def get_csv(file_name):
token = '' # GitHub TOKEN
repo_path = 'CSSEGISandData/COVID-19'
daily_reports_dir_path = 'https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_daily_reports/'
time_series_dir_path = 'https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/'
dr_repo_file_list = 'csse_covid_19_data/csse_covid_19_daily_reports'
git = Github(token)
repo = git.get_repo(repo_path)
daily_reports_file_list = repo.get_contents(dr_repo_file_list)
if file_name == 'daily_reports':
daily_reports_file_path = daily_reports_dir_path + str(
daily_reports_file_list[-2]).split('/')[-1].split(".")[0] + '.csv'
req = requests.get(daily_reports_file_path)
url_content = req.content
csv_file = open('daily_report.csv', 'wb')
csv_file.write(url_content)
csv_file.close()
else:
confirmed_global_file_path = time_series_dir_path + 'time_series_covid19_confirmed_global.csv'
deaths_global_file_path = time_series_dir_path + 'time_series_covid19_deaths_global.csv'
recovered_global_file_path = time_series_dir_path + 'time_series_covid19_recovered_global.csv'
return confirmed_global_file_path, deaths_global_file_path, recovered_global_file_path
def get_kaggle_credential_from_secret_repository(
repository: str, location: str, gh_token: str) -> KaggleCredential:
gh = Github(gh_token)
cred_repo = gh.get_repo(repository)
kaggle_cred_res = cred_repo.get_contents(location)
kaggle_cred = json.loads(kaggle_cred_res.decoded_content)
if 'key' not in kaggle_cred or 'username' not in kaggle_cred:
raise RuntimeError('Cannot find username or key in kaggle.json file.')
kaggle_username = kaggle_cred['username']
kaggle_key = kaggle_cred['key']
ret_cred = KaggleCredential(kaggle_username, kaggle_key)
return ret_cred
import pandas as pd
import os
desired_width = 320
pd.set_option('display.width', desired_width)
pd.set_option('display.max_columns', 10)
# making path for loading
currPath = os.getcwd()
inPath = os.path.join(currPath, "output")
# import from github -- need token
from github.MainClass import Github
g = Github('PUT_YOUR_TOKEN_HERE')
repo = g.get_repo("Transcranial-Solutions/ICONProject")
# making proper logo web address & name using logo
file_list = repo.get_contents("vote_analysis/output/logos")
split_file_list = lambda x: str(x).split('"')[1]
file_list = list(map(split_file_list, file_list))
split_logo_list = lambda x: str(x).split('/')[-1].split('.')[0]
logo_list = list(map(split_logo_list, file_list))
github_dir_path = 'https://raw.githubusercontent.com/Transcranial-Solutions/ICONProject/master/'
web_list = [github_dir_path + s for s in file_list]
# dataframe - name by logo and web address
logo_df = pd.DataFrame({'name_by_logo': logo_list, 'logo': web_list})
logo_df = logo_df.iloc[logo_df.logo.str.lower().argsort()].reset_index(drop=True)
class GithubService:
"""Contains convenience methods and properties for Github-related
functionality.
An adapter to the functionality of the PyGithub library.
"""
def __init__(self, access_token: str):
"""Constructor.
:param str access_token: the access token to use for connecting
"""
self.client = Github(login_or_token=access_token)
@lru_cache(maxsize=None)
def get_repo(self, repo_name: str) -> Repository:
"""Return the repository object with the given name.
:param str repo_name: the full name of the repository
:return: the repository or None if not found
:rtype: github.Repository.Repository
"""
return self.client.get_repo(repo_name)
@lru_cache(maxsize=None)
def get_pr(self, repo_name: str, pr_num: int):
"""Return the pull request object with the given number.
:param str repo_name: the name of the repository the PR is in
:param int pr_num: the identifier of the pull request
:return: the pull request object
:rtype: PullRequest
"""
repo = self.get_repo(repo_name)
if repo:
return repo.get_pull(pr_num)
def create_pr_comment(self, repo_name: str, pr_num: int, body: str) -> dict:
"""Create a comment on the pull request with the given info.
:param str repo_name: the name of the repository the PR is in
:param int pr_num: the identifier of the pull request
:param str body: the body of the comment to add
:return: a dictionary with information about the created comment
:rtype: dict
"""
pr = self.get_pr(repo_name, pr_num)
issue = pr.as_issue()
comment = issue.create_comment(body)
return {'id': comment.id, 'html_url': comment.html_url}
def get_pr_comments(self, repo_name: str, pr_num: int) -> List[dict]:
"""Return a list of comments on the PR with the given number.
:param str repo_name: the name of the repository the PR is in
:param int pr_num: the identifier of the pull request
:return: a list of all comments, formatted as:
[
{'id': <comment_id>, 'body': <body>, 'updated_at': <updated_at>},
...
