ab_0 conda-forge folium 0.14.0 pyhd8ed1ab_0 conda-forge font-ttf-dejavu-sans-mono 2.37 hab24e00_0 conda-forge font-ttf-inconsolata 3.000 h77eed37_0 conda-forge font-ttf-source-code-pro 2.038 h77eed37_0 conda-forge font-ttf-ubuntu 0.83 hab24e00_0 conda-forge fontconfig 2.14.2 h14ed4e7_0 conda-forge fonts-conda-ecosystem 1 0 conda-forge fonts-conda-forge 1 0 conda-forge fonttools 4.40.0 pypi_0 pypi fqdn 1.5.1 pypi_0 pypi freetype 2.12.1 hca18f0e_1 conda-forge freexl 1.0.6 h166bdaf_1 conda-forge fribidi 1.0.10 h36c2ea0_0 conda-forge frozenlist 1.3.3 py38h0a891b7_0 conda-forge fsspec 2023.6.0 pyh1a96a4e_0 conda-forge furl 2.1.3 pyhd8ed1ab_0 conda-forge future 0.18.3 pyhd8ed1ab_0 conda-forge fuzzywuzzy 0.18.0 pyhd8ed1ab_0 conda-forge gast 0.4.0 pyh9f0ad1d_0 conda-forge gdal 3.3.1 py38hbfa483c_2 conda-forge gdk-pixbuf 2.42.10 h5eee18b_0 defaults gdown 4.7.1 pyhd8ed1ab_0 conda-forge geographiclib 1.52 pyhd8ed1ab_0 conda-forge geoindex 0.0.1 pypi_0 pypi geojson 3.0.1 pyhd8ed1ab_0 conda-forge geopandas 0.13.2 pyhd8ed1ab_1 conda-forge geopandas-base 0.13.2 pyha770c72_1 conda-forge geopy 2.3.0 pyhd8ed1ab_0 conda-forge geopyspark 0.4.3 pypi_0 pypi geos 3.9.1 h9c3ff4c_2 conda-forge geosnap 0.11.0 pyhd8ed1ab_0 conda-forge geospark 1.3.1 pyhd8ed1ab_0 conda-forge geotiff 1.6.0 h4f31c25_6 conda-forge geoviews 1.10.0 pyhd8ed1ab_0 conda-forge geoviews-core 1.10.0 pyha770c72_0 conda-forge gettext 0.21.1 h27087fc_0 conda-forge gflags 2.2.2 he1b5a44_1004 conda-forge giddy 2.3.4 pyhd8ed1ab_0 conda-forge giflib 5.2.1 h0b41bf4_3 conda-forge gitdb 4.0.10 pyhd8ed1ab_0 conda-forge gitpython 3.1.31 pyhd8ed1ab_0 conda-forge glib 2.72.1 h6239696_0 conda-forge glib-tools 2.72.1 h6239696_0 conda-forge glog 0.5.0 h48cff8f_0 conda-forge glpk 4.65 h9202a9a_1004 conda-forge gmp 6.2.1 h58526e2_0 conda-forge gmpy2 2.1.2 py38h793c122_1 conda-forge google-api-core 2.10.0 pyhd8ed1ab_0 conda-forge google-api-python-client 2.89.0 pyhd8ed1ab_0 conda-forge google-auth 2.20.0 pyh1a96a4e_0 conda-forge google-auth-httplib2 0.1.0 pyhd8ed1ab_1 conda-forge google-auth-oauthlib 1.0.0 pypi_0 pypi google-pasta 0.2.0 pyh8c360ce_0 conda-forge googleapis-common-protos 1.57.0 py38h578d9bd_0 conda-forge googlemaps 2.5.1 py_0 conda-forge gptcache 0.1.38 pypi_0 pypi graph-tool 2.45 py38h7041675_2 conda-forge graph-tool-base 2.45 py38hba1c032_2 conda-forge graphistry 0.20.5 pypi_0 pypi graphite2 1.3.14 h295c915_1 defaults graphviz 2.50.0 h85b4f2f_1 conda-forge greenlet 2.0.2 py38h17151c0_1 conda-forge grpc-cpp 1.42.0 h7e358d9_0 conda-forge grpcio 1.59.0 pypi_0 pypi gsl 2.7.1 h6e86dc7_1 defaults gst-plugins-base 1.18.5 hf529b03_2 conda-forge gstreamer 1.18.5 h9f60fe5_3 conda-forge gtfspy 0.0.4 pypi_0 pypi gtk2 2.24.33 h539f30e_1 conda-forge gtk3 3.24.31 h952b7bf_2 conda-forge gts 0.7.6 h64030ff_2 conda-forge guidance 0.0.64 pypi_0 pypi gurobi 10.0.2 py38_0 gurobi h3 3.7.6 pypi_0 pypi