Installation#

The following sections will guide you through the installation of CLIMADA and its dependencies.

Attention

CLIMADA has a complicated set of dependencies that cannot be installed with pip alone. Please follow the installation instructions carefully! We recommend to use Anaconda for creating a suitable software environment to execute CLIMADA.

All following instructions should work on any operating system (OS) that is supported by Anaconda, including in particular: Windows, macOS, and Linux.

Note

When mentioning the terms “terminal” or “command line” in the following, we are referring to the “Terminal” apps on macOS or Linux and the “Anaconda Prompt” on Windows.

Prerequisites#

Make sure you are using the latest version of your OS. Install any outstanding updates.
Free up at least 10 GB of free storage space on your machine. Anaconda and the CLIMADA dependencies will require around 5 GB of free space, and you will need at least that much additional space for storing the input and output data of CLIMADA.
Ensure a stable internet connection for the installation procedure. All dependencies will be downloaded from the internet. Do not use a metered, mobile connection!
Install Anaconda, following the installation instructions for your OS.
Create a workspace directory. To make sure that your user can manipulate it without special privileges, use a subdirectory of your user/home directory. Do not use a directory that is synchronized by cloud storage systems like OneDrive, iCloud or Polybox!
Linux users need to make sure they have git and curl installed. Ubuntu and Debian users may use APT:
```
apt update
apt install curl git
```
Both commands will probably require administrator rights, which can be enabled by prepending sudo.

Hint

If you need help with the vocabulary used on this page, refer to the Glossary.

Decide on Your Entry Level!#

Depening on your level of expertise, we provide two different approaches:

If you have never worked with a command line, or if you just want to give CLIMADA a try, follow the simple instructions.
If you want to use the very latest development version of CLIMADA or even develop new CLIMADA code, follow the advanced instructions. If you want to install CLIMADA Petals, also follow these.

Both approaches are not mutually exclusive. After successful installation, you may switch your setup at any time.

Simple Instructions#

These instructions will install the most recent stable version of CLIMADA without cloning its repository.

Open the command line and navigate to the workspace directory you created. The command for entering a directory is cd. Use the following command, where you replace <path/to/workspace> with the actual path of the workspace folder:
```
cd <path/to/workspace>
```
Download the Anaconda environment specifications for CLIMADA using curl:
```
curl -o env_climada.yml https://raw.githubusercontent.com/CLIMADA-project/climada_python/main/requirements/env_climada.yml
```
Alternatively, download the file through your browser and place it into the workspace directory: env_climada.yml
Instruct Anaconda to create a new environment called climada_env from the specification file:
```
conda env create -n climada_env -f env_climada.yml
```
This might take around 5 minutes, depending on your internet connection speed and computer hardware.
Activate the environment:
```
conda activate climada_env
```
You should now see (climada_env) appear in the beginning of your command prompt. This means the environment is activated.
Download and install the stable CLIMADA version using pip:
```
python -m pip install climada
```
Verify that everything is installed correctly by executing a single test:
```
python -m unittest climada.engine.test.test_impact
```
Executing CLIMADA for the first time will take some time because it will generate a directory tree in your home/user directory. After a while, some text should appear in your terminal. In the end, you should see an “Ok”. If so, great! You are good to go.

Advanced Instructions#

For advanced Python users or developers of CLIMADA, we recommed cloning the CLIMADA repository and installing the package from source.

Open the command line and navigate to the workspace directory you created using cd. Replace <path/to/workspace> with the path of the directory that contains the workspace folder:
```
cd <path/to/workspace>
```
Clone CLIMADA from its GitHub repository. Enter the directory and check out the branch of your choice. The latest development version will be available under the branch develop.
```
git clone https://github.com/CLIMADA-project/climada_python.git
cd climada_python
git checkout develop
```
Create an Anaconda environment called climada_env for installing CLIMADA. Use the default environment specs in env_climada.yml to create it, and update it with the env_developer.yml specs. Then activate the environment:
```
conda env create -n climada_env -f requirements/env_climada.yml
conda env update -n climada_env -f requirements/env_developer.yml
conda activate climada_env
```
Install the local CLIMADA source files as Python package using pip:
```
python -m pip install -e ./
```
Hint

Using a path ./ (referring to the path you are currently located at) will instruct pip to install the local files instead of downloading the module from the internet. The -e (for “editable”) option further instructs pip to link to the source files instead of copying them during installation. This means that any changes to the source files will have immediate effects in your environment, and re-installing the module is never required.
Verify that everything is installed correctly by executing a single test:
```
python -m unittest climada.engine.test.test_impact
```
Executing CLIMADA for the first time will take some time because it will generate a directory tree in your home/user directory. If this test passes, great! You are good to go.

