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flixopt.config

Classes

CONFIG

Configuration for flixopt library.

Always call CONFIG.apply() after changes.

Note

flixopt uses loguru <https://loguru.readthedocs.io/>_ for logging.

Attributes:

Name Type Description
Logging

Logging configuration.
Modeling

Optimization modeling parameters.
Solving

Solver configuration and default parameters.
Plotting

Plotting configuration.
config_name str

Configuration name.

Examples:

Python
CONFIG.Logging.console = True
CONFIG.Logging.level = 'DEBUG'
CONFIG.apply()

Load from YAML file:

YAML
logging:
  level: DEBUG
  console: true
  file: app.log
solving:
  mip_gap: 0.001
  time_limit_seconds: 600

Classes

Logging

Logging configuration.

Silent by default. Enable via console=True or file='path'.

Attributes:

Name Type Description
level Literal['DEBUG', 'INFO', 'SUCCESS', 'WARNING', 'ERROR', 'CRITICAL']

Logging level (DEBUG, INFO, SUCCESS, WARNING, ERROR, CRITICAL).
file str | None

Log file path for file logging (None to disable).
console bool | Literal['stdout', 'stderr']

Enable console output (True/'stdout' or 'stderr').
max_file_size int

Max file size in bytes before rotation.
backup_count int

Number of backup files to keep.
verbose_tracebacks bool

Show detailed tracebacks with variable values.

Examples:

Python
# Enable console logging
CONFIG.Logging.console = True
CONFIG.Logging.level = 'DEBUG'
CONFIG.apply()

# File logging with rotation
CONFIG.Logging.file = 'app.log'
CONFIG.Logging.max_file_size = 5_242_880  # 5MB
CONFIG.apply()

# Console to stderr
CONFIG.Logging.console = 'stderr'
CONFIG.apply()
Note

For advanced formatting or custom loguru configuration, use loguru's API directly after calling CONFIG.apply():

Python
from loguru import logger

CONFIG.apply()  # Basic setup
logger.add('custom.log', format='{time} {message}')
Modeling

Optimization modeling parameters.

Attributes:

Name Type Description
big int

Large number for big-M constraints.
epsilon float

Tolerance for numerical comparisons.
big_binary_bound int

Upper bound for binary constraints.
Solving

Solver configuration and default parameters.

Attributes:

Name Type Description
mip_gap float

Default MIP gap tolerance for solver convergence.
time_limit_seconds int

Default time limit in seconds for solver runs.
log_to_console bool

Whether solver should output to console.
log_main_results bool

Whether to log main results after solving.

Examples:

Python
# Set tighter convergence and longer timeout
CONFIG.Solving.mip_gap = 0.001
CONFIG.Solving.time_limit_seconds = 600
CONFIG.Solving.log_to_console = False
CONFIG.apply()
Plotting

Plotting configuration.

Configure backends via environment variables: - Matplotlib: Set MPLBACKEND environment variable (e.g., 'Agg', 'TkAgg') - Plotly: Set PLOTLY_RENDERER or use plotly.io.renderers.default

Attributes:

Name Type Description
default_show bool

Default value for the show parameter in plot methods.
default_engine Literal['plotly', 'matplotlib']

Default plotting engine.
default_dpi int

Default DPI for saved plots.
default_facet_cols int

Default number of columns for faceted plots.
default_sequential_colorscale str

Default colorscale for heatmaps and continuous data.
default_qualitative_colorscale str

Default colormap for categorical plots (bar/line/area charts).

Examples:

Python
# Set consistent theming
CONFIG.Plotting.plotly_template = 'plotly_dark'
CONFIG.apply()

# Configure default export and color settings
CONFIG.Plotting.default_dpi = 600
CONFIG.Plotting.default_sequential_colorscale = 'plasma'
CONFIG.Plotting.default_qualitative_colorscale = 'Dark24'
CONFIG.apply()

Functions

reset classmethod
Python
reset()

Reset all configuration values to defaults.

apply classmethod
Python
apply()

Apply current configuration to logging system.

load_from_file classmethod
Python
load_from_file(config_file: str | Path)

Load configuration from YAML file and apply it.

Parameters:

Name Type Description Default
config_file str | Path

Path to the YAML configuration file.

 required

Raises:

Type Description
FileNotFoundError

If the config file does not exist.
to_dict classmethod
Python
to_dict() -> dict

Convert the configuration class into a dictionary for JSON serialization.

Returns:

Type Description
dict

Dictionary representation of the current configuration.
silent classmethod
Python
silent() -> type[CONFIG]

Configure for silent operation.

Disables console logging, solver output, and result logging for clean production runs. Does not show plots. Automatically calls apply().

debug classmethod
Python
debug() -> type[CONFIG]

Configure for debug mode with verbose output.

Enables console logging at DEBUG level, verbose tracebacks, and all solver output for troubleshooting. Automatically calls apply().

exploring classmethod
Python
exploring() -> type[CONFIG]

Configure for exploring flixopt

Enables console logging at INFO level and all solver output. Also enables browser plotting for plotly with showing plots per default

browser_plotting classmethod
Python
browser_plotting() -> type[CONFIG]

Configure for interactive usage with plotly to open plots in browser.

Sets plotly.io.renderers.default = 'browser'. Useful for running examples and viewing interactive plots. Does NOT modify CONFIG.Plotting settings.

Respects FLIXOPT_CI environment variable if set.

Functions

change_logging_level

Python
change_logging_level(level_name: Literal['DEBUG', 'INFO', 'SUCCESS', 'WARNING', 'ERROR', 'CRITICAL'])

Change the logging level for the flixopt logger.

.. deprecated:: 2.1.11 Use CONFIG.Logging.level = level_name and CONFIG.apply() instead. This function will be removed in version 3.0.0.

Parameters:

Name Type Description Default
level_name Literal['DEBUG', 'INFO', 'SUCCESS', 'WARNING', 'ERROR', 'CRITICAL']

The logging level to set.

 required

Examples:

Python Console Session
>>> change_logging_level('DEBUG')  # deprecated
>>> # Use this instead:
>>> CONFIG.Logging.level = 'DEBUG'
>>> CONFIG.apply()