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Factorio analysis: data munging
The 2019 Stack Overflow Developer Survey Results Are InMoving average of a data seriesLinear Regression and data manipulationHarmonic analysis of time series applied to arraysGmail Data AnalysisPython differential analysis of heat loss across a pipeProcessing simulation data from power flow analysisLoading a Protein Data Bank file into a numpy matrixAnalysis of airport utilization using PANDASOptimizing Python loop with Numba for live load analysisSimple data analysis for forecasting
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
12
$begingroup$
This project is... a little ridiculous. It's working, but it's a complete mess.
Data about Factorio's game economy are pulled from the wiki via the MediaWiki API, scrubbed, preprocessed, and thrown into Scipy for linear programming analysis using the MOSEK interior point method.
The pull script only depends on requests:
#!/usr/bin/env python3
import json, lzma, re
from os.path import getsize
from requests import Session
from sys import stdout
session = Session()
def get_mediawiki(content=False, progress=None, **kwargs):
"""
https://stable.wiki.factorio.com is an instance of MediaWiki.
The API endpoint is
https://stable.wiki.factorio.com/api.php
"""
params = 'action': 'query',
'format': 'json',
**kwargs
if content:
params.update('prop': 'revisions',
'rvprop': 'content')
so_far = 0
while True:
resp = session.get('https://stable.wiki.factorio.com/api.php',
params=params)
resp.raise_for_status()
doc = resp.json()
pages = doc['query']['pages'].values()
if content:
full_pages = tuple(p for p in pages if 'revisions' in p)
if progress:
so_far += len(full_pages)
progress(so_far, len(pages))
yield from full_pages
else:
yield from pages
if 'batchcomplete' in doc:
break
params.update(doc['continue'])
def get_category(name, content=False, progress=None, **kwargs):
return get_mediawiki(content=content, progress=progress,
generator='categorymembers',
gcmtitle=f'Category:name',
gcmtype='page',
gcmlimit=500,
**kwargs)
def get_archived_titles():
return get_category('Archived')
def get_infoboxes(progress):
return get_category('Infobox_page', content=True, progress=progress)
def get_inter_tables(titles, progress):
return get_mediawiki(content=True, progress=progress,
titles='|'.join(titles))
line_re = re.compile(r'ns*|')
var_re = re.compile(
r'^s*'
r'(S+)'
r's*=s*'
r'(.+?)'
r's*$')
def parse_infobox(page):
"""
Example:
mining-area=2×2
<noinclude>
[[Category:Infobox page]]
</noinclude>
Splitting on newline isn't a great idea, because
https://www.mediawiki.org/wiki/Help:Templates#Named_parameters
shows that only the pipe is mandatory as a separator. However, only
splitting on pipe is worse, because there are pipes on the inside of links.
"""
content = page['revisions'][0]['*']
entries = (
var_re.match(e)
for e in line_re.split(
content.split('', maxsplit=1)[1]
.rsplit('', maxsplit=1)[0]
)
)
title = page['title'].split(':', maxsplit=1)[1]
d = 'pageid': page['pageid'],
'title': title
d.update(dict(e.groups() for e in entries if e))
return d
part_tok = r's*([^|]*?)'
border_tok = r's*|'
row_image_re = re.compile(
r's*'
r'(?P<type>w+)'
f'border_tok'
f'part_tok'
r'(?:'
f'border_tok'
f'part_tok'
r')?'
r'(?:'
f'border_tok'
r'[^]*'
r')?'
r's*'
r'(?P<sep>'
r'(?:'
r'|||+|→'
r')?'
r')',
)
def iter_cells(row):
"""
e.g.
