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Initial setup

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Brad Brown
2022-07-24 16:26:21 -05:00
commit 7665938ac3
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.flake8 Normal file
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[flake8]
max-line-length = 88
inline-quotes = "

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README.md Normal file
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# CFP Resume Loader
## What is it
Currently, just a collection of logic to pull/scrape relevant data
from various sources and storing CSV files with the desired data.
## Setup
On a Mac/Linux machine with a default python version >= 3.9,
just run `./setup.sh` and you should get
a poetry env with the relevant requirements installed.
On a Windows machine, you should be able to achieve the same thing
via WSLv2.
For instructions on installing WSL, [see here](https://docs.microsoft.com/en-us/windows/wsl/install).
To run a WSL terminal once installed,
you should be able to open Windows Terminal and enter `wsl`.
(Modern Windows usage is not this author's forte, so YMMV)
## Running
Once your setup is established,
you can call the script via `poetry run cfpresume`.
For details on options, add a `--help` flag at the end of that command.
By default, it will run all import sources and create a csv file for each.
## Development
Code is formatted with [black](https://black.readthedocs.io/en/stable/),
linted with [flake8](https://flake8.pycqa.org/en/latest/),
and type-checked with [mypy](https://mypy.readthedocs.io/en/stable/).
## Future Plans
The immediate plan is to add more sources to this code,
and extend the logic to load them in parallel rather than sequentially.
After that work is complete,
the next goal is to integrate the source data into the processing logic,
either by inserting the data into a target Excel file tab,
or by integrating the final report preparation itself into this code logic.

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cfpresume/__init__.py Normal file
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import argparse
from . import espn_fpi, sagarin, sharp
LOADER_DICT = {
"FPI": espn_fpi.FpiLoader,
"Sagarin": sagarin.SagarinLoader,
"Sharp": sharp.SharpLoader,
}
LOADER_NAMES = list(LOADER_DICT.keys())
def cli_load():
parser = argparse.ArgumentParser("cfpresume")
parser.add_argument(
"-l",
"--loaders",
choices=LOADER_NAMES,
nargs="*",
default=LOADER_NAMES,
help="specify only select loaders to check.",
)
args = parser.parse_args()
for loader in args.loaders:
LOADER_DICT[loader]().update()

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cfpresume/base.py Normal file
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import csv
import os
import pathlib
import typing
import playwright.sync_api
ScoreList = typing.List[typing.Dict[str, typing.Union[str, float]]]
HEADLESS = False if os.getenv("DEBUG") else False
class BaseLoader:
PAGE_URL: str
FILENAME: str
#################
# Table Parsing #
#################
def _data_by_row(self, table):
rows = [
[td.inner_text() for td in tr.query_selector_all("td")]
for tr in table.query_selector_all("tr")
]
return rows
def _find_tables(self, page):
page.wait_for_selector("table")
tables = page.query_selector_all("table")
return tables
def _column_from_table(self, table, index):
return [row[index] for row in self._data_by_row(table) if row]
################
# Base Helpers #
################
def _data_from_page(self, page):
raise NotImplementedError
def _get_page_data(self):
with playwright.sync_api.sync_playwright() as p:
browser = p.chromium.launch(headless=HEADLESS)
page = browser.new_page()
page.goto(self.PAGE_URL)
content = self._data_from_page(page)
browser.close()
return content
##################
# Public Methods #
##################
def get_data(
self,
) -> ScoreList:
return self._get_page_data()
def write_data(self, data):
with pathlib.Path(f"{self.FILENAME}.csv").open("w") as fo:
dw = csv.DictWriter(fo, fieldnames=["Team", "Value"])
dw.writeheader()
dw.writerows(data)
def update(self):
return self.write_data(self.get_data())

