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Optimise imports

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This commit is contained in:
Daoud Clarke 2021-12-05 20:38:05 +00:00
parent 312f32bf61
commit 14817d7657
3 changed files with 52 additions and 52 deletions
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17
extract.py
View file

@ -2,13 +2,10 @@
Extract content from HTML files and store it as compressed JSON
"""
import json
import os
from io import BytesIO
from pathlib import Path
from urllib.parse import urlparse
import spacy as spacy
import boto3
from justext import get_stoplist
from justext.core import LENGTH_LOW_DEFAULT, LENGTH_HIGH_DEFAULT, STOPWORDS_LOW_DEFAULT, \
STOPWORDS_HIGH_DEFAULT, MAX_LINK_DENSITY_DEFAULT, NO_HEADINGS_DEFAULT, \
@ -16,18 +13,11 @@ from justext.core import LENGTH_LOW_DEFAULT, LENGTH_HIGH_DEFAULT, STOPWORDS_LOW_
ParagraphMaker, classify_paragraphs, revise_paragraph_classification
from langdetect import detect
from lxml.etree import ParserError
from pyspark.sql import DataFrame
from pyspark.sql import SparkSession, SQLContext
from pyspark.sql.functions import col
from pyspark.sql.types import StructType, StructField, StringType, LongType
from pyspark.sql.functions import expr, col
from pyspark import SparkFiles
import boto3
from warcio import ArchiveIterator
OUTPUT_PATH = 's3://tinysearch/outputs/index'
MAX_URI_LENGTH = 150
@ -39,9 +29,6 @@ MAX_RESULTS_PER_HASH = 200
PAGE_SIZE = 4096
nlp = spacy.load("en_core_web_sm", disable=['lemmatizer', 'ner'])
index_schema = StructType([
StructField("term_hash", LongType(), False),
StructField("data", StringType(), False),