|
|| 10} + time
|| 1
or
| Imagelink
|| Imagelink
|| Icon + 5
→ Heavy oil + (Icon 40)
"""
cell = []
for m in row_image_re.finditer(row):
if m.group('sep') == '||':
cell.append(m.groups()[:-1])
yield cell
cell = []
else:
cell.append(m.groups())
if cell:
yield cell
def parse_inter_table(page):
"""
Example:
or
1
+ time || 1
|-
| Icon || icon + time || 1
|-
|}
"""
title = page['title']
content = page['revisions'][0]['*']
if '|]+)}')
def wood_mining(self) -> Iterable[MiningRecipe]:
miners = tuple(
ManualMiner(tool)
for tool in all_items.values()
if tool.prototype_type == 'mining-tool'
)
for m in self.tree_re.finditer(self.resource.mining_time):
mining_time, source = int(m[1]), m[2]
for miner in miners:
yield self.produce(
MiningRecipe, miner,
mining_hardness=float(self.resource.mining_hardness),
mining_time=mining_time,
title=f'self.resource (miner from source)')
def make(self) -> Iterable[Recipe]:
if self.rates:
if self.resource.prototype_type == 'technology':
yield self.produce(
TechRecipe, self.producers[0],
cost_multiplier=float(self.resource.cost_multiplier))
elif self.resource.title == 'Energy':
yield self.produce(Recipe, self.producers[0])
else:
yield from self.for_energy(Recipe)
elif self.resource.title == 'Raw wood':
yield from self.wood_mining()
elif self.resource.mining_time:
yield from self.for_energy(
MiningRecipe,
mining_hardness=float(self.resource.mining_hardness),
mining_time=float(self.resource.mining_time))
elif self.resource.title == 'Crude oil':
yield from self.for_energy(FluidRecipe)
elif self.resource.title == 'Water':
yield self.produce(FluidRecipe, self.producers[0])
else:
raise NotImplementedError()
def parse_power(s: str) -> float:
m = power_re.search(s)
return float(m[1]) * si_facs[m[2]]
def items_of_type(t: str) -> Iterable[Item]:
return (i for i in all_items.values()
if i.prototype_type == t)
barrel_re = re.compile(r'empty .+ barrel')
def parse_producers(s: str) -> Iterable[Item]:
for p in s.split('+'):
p = p.strip().lower()
if p == 'furnace':
yield from items_of_type('furnace')
elif p == 'assembling machine':
yield from (all_items[f'assembling machine i']
for i in range(1, 4))
elif p == 'mining drill':
yield from (all_items[f't mining drill']
for t in ('burner', 'electric'))
elif p == 'manual' or barrel_re.match(p):
continue
else:
yield all_items[p]
def trim(items: dict):
to_delete = tuple(k for k, v in items.items() if not v.keep)
print(f'Dropping len(to_delete) items...')
for k in to_delete:
del items[k]
def energy_data() -> dict:
solar_ave = parse_power(next(
s for s in all_items['solar panel'].power_output.split('<br/>')
if 'average' in s))
eng = all_items['steam engine']
eng_rate = float(eng.fluid_consumption
.split('/')[0])
eng_power = parse_power(eng.power_output)
turbine = all_items['steam turbine']
turbine_rate = float(turbine.fluid_consumption
.split('/')[0])
turbine_power_500 = 5.82e6 # ignore non-precise data and use this instead
turbine_power_165 = 1.8e6 # from wiki page body
return
'title': 'Energy',
'recipes': (
'building': 'Solar panel',
'process': 'Energy (Solar panel)',
'inputs':
'Time': 1
,
'outputs':
'Energy': solar_ave
,
'building': 'Steam engine',
'process': 'Energy (Steam engine)',
'inputs':
'Time': 1,
'Steam165': eng_rate
,
'outputs':
'Energy': eng_power
,
'building': 'Steam turbine',
'process': 'Energy (Steam turbine @ 165C)',
'inputs':
'Time': 1,
'Steam165': turbine_rate
,
'outputs':
'Energy': turbine_power_165
,
'building': 'Steam turbine',
'process': 'Energy (Steam turbine @ 500C)',
'inputs':
'Time': 1,
'Steam500': turbine_rate
,
'outputs':
'Energy': turbine_power_500
)
def load(fn: str):
with lzma.open(fn) as f:
global all_items
all_items = k.lower(): Item(d) for k, d in json.load(f).items()
all_items['energy'] = Item(energy_data())
def get_recipes() -> (Dict[str, Recipe], Set[str]):
recipes =
resources = set()
for item in all_items.values():
item_recipes = tuple(item.get_recipes())
recipes.update(i.title: i for i in item_recipes)
for recipe in item_recipes:
resources.update(recipe.rates.keys())
return recipes, resources
def field_size(names: Iterable) -> int:
return max(len(str(o)) for o in names)
def write_csv_for_r(recipes: Sequence[Recipe], resources: Sequence[str],
fn: str):
# Recipes going down, resources going right
rec_width = field_size(recipes)
float_width = 15
col_format = f':float_width+8'