h5py 2.10.0 nompi_py38h9915d05_106 conda-forge harfbuzz 3.1.1 h83ec7ef_0 conda-forge hdf4 4.2.15 h9772cbc_5 conda-forge hdf5 1.10.6 nompi_h6a2412b_1114 conda-forge heapdict 1.0.1 py_0 defaults hicolor-icon-theme 0.17 ha770c72_2 conda-forge holoviews 1.16.2 pyhd8ed1ab_0 conda-forge httplib2 0.22.0 pyhd8ed1ab_0 conda-forge huggingface-hub 0.17.3 pypi_0 pypi icu 68.2 h9c3ff4c_0 conda-forge idna 3.4 pyhd8ed1ab_0 conda-forge imagecodecs 2021.8.26 py38hf0132c2_1 defaults imagecodecs-lite 2019.12.3 py38h26c90d9_6 conda-forge imageio 2.31.1 pyh24c5eb1_0 conda-forge imagesize 1.4.1 pypi_0 pypi importlib-metadata 6.7.0 pyha770c72_0 conda-forge importlib-resources 5.12.0 pyhd8ed1ab_0 conda-forge importlib_metadata 6.7.0 hd8ed1ab_0 conda-forge importlib_resources 5.12.0 pyhd8ed1ab_0 conda-forge inequality 1.0.0 py_0 defaults infinity 1.5 pyhd8ed1ab_0 conda-forge iniconfig 2.0.0 pyhd8ed1ab_0 conda-forge intervals 0.9.2 pyhd8ed1ab_0 conda-forge ipyfilechooser 0.6.0 pypi_0 pypi ipykernel 6.23.1 pyh210e3f2_0 conda-forge ipyleaflet 0.17.3 pyhd8ed1ab_0 conda-forge ipython 8.3.0 pypi_0 pypi ipython-sql 0.4.1 pypi_0 pypi ipython_genutils 0.2.0 py_1 conda-forge ipywidgets 7.7.5 pypi_0 pypi isoduration 20.11.0 pypi_0 pypi isort 5.12.0 pypi_0 pypi isoweek 1.3.3 pypi_0 pypi itsdangerous 2.1.2 pyhd8ed1ab_0 conda-forge jbig 2.1 h7f98852_2003 conda-forge jedi 0.18.2 pyhd8ed1ab_0 conda-forge jeepney 0.8.0 pyhd8ed1ab_0 conda-forge jellyfish 0.11.2 pypi_0 pypi jinja2 3.1.2 pyhd8ed1ab_1 conda-forge jmespath 1.0.1 pyhd8ed1ab_0 conda-forge joblib 1.2.0 pyhd8ed1ab_0 conda-forge jpeg 9e h0b41bf4_3 conda-forge jpype1 1.4.1 py38h43d8883_1 conda-forge json-c 0.15 h98cffda_0 conda-forge json5 0.9.14 pypi_0 pypi jsoncpp 1.9.4 h4bd325d_3 conda-forge jsonlines 1.2.0 pyh9f0ad1d_2 conda-forge jsonpointer 2.4 pypi_0 pypi jsonschema 4.17.3 pyhd8ed1ab_0 conda-forge jupyter-lsp 2.2.0 pypi_0 pypi jupyter-server 2.7.0 pypi_0 pypi jupyter_client 8.2.0 pyhd8ed1ab_0 conda-forge jupyter_core 5.3.0 py38h578d9bd_0 conda-forge jupyter_events 0.6.3 pyhd8ed1ab_0 conda-forge jupyter_server 2.6.0 pyhd8ed1ab_0 conda-forge jupyter_server_terminals 0.4.4 pyhd8ed1ab_1 conda-forge jupyterlab 4.0.3 pypi_0 pypi jupyterlab-server 2.24.0 pypi_0 pypi jupyterlab-widgets 1.1.0 pypi_0 pypi jupyterlab_pygments 0.2.2 pyhd8ed1ab_0 conda-forge jupyterlab_widgets 3.0.7 pyhd8ed1ab_1 conda-forge jxrlib 1.1 h7f98852_2 conda-forge kealib 1.4.14 hcc255d8_2 conda-forge keras 2.13.1 pypi_0 pypi keras-preprocessing 1.1.2 pyhd8ed1ab_0 conda-forge keyring 21.7.0 py38h578d9bd_0 conda-forge kiwisolver 1.4.4 py38h43d8883_1 conda-forge knot-floer-homology 1.1 pypi_0 pypi krb5 1.19.4 h568e23c_0 defaults langcodes 3.3.0 pypi_0 pypi laspy 2.3.0 pyha21a80b_0 conda-forge laszip 3.4.3 h9c3ff4c_2 conda-forge laz-perf 3.3.0 hf52228f_0 conda-forge lcms2 2.15 hfd0df8a_0 conda-forge ld_impl_linux-64 2.40 h41732ed_0 