85
poetry.lock generated
View file

@ -72,6 +72,17 @@ python-versions = "*"
[package.dependencies]
lxml = ">=4.4.2"
[[package]]
name = "langdetect"
version = "1.0.9"
description = "Language detection library ported from Google's language-detection."
category = "main"
optional = false
python-versions = "*"
[package.dependencies]
six = "*"
[[package]]
name = "lxml"
version = "4.6.4"
@ -86,14 +97,6 @@ html5 = ["html5lib"]
htmlsoup = ["beautifulsoup4"]
source = ["Cython (>=0.29.7)"]
[[package]]
name = "numpy"
version = "1.21.1"
description = "NumPy is the fundamental package for array computing with Python."
category = "main"
optional = false
python-versions = ">=3.7"
[[package]]
name = "numpy"
version = "1.21.4"
@ -123,6 +126,31 @@ pytz = ">=2017.3"
[package.extras]
test = ["hypothesis (>=3.58)", "pytest (>=6.0)", "pytest-xdist"]
[[package]]
name = "py4j"
version = "0.10.9.2"
description = "Enables Python programs to dynamically access arbitrary Java objects"
category = "main"
optional = false
python-versions = "*"
[[package]]
name = "pyspark"
version = "3.2.0"
description = "Apache Spark Python API"
category = "main"
optional = false
python-versions = ">=3.6"
[package.dependencies]
py4j = "0.10.9.2"
[package.extras]
ml = ["numpy (>=1.7)"]
mllib = ["numpy (>=1.7)"]
pandas_on_spark = ["numpy (>=1.14)", "pandas (>=0.23.2)", "pyarrow (>=1.0.0)"]
sql = ["pandas (>=0.23.2)", "pyarrow (>=1.0.0)"]
[[package]]
name = "python-dateutil"
version = "2.8.2"
@ -207,7 +235,7 @@ six = "*"
[metadata]
lock-version = "1.1"
python-versions = "^3.9"
content-hash = "b8a9967839a08627a26c7d1517ef8dc0c08b9c0f15cdeee6efc9381e07d522ab"
content-hash = "289e6a040c51398a25649cea5969bdb398893f8dbb62d7058a14b017d8fa82a5"
[metadata.files]
beautifulsoup4 = [
@ -234,6 +262,10 @@ justext = [
{file = "jusText-3.0.0-py2.py3-none-any.whl", hash = "sha256:86b48f5b1d99505acd072f5831def6cd3f1306043651c524a1c609e62e3544e4"},
{file = "jusText-3.0.0.tar.gz", hash = "sha256:7640e248218795f6be65f6c35fe697325a3280fcb4675d1525bcdff2b86faadf"},
]
langdetect = [
{file = "langdetect-1.0.9-py2-none-any.whl", hash = "sha256:7cbc0746252f19e76f77c0b1690aadf01963be835ef0cd4b56dddf2a8f1dfc2a"},
{file = "langdetect-1.0.9.tar.gz", hash = "sha256:cbc1fef89f8d062739774bd51eda3da3274006b3661d199c2655f6b3f6d605a0"},
]
lxml = [
{file = "lxml-4.6.4-cp27-cp27m-macosx_10_14_x86_64.whl", hash = "sha256:bbf2dc330bd44bfc0254ab37677ec60f7c7ecea55ad8ba1b8b2ea7bf20c265f5"},
{file = "lxml-4.6.4-cp27-cp27m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b667c51682fe9b9788c69465956baa8b6999531876ccedcafc895c74ad716cd8"},
@ -297,34 +329,6 @@ lxml = [
{file = "lxml-4.6.4.tar.gz", hash = "sha256:daf9bd1fee31f1c7a5928b3e1059e09a8d683ea58fb3ffc773b6c88cb8d1399c"},
]
numpy = [
{file = "numpy-1.21.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:38e8648f9449a549a7dfe8d8755a5979b45b3538520d1e735637ef28e8c2dc50"},
{file = "numpy-1.21.1-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:fd7d7409fa643a91d0a05c7554dd68aa9c9bb16e186f6ccfe40d6e003156e33a"},
{file = "numpy-1.21.1-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:a75b4498b1e93d8b700282dc8e655b8bd559c0904b3910b144646dbbbc03e062"},
{file = "numpy-1.21.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1412aa0aec3e00bc23fbb8664d76552b4efde98fb71f60737c83efbac24112f1"},
{file = "numpy-1.21.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e46ceaff65609b5399163de5893d8f2a82d3c77d5e56d976c8b5fb01faa6b671"},
{file = "numpy-1.21.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:c6a2324085dd52f96498419ba95b5777e40b6bcbc20088fddb9e8cbb58885e8e"},
{file = "numpy-1.21.1-cp37-cp37m-win32.whl", hash = "sha256:73101b2a1fef16602696d133db402a7e7586654682244344b8329cdcbbb82172"},
{file = "numpy-1.21.1-cp37-cp37m-win_amd64.whl", hash = "sha256:7a708a79c9a9d26904d1cca8d383bf869edf6f8e7650d85dbc77b041e8c5a0f8"},
{file = "numpy-1.21.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:95b995d0c413f5d0428b3f880e8fe1660ff9396dcd1f9eedbc311f37b5652e16"},
{file = "numpy-1.21.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:635e6bd31c9fb3d475c8f44a089569070d10a9ef18ed13738b03049280281267"},