rec_format = 'n:' + str(rec_width+1) + ''
with lzma.open(fn, 'wt') as f:
f.write(' '*(rec_width+1))
for res in resources:
f.write(col_format.format(f'res,'))
for rec in recipes:
f.write(rec_format.format(f'rec,'))
for res in resources:
x = rec.rates.get(res, 0)
col_format = f':+len(res).float_widthe,'
f.write(col_format.format(x))
def write_for_numpy(recipes: Sequence[Recipe], resources: Sequence[str],
meta_fn: str, npz_fn: str):
rec_names = [r.title for r in recipes]
w_rec = max(len(r) for r in rec_names)
recipe_names = np.array(rec_names, copy=False, dtype=f'Uw_rec')
w_res = max(len(r) for r in resources)
resource_names = np.array(resources, copy=False, dtype=f'Uw_res')
np.savez_compressed(meta_fn, recipe_names=recipe_names, resource_names=resource_names)
rec_mat = lil_matrix((len(resources), len(recipes)))
for j, rec in enumerate(recipes):
for res, q in rec.rates.items():
i = resources.index(res)
rec_mat[i, j] = q
save_npz(npz_fn, rec_mat.tocsr())
def file_banner(fn):
print(f'fn getsize(fn)//1024 kiB')
def main():
fn = 'items.json.xz'
print(f'Loading fn... ', end='')
load(fn)
print(f'len(all_items) items')
trim(all_items)
print('Calculating recipes... ', end='')
recipes, resources = get_recipes()
print(f'len(recipes) recipes, len(resources) resources')
resources = sorted(resources)
recipes = sorted(recipes.values(), key=lambda i: i.title)
print('Saving files for numpy...')
meta_fn, npz_fn = 'recipe-names.npz', 'recipes.npz'
write_for_numpy(recipes, resources, meta_fn, npz_fn)
file_banner(meta_fn)
file_banner(npz_fn)
fn = 'recipes.csv.xz'
print(f'Saving recipes for use by R...')
stdout.flush()
write_csv_for_r(recipes, resources, fn)
file_banner(fn)
if __name__ == '__main__':
main()
That's followed by an analysis script that I won't post here, to constrain the scope of this first review.
items.json.xz is somewhat large; an excerpt is:
→'
r')?'
r')',
)
def iter_cells(row):
"""
e.g.
+ time
|| 1
or
| Imagelink
|| Imagelink
|| Icon + 5
→ Heavy oil + (Icon 40)
"""
cell = []
for m in row_image_re.finditer(row):
if m.group('sep') == '||':
cell.append(m.groups()[:-1])
yield cell
cell = []
else:
cell.append(m.groups())
if cell:
yield cell
def parse_inter_table(page):
"""
Example:
or
1
+ time || 1
|-
| Icon || icon + time || 1
|-
|}
"""
title = page['title']
content = page['revisions'][0]['*']
if '|]+)}')
def wood_mining(self) -> Iterable[MiningRecipe]:
miners = tuple(
ManualMiner(tool)
for tool in all_items.values()
if tool.prototype_type == 'mining-tool'
)
for m in self.tree_re.finditer(self.resource.mining_time):
mining_time, source = int(m[1]), m[2]
for miner in miners:
yield self.produce(
MiningRecipe, miner,
mining_hardness=float(self.resource.mining_hardness),
mining_time=mining_time,
title=f'self.resource (miner from source)')
def make(self) -> Iterable[Recipe]:
if self.rates:
if self.resource.prototype_type == 'technology':
yield self.produce(
TechRecipe, self.producers[0],
cost_multiplier=float(self.resource.cost_multiplier))
elif self.resource.title == 'Energy':
yield self.produce(Recipe, self.producers[0])
else:
yield from self.for_energy(Recipe)
elif self.resource.title == 'Raw wood':
yield from self.wood_mining()
elif self.resource.mining_time:
yield from self.for_energy(
MiningRecipe,
mining_hardness=float(self.resource.mining_hardness),
mining_time=float(self.resource.mining_time))
elif self.resource.title == 'Crude oil':
yield from self.for_energy(FluidRecipe)
elif self.resource.title == 'Water':
yield self.produce(FluidRecipe, self.producers[0])
else:
raise NotImplementedError()
def parse_power(s: str) -> float:
m = power_re.search(s)
return float(m[1]) * si_facs[m[2]]
def items_of_type(t: str) -> Iterable[Item]:
return (i for i in all_items.values()
if i.prototype_type == t)
barrel_re = re.compile(r'empty .+ barrel')
def parse_producers(s: str) -> Iterable[Item]:
for p in s.split('+'):
p = p.strip().lower()
if p == 'furnace':
yield from items_of_type('furnace')
elif p == 'assembling machine':
yield from (all_items[f'assembling machine i']
for i in range(1, 4))
elif p == 'mining drill':
yield from (all_items[f't mining drill']
for t in ('burner', 'electric'))
elif p == 'manual' or barrel_re.match(p):
continue
else:
yield all_items[p]
def trim(items: dict):
to_delete = tuple(k for k, v in items.items() if not v.keep)
print(f'Dropping len(to_delete) items...')