conda-forge legendgram 0.0.3 py_1 conda-forge lerc 3.0 h9c3ff4c_0 conda-forge levenshtein 0.21.1 py38h17151c0_0 conda-forge libaec 1.0.6 hcb278e6_1 conda-forge libblas 3.9.0 17_linux64_openblas conda-forge libbrotlicommon 1.0.9 h166bdaf_8 conda-forge libbrotlidec 1.0.9 h166bdaf_8 conda-forge libbrotlienc 1.0.9 h166bdaf_8 conda-forge libcblas 3.9.0 17_linux64_openblas conda-forge libclang 16.0.6 pypi_0 pypi libcups 2.3.3 h3e49a29_2 conda-forge libcurl 7.88.1 h91b91d3_0 defaults libdap4 3.20.6 hd7c4107_2 conda-forge libdeflate 1.8 h7f98852_0 conda-forge libedit 3.1.20221030 h5eee18b_0 defaults libev 4.33 h516909a_1 conda-forge libevent 2.1.10 h9b69904_4 conda-forge libexpat 2.5.0 hcb278e6_1 conda-forge 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sphinxcontrib-serializinghtml 1.1.5 pypi_0 pypi spint 1.0.7 pyhd8ed1ab_0 conda-forge splot 1.1.5.post1 pyhd8ed1ab_0 conda-forge spopt 0.5.0 pyhd8ed1ab_0 conda-forge spreg 1.3.2 pyhd8ed1ab_0 conda-forge spvcm 0.3.0 py_0 defaults sql 2022.4.0 pypi_0 pypi sqlalchemy 2.0.16 py38h01eb140_0 conda-forge sqlalchemy-utils 0.41.1 pyhd8ed1ab_0 conda-forge sqlalchemy-utils-arrow 0.41.1 pyhd8ed1ab_0 conda-forge sqlalchemy-utils-babel 0.41.1 pyhd8ed1ab_0 conda-forge sqlalchemy-utils-base 0.41.1 pyhd8ed1ab_0 conda-forge sqlalchemy-utils-color 0.41.1 pyhd8ed1ab_0 conda-forge sqlalchemy-utils-encrypted 0.41.1 pyhd8ed1ab_0 conda-forge sqlalchemy-utils-intervals 0.41.1 pyhd8ed1ab_0 conda-forge sqlalchemy-utils-password 0.41.1 pyhd8ed1ab_0 conda-forge sqlalchemy-utils-pendulum 0.41.1 pyhd8ed1ab_0 conda-forge sqlalchemy-utils-phone 0.41.1 pyhd8ed1ab_0 conda-forge sqlalchemy-utils-timezone 0.41.1 pyhd8ed1ab_0 conda-forge sqlalchemy-utils-url 0.41.1 pyhd8ed1ab_0 conda-forge sqlite 3.42.0 h2c6b66d_0 conda-forge sqlparse 0.4.4 pyhd8ed1ab_0 conda-forge srsly 2.4.8 pypi_0 pypi stack_data 0.6.2 pyhd8ed1ab_0 conda-forge statsmodels 0.13.5 py38h26c90d9_2 conda-forge suitesparse 5.10.1 h9e50725_1 conda-forge sympy 1.12 pypyh9d50eac_103 conda-forge tabulate 0.9.0 pypi_0 pypi tbb 2021.8.0 hdb19cb5_0 defaults tblib 1.7.0 pyhd8ed1ab_0 conda-forge tenacity 8.2.2 pyhd8ed1ab_0 conda-forge tensorboard 2.13.0 pypi_0 pypi tensorboard-data-server 0.7.1 pypi_0 pypi tensorboard-plugin-wit 1.8.1 pyhd8ed1ab_0 conda-forge tensorflow 2.13.1 pypi_0 pypi tensorflow-estimator 2.13.0 pypi_0 pypi tensorflow-io-gcs-filesystem 0.34.0 pypi_0 pypi termcolor 2.3.0 pyhd8ed1ab_0 conda-forge terminado 0.17.1 pyh41d4057_0 conda-forge testpath 0.6.0 pyhd8ed1ab_0 conda-forge texttable 1.6.7 pyhd8ed1ab_0 conda-forge thinc 8.2.1 pypi_0 pypi threadpool 1.3.2 pypi_0 pypi threadpoolctl 3.1.0 pyh8a188c0_0 conda-forge tifffile 2021.11.2 pyhd8ed1ab_0 conda-forge tiktoken 0.4.0 pypi_0 pypi tiledb 2.3.4 he87e0bf_0 conda-forge tinycss2 1.1.1 pypi_0 pypi tk 8.6.12 h27826a3_0 conda-forge tobler 0.10 pyhd8ed1ab_0 conda-forge tokenizers 0.14.1 pypi_0 