<commit_before>graphhopper:

  # OpenStreetMap input file PBF or XML, can be changed via command line -Ddw.graphhopper.datareader.file=some.pbf
  datareader.file: ""
  # Local folder used by graphhopper to store its data
  graph.location: graph-cache

  ##### Vehicles #####


  # More options: foot,hike,bike,bike2,mtb,racingbike,motorcycle,car4wd,wheelchair (comma separated)
  # bike2 takes elevation data into account (like up-hill is slower than down-hill) and requires enabling graph.elevation.provider below.
  graph.flag_encoders: car

  # Enable turn restrictions for car or motorcycle.
  # graph.flag_encoders: car|turn_costs=true

  # Add additional information to every edge. Used for path details (#1548), better instructions (#1844) and tunnel/bridge interpolation (#798).
  # Default values are: road_class,road_class_link,road_environment,max_speed,road_access (since #1805)
  # More are: surface,max_width,max_height,max_weight,max_axle_load,max_length,hazmat,hazmat_tunnel,hazmat_water,toll,track_type
  # graph.encoded_values: surface,toll,track_type

  ##### Routing Profiles ####

  # Routing can be done for the following list of profiles. Note that it is required to specify all the profiles you
  # would like to use here. The fields of each profile are as follows:
  # - name (required): a unique string identifier for the profile
  # - vehicle (required): refers to the `graph.flag_encoders` used for this profile
  # - weighting (required): the weighting used for this profile, e.g. fastest,shortest or short_fastest
  # - turn_costs (true/false, default: false): whether or not turn restrictions should be applied for this profile.
  #   this will only work if the `graph.flag_encoders` for the given `vehicle` is configured with `|turn_costs=true`.
  #
  # Depending on the above fields there are other properties that can be used, e.g.
  # - distance_factor: 0.1 (can be used to fine tune the time/distance trade-off of short_fastest weighting)
  # - u_turn_costs: 60 (time-penalty for doing a u-turn in seconds (only possible when `turn_costs: true`)).
  #   Note that since the u-turn costs are given in seconds the weighting you use should also calculate the weight
  #   in seconds, so for example it does not work with shortest weighting.
  #
  # To prevent long running routing queries you should usually enable either speed or hybrid mode for all the given
  # profiles (see below). Otherwise you should at least limit the number of `routing.max_visited_nodes`.
  profiles:
    - name: car
      vehicle: car
      weighting: fastest

  #  - name: car_with_turn_costs
  #    vehicle: car
  #    weighting: short_fastest
  #    distance_factor: 0.1
  #    turn_costs: true
  #    u_turn_costs: 60

  # Speed mode:
  # Its possible to speed up routing by doing a special graph preparation (Contraction Hierarchies, CH). This requires
  # more RAM/disk space for holding the prepared graph but also means less memory usage per request. Using the following
  # list you can define for which of the above routing profiles such preparation shall be performed. Note that to support
  # profiles with `turn_costs: true` a more elaborate preparation is required (longer preparation time and more memory
  # usage) and the routing will also be slower than with `turn_costs: false`.
  profiles_ch:
    - profile: car
  #   - profile: car_with_turn_costs

  # Hybrid mode:
  # Similar to speed mode, the hybrid mode (Landmarks, LM) also speeds up routing by doing calculating auxiliary data
  # in advance. Its not as fast as speed mode, but more flexible.
  profiles_lm: []

  ##### Elevation #####


  # To populate your graph with elevation data use SRTM, default is noop (no elevation)
  # graph.elevation.provider: srtm


  # default location for cache is /tmp/srtm
  # graph.elevation.cache_dir: ./srtmprovider/


  # If you have a slow disk or plenty of RAM change the default MMAP to:
  # graph.elevation.dataaccess: RAM_STORE



  #### Speed, hybrid and flexible mode ####


  # To make CH preparation faster for multiple profiles you can increase the default threads if you have enough RAM.
  # Change this setting only if you know what you are doing and if the default worked for you.
  # prepare.ch.threads: 1

  # To tune the performance vs. memory usage for the hybrid mode use
  # prepare.lm.landmarks: 16

  # Make landmark preparation parallel if you have enough RAM. Change this only if you know what you are doing and if
  # the default worked for you.
  # prepare.lm.threads: 1

<commit_msg>config-example.yml: minor fix<commit_after>graphhopper:

