- #HOW TO INSTALL JUPYTER LAB EXTENSION WITH CONDA UPDATE#
- #HOW TO INSTALL JUPYTER LAB EXTENSION WITH CONDA DOWNLOAD#
Latest version of these extentions don’t require additional configuration after install.Ĭan verify everything with jupyter labextension list (should see “enabled OK” for at least 6 extensions) Now when you type python it should run the python executable in the new conda environment, and all of the GDA packages will be available! Try it, run python, then import geopandas (shouldn’t see any errors), then exit() You should see a slightly different terminal prompt display with (uwgda2022) You can try installing with mamba: mamba env create -f environment.yml If this fails, please post the error message to the #it_help Slack channel
#HOW TO INSTALL JUPYTER LAB EXTENSION WITH CONDA DOWNLOAD#
This will take a few minutes to download and unzip all of the packages. Open a terminal on your machine, and run the following: conda env create -f environment.yml Because many of these projects are under active development, new versions are released during the quarter, potentially changing/breaking some functionality.įor your personal setup, you can remove the version numbers, so conda will automatically fetch the latest version of each package, and you can access latest features (but no guarantee that the existing GDA notebooks will run out of the box).Ĭreate the uwgda2022 conda environment on your local machine This is not necessary, but is a best practice for our classroom situation. Note that we may have “pinned” version numbers for some packages (e.g., - python=3.9). The first line uwgda2022 defines the conda environment name. View it with a text editor and note that it is basically just a list of package names (many you will recognize from this course). On Github, you can right-click on the “RAW” button in your browser, and “save link as” to save locally. This configuration file contains all of the packages/versions we used on the Jupyterhub this quarter.ĭownload (or copy the content of) this text file to your computer. The environment used for the GDA course is in uwgda-image-2022 repo in the UW-GDA Github organization: Run the following to see various useful info about your install: Close your terminal/shell, then open a new terminal session and type conda to verify a successfull installation. While Anaconda may be easiest for beginners, we recommend miniconda for a more a lighter, faster, more customizable installation that requires less disk space.įollow the instructions for installation: Miniconda gives you just the conda package manager, while Anaconda provides the same package manager along with a large set of common Python packages.
#HOW TO INSTALL JUPYTER LAB EXTENSION WITH CONDA UPDATE#
You may want to conda update conda if it’s been a while since you installed.ĭownloand and install the Python 3 version of Miniconda or Anaconda.
Note: If you have an existing conda install, you can skip this section and go straight to ‘Create the GDA environment’ section. Strategies for Dynamic DEM Data Download and UseĠ8: Vector time series: SNOTEL data for the Western U.S.Ġ8 Excercises: Vector time series, SNOTELĠ9: Multidimensional (N-d) Arrays: xarray, ERA5 Climate reanalysisĠ9 Introduction: Multidimensional (N-d) arrays, xarray, ERA5 climate reanalysis dataĠ9 Exercises 1: Intro and Global Climatology Vector 2: Geometries, Spatial Operations and Visualization ExercisesĠ7: Reprojection, Clipping, Sampling, Zonal Stats Vector 2: Geometries, Spatial Operations and Visualization Demo A quick, practical intro to the Jupyter Notebookĭemo: Projection Tradeoffs and Distortion - TissotĠ5: Raster Fundamentals: GDAL, rasterio, Landsat-8ĭemo: Raster fundamentals, Rasterio, Band Math with Arraysĭemo: NumPy array masking, indexing, selectionĠ6: Geometries, Spatial Operations, Visualization
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