for k in to_delete:
del items[k]
def energy_data() -> dict:
solar_ave = parse_power(next(
s for s in all_items['solar panel'].power_output.split('<br/>')
if 'average' in s))
eng = all_items['steam engine']
eng_rate = float(eng.fluid_consumption
.split('/')[0])
eng_power = parse_power(eng.power_output)
turbine = all_items['steam turbine']
turbine_rate = float(turbine.fluid_consumption
.split('/')[0])
turbine_power_500 = 5.82e6 # ignore non-precise data and use this instead
turbine_power_165 = 1.8e6 # from wiki page body
return
'title': 'Energy',
'recipes': (
'building': 'Solar panel',
'process': 'Energy (Solar panel)',
'inputs':
'Time': 1
,
'outputs':
'Energy': solar_ave
,
'building': 'Steam engine',
'process': 'Energy (Steam engine)',
'inputs':
'Time': 1,
'Steam165': eng_rate
,
'outputs':
'Energy': eng_power
,
'building': 'Steam turbine',
'process': 'Energy (Steam turbine @ 165C)',
'inputs':
'Time': 1,
'Steam165': turbine_rate
,
'outputs':
'Energy': turbine_power_165
,
'building': 'Steam turbine',
'process': 'Energy (Steam turbine @ 500C)',
'inputs':
'Time': 1,
'Steam500': turbine_rate
,
'outputs':
'Energy': turbine_power_500
)
def load(fn: str):
with lzma.open(fn) as f:
global all_items
all_items = k.lower(): Item(d) for k, d in json.load(f).items()
all_items['energy'] = Item(energy_data())
def get_recipes() -> (Dict[str, Recipe], Set[str]):
recipes =
resources = set()
for item in all_items.values():
item_recipes = tuple(item.get_recipes())
recipes.update(i.title: i for i in item_recipes)
for recipe in item_recipes:
resources.update(recipe.rates.keys())
return recipes, resources
def field_size(names: Iterable) -> int:
return max(len(str(o)) for o in names)
def write_csv_for_r(recipes: Sequence[Recipe], resources: Sequence[str],
fn: str):
# Recipes going down, resources going right
rec_width = field_size(recipes)
float_width = 15
col_format = f':float_width+8'
rec_format = 'n:' + str(rec_width+1) + ''
with lzma.open(fn, 'wt') as f:
f.write(' '*(rec_width+1))
for res in resources:
f.write(col_format.format(f'res,'))
for rec in recipes:
f.write(rec_format.format(f'rec,'))
for res in resources:
x = rec.rates.get(res, 0)
col_format = f':+len(res).float_widthe,'
f.write(col_format.format(x))
def write_for_numpy(recipes: Sequence[Recipe], resources: Sequence[str],
meta_fn: str, npz_fn: str):
rec_names = [r.title for r in recipes]
w_rec = max(len(r) for r in rec_names)
recipe_names = np.array(rec_names, copy=False, dtype=f'Uw_rec')
w_res = max(len(r) for r in resources)
resource_names = np.array(resources, copy=False, dtype=f'Uw_res')
np.savez_compressed(meta_fn, recipe_names=recipe_names, resource_names=resource_names)
rec_mat = lil_matrix((len(resources), len(recipes)))
for j, rec in enumerate(recipes):
for res, q in rec.rates.items():
i = resources.index(res)
rec_mat[i, j] = q
save_npz(npz_fn, rec_mat.tocsr())
def file_banner(fn):
print(f'fn getsize(fn)//1024 kiB')
def main():
fn = 'items.json.xz'
print(f'Loading fn... ', end='')
load(fn)
print(f'len(all_items) items')
trim(all_items)
print('Calculating recipes... ', end='')
recipes, resources = get_recipes()
print(f'len(recipes) recipes, len(resources) resources')
resources = sorted(resources)
recipes = sorted(recipes.values(), key=lambda i: i.title)
print('Saving files for numpy...')