pypi toml 0.10.2 pyhd8ed1ab_0 conda-forge tomli 1.2.2 pyhd8ed1ab_0 conda-forge toolz 0.12.0 pyhd8ed1ab_0 conda-forge torch 2.1.0 pypi_0 pypi torch-geometric 2.3.1 pypi_0 pypi torchvision 0.16.0 pypi_0 pypi tornado 6.3.2 py38h01eb140_0 conda-forge tqdm 4.65.0 pyhd8ed1ab_1 conda-forge traitlets 5.9.0 pyhd8ed1ab_0 conda-forge traittypes 0.2.1 pyh9f0ad1d_2 conda-forge transformers 4.34.0 pypi_0 pypi triton 2.1.0 pypi_0 pypi typed-ast 1.5.4 py38h0a891b7_1 conda-forge typer 0.9.0 pypi_0 pypi typing-extensions 4.8.0 pypi_0 pypi typing_utils 0.1.0 pyhd8ed1ab_0 conda-forge tzcode 2023c h0b41bf4_0 conda-forge tzdata 2023c h71feb2d_0 conda-forge uc-micro-py 1.0.1 pyhd8ed1ab_0 conda-forge ujson 5.7.0 py38h8dc9893_0 conda-forge unicodedata2 15.0.0 py38h0a891b7_0 conda-forge urbanaccess 0.2.2 pyhd3deb0d_0 conda-forge urbanpy 0.2.1 pypi_0 pypi uri-template 1.3.0 pypi_0 pypi uritemplate 4.1.1 pyhd8ed1ab_0 conda-forge urllib3 1.26.16 py38h06a4308_0 defaults us 3.1.1 pypi_0 pypi versioneer 0.28 pyhd8ed1ab_0 conda-forge vincent 0.4.4 py_1 Esri wasabi 1.1.2 pypi_0 pypi wcwidth 0.2.6 pyhd8ed1ab_0 conda-forge weasel 0.3.2 pypi_0 pypi webcolors 1.13 pypi_0 pypi webencodings 0.5.1 py_1 conda-forge websocket-client 1.4.0 pypi_0 pypi werkzeug 2.3.6 pyhd8ed1ab_0 conda-forge wget 1.21.4 h91b91d3_1 defaults wheel 0.40.0 pyhd8ed1ab_0 conda-forge whitebox 2.3.1 pyhd8ed1ab_0 conda-forge widgetsnbextension 3.6.4 pypi_0 pypi wrapt 1.15.0 py38h1de0b5d_0 conda-forge xarray 2022.11.0 py38h06a4308_0 defaults xerces-c 3.2.3 h9d8b166_3 conda-forge xlrd 2.0.1 pyhd8ed1ab_3 conda-forge xlsxwriter 3.1.2 pyhd8ed1ab_0 conda-forge xorg-fixesproto 5.0 h7f98852_1002 conda-forge xorg-inputproto 2.3.2 h7f98852_1002 conda-forge xorg-kbproto 1.0.7 h7f98852_1002 conda-forge xorg-libice 1.1.1 hd590300_0 conda-forge xorg-libsm 1.2.4 h7391055_0 conda-forge xorg-libx11 1.8.6 h8ee46fc_0 conda-forge xorg-libxau 1.0.11 hd590300_0 conda-forge xorg-libxdmcp 1.1.3 h7f98852_0 conda-forge xorg-libxext 1.3.4 h0b41bf4_2 conda-forge xorg-libxfixes 5.0.3 h7f98852_1004 conda-forge xorg-libxi 1.7.10 h7f98852_0 conda-forge xorg-libxrender 0.9.10 h7f98852_1003 conda-forge xorg-libxtst 1.2.3 h7f98852_1002 conda-forge xorg-recordproto 1.14.2 h7f98852_1002 conda-forge xorg-renderproto 0.11.1 h7f98852_1002 conda-forge xorg-xextproto 7.3.0 h0b41bf4_1003 conda-forge xorg-xproto 7.0.31 h7f98852_1007 conda-forge xyzservices 2023.5.0 pyhd8ed1ab_1 conda-forge xz 5.2.10 h5eee18b_1 defaults yaml 0.2.5 h7f98852_2 conda-forge yarl 1.9.2 py38h01eb140_0 conda-forge zeromq 4.3.4 h9c3ff4c_1 conda-forge zfp 0.5.5 h9c3ff4c_8 conda-forge zict 3.0.0 pyhd8ed1ab_0 conda-forge zipp 3.15.0 pyhd8ed1ab_0 conda-forge zlib 1.2.13 hd590300_5 conda-forge zlib-ng 2.0.7 h0b41bf4_0 conda-forge zstandard 0.19.0 py38h5945529_1 conda-forge zstd 1.5.2 h3eb15da_6 conda-forge
Let's briefly splotlight two new packages: us and urbanpy!