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cfpresume/espn_fpi.py Normal file
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from . import base
class FpiLoader(base.BaseLoader):
PAGE_URL = "https://www.espn.com/college-football/fpi"
FILENAME = "espn_fpi"
TEAM_NAME_INDEX = 0
FPI_INDEX = 1
def _data_from_page(self, page):
tables = self._find_tables(page)
# The display is split into two adjoined tables:
# the first with team name/conference info,
# the second with the performance data.
teams, data = tables
team_names = self._column_from_table(teams, self.TEAM_NAME_INDEX)
fpi_values = self._column_from_table(data, self.FPI_INDEX)
team_fpis = [{"Team": t, "Value": v} for (t, v) in zip(team_names, fpi_values)]
return team_fpis

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cfpresume/sagarin.py Normal file
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import re
import bs4
from . import base
RATING_RE = re.compile(
r"""
\s
\d+ # Ranking number
\s+ # whitespace
(?P<school_name>.+) # School Name
\s+ # whitespace
A+ # Div A-rating
\s+ # whitespace
= # equal sign
\s+ # whitespace
(?P<rating>[\d\.]+) # rating value
""",
re.VERBOSE,
)
class SagarinLoader(base.BaseLoader):
PAGE_URL = "http://sagarin.com/sports/cfsend.htm"
FILENAME = "sagarin"
def _data_from_page(self, page):
content = page.content()
soup = bs4.BeautifulSoup(content, "html.parser")
results = []
for line in soup.get_text().splitlines():
if match := RATING_RE.search(line):
groups = match.groupdict()
results.append(
{
"Team": groups["school_name"].strip(),
"Value": float(groups["rating"]),
}
)
return results

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cfpresume/sharp.py Normal file
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import time
import warnings
from . import base
class SharpLoader(base.BaseLoader):
PAGE_URL: str = (
"https://datastudio.google.com/reporting/"
"1nDa3ltAUeZWFJfQz4AN3nDA64lDV4PBE/page/KR4p"
)
FILENAME: str = "sharp"
def __init__(self):
warnings.warn(
"This loader is a work in progress,"
" only loading the first few rows currently."
)
super().__init__()
def _frame_finder(self, page):
return [f for f in page.frames if "datastudio.google.com" in f.url]
def _find_sheets_frame(self, page):
timeout_time = time.monotonic() + 45
gstudio = self._frame_finder(page)
while not gstudio:
if time.monotonic() > timeout_time:
raise TimeoutError
time.sleep(3)
gstudio = self._frame_finder(page)
return gstudio[0]
def _data_from_page(self, page):
page.wait_for_selector(".headerRow")
header_row = page.query_selector(".headerRow")
headers = [
item.inner_text() for item in header_row.query_selector_all(".headerCell")
]
body = page.query_selector(".tableBody")
rows = body.query_selector_all(".row")
results = []
for row in rows:
cells = [cell.inner_text() for cell in row.query_selector_all(".cell")]
row_dict = {k: v for (k, v) in zip(headers, cells)}
results.append(
{"Team": row_dict["School"], "Value": row_dict["Beta_Rank▼"]}
)
return results

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28
pyproject.toml Normal file
View File

@@ -0,0 +1,28 @@
[tool.poetry]
name = "cfpresume"
version = "0.1.0"
description = "Data Loader for CFP Resume Ranking sources"
authors = ["Brad Brown <brad@bradsbrown.com>"]
[tool.poetry.dependencies]
python = "^3.9"
beautifulsoup4 = "^4.11.1"
playwright = "^1.24.0"
[tool.poetry.dev-dependencies]
black = "^22.6.0"
flake8 = "^4.0.1"
mypy = "^0.971"
types-requests = "^2.28.3"
isort = "^5.10.1"
[tool.poetry.scripts]
cfpresume = "cfpresume:cli_load"
[[tool.mypy.overrides]]
module = "bs4.*"
ignore_missing_imports = true
[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"

6
self-check.sh Executable file
View File

@@ -0,0 +1,6 @@
#!/usr/bin/env sh
set -e
black .
flake8 .
mypy .

9
setup.sh Executable file
View File

@@ -0,0 +1,9 @@
#!/usr/bin/env sh
command -v poetry; EXIT_CODE=$?
if [ "$EXIT_CODE" != "0" ]; then
python -m pip install poetry
fi
poetry install