Sankt Johann am Wimberg
Sankt Johann am Wimberg is a municipality in the district of Rohrbach in the Austrian state of Upper Austria.
Sankt Johann am Wimberg | |
|---|---|
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 Coat of arms | |
 Location in the district | |
  Sankt Johann am Wimberg Location within Austria | |
| Coordinates: 48°29′19″N 14°07′51″E | |
| Country | Austria |
| State | Upper Austria |
| District | Rohrbach |
| Government | |
| • Mayor | Albert Stürmer (ÖVP) |
| Area | |
| • Total | 19.77 km2 (7.63 sq mi) |
| Elevation | 720 m (2,360 ft) |
| Population (2018-01-01)[2] | |
| • Total | 1,029 |
| • Density | 52/km2 (130/sq mi) |
| Time zone | UTC+1 (CET) |
| • Summer (DST) | UTC+2 (CEST) |
| Postal code | 4172 |
| Area code | 07217 |
| Vehicle registration | RO |
| Website | www.stjohannamwimberg.at |
Geography
Sankt Johann am Wimberg lies in the eastern part of the district of Rohrbach in the upper Mühlviertel.
gollark: If this worked as expected, in theory you could do```pythonraise quibble("abcd")```but alas, no.
gollark: But which runs much faster.
gollark: ```pythonfrom requests_futures.sessions import FuturesSessionimport concurrent.futures as futuresimport randomtry: import cPickle as pickleexcept ImportError: import pickletry: words_to_synonyms = pickle.load(open(".wtscache")) synonyms_to_words = pickle.load(open(".stwcache"))except: words_to_synonyms = {} synonyms_to_words = {}def add_to_key(d, k, v): d[k] = d.get(k, set()).union(set(v))def add_synonyms(syns, word): for syn in syns: add_to_key(synonyms_to_words, syn, [word]) add_to_key(words_to_synonyms, word, syns)def concat(list_of_lists): return sum(list_of_lists, [])def add_words(words): s = FuturesSession(max_workers=100) future_to_word = {s.get("https://api.datamuse.com/words", params={"ml": word}): word for word in words} future_to_word.update({s.get("https://api.datamuse.com/words", params={"ml": word, "v": "enwiki"}): word for word in words}) for future in futures.as_completed(future_to_word): word = future_to_word[future] try: data = future.result().json() except Exception as exc: print(f"{exc} fetching {word}") else: add_synonyms([w["word"] for w in data], word)def getattr_hook(obj, key): results = list(synonyms_to_words.get(key, set()).union(words_to_synonyms.get(key, set()))) if len(results) > 0: return obj.__getattribute__(random.choice(results)) else: raise AttributeError(f"Attribute {key} not found.")def wrap(obj): add_words(dir(obj)) obj.__getattr__ = lambda key: getattr_hook(obj, key)wrap(__builtins__)print(words_to_synonyms["Exception"])```New version which tends to reduce weirder output.
gollark: https://github.com/joelgrus/fizz-buzz-tensorflow/blob/master/Fizz%20Buzz%20in%20Tensorflow.ipynb
gollark: ?remind 5d Misuse ?remind even more. Suggestions: nested reminds (is that possible)?
References
- "Dauersiedlungsraum der Gemeinden Politischen Bezirke und Bundesländer - Gebietsstand 1.1.2018". Statistics Austria. Retrieved 10 March 2019.
- "Einwohnerzahl 1.1.2018 nach Gemeinden mit Status, Gebietsstand 1.1.2018". Statistics Austria. Retrieved 9 March 2019.
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