meta_fn, npz_fn = 'recipe-names.npz', 'recipes.npz'
write_for_numpy(recipes, resources, meta_fn, npz_fn)
file_banner(meta_fn)
file_banner(npz_fn)
fn = 'recipes.csv.xz'
print(f'Saving recipes for use by R...')
stdout.flush()
write_csv_for_r(recipes, resources, fn)
file_banner(fn)
if __name__ == '__main__':
main()
That's followed by an analysis script that I won't post here, to constrain the scope of this first review.
items.json.xz is somewhat large; an excerpt is:
"Advanced circuit":
"pageid": 38306,
"title": "Advanced circuit",
"prototype-type": "item",
"internal-name": "advanced-circuit",
"expensive-total-raw": "Time, 14 + Copper plate, 14 + Iron plate, 4 + Plastic bar, 4",
"expensive-recipe": "Time, 6 + Copper cable, 8 + Electronic circuit, 2 + Plastic bar, 4",
"category": "Intermediate products",
"stack-size": "200",
"recipe": "Time, 6 + Copper cable, 4 + Electronic circuit, 2 + Plastic bar, 2",
"total-raw": "Time, 9.5 + Copper plate, 5 + Iron plate, 2 + Plastic bar, 2",
"required-technologies": "Advanced electronics",
"producers": "Manual + Assembling machine 2+Assembling machine 3",
"consumers": "Artillery turret + Artillery wagon + Beacon + Centrifuge + Distractor capsule + Efficiency module + Efficiency module 2 + Efficiency module 3 + Electric furnace + Energy shield + Express splitter + Active provider chest + Buffer chest + Passive provider chest + Requester chest + Storage chest + Logistic robot + Modular armor + Nightvision + Nuclear reactor + Personal roboport + Processing unit + Productivity module + Productivity module 2 + Productivity module 3 + Roboport + Science pack 3 + Portable solar panel + Speed module + Speed module 2 + Speed module 3 + Stack inserter + Substation + Tank",
"archived": false
,
"Advanced oil processing (research)":
"pageid": 38335,
"title": "Advanced oil processing (research)",
"prototype-type": "technology",
"internal-name": "advanced-oil-processing",
"allows": "Coal liquefaction",
"expensive-cost-multiplier": "300",
"category": "Technology",
"cost": "Time, 30 + Science pack 1, 1 + Science pack 2, 1 + Science pack 3, 1",
"cost-multiplier": "75",
"required-technologies": "Oil processing",
"effects": "Advanced oil processing + Heavy oil cracking + Light oil cracking",
"archived": false
,
It's just as easy for you to generate it yourself. Similarly, here is an excerpt of recipes.csv.xz:
Accumulator, Active provider chest, Advanced circuit, Advanced electronics (research),Advanced electronics 2 (research),Advanced material processing (research),Advanced material processing 2 (research),Advanced oil processing (research),Area, Arithmetic combinator, Artillery (research), Artillery shell, Artillery shell range (research),Artillery shell shooting speed (research),Artillery targeting remote,Artillery turret, Artillery wagon, Assembling machine 1, Assembling machine 2, Assembling machine 3, Atomic bomb, Atomic bomb (research),Auto character logistic trash slots (research),Automated rail transportation (research),Automation (research), Automation 2 (research),Automation 3 (research),Automobilism (research),Battery, Battery (research), Battery MK1, Battery MK2 equipment (research),Battery equipment (research),Beacon, Big electric pole, Boiler, Braking force (research),Buffer chest, Bullet damage (research),Bullet shooting speed (research),Burner inserter, Burner mining drill, Cannon shell, Cannon shell damage (research),Cannon shell shooting speed (research),Car, Cargo wagon, Centrifuge, Character logistic slots (research),Character logistic trash slots (research),Chemical plant, Circuit network (research),Cliff explosives, Cliff explosives (research),Cluster grenade, Coal, Coal liquefaction (research),Combat robot damage (research),Combat robotics (research),Combat robotics 2 (research),Combat robotics 3 (research),Combat shotgun, Concrete, Concrete (research), Constant combinator, Construction