us¶
The us package is very useful for quickly retrieving data our US states and territories. For more information check out their README. For example, we can easily loop through the states and their FIPS codes:
In [2]:
import us
for state in us.states.STATES:
print(state, state.fips)
Alabama 01 Alaska 02 Arizona 04 Arkansas 05 California 06 Colorado 08 Connecticut 09 Delaware 10 Florida 12 Georgia 13 Hawaii 15 Idaho 16 Illinois 17 Indiana 18 Iowa 19 Kansas 20 Kentucky 21 Louisiana 22 Maine 23 Maryland 24 Massachusetts 25 Michigan 26 Minnesota 27 Mississippi 28 Missouri 29 Montana 30 Nebraska 31 Nevada 32 New Hampshire 33 New Jersey 34 New Mexico 35 New York 36 North Carolina 37 North Dakota 38 Ohio 39 Oklahoma 40 Oregon 41 Pennsylvania 42 Rhode Island 44 South Carolina 45 South Dakota 46 Tennessee 47 Texas 48 Utah 49 Vermont 50 Virginia 51 Washington 53 West Virginia 54 Wisconsin 55 Wyoming 56
The package can also easily grab shapefiles for us. Let's use us to get the URL to Illinois counties and then plot that data with geopandas:
In [3]:
us.states.IL.shapefile_urls()
Out[3]:
{'tract': 'https://www2.census.gov/geo/tiger/TIGER2010/TRACT/2010/tl_2010_17_tract10.zip',
'cd': 'https://www2.census.gov/geo/tiger/TIGER2010/CD/111/tl_2010_17_cd111.zip',
'county': 'https://www2.census.gov/geo/tiger/TIGER2010/COUNTY/2010/tl_2010_17_county10.zip',
'state': 'https://www2.census.gov/geo/tiger/TIGER2010/STATE/2010/tl_2010_17_state10.zip',
'zcta': 'https://www2.census.gov/geo/tiger/TIGER2010/ZCTA5/2010/tl_2010_17_zcta510.zip',
'block': 'https://www2.census.gov/geo/tiger/TIGER2010/TABBLOCK/2010/tl_2010_17_tabblock10.zip',
'blockgroup': 'https://www2.census.gov/geo/tiger/TIGER2010/BG/2010/tl_2010_17_bg10.zip'}
In [4]:
import geopandas as gpd
url_dict = us.states.IL.shapefile_urls()
url = url_dict['county']
gdf = gpd.read_file(url)
gdf.explore()
Out[4]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [5]:
import urbanpy as up
boundaries = up.download.nominatim_osm('Lima, Peru', expected_position=2)
boundaries.plot()
Out[5]:
<Axes: >
torch¶
torch (pytorch) is a popular machine learning package in Python. Below we run one of their basic examples to "learn" a sine function:
In [6]:
# -*- coding: utf-8 -*-
import torch
import math
dtype = torch.float
device = "cuda" if torch.cuda.is_available() else "cpu"
torch.set_default_device(device)
