### Foresight Configuration Example

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/configuration.md

YAML syntax for configuring foresight settings. Ensure planning horizon is set for myopic or perfect foresight.

```yaml
{{ yaml_section("foresight") }}
```

--------------------------------

### Configuration Example for Biomass Share

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/supply_demand.md

This YAML snippet shows a configuration example related to the share of unsustainable biomass use that is retained. Adjust this to control how unsustainable biomass is handled in the model.

```yaml
{{ yaml_section("biomass.share_unsustainable_use_retained") }}
```

--------------------------------

### Scenario Configuration Example

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/configuration.md

YAML syntax for configuring top-level scenario settings. This section is linked to wildcards for running multiple scenarios.

```yaml
{{ yaml_section("scenario") }}
```

--------------------------------

### Select Solver

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/tutorial.md

Pick a solver for the optimization problem. This example specifies the HiGHS solver.

```yaml
{{ yaml_section("solving.solver", source="test/config.electricity.yaml") }}
```

--------------------------------

### OETC Usage Log Example

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/oetc.md

An example log output demonstrating the OETC integration process during model optimization. It shows steps like signing in, fetching credentials, submitting jobs, and job completion status.

```log
INFO:linopy.oetc:OETC - Signing in...
INFO:linopy.oetc:OETC - Signed in
INFO:linopy.oetc:OETC - Fetching user GCP credentials...
INFO:linopy.oetc:OETC - Fetched user GCP credentials
INFO:linopy.oetc:OETC - Submitting compute job...
INFO:linopy.oetc:OETC - Compute job 992616b6-0f24-4ab5-8675-ba8098d795fa started
INFO:linopy.oetc:OETC - Waiting for job 992616b6-0f24-4ab5-8675-ba8098d795fa to complete...
INFO:linopy.oetc:OETC - Job 992616b6-0f24-4ab5-8675-ba8098d795fa status: PENDING, checking again in 30 seconds...
INFO:linopy.oetc:OETC - Job 992616b6-0f24-4ab5-8675-ba8098d795fa status: PENDING, checking again in 45 seconds...
INFO:linopy.oetc:OETC - Job 992616b6-0f24-4ab5-8675-ba8098d795fa completed successfully!
INFO:linopy.oetc:OETC - Model solved successfully. Status: ok
INFO:linopy.oetc:OETC - Objective value: 3.11e+07
```

--------------------------------

### Example Generated Default Config YAML

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/validation_dev.md

Illustrates the structure of the default configuration YAML file after regeneration, reflecting added options and sections.

```yaml
logging:
  level: INFO
  format: "% (levelname)s:% (name)s:% (message)s"
  new_option: 0.5
  file:
    enabled: false
    path: logs/pypsa.log
    format: null
```

--------------------------------

### Snakemake Job Execution Log Example

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/tutorial.md

This console output shows the status and details of jobs being executed by Snakemake. It lists the job name, input/output files, logs, and resource allocation for a specific rule.

```console
rule build_powerplants:
    input: resources/test/networks/base_s_6.nc, data/custom_powerplants.csv
    output: resources/test/powerplants_s_6.csv
    log: logs/test/build_powerplants_s_6.log
    jobid: 43
    benchmark: benchmarks/test/build_powerplants_s_6
    reason: Missing output files: resources/test/powerplants_s_6.csv; Input files updated by another job: resources/test/networks/base_s_6.nc
    wildcards: clusters=6
    resources: tmpdir=<TBD>, mem_mb=7000, mem_mib=6676
```

--------------------------------

### Select Weather Data Source for Renewables

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/tutorial.md

Choose the weather data source for calculating potentials and capacity factor time-series for renewable carriers. This example selects ERA-5 for solar.

```yaml
{{ yaml_section("renewable.solar.cutout") }}
```

--------------------------------

### Install Gurobi Solver with Conda

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/installation.md

Installs the Gurobi solver version 12.0.1 into the active conda environment. Ensure you have a Gurobi license separately.

```bash
conda activate pypsa-eur
conda install -c gurobi gurobi"=12.0.1"
```

--------------------------------

### Run PyPSA-Eur Tutorial Workflow

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/tutorial.md

Execute the snakemake workflow for the PyPSA-Eur tutorial with a specific configuration file. This command initiates the process of building and solving the simplified power system model.

```bash
snakemake -call results/test-elec/networks/base_s_6_elec_.nc --configfile config/test/config.electricity.yaml
```

--------------------------------

### Activate Conda Environment

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/installation.md

Activate the 'pypsa-eur' conda environment to access its installed packages.

```bash
$ conda activate pypsa-eur
```

--------------------------------

### Configure Tutorial Data

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/configuration.md

Enable or disable the retrieval of the tutorial data set. Defaults to false.

```yaml
tutorial: false
```

--------------------------------

### Configure Selected Countries

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/tutorial.md

Limit the spatial scope of the model to specific countries. This example shows how to include only Belgium.

```yaml
{{ yaml_section("countries", source="test/config.electricity.yaml") }}
```

--------------------------------

### Clean Repository and Run All Collection Rule

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/tutorial_sector.md

Execute these commands to clean the repository and then run the 'all' collection rule for larger-scale analyses. Ensure 'config/config.yaml' is modified beforehand.

```console
snakemake -call purge
snakemake -call all
```

--------------------------------

### Electricity Configuration

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/configuration.md

Configuration settings specifically for the electricity sector. This section allows for detailed setup of electricity-related parameters.

```yaml
{{ yaml_section("electricity") }}
```