robot, Construction robotics (research),Copper cable, Copper ore, Copper plate, Crude oil, Decider combinator, Defender capsule, Destroyer capsule, Discharge defense, Discharge defense (research),Discharge defense remote,Distractor capsule, Effect transmission (research),Efficiency module, Efficiency module (research),Efficiency module 2, Efficiency module 2 (research),Efficiency module 3, Efficiency module 3 (research),Electric energy accumulators (research),Electric energy distribution 1 (research),Electric energy distribution 2 (research),Electric engine (research),Electric engine unit, Electric furnace, Electric mining drill, Electronic circuit, Electronics (research),Empty barrel, Energy, Energy shield, Energy shield MK2, Energy shield MK2 equipment (research),Energy shield equipment (research),Engine (research), Engine unit, Exoskeleton, Exoskeleton equipment (research),Explosive cannon shell,Explosive rocket, Explosive rocketry (research),Explosive uranium cannon shell,Explosives, Explosives (research), Express splitter, Express transport belt,Express underground belt,Fast inserter, Fast splitter, Fast transport belt, Fast underground belt, Filter inserter, Firearm magazine, Flamethrower, Flamethrower (research),Flamethrower ammo, Flamethrower damage (research),Flamethrower turret, Flammables (research), Flight (research), Fluid handling (research),Fluid wagon, Fluid wagon (research),Flying robot frame, Follower robot 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+0.000000000000000e+00,
The main thing that needs work is the recipe factory code. It sprinkles logic about item types where it doesn't belong, and that really needs to be improved. I have some ideas about how to do that, but I'd like to hear from the community (on that, and any other wrinkles you find).
python parsing numpy scipy
python parsing numpy scipy
python parsing numpy scipy
asked Apr 8 at 2:14
ReinderienReinderien
5,445927
asked Apr 8 at 2:14
ReinderienReinderien
5,445927
edited Apr 8 at 19:25
Reinderien
asked Apr 8 at 2:14
ReinderienReinderien
5,445927
asked Apr 8 at 2:14
ReinderienReinderien
5,445927
asked Apr 8 at 2:14
ReinderienReinderien
5,445927
5,445927
add a comment |
4
$begingroup$
All the data is in machine readable lua files - even version-tagged in the official repository: github.com/wube/factorio-data. There's also existing python tooling to read the lua github.com/jcranmer/factorio-tools (not sure what state that it is in).
$endgroup$
– Zulan
Apr 8 at 13:08
$begingroup$
Could you provide an example of what the output of this looks like?
$endgroup$
– Simon Forsberg♦
Apr 8 at 15:03
$begingroup$
@SimonForsberg Added, though it's more helpful to just run the scripts and get the full output.
$endgroup$
– Reinderien
Apr 8 at 19:26
4
4
$begingroup$
All the data is in machine readable lua files - even version-tagged in the official repository: github.com/wube/factorio-data. There's also existing python tooling to read the lua github.com/jcranmer/factorio-tools (not sure what state that it is in).
$endgroup$
– Zulan
Apr 8 at 13:08
$begingroup$
All the data is in machine readable lua files - even version-tagged in the official repository: github.com/wube/factorio-data. There's also existing python tooling to read the lua github.com/jcranmer/factorio-tools (not sure what state that it is in).
$endgroup$
– Zulan
Apr 8 at 13:08
$begingroup$
Could you provide an example of what the output of this looks like?
$endgroup$
– Simon Forsberg♦
Apr 8 at 15:03
$begingroup$
Could you provide an example of what the output of this looks like?
$endgroup$
– Simon Forsberg♦
Apr 8 at 15:03
$begingroup$
@SimonForsberg Added, though it's more helpful to just run the scripts and get the full output.
$endgroup$
– Reinderien
Apr 8 at 19:26
$begingroup$
@SimonForsberg Added, though it's more helpful to just run the scripts and get the full output.