# Create Tensors to hold input and outputs.
# By default, requires_grad=False, which indicates that we do not need to
# compute gradients with respect to these Tensors during the backward pass.
x = torch.linspace(-math.pi, math.pi, 2000, dtype=dtype)
y = torch.sin(x)
# Create random Tensors for weights. For a third order polynomial, we need
# 4 weights: y = a + b x + c x^2 + d x^3
# Setting requires_grad=True indicates that we want to compute gradients with
# respect to these Tensors during the backward pass.
a = torch.randn((), dtype=dtype, requires_grad=True)
b = torch.randn((), dtype=dtype, requires_grad=True)
c = torch.randn((), dtype=dtype, requires_grad=True)
d = torch.randn((), dtype=dtype, requires_grad=True)
learning_rate = 1e-6
for t in range(2000):
# Forward pass: compute predicted y using operations on Tensors.
y_pred = a + b * x + c * x ** 2 + d * x ** 3
# Compute and print loss using operations on Tensors.
# Now loss is a Tensor of shape (1,)
# loss.item() gets the scalar value held in the loss.
loss = (y_pred - y).pow(2).sum()
if t % 100 == 99:
print("Step: ", t, "Loss: ", loss.item())
# Use autograd to compute the backward pass. This call will compute the
# gradient of loss with respect to all Tensors with requires_grad=True.
# After this call a.grad, b.grad. c.grad and d.grad will be Tensors holding
# the gradient of the loss with respect to a, b, c, d respectively.
loss.backward()
# Manually update weights using gradient descent. Wrap in torch.no_grad()
# because weights have requires_grad=True, but we don't need to track this
# in autograd.
with torch.no_grad():
a -= learning_rate * a.grad
b -= learning_rate * b.grad
c -= learning_rate * c.grad
d -= learning_rate * d.grad
# Manually zero the gradients after updating weights
a.grad = None
b.grad = None
c.grad = None
d.grad = None
print(f'Result: y = {a.item()} + {b.item()} x + {c.item()} x^2 + {d.item()} x^3')
Step: 99 Loss: 1849.099365234375 Step: 199 Loss: 1283.896240234375 Step: 299 Loss: 893.1431884765625 Step: 399 Loss: 622.7196044921875 Step: 499 Loss: 435.38226318359375 Step: 599 Loss: 305.47705078125 Step: 699 Loss: 215.310546875 Step: 799 Loss: 152.66900634765625 Step: 899 Loss: 109.11079406738281 Step: 999 Loss: 78.79593658447266 Step: 1099 Loss: 57.6804313659668 Step: 1199 Loss: 42.96067810058594 Step: 1299 Loss: 32.69140625 Step: 1399 Loss: 25.52174949645996 Step: 1499 Loss: 20.51251220703125 Step: 1599 Loss: 17.01030158996582 Step: 1699 Loss: 14.560098648071289 Step: 1799 Loss: 12.844829559326172 Step: 1899 Loss: 11.643320083618164 Step: 1999 Loss: 10.801212310791016 Result: y = 0.04437532275915146 + 0.871370255947113 x + -0.0076554822735488415 x^2 + -0.09541129320859909 x^3
Next, we can plot the results against a sine function to see how well we did:
In [7]:
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(-math.pi, math.pi, num=100)