Install CLIMADA Petals (Optional)#

CLIMADA is divided into two repositories, CLIMADA Core (climada_python) and CLIMADA Petals (climada_petals). The Core contains all the modules necessary for probabilistic impact, averted damage, uncertainty and forecast calculations. Data for hazard, exposures and impact functions can be obtained from the CLIMADA Data API. Hazard and Exposures subclasses are included as demonstrators only.

Attention

CLIMADA Petals is not a standalone module and requires CLIMADA Core to be installed!

CLIMADA Petals contains all the modules for generating data (e.g., TC_Surge, WildFire, OpenStreeMap, …). New modules are developed and tested here. Some data created with modules from Petals is available to download from the Data API. This works with just CLIMADA Core installed. CLIMADA Petals can be used to generate additional data of this type, or to have a look at the tutorials for all data types available from the API.

To install CLIMADA Petals, we assume you have already installed CLIMADA Core with the advanced instructions above.

Open the command line and navigate to the workspace directory.
Clone CLIMADA Petals from its repository. Enter the directory and check out the branch of your choice. The latest development version will be available under the branch develop.
```
git clone https://github.com/CLIMADA-project/climada_petals.git
cd climada_petals
git checkout develop
```

Update the Anaconda environment with the specifications from Petals and activate it:

conda env update -n climada_env -f requirements/env_climada.yml
conda env update -n climada_env -f requirements/env_developer.yml
conda activate climada_env

Install the CLIMADA Petals package:
```
python -m pip install -e ./
```

Apps for Programming in Python#

To work with CLIMADA, you will need an application that supports Jupyter Notebooks. There are plugins available for nearly every code editor or IDE, but if you are unsure about which to choose, we recommend JupyterLab or Spyder.

JupyterLab#

Install JupyterLab into the Anaconda environment:

conda install -n climada_env -c conda-forge jupyterlab

Make sure that the climada_env is activated (see above) and then start JupyterLab:
```
conda env activate climada_env
jupyter-lab
```
JupyterLab will open in a new window of your default browser.

Spyder#

Installing Spyder into the existing Anaconda environment for CLIMADA might fail depending on the exact versions of dependencies installed. Therefore, we recommend installing Spyder in a separate environment, and then connecting it to a kernel in the original climada_env.

Follow the Spyder installation instructions. Make sure you install it with conda!
Check the version of the Spyder kernel in the new environment:
```
conda env export -n spyder-env | grep spyder-kernels
```
This will return a line like this:
```
- spyder-kernels=X.Y.Z=<hash>
```
Copy the part spyder-kernels=X.Y.Z (until the second =) and paste it into the following command to install the same kernel version into the climada_env:
```
conda install -n climada_env spyder-kernels=X.Y.Z
```
Obtain the path to the Python interpreter of your climada_env. Execute the following commands:
```
conda activate climada_env
python -c "import sys; print(sys.executable)"
```
Copy the resulting path.
Open Spyder. You can do so from the Anaconda Navigator, or by activating the new environment and launching it through the command line:
```
conda activate spyder-env
spyder
```
Set the Python interpreter used by Spyder to the one of climada_env. Select Preferences > Python Interpreter > Use the following interpreter and paste the iterpreter path you copied from the climada_env.

FAQs#

Answers to frequently asked questions.

Updating CLIMADA#

We recommend keeping CLIMADA up-to-date. To update, follow the instructions based on your installation type:

Simple Instructions: Activate the environment and update CLIMADA using pip:
```
conda activate climada_env
python -m pip install -U climada
```
Then, download the latest environment specifications: env_climada.yml. Use them to update the existing environment:
```
conda env update -n climada_env -f env_climada.yml
```

Advanced Instructions: Move into your local CLIMADA repository and pull the latest version of your respective branch:

cd <path/to/workspace>/climada_python
git pull

Then, update the environment:

conda env update -n climada_env -f requirements/env_climada.yml
conda env update -n climada_env -f requirements/env_developer.yml

The same instructions apply for CLIMADA Petals.

