Files
zulip/zerver/lib/generate_test_data.py
Anders Kaseorg 365fe0b3d5 python: Sort imports with isort.
Fixes #2665.

Regenerated by tabbott with `lint --fix` after a rebase and change in
parameters.

Note from tabbott: In a few cases, this converts technical debt in the
form of unsorted imports into different technical debt in the form of
our largest files having very long, ugly import sequences at the
start.  I expect this change will increase pressure for us to split
those files, which isn't a bad thing.

Signed-off-by: Anders Kaseorg <anders@zulip.com>
2020-06-11 16:45:32 -07:00

201 lines
6.1 KiB
Python

import itertools
import os
import random
from typing import Any, Dict, List
import ujson
from scripts.lib.zulip_tools import get_or_create_dev_uuid_var_path
def load_config() -> Dict[str, Any]:
with open("zerver/tests/fixtures/config.generate_data.json") as infile:
config = ujson.load(infile)
return config
def generate_topics(num_topics: int) -> List[str]:
config = load_config()["gen_fodder"]
topics = []
# Make single word topics account for 30% of total topics.
# Single word topics are most common, thus
# it is important we test on it.
num_single_word_topics = num_topics // 3
for _ in itertools.repeat(None, num_single_word_topics):
topics.append(random.choice(config["nouns"]))
sentence = ["adjectives", "nouns", "connectors", "verbs", "adverbs"]
for pos in sentence:
# Add an empty string so that we can generate variable length topics.
config[pos].append("")
for _ in itertools.repeat(None, num_topics - num_single_word_topics):
generated_topic = [random.choice(config[pos]) for pos in sentence]
topic = " ".join(filter(None, generated_topic))
topics.append(topic)
return topics
def load_generators(config: Dict[str, Any]) -> Dict[str, Any]:
results = {}
cfg = config["gen_fodder"]
results["nouns"] = itertools.cycle(cfg["nouns"])
results["adjectives"] = itertools.cycle(cfg["adjectives"])
results["connectors"] = itertools.cycle(cfg["connectors"])
results["verbs"] = itertools.cycle(cfg["verbs"])
results["adverbs"] = itertools.cycle(cfg["adverbs"])
results["emojis"] = itertools.cycle(cfg["emoji"])
results["links"] = itertools.cycle(cfg["links"])
results["maths"] = itertools.cycle(cfg["maths"])
results["inline-code"] = itertools.cycle(cfg["inline-code"])
results["code-blocks"] = itertools.cycle(cfg["code-blocks"])
results["quote-blocks"] = itertools.cycle(cfg["quote-blocks"])
results["lists"] = itertools.cycle(cfg["lists"])
return results
def parse_file(config: Dict[str, Any], gens: Dict[str, Any], corpus_file: str) -> List[str]:
# First, load the entire file into a dictionary,
# then apply our custom filters to it as needed.
paragraphs: List[str] = []
with open(corpus_file) as infile:
# OUR DATA: we need to separate the person talking and what they say
paragraphs = remove_line_breaks(infile)
paragraphs = add_flair(paragraphs, gens)
return paragraphs
def get_flair_gen(length: int) -> List[str]:
# Grab the percentages from the config file
# create a list that we can consume that will guarantee the distribution
result = []
for k, v in config["dist_percentages"].items():
result.extend([k] * int(v * length / 100))
result.extend(["None"] * (length - len(result)))
random.shuffle(result)
return result
def add_flair(paragraphs: List[str], gens: Dict[str, Any]) -> List[str]:
# roll the dice and see what kind of flair we should add, if any
results = []
flair = get_flair_gen(len(paragraphs))
for i in range(len(paragraphs)):
key = flair[i]
if key == "None":
txt = paragraphs[i]
elif key == "italic":
txt = add_md("*", paragraphs[i])
elif key == "bold":
txt = add_md("**", paragraphs[i])
elif key == "strike-thru":
txt = add_md("~~", paragraphs[i])
elif key == "quoted":
txt = ">" + paragraphs[i]
elif key == "quote-block":
txt = paragraphs[i] + "\n" + next(gens["quote-blocks"])
elif key == "inline-code":
txt = paragraphs[i] + "\n" + next(gens["inline-code"])
elif key == "code-block":
txt = paragraphs[i] + "\n" + next(gens["code-blocks"])
elif key == "math":
txt = paragraphs[i] + "\n" + next(gens["maths"])
elif key == "list":
txt = paragraphs[i] + "\n" + next(gens["lists"])
elif key == "emoji":
txt = add_emoji(paragraphs[i], next(gens["emojis"]))
elif key == "link":
txt = add_link(paragraphs[i], next(gens["links"]))
elif key == "picture":
txt = txt # TODO: implement pictures
results.append(txt)
return results
def add_md(mode: str, text: str) -> str:
# mode means: bold, italic, etc.
# to add a list at the end of a paragraph, * iterm one\n * item two
# find out how long the line is, then insert the mode before the end
vals = text.split()
start = random.randrange(len(vals))
end = random.randrange(len(vals) - start) + start
vals[start] = mode + vals[start]
vals[end] = vals[end] + mode
return " ".join(vals).strip()
def add_emoji(text: str, emoji: str) -> str:
vals = text.split()
start = random.randrange(len(vals))
vals[start] = vals[start] + " " + emoji + " "
return " ".join(vals)
def add_link(text: str, link: str) -> str:
vals = text.split()
start = random.randrange(len(vals))
vals[start] = vals[start] + " " + link + " "
return " ".join(vals)
def remove_line_breaks(fh: Any) -> List[str]:
# We're going to remove line breaks from paragraphs
results = [] # save the dialogs as tuples with (author, dialog)
para = [] # we'll store the lines here to form a paragraph
for line in fh:
text = line.strip()
if text != "":
para.append(text)
else:
if para:
results.append(" ".join(para))
# reset the paragraph
para = []
if para:
results.append(" ".join(para))
return results
def write_file(paragraphs: List[str], filename: str) -> None:
with open(filename, "w") as outfile:
outfile.write(ujson.dumps(paragraphs))
def create_test_data() -> None:
gens = load_generators(config) # returns a dictionary of generators
paragraphs = parse_file(config, gens, config["corpus"]["filename"])
write_file(paragraphs, os.path.join(get_or_create_dev_uuid_var_path('test-backend'),
"test_messages.json"))
config = load_config()
if __name__ == "__main__":
create_test_data()