y = [a.item() + b.item() * i + c.item() * i**2 + d.item() * i**3 for i in x]
plt.plot(x, np.sin(x), label="sin(x)")
plt.plot(x, y, label="Pytorch approx.")
plt.legend()
plt.show()
Java now loaded in Python 3 0.9.4 Kernel¶
A handful of the new packages required Java, so the new kernel uses the new cybergis/0.9.0 metamodule which loads Java 11! You can check out the loaded modules by loading the module command and running module list:
In [8]:
import sys, os
sys.path.insert(0, os.path.join(os.environ['MODULESHOME'], "init"))
from env_modules_python import module
In [9]:
module("list")
Currently Loaded Modules: 1) GCCcore/8.3.0 44) x265/3.2-GCCcore-8.3.0 2) zlib/1.2.11-GCCcore-8.3.0 45) util-linux/2.34-GCCcore-8.3.0 3) binutils/2.32-GCCcore-8.3.0 46) fontconfig/2.13.1-GCCcore-8.3.0 4) GCC/8.3.0 47) xorg-macros/1.19.2-GCCcore-8.3.0 5) numactl/2.0.12-GCCcore-8.3.0 48) X11/20190717-GCCcore-8.3.0 6) XZ/5.2.4-GCCcore-8.3.0 49) FriBidi/1.0.5-GCCcore-8.3.0 7) libxml2/2.9.9-GCCcore-8.3.0 50) FFmpeg/4.2.1-GCCcore-8.3.0 8) libpciaccess/0.14-GCCcore-8.3.0 51) pixman/0.38.4-GCCcore-8.3.0 9) hwloc/1.11.12-GCCcore-8.3.0 52) libffi/3.2.1-GCCcore-8.3.0 10) OpenMPI/3.1.4-GCC-8.3.0 53) GLib/2.62.0-GCCcore-8.3.0 11) OpenBLAS/0.3.7-GCC-8.3.0 54) cairo/1.16.0-GCCcore-8.3.0 12) gompi/2019b 55) GMP/6.1.2-GCCcore-8.3.0 13) FFTW/3.3.8-gompi-2019b 56) nettle/3.5.1-GCCcore-8.3.0 14) ScaLAPACK/2.0.2-gompi-2019b 57) libdrm/2.4.99-GCCcore-8.3.0 15) foss/2019b 58) LLVM/9.0.0-GCCcore-8.3.0 16) bzip2/1.0.8-GCCcore-8.3.0 59) libunwind/1.3.1-GCCcore-8.3.0 17) ncurses/6.1-GCCcore-8.3.0 60) Mesa/19.1.7-GCCcore-8.3.0 18) gettext/0.20.1-GCCcore-8.3.0 61) libGLU/9.0.1-GCCcore-8.3.0 19) libpng/1.6.37-GCCcore-8.3.0 62) gzip/1.10-GCCcore-8.3.0 20) libreadline/8.0-GCCcore-8.3.0 63) lz4/1.9.2-GCCcore-8.3.0 21) Szip/2.1.1-GCCcore-8.3.0 64) zstd/1.4.4-GCCcore-8.3.0 22) HDF5/1.10.5-gompi-2019b 65) GRASS/7.8.3-foss-2019b 23) cURL/7.66.0-GCCcore-8.3.0 66) MPICH/3.3.2-GCC-8.3.0 24) netCDF/4.7.1-gompi-2019b 67) RHESSysEastCoast/7.2.0-foss-2019b 25) expat/2.2.7-GCCcore-8.3.0 68) netCDF-Fortran/4.5.2-gompi-2019b 26) GEOS/3.8.0-GCC-8.3.0 69) SUMMA/3.0.3-foss-2019b 27) Tcl/8.6.9-GCCcore-8.3.0 70) TauDEM/5.3.8-foss-2019b 28) SQLite/3.29.0-GCCcore-8.3.0 71) WRF/4.2.1-foss-2019b-dmpar 29) NASM/2.14.02-GCCcore-8.3.0 72) WPS/4.2-foss-2019b-dmpar 30) libjpeg-turbo/2.0.3-GCCcore-8.3.0 73) find_inlets/20191210-foss-2019b 31) JasPer/2.0.14-GCCcore-8.3.0 74) Boost/1.71.0-gompi-2019b 32) LibTIFF/4.0.10-GCCcore-8.3.0 75) Xvfb/1.20.8-GCCcore-8.3.0 33) PCRE/8.43-GCCcore-8.3.0 76) protozero/1.7.0-GCCcore-8.3.0 34) PROJ/6.2.1-GCCcore-8.3.0 77) sparsehash/2.0.3-GCCcore-8.3.0 35) libgeotiff/1.5.1-GCCcore-8.3.0 78) libosmium/2.15.6-foss-2019b 36) libtirpc/1.2.6-GCCcore-8.3.0 79) SoPlex/4.0.1-foss-2019b 37) HDF/4.2.14-GCCcore-8.3.0 80) PostgreSQL/12.4-GCCcore-8.3.0 38) GDAL/3.0.2-foss-2019b 81) protobuf/3.10.0-GCCcore-8.3.0 39) FreeXL/1.0.5-GCCcore-8.3.0 82) protobuf-c/1.3.3-GCCcore-8.3.0 40) libspatialite/4.3.0a-GCC-8.3.0 83) PostGIS/3.1.2-foss-2019b 41) freetype/2.10.1-GCCcore-8.3.0 84) Java/11.0.2 42) x264/20190925-GCCcore-8.3.0 85) cybergisx/0.9.0 43) LAME/3.100-GCCcore-8.3.0