]
:rtype: list
"""
pr = self.get_pr(repo_name, pr_num)
issue = pr.as_issue()
comments = issue.get_comments()
return [
{'id': comment.id, 'body': comment.body, 'updated_at': comment.updated_at}
for comment in comments
]
def delete_pr_comment(self, repo_name: str, pr_num: int, comment_id: int) -> bool:
"""Delete the PR comment with the given id
:param str repo_name: the name of the repository the PR is in
:param int pr_num: the identifier of the pull request
:param int comment_id: the ID of the comment to delete
:return: True if found and deleted successfully, False otherwise
:rtype: bool
"""
pr = self.get_pr(repo_name, pr_num)
issue = pr.as_issue()
comment = issue.get_comment(comment_id)
if comment is None:
return False
comment.delete()
return True
def read_from_github():
# Input: no
# Outputs: the main datasets ready to use
# Function: reads the files from GitHub
# Online Github path
from github.MainClass import Github
token = 'f1d4c930800cb3e782c1b61b86101c97deefc4c7'
# connected to GitHub using my credentials
g = Github(token)
# load the repo
repo = g.get_repo("CSSEGISandData/COVID-19")
file_list = repo.get_contents("csse_covid_19_data/csse_covid_19_time_series")
github_dir_path = 'https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/'
file_path_confirmed_US = github_dir_path + str(file_list[-5]).split('/')[-1].split(".")[0]+ '.csv'
confirmed_US = pd.read_csv(file_path_confirmed_US, error_bad_lines=False)
confirmed_US = confirmed_US.drop(['UID', 'iso2', 'iso3', 'code3', 'FIPS', 'Admin2', 'Combined_Key'], axis=1)
confirmed_US=confirmed_US.rename(columns = {'Province_State':'Province/State',
'Country_Region':'Country/Region',
'Long_':'Long'})
confirmed_info = confirmed_US.groupby(["Province/State"])['Lat','Long','Country/Region'].agg({
'Lat' :lambda x: x.mean(),
'Long' :lambda x: x.mean(),
'Country/Region':lambda x: x.unique()
})
cases = confirmed_US.drop(columns=['Country/Region', 'Lat', 'Long']).set_index('Province/State')
cases = cases.groupby(["Province/State"]).sum()
confirmed_US = confirmed_info.merge(cases, left_index=True, right_index=True).reset_index()
confirmed_US = confirmed_US[confirmed_US['Long'].isna() == False]
confirmed_US = confirmed_US[confirmed_US['Lat'].isna() == False]
confirmed_US = confirmed_US[confirmed_US['Long'] != 0]
confirmed_US = confirmed_US[confirmed_US['Lat'] != 0]
file_path_confirmed = github_dir_path + str(file_list[-4]).split('/')[-1].split(".")[0]+ '.csv'
confirmed = pd.read_csv(file_path_confirmed, error_bad_lines=False)
confirmed = pd.concat([confirmed_US,confirmed])
file_path_died_US = github_dir_path + str(file_list[-3]).split('/')[-1].split(".")[0]+ '.csv'
died_US = pd.read_csv(file_path_died_US, error_bad_lines=False)
died_US = died_US.drop(['UID', 'iso2', 'iso3', 'code3', 'FIPS', 'Admin2', 'Combined_Key', 'Population'], axis=1)
died_US=died_US.rename(columns = {'Province_State':'Province/State',
'Country_Region':'Country/Region',
'Long_':'Long'})
died_info = died_US.groupby(["Province/State"])['Lat','Long','Country/Region'].agg({
'Lat' :lambda x: x.mean(),
'Long' :lambda x: x.mean(),
'Country/Region':lambda x: x.unique()
})
deaths = died_US.drop(columns=['Country/Region', 'Lat', 'Long']).set_index('Province/State')
deaths = deaths.groupby(["Province/State"]).sum()
died_US = died_info.merge(deaths, left_index=True, right_index=True).reset_index()
died_US = died_US[died_US['Long'].isna() == False]
died_US = died_US[died_US['Lat'].isna() == False]
died_US = died_US[died_US['Long'] != 0]
died_US = died_US[died_US['Lat'] != 0]
#
file_path_died = github_dir_path + str(file_list[-2]).split('/')[-1].split(".")[0]+ '.csv'
died = pd.read_csv(file_path_died, error_bad_lines=False)
died = pd.concat([died_US,died])
file_path_recovered = github_dir_path + str(file_list[-1]).split('/')[-1].split(".")[0]+ '.csv'
recovered = pd.read_csv(file_path_recovered, error_bad_lines=False)
# preprocessing to add total column
confirmed = preprocessing(confirmed)
died = preprocessing(died)
recovered = preprocessing(recovered)
# demographics
population_statistics = pd.read_csv("population_statistics.csv")
return confirmed, died, recovered, population_statistics
import csv
import requests
import os
import sys
from github.MainClass import Github
import pandas as pd
# BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# sys.path.insert(0, BASE_DIR)
from simple_prognozer.config import TOKEN
REPO_PATH = 'CSSEGISandData/COVID-19'
GIT = Github(TOKEN)
REPO = GIT.get_repo(REPO_PATH)
DR_REPO_FILE_LIST = 'csse_covid_19_data/csse_covid_19_daily_reports'
DAILY_REPORTS_DIR_PATH = ('https://github.com/CSSEGISandData/COVID-19/raw/'
'master/csse_covid_19_data'
'/csse_covid_19_daily_reports/'
)
def get_csv(file_name):
print('Getting daily report csv...')
daily_reports_file_list = REPO.get_contents(DR_REPO_FILE_LIST)
if file_name == 'daily_reports':
daily_reports_file_path = DAILY_REPORTS_DIR_PATH +\
str(daily_reports_file_list[-2]).split('/')[-1].split(".")[
minify_inited = False
# Init flask
app = Flask(__name__, template_folder="game")
if compress_inited:
Compress(app)
if minify_inited:
minify(app=app, js=False, caching_limit=0)
import before_after_req # noqa: F401,E402
# Init github
if os.getenv("GITHUB_VERSION_PAT") is not None:
github_instance = Github(os.getenv("GITHUB_VERSION_PAT"))
else:
github_instance = Github()
rep = github_instance.get_repo("KTibow/scorecard")
def sleep(timefor):
"""
Sleep, but catch interrupts and whatever.
Args:
timefor: The amount of time to sleep in seconds.
"""
for _index in range(round(timefor * 16.0)):
time.sleep(1 / 16)
commit_number = 0