  # OpenStreetMap input file PBF or XML, can be changed via command line -Ddw.graphhopper.datareader.file=some.pbf
  datareader.file: ""
  # Local folder used by graphhopper to store its data
  graph.location: graph-cache

  ##### Vehicles #####


  # More options: foot,hike,bike,bike2,mtb,racingbike,motorcycle,car4wd,wheelchair (comma separated)
  # bike2 takes elevation data into account (like up-hill is slower than down-hill) and requires enabling graph.elevation.provider below.
  graph.flag_encoders: car

  # Enable turn restrictions for car or motorcycle.
  # graph.flag_encoders: car|turn_costs=true

  # Add additional information to every edge. Used for path details (#1548), better instructions (#1844) and tunnel/bridge interpolation (#798).
  # Default values are: road_class,road_class_link,road_environment,max_speed,road_access (since #1805)
  # More are: surface,max_width,max_height,max_weight,max_axle_load,max_length,hazmat,hazmat_tunnel,hazmat_water,toll,track_type
  # graph.encoded_values: surface,toll,track_type

  ##### Routing Profiles ####

  # Routing can be done for the following list of profiles. Note that it is required to specify all the profiles you
  # would like to use here. The fields of each profile are as follows:
  # - name (required): a unique string identifier for the profile
  # - vehicle (required): refers to the `graph.flag_encoders` used for this profile
  # - weighting (required): the weighting used for this profile, e.g. fastest,shortest or short_fastest
  # - turn_costs (true/false, default: false): whether or not turn restrictions should be applied for this profile.
  #   this will only work if the `graph.flag_encoders` for the given `vehicle` is configured with `|turn_costs=true`.
  #
  # Depending on the above fields there are other properties that can be used, e.g.
  # - distance_factor: 0.1 (can be used to fine tune the time/distance trade-off of short_fastest weighting)
  # - u_turn_costs: 60 (time-penalty for doing a u-turn in seconds (only possible when `turn_costs: true`)).
  #   Note that since the u-turn costs are given in seconds the weighting you use should also calculate the weight
  #   in seconds, so for example it does not work with shortest weighting.
  #
  # To prevent long running routing queries you should usually enable either speed or hybrid mode for all the given
  # profiles (see below). Otherwise you should at least limit the number of `routing.max_visited_nodes`.
  profiles:
    - name: car
      vehicle: car
      weighting: fastest

  #  - name: car_with_turn_costs
  #    vehicle: car
  #    weighting: short_fastest
  #    distance_factor: 0.1
  #    turn_costs: true
  #    u_turn_costs: 60

  # Speed mode:
  # Its possible to speed up routing by doing a special graph preparation (Contraction Hierarchies, CH). This requires
  # more RAM/disk space for holding the prepared graph but also means less memory usage per request. Using the following
  # list you can define for which of the above routing profiles such preparation shall be performed. Note that to support
  # profiles with `turn_costs: true` a more elaborate preparation is required (longer preparation time and more memory
  # usage) and the routing will also be slower than with `turn_costs: false`.
  profiles_ch:
    - profile: car
  #   - profile: car_with_turn_costs

  # Hybrid mode:
  # Similar to speed mode, the hybrid mode (Landmarks, LM) also speeds up routing by doing calculating auxiliary data
  # in advance. Its not as fast as speed mode, but more flexible.
  profiles_lm: []

  ##### Elevation #####


  # To populate your graph with elevation data use SRTM, default is noop (no elevation). Read more about it in docs/core/elevation.md
  # graph.elevation.provider: srtm


  # default location for cache is /tmp/srtm
  # graph.elevation.cache_dir: ./srtmprovider/


  # If you have a slow disk or plenty of RAM change the default MMAP to:
  # graph.elevation.dataaccess: RAM_STORE



  #### Speed, hybrid and flexible mode ####


  # To make CH preparation faster for multiple profiles you can increase the default threads if you have enough RAM.
  # Change this setting only if you know what you are doing and if the default worked for you.
  # prepare.ch.threads: 1

  # To tune the performance vs. memory usage for the hybrid mode use
  # prepare.lm.landmarks: 16

  # Make landmark preparation parallel if you have enough RAM. Change this only if you know what you are doing and if
  # the default worked for you.
  # prepare.lm.threads: 1


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