$endgroup$
– Reinderien
Apr 8 at 19:26
add a comment |
1 Answer
1
active
oldest
votes
6
$begingroup$
You can simplify your 'verbose' multi-line regexes by using the
re.Xflag.var_re = re.compile(r'''
^s*
(S+)
s*=s*
(.+?)
s*$
''', re.X)
The preferred way of wrapping long lines is by using Python's implied line continuation inside parentheses, brackets and braces. Long lines can be broken over multiple lines by wrapping expressions in parentheses. These should be used in preference to using a backslash for line continuation. - PEP 8
if (resource.mining_time
or resource.title in 'Crude oil', 'Water'):
...Whilst it goes against the style in your code, I prefer the following:
if (resource.mining_time
or resource.title in 'Crude oil', 'Water'
):
...
answered Apr 8 at 2:56
PeilonrayzPeilonrayz
26.6k339112
$endgroup$
add a comment |
Your Answer
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6
$begingroup$
You can simplify your 'verbose' multi-line regexes by using the
re.Xflag.var_re = re.compile(r'''
^s*
(S+)
s*=s*
(.+?)
s*$
''', re.X)
The preferred way of wrapping long lines is by using Python's implied line continuation inside parentheses, brackets and braces. Long lines can be broken over multiple lines by wrapping expressions in parentheses. These should be used in preference to using a backslash for line continuation. - PEP 8
if (resource.mining_time
or resource.title in 'Crude oil', 'Water'):
...Whilst it goes against the style in your code, I prefer the following:
if (resource.mining_time
or resource.title in 'Crude oil', 'Water'
):
...
answered Apr 8 at 2:56
PeilonrayzPeilonrayz
26.6k339112
$endgroup$
add a comment |
6
$begingroup$
You can simplify your 'verbose' multi-line regexes by using the
re.Xflag.var_re = re.compile(r'''
^s*
(S+)
s*=s*
(.+?)
s*$
''', re.X)
The preferred way of wrapping long lines is by using Python's implied line continuation inside parentheses, brackets and braces. Long lines can be broken over multiple lines by wrapping expressions in parentheses. These should be used in preference to using a backslash for line continuation. - PEP 8
if (resource.mining_time
or resource.title in 'Crude oil', 'Water'):
...Whilst it goes against the style in your code, I prefer the following:
if (resource.mining_time
or resource.title in 'Crude oil', 'Water'
):
...
answered Apr 8 at 2:56
PeilonrayzPeilonrayz
26.6k339112
$endgroup$
add a comment |
6
6
6
$begingroup$
You can simplify your 'verbose' multi-line regexes by using the
re.Xflag.var_re = re.compile(r'''
^s*
(S+)
s*=s*
(.+?)
s*$
''', re.X)
The preferred way of wrapping long lines is by using Python's implied line continuation inside parentheses, brackets and braces. Long lines can be broken over multiple lines by wrapping expressions in parentheses. These should be used in preference to using a backslash for line continuation. - PEP 8
if (resource.mining_time
or resource.title in 'Crude oil', 'Water'):
...Whilst it goes against the style in your code, I prefer the following:
if (resource.mining_time
or resource.title in 'Crude oil', 'Water'
):
...
answered Apr 8 at 2:56
PeilonrayzPeilonrayz
26.6k339112
$endgroup$
You can simplify your 'verbose' multi-line regexes by using the
re.Xflag.var_re = re.compile(r'''
^s*
(S+)
s*=s*
(.+?)
s*$
''', re.X)
The preferred way of wrapping long lines is by using Python's implied line continuation inside parentheses, brackets and braces. Long lines can be broken over multiple lines by wrapping expressions in parentheses. These should be used in preference to using a backslash for line continuation. - PEP 8
if (resource.mining_time
or resource.title in 'Crude oil', 'Water'):
...Whilst it goes against the style in your code, I prefer the following:
if (resource.mining_time
or resource.title in 'Crude oil', 'Water'
):
...
answered Apr 8 at 2:56
PeilonrayzPeilonrayz
26.6k339112
edited Apr 8 at 3:00
answered Apr 8 at 2:56
PeilonrayzPeilonrayz
26.6k339112
answered Apr 8 at 2:56
PeilonrayzPeilonrayz
26.6k339112
answered Apr 8 at 2:56
PeilonrayzPeilonrayz
26.6k339112
26.6k339112
add a comment |
add a comment |
draft saved
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4
$begingroup$
All the data is in machine readable lua files - even version-tagged in the official repository: github.com/wube/factorio-data. There's also existing python tooling to read the lua github.com/jcranmer/factorio-tools (not sure what state that it is in).
$endgroup$
– Zulan
Apr 8 at 13:08
$begingroup$
Could you provide an example of what the output of this looks like?
$endgroup$
– Simon Forsberg♦
Apr 8 at 15:03
$begingroup$
@SimonForsberg Added, though it's more helpful to just run the scripts and get the full output.
$endgroup$
– Reinderien
Apr 8 at 19:26