#EOS

Currently you can use engine following way:

from eos import *
from eos.holder_filter import *


data_handler = JsonDataHandler('data_folder/phobos/')  # Folder with Phobos data dump
cache_handler = JsonCacheHandler('data_folder/cache/eos_tq.json.bz2')
SourceManager.add('tiamat', data_handler, cache_handler, make_default=True)

skill_groups = set(row['groupID'] for row in data_handler.get_evegroups() if row['categoryID'] == 16)
skills = set(row['typeID'] for row in data_handler.get_evetypes() if row['groupID'] in skill_groups)

fit = Fit()
fit.ship = Ship(32311)  # Navy Typhoon

for skill_id in skills:
    fit.skills.add(Skill(skill_id, level=5))

# 4x 800mm with hail
fit.modules.high.equip(Module(2929, state=State.overload, charge=Charge(12779)))
fit.modules.high.equip(Module(2929, state=State.overload, charge=Charge(12779)))
fit.modules.high.equip(Module(2929, state=State.overload, charge=Charge(12779)))
fit.modules.high.equip(Module(2929, state=State.overload, charge=Charge(12779)))
# 4x Torp launcher with nova rages
fit.modules.high.equip(Module(2420, state=State.overload, charge=Charge(24519)))
fit.modules.high.equip(Module(2420, state=State.overload, charge=Charge(24519)))
fit.modules.high.equip(Module(2420, state=State.overload, charge=Charge(24519)))
fit.modules.high.equip(Module(2420, state=State.overload, charge=Charge(24519)))

fit.modules.med.equip(Module(5945, state=State.overload))  # Top named 100MN MWD
fit.modules.med.equip(Module(4833, state=State.active, charge=Charge(32014)))  # Named med cap injector with 800
fit.modules.med.equip(Module(9622, state=State.active))  # Named EM hardener
fit.modules.med.equip(Module(5443, state=State.active))  # Best named scram
fit.modules.med.equip(Module(2281, state=State.active))  # T2 invuln

fit.modules.low.equip(Module(2048, state=State.online))   # T2 DC
fit.modules.low.equip(Module(519, state=State.online))    # T2 gyrostab
fit.modules.low.equip(Module(519, state=State.online))    # T2 gyrostab
fit.modules.low.equip(Module(22291, state=State.online))  # T2 BCU
fit.modules.low.equip(Module(22291, state=State.online))  # T2 BCU
fit.modules.low.equip(Module(4405, state=State.online))   # T2 DDA
fit.modules.low.equip(Module(4405, state=State.online))   # T2 DDA

fit.rigs.equip(Rig(26082))  # T1 therm rig
fit.rigs.equip(Rig(26088))  # T1 extender
fit.rigs.equip(Rig(26088))  # T1 extender

# 8x Ogre II
fit.drones.add(Drone(2446, state=State.active))
fit.drones.add(Drone(2446, state=State.active))
fit.drones.add(Drone(2446, state=State.active))
fit.drones.add(Drone(2446, state=State.active))
fit.drones.add(Drone(2446, state=State.active))
fit.drones.add(Drone(2446, state=State.offline))
fit.drones.add(Drone(2446, state=State.offline))
fit.drones.add(Drone(2446, state=State.offline))

fit.implants.add(Implant(13231))  # 3% torp dmg
fit.implants.add(Implant(10228))  # 3% shield capacity
fit.implants.add(Implant(24663))  # zor hyperlink
fit.implants.add(Implant(13244))  # 3% turret dmg
fit.implants.add(Implant(13219))  # 3% large projectile dmg

fit.boosters.add(Booster(28672))  # Synth crash
fit.boosters.add(Booster(28674))  # Synth drop

fit.validate()

---

Fit validation method currently raises exception if any fit check fails, its argument contains dictionary which explains what is wrong. If we make additional drone active, following data will be returned:

{<Drone(type_id=2446, state=3)>: {
    <Restriction.drone_bandwidth: 5>: ResourceErrorData(total_use=150.0, output=125.0, holder_use=25.0),
    <Restriction.launched_drone: 6>: SlotAmountErrorData(slots_used=6, slots_max_allowed=5)},
...
}

Keys of dictionary are problematic holders (in this case, all in-space drones of ship), values are dictionaries too, which list problems with given module. Keys of this dictionary are restriction IDs (eos.Restriction object), with 5 being drone bandwidth restriction, and 6 being amount of drones this fit can use; values contain detailed data about the problem.

Attributes of any item are accessible via dictionary-like objects like phoon.attributes, e.g.:

>>> fit.ship.attributes[37] # maxVelocity
1841.6155389908258

Stats of fit can be fetched using 'stats' access point. For example, few regular ones:

>>> fit.stats.agility_factor
15.70747757338698
>>> fit.stats.cpu.used
821.0

And few more advanced (total uniform EHP of fit, and shield EHP vs EM damage):

>>> fit.stats.get_ehp(DamageTypes(em=25, thermal=25, kinetic=25, explosive=25)).total
95329.19886256836
>>> fit.stats.get_ehp(DamageTypes(em=1, thermal=0, kinetic=0, explosive=0)).shield
50013.690833719105

DPS can be fetched with various parameters, for example, should it take reload into consideration or not:

>>> fit.stats.get_nominal_dps(reload=False).total
1931.374697718373
>>> fit.stats.get_nominal_dps(reload=True).total
1857.2875753203057

Specific damage type is accessible too (in this case, hail deals some kinetic damage):

>>> fit.stats.get_nominal_dps(reload=False).kinetic
136.64914857525073

Get effective DPS against passed damage profile:

>>> fit.stats.get_nominal_dps(target_resistances=DamageTypes(em=0.2, thermal=0.3, kinetic=0.4, explosive=0.5)).total
1072.8636430538475

Get dps using built-in filters:

>>> fit.stats.get_nominal_dps(holder_filter=turret_filter).total
637.6960266845034
>>> fit.stats.get_nominal_dps(holder_filter=missile_filter).total
826.1217743481901
>>> fit.stats.get_nominal_dps(holder_filter=drone_filter).total
467.55689668567936

You can compose your own filters or combine existing:

>>> fit.stats.get_nominal_dps(holder_filter=lambda h: turret_filter(h) or missile_filter(h)).total
1463.8178010326933

Not all stats are implemented yet, more to come soon.