Installing More Packages#

You might use CLIMADA in code that requires more packages than the ones readily available in the CLIMADA Anaconda environment. If so, prefer installing these packages via Anaconda, and only rely on pip if that fails. The default channels of Anaconda sometimes contain outdated versions. Therefore, use the conda-forge channel:

conda install -n climada_env -c conda-forge <package>

Only if the desired package (version) is not available, go for pip:

conda activate climada_env
python -m pip install <package>

Verifying Your Installation#

If you followed the installation instructions, you already executed a single unit test. This test, however, will not cover all issues that could occur within your installation setup. If you are unsure if everything works as intended, try running all unit tests. This is only available for advanced setups! Move into the CLIMADA repository, activate the environment and then execute the tests:

cd <path/to/workspace>/climada_python
conda activate climada_env
python -m unittest -s climada/ -p "test*.py"

Error: `ModuleNotFoundError`#

Something is wrong with the environment you are using. After each of the following steps, check if the problem is solved, and only continue if it is not:

Make sure you are working in the CLIMADA environment:
```
conda activate climada_env
```
Update the conda environment and CLIMADA.
Anaconda will notify you if it is not up-to-date. In this case, follow its instructions to update it. Then, repeat the last step and update the environment and CLIMADA (again).
Install the missing package manually. Follow the instructions for installing more packages.
If you reached this point, something is severely broken. The last course of action is to delete your CLIMADA environment:
```
conda deactivate
conda env remove -n climada_env
```
Now repeat the installation process.
Still no good? Please raise an issue on GitHub to get help.

Changing the Logging Level#

By default the logging level is set to INFO, which is quite verbose. You can change this setting in multiple ways:

Adjust the configuration file climada.conf by setting a the value of the global.log_level property.

Set a global logging level in your Python script:

from climada.util.config import LOGGER
from logging import WARNING
LOGGER.setLevel(WARNING)

Set a local logging level in a context manager:

from climada.util import log_level
with log_level(level="WARNING"):
    # This code only emits log levels 'WARNING' or higher
    foo()

# Default logging level again
bar()

All of these approaches can also be combined.

Mamba Instead of Anaconda#

If you prefer using Mamba, you should be able to simply replace all conda commands with mamba, except conda activate and conda deactivate. Note that we can only provide limited support for Mamba installations!

Error: `operation not permitted`#

Conda might report a permission error on macOS Mojave. Carefully follow these instructions: https://github.com/conda/conda/issues/8440#issuecomment-481167572

No `impf_TC` Column in `GeoDataFrame`#

This may happen when a demo file from CLIMADA was not updated after the change in the impact function naming pattern from if_ to impf_ when CLIMADA v2.2.0 was released. Execute

conda activate climada_env
python -c "import climada; climada.setup_climada_data(reload=True)"

The What Now? (Glossary)#

You might have become confused about all the names thrown at you. Let’s clear that up:

Terminal, Command Line: A text-only program for interacting with your computer (the old fashioned way).
Anaconda, conda: The program that installs all requirements and creates a suitable environment for CLIMADA.
Environment (Programming): A setup where only a specific set of modules and programs can interact. This is especially useful if you want to install programs with mutually incompatible requirements.
pip: The Python package installer.
git: A popular version control software for programming code (or any text-based set of files).
GitHub: A website that publicly hosts git repositories.
git Repository: A collection of files and their entire revision/version history, managed by git.
Cloning: The process and command (git clone) for downloading a git repository.
IDE: Integrated Development Environment. A fancy source code editor tailored for software development and engineering.

CLIMADA 3.3.0 documentation

Installation

Contents

Installation#

Prerequisites#

Decide on Your Entry Level!#

Simple Instructions#

Advanced Instructions#

Install CLIMADA Petals (Optional)#

Apps for Programming in Python#

JupyterLab#

Spyder#

FAQs#

Updating CLIMADA#

Installing More Packages#

Verifying Your Installation#

Error: `ModuleNotFoundError`#

Changing the Logging Level#

Mamba Instead of Anaconda#

Error: `operation not permitted`#

No `impf_TC` Column in `GeoDataFrame`#

The What Now? (Glossary)#

CLIMADA 3.3.0 documentation

Installation

Contents

Installation#

Prerequisites#

Decide on Your Entry Level!#

Simple Instructions#

Advanced Instructions#

Install CLIMADA Petals (Optional)#

Apps for Programming in Python#

JupyterLab#

Spyder#

FAQs#

Updating CLIMADA#

Installing More Packages#

Verifying Your Installation#

Error: ModuleNotFoundError#

Changing the Logging Level#

Mamba Instead of Anaconda#

Error: operation not permitted#

No impf_TC Column in GeoDataFrame#

The What Now? (Glossary)#

Error: `ModuleNotFoundError`#

Error: `operation not permitted`#

No `impf_TC` Column in `GeoDataFrame`#