{file = "numpy-1.21.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:4a3d5fb89bfe21be2ef47c0614b9c9c707b7362386c9a3ff1feae63e0267ccb6"},
{file = "numpy-1.21.1-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:8a326af80e86d0e9ce92bcc1e65c8ff88297de4fa14ee936cb2293d414c9ec63"},
{file = "numpy-1.21.1-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:791492091744b0fe390a6ce85cc1bf5149968ac7d5f0477288f78c89b385d9af"},
{file = "numpy-1.21.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0318c465786c1f63ac05d7c4dbcecd4d2d7e13f0959b01b534ea1e92202235c5"},
{file = "numpy-1.21.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9a513bd9c1551894ee3d31369f9b07460ef223694098cf27d399513415855b68"},
{file = "numpy-1.21.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:91c6f5fc58df1e0a3cc0c3a717bb3308ff850abdaa6d2d802573ee2b11f674a8"},
{file = "numpy-1.21.1-cp38-cp38-win32.whl", hash = "sha256:978010b68e17150db8765355d1ccdd450f9fc916824e8c4e35ee620590e234cd"},
{file = "numpy-1.21.1-cp38-cp38-win_amd64.whl", hash = "sha256:9749a40a5b22333467f02fe11edc98f022133ee1bfa8ab99bda5e5437b831214"},
{file = "numpy-1.21.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:d7a4aeac3b94af92a9373d6e77b37691b86411f9745190d2c351f410ab3a791f"},
{file = "numpy-1.21.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:d9e7912a56108aba9b31df688a4c4f5cb0d9d3787386b87d504762b6754fbb1b"},
{file = "numpy-1.21.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:25b40b98ebdd272bc3020935427a4530b7d60dfbe1ab9381a39147834e985eac"},
{file = "numpy-1.21.1-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:8a92c5aea763d14ba9d6475803fc7904bda7decc2a0a68153f587ad82941fec1"},
{file = "numpy-1.21.1-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:05a0f648eb28bae4bcb204e6fd14603de2908de982e761a2fc78efe0f19e96e1"},
{file = "numpy-1.21.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f01f28075a92eede918b965e86e8f0ba7b7797a95aa8d35e1cc8821f5fc3ad6a"},
{file = "numpy-1.21.1-cp39-cp39-win32.whl", hash = "sha256:88c0b89ad1cc24a5efbb99ff9ab5db0f9a86e9cc50240177a571fbe9c2860ac2"},
{file = "numpy-1.21.1-cp39-cp39-win_amd64.whl", hash = "sha256:01721eefe70544d548425a07c80be8377096a54118070b8a62476866d5208e33"},
{file = "numpy-1.21.1-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:2d4d1de6e6fb3d28781c73fbde702ac97f03d79e4ffd6598b880b2d95d62ead4"},
{file = "numpy-1.21.1.zip", hash = "sha256:dff4af63638afcc57a3dfb9e4b26d434a7a602d225b42d746ea7fe2edf1342fd"},
{file = "numpy-1.21.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:8890b3360f345e8360133bc078d2dacc2843b6ee6059b568781b15b97acbe39f"},
{file = "numpy-1.21.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:69077388c5a4b997442b843dbdc3a85b420fb693ec8e33020bb24d647c164fa5"},
{file = "numpy-1.21.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e89717274b41ebd568cd7943fc9418eeb49b1785b66031bc8a7f6300463c5898"},
@ -382,6 +386,13 @@ pandas = [
{file = "pandas-1.3.4-cp39-cp39-win_amd64.whl", hash = "sha256:a51528192755f7429c5bcc9e80832c517340317c861318fea9cea081b57c9afd"},
{file = "pandas-1.3.4.tar.gz", hash = "sha256:a2aa18d3f0b7d538e21932f637fbfe8518d085238b429e4790a35e1e44a96ffc"},
]
py4j = [
{file = "py4j-0.10.9.2-py2.py3-none-any.whl", hash = "sha256:bf0485388e415ff26710d2dc719cb0ede16cf1164b1ee757e0ebb2e98c471521"},
{file = "py4j-0.10.9.2.tar.gz", hash = "sha256:624f97c363b8dd84822bc666b12fa7f7d97824632b2ff3d852cc491359ce7615"},
]
pyspark = [
{file = "pyspark-3.2.0.tar.gz", hash = "sha256:bfea06179edbfb4bc76a0f470bd3c38e12f00e1023e3ad0373558d07cff102ab"},
]
python-dateutil = [
{file = "python-dateutil-2.8.2.tar.gz", hash = "sha256:0123cacc1627ae19ddf3c27a5de5bd67ee4586fbdd6440d9748f8abb483d3e86"},
{file = "python_dateutil-2.8.2-py2.py3-none-any.whl", hash = "sha256:961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9"},

2
pyproject.toml
View file

@ -15,6 +15,8 @@ beautifulsoup4 = "^4.10.0"
lxml = "^4.6.4"
jusText = "^3.0.0"
pandas = "^1.3.4"
pyspark = "^3.2.0"
langdetect = "^1.0.9"
[tool.poetry.dev-dependencies]