--------------------------------

### Configure Version

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/configuration.md

Set the version of PyPSA-Eur. This is a descriptive setting.

```yaml
version: v2026.02.0
```

--------------------------------

### Read buses.csv in R

Source: https://github.com/pypsa/pypsa-eur/blob/master/data/entsoegridkit/README.md

Example of reading the buses.csv file using R's read.csv function. Assumes the file is in the current directory.

```R
buses <- read.csv("buses.csv", header=TRUE, quote="'")
```

--------------------------------

### Configure Logging

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/configuration.md

Set up top-level logging configurations for the application.

```yaml
logging:
  level: INFO
  format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
```

--------------------------------

### Configure Run Scenarios

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/configuration.md

Define settings for running and storing scenarios with different configurations within the same directory.

```yaml
run:
  output_dir: "/path/to/results"
  scenarios:
    - name: "scenario_a"
      config: { "resolution": "hourly" }
    - name: "scenario_b"
      config: { "resolution": "daily" }
```

--------------------------------

### YAML Configuration for Solar PV

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/configuration.md

YAML configuration for solar photovoltaic (PV) installations. Use this to set parameters specific to solar energy generation.

```yaml
renewable:
    solar:
        # Configuration for solar PV
        # Example parameters would go here
```

--------------------------------

### Load PyPSA Network for Analysis

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/tutorial.md

Load a solved PyPSA network from a file for subsequent analysis in Python.

```python
import pypsa

n = pypsa.Network("results/test-elec/networks/base_s_6_elec_.nc")
```

--------------------------------

### Run PyPSA-EUR Network Combinations

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/tutorial.md

Execute Snakemake to run all combinations of wildcard values defined in the configuration file for electricity networks.

```console
snakemake -call resources/test/networks/base.nc --configfile config/test/config.electricity.yaml
```

```console
snakemake -call resources/test/networks/base_s.nc --configfile config/test/config.electricity.yaml
```

```console
snakemake -call resources/test/networks/base_s_6.nc --configfile config/test/config.electricity.yaml
```

```console
snakemake -call resources/test/networks/base_s_6_elec_.nc --configfile config/test/config.electricity.yaml
```

--------------------------------

### YAML Configuration for Offshore Wind (AC)

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/configuration.md

Specific YAML configuration for offshore wind farms using AC connections. This is useful for defining parameters relevant to AC-linked offshore installations.

```yaml
renewable:
    offwind-ac:
        # Configuration for offshore wind (AC)
        # Example parameters would go here
```

--------------------------------

### Add New Config Option with Pydantic Field

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/validation_dev.md

Demonstrates adding a new float option with default value, range constraints, and examples using Pydantic's Field function.

```python
from typing import Literal
from pydantic import Field
from scripts.lib.validation.config._base import ConfigModel

class LoggingConfig(ConfigModel):
    """Configuration for top level `logging` settings."""

    # ... existing fields ...

    # An option with default 0.5, float type and between 0 and 1. If anything else is passed,
    # the validation will fail
    new_option: float = Field(
        0.5,  # default value
        description="Threshold for the new feature.",  # shown in docs and IDE
        ge=0,  # greater than or equal
        le=1,  # less than or equal
        examples=[0.3, 0.7],  # example values for docs
    )
```

--------------------------------

### Configure Atlite Settings

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/tutorial.md

Adapt the required range of coordinates for weather data to match the selected countries for accurate renewable energy modeling.

```yaml
{{ yaml_section("atlite", source="test/config.electricity.yaml") }}
```

--------------------------------

### Solving Configuration Settings

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/configuration.md

Configure the settings related to the solving process of the energy system model. This includes parameters that affect optimization and simulation performance.

```yaml
solving:
    # Configuration for solving settings
    # Example:
    # some_solving_setting: value
```

--------------------------------

### Configure Perfect Foresight Scenario

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/foresight.md

Adjust config/config.perfect.yaml to enable perfect foresight scenarios. This is an experimental feature.

```yaml
foresight: perfect
```

--------------------------------

### Read buses.csv in Python

Source: https://github.com/pypsa/pypsa-eur/blob/master/data/entsoegridkit/README.md

Example of reading the buses.csv file using Python's csv module. It customizes the dialect to use single quotes for string quoting and handles file opening in binary mode.

```Python
import io, csv
class dialect(csv.excel):
    quotechar = "'"
with io.open('buses.csv', 'rb') as handle:
    buses = list(csv.DictReader(handle, dialect))
```

--------------------------------

### Clean and Run PyPSA-EUR

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/tutorial.md

Purge previous results and then run the 'solve_elec_networks' collection rule for larger scale simulations.

```console
snakemake -call purge
snakemake -call solve_elec_networks
```

--------------------------------

### Configure Xpress Solver (Default)

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/installation.md

Sets the default Xpress solver for PyPSA-EUR. Requires the 'xpress' Python package and environment variables XPRESSDIR and XPAUTH_PATH to be set.

```yaml
solving:
  solver:
    name: xpress
    options: xpress-default
```

--------------------------------

### Run Snakemake with Specific Configuration

Source: https://github.com/pypsa/pypsa-eur/blob/master/doc/tutorial.md

Execute a Snakemake rule to solve a simplified network model. This command specifies the output file and the configuration file to use for the run.

```console
$ snakemake -call results/test-elec/networks/base_s_6_elec_.nc --configfile config/test/config.electricity.yaml
```