Out[9]:
(None, '\nCurrently Loaded Modules:\n 1) GCCcore/8.3.0 44) x265/3.2-GCCcore-8.3.0\n 2) zlib/1.2.11-GCCcore-8.3.0 45) util-linux/2.34-GCCcore-8.3.0\n 3) binutils/2.32-GCCcore-8.3.0 46) fontconfig/2.13.1-GCCcore-8.3.0\n 4) GCC/8.3.0 47) xorg-macros/1.19.2-GCCcore-8.3.0\n 5) numactl/2.0.12-GCCcore-8.3.0 48) X11/20190717-GCCcore-8.3.0\n 6) XZ/5.2.4-GCCcore-8.3.0 49) FriBidi/1.0.5-GCCcore-8.3.0\n 7) libxml2/2.9.9-GCCcore-8.3.0 50) FFmpeg/4.2.1-GCCcore-8.3.0\n 8) libpciaccess/0.14-GCCcore-8.3.0 51) pixman/0.38.4-GCCcore-8.3.0\n 9) hwloc/1.11.12-GCCcore-8.3.0 52) libffi/3.2.1-GCCcore-8.3.0\n 10) OpenMPI/3.1.4-GCC-8.3.0 53) GLib/2.62.0-GCCcore-8.3.0\n 11) OpenBLAS/0.3.7-GCC-8.3.0 54) cairo/1.16.0-GCCcore-8.3.0\n 12) gompi/2019b 55) GMP/6.1.2-GCCcore-8.3.0\n 13) FFTW/3.3.8-gompi-2019b 56) nettle/3.5.1-GCCcore-8.3.0\n 14) ScaLAPACK/2.0.2-gompi-2019b 57) libdrm/2.4.99-GCCcore-8.3.0\n 15) foss/2019b 58) LLVM/9.0.0-GCCcore-8.3.0\n 16) bzip2/1.0.8-GCCcore-8.3.0 59) libunwind/1.3.1-GCCcore-8.3.0\n 17) ncurses/6.1-GCCcore-8.3.0 60) Mesa/19.1.7-GCCcore-8.3.0\n 18) gettext/0.20.1-GCCcore-8.3.0 61) libGLU/9.0.1-GCCcore-8.3.0\n 19) libpng/1.6.37-GCCcore-8.3.0 62) gzip/1.10-GCCcore-8.3.0\n 20) libreadline/8.0-GCCcore-8.3.0 63) lz4/1.9.2-GCCcore-8.3.0\n 21) Szip/2.1.1-GCCcore-8.3.0 64) zstd/1.4.4-GCCcore-8.3.0\n 22) HDF5/1.10.5-gompi-2019b 65) GRASS/7.8.3-foss-2019b\n 23) cURL/7.66.0-GCCcore-8.3.0 66) MPICH/3.3.2-GCC-8.3.0\n 24) netCDF/4.7.1-gompi-2019b 67) RHESSysEastCoast/7.2.0-foss-2019b\n 25) expat/2.2.7-GCCcore-8.3.0 68) netCDF-Fortran/4.5.2-gompi-2019b\n 26) GEOS/3.8.0-GCC-8.3.0 69) SUMMA/3.0.3-foss-2019b\n 27) Tcl/8.6.9-GCCcore-8.3.0 70) TauDEM/5.3.8-foss-2019b\n 28) SQLite/3.29.0-GCCcore-8.3.0 71) WRF/4.2.1-foss-2019b-dmpar\n 29) NASM/2.14.02-GCCcore-8.3.0 72) WPS/4.2-foss-2019b-dmpar\n 30) libjpeg-turbo/2.0.3-GCCcore-8.3.0 73) find_inlets/20191210-foss-2019b\n 31) JasPer/2.0.14-GCCcore-8.3.0 74) Boost/1.71.0-gompi-2019b\n 32) LibTIFF/4.0.10-GCCcore-8.3.0 75) Xvfb/1.20.8-GCCcore-8.3.0\n 33) PCRE/8.43-GCCcore-8.3.0 76) protozero/1.7.0-GCCcore-8.3.0\n 34) PROJ/6.2.1-GCCcore-8.3.0 77) sparsehash/2.0.3-GCCcore-8.3.0\n 35) libgeotiff/1.5.1-GCCcore-8.3.0 78) libosmium/2.15.6-foss-2019b\n 36) libtirpc/1.2.6-GCCcore-8.3.0 79) SoPlex/4.0.1-foss-2019b\n 37) HDF/4.2.14-GCCcore-8.3.0 80) PostgreSQL/12.4-GCCcore-8.3.0\n 38) GDAL/3.0.2-foss-2019b 81) protobuf/3.10.0-GCCcore-8.3.0\n 39) FreeXL/1.0.5-GCCcore-8.3.0 82) protobuf-c/1.3.3-GCCcore-8.3.0\n 40) libspatialite/4.3.0a-GCC-8.3.0 83) PostGIS/3.1.2-foss-2019b\n 41) freetype/2.10.1-GCCcore-8.3.0 84) Java/11.0.2\n 42) x264/20190925-GCCcore-8.3.0 85) cybergisx/0.9.0\n 43) LAME/3.100-GCCcore-8.3.0\n\n \n\n')
In [ ]: