def get_weekly_experts(self,
pos,
scoring='STD',
year=utils.get_current_season(),
week=utils.get_current_week()):
"""
Scrape weekly experts for one position and scoring option and return results in a Pandas dataframe. Include
whether the expert is checked to be included in the FantasyPros consensus rankings. (NOTE: check marks will
probably only be accurate for the current year.)
Wrapper around _scrape_experts method with some input validation.
:param pos: position (string)
:param scoring: scoring option -- one of ['STD', 'HALF', 'PPR']
:param year: year, defaults to current year (int)
:param week: week, defaults to current week (int)
:return: Pandas dataframe with expert list
"""
if week == 0:
print(f"Returning draft experts because 'week' was set to 0.")
return self.get_draft_experts(pos=pos, scoring=scoring, year=year)
_check_scoring(pos, scoring)
payload = {'year': year, 'week': week}
url = self._weekly_url_dict[scoring.upper()].format(pos=pos.lower())
df = self._scrape_experts(url=url, payload=payload)
return df
def get_draft_experts(self,
pos='ALL',
scoring='STD',
year=utils.get_current_season()):
"""
Scrape draft experts for one position and scoring option and return results in a Pandas dataframe. Include
whether the expert is checked to be included in the FantasyPros consensus rankings. (NOTE: check marks will
probably only be accurate for the current year.)
Wrapper around _scrape_experts method with some input validation.
:param pos: position (string)
:param scoring: scoring option -- one of ['STD', 'HALF', 'PPR']
:param year: year, defaults to current year (int)
:return: Pandas dataframe with expert list
"""
if pos == 'ALL':
url = self._draft_overall_url_dict[scoring.upper()]
elif pos.upper() in _draft_positions:
_check_scoring(pos, scoring)
url = self._draft_overall_url_dict[scoring.upper()].format(
pos=pos.lower())
else:
raise ValueError(
f"Invalid position for draft rankings -- should be in {['ALL'] + _draft_positions}"
)
payload = {'year': year}
df = self._scrape_experts(url=url, payload=payload)
return df
def write_draft_experts(self,
year=utils.get_current_season(),
update_master=True):
"""
Write the experts currently available for draft rankings to CSV files. One CSV file per expert/position/scoring
combination. For example:
./experts/2019/draft/2019_expert_list_draft_OVERALL_STD.csv
Repeatedly calls the get_draft_experts method and writes the returned dataframe to CSV.
Maintains a "master" file containing information about every expert that has ever been scraped.
NOTE: check marks will probably not be accurate if this method is run for a year earlier than the current year.
:param year: the season year to return experts for (int) (defaults to current year)
:param update_master: if True, update the master file with the results
"""
combined_df = pd.DataFrame()
directory = os.path.join(self.expert_dir, str(year), 'draft')
# first do the overall rankings
for scoring in ['STD', 'HALF', 'PPR']:
df = self.get_draft_experts(pos='ALL', scoring=scoring, year=year)
file = os.path.join(
directory,
f'{year}_expert_list_draft_OVERALL_{scoring.upper()}.csv')
utils.write_df(df=df, filepath=file, verbose=self.verbose)
if update_master:
combined_df = combined_df.append(df)
# then do positional rankings
for pos in _draft_positions:
for scoring in _pos_scoring_dict[pos]:
df = self.get_draft_experts(pos=pos,
scoring=scoring,
year=year)
file = os.path.join(
directory,
f'{year}_expert_list_draft_{pos.upper()}_{scoring.upper()}.csv'
)
utils.write_df(df=df, filepath=file, verbose=self.verbose)
if update_master:
combined_df = combined_df.append(df)
if update_master:
rank_id = f'{year}_draft'
combined_df = (combined_df.groupby(
['expert_id', 'expert_name', 'site'],
as_index=False).agg({'timestamp': 'min'}))
self._update_master(df=combined_df, rank_id=rank_id)
def write_draft_rankings(self,
year=utils.get_current_season(),
start_exp=0):
"""
Write the draft rankings for all available FantasyPros experts to CSV files. Available experts are read from
the expert master file. One CSV file per expert/position/scoring combination. For example:
./rankings/2019/draft/2019_draft_9_Scott Pianowski_Yahoo! Sports_OVERALL_STD.csv
Repeatedly calls the get_draft_rankings method and writes the returned dataframe to CSV.
:param year: the season year to return rankings for (int) (defaults to current year)
:param start_exp: the expert ID number to start with (defaults to 0 to scrape all experts)
"""
expert_df = self._get_all_experts()
for i, row in expert_df.iterrows():
expert_id = row['expert_id']
expert_name = row['expert_name']
site = row['site']
if expert_id < start_exp:
continue
# first get overall rankings
for scoring in ['STD', 'HALF', 'PPR']:
rank_df = self.get_draft_rankings(expert_id=expert_id,
scoring=scoring,
pos='ALL',
year=year)
# write to CSV if results were found
if rank_df.shape[0] > 0:
filename = f'{year}_draft_{expert_id}_{expert_name}_{site}_OVERALL_{scoring}.csv'
path = os.path.join(self.ranking_dir, str(year), 'draft',
filename)
utils.write_df(rank_df, path, verbose=self.verbose)
# then get positional rankings
for pos in _draft_positions:
for scoring in _pos_scoring_dict[pos]:
rank_df = self.get_draft_rankings(expert_id=expert_id,
scoring=scoring,
pos=pos,
year=year)
# write to CSV if results were found
if rank_df.shape[0] > 0:
filename = f'{year}_draft_{expert_id}_{expert_name}_{site}_{pos.upper()}_{scoring}.csv'
path = os.path.join(self.ranking_dir, str(year),
'draft', filename)
utils.write_df(rank_df, path, verbose=self.verbose)
def write_weekly_experts(self,
year=utils.get_current_season(),
week=utils.get_current_week(),
update_master=True):
"""
Write the experts currently available for weekly rankings to CSV files. One CSV file per expert/position/scoring
combination. For example:
./experts/2019/weekly/week1/2019_expert_list_week1_RB_STD.csv
Repeatedly calls the get_weekly_experts method and writes the returned dataframe to CSV.
Maintains a "master" file containing information about every expert that has ever been scraped.
NOTE: check marks will probably not be accurate if this method is run for a year earlier than the current year.
:param year: the season year to return experts for (int) (defaults to current year)
:param week: the week number to return experts for (int) (defaults to current week number)
:param update_master: if True, update the master file with the results
"""
if week == 0:
print(f"Writing draft experts because 'week' was set to 0.")
# this won't return anything, but it will prevent the rest of this method from running
return self.write_draft_experts(year=year,
update_master=update_master)
combined_df = pd.DataFrame()
directory = os.path.join(self.expert_dir, str(year), 'weekly',
f'week{week}')
for pos in _pos_scoring_dict.keys():
for scoring in _pos_scoring_dict[pos]:
df = self.get_weekly_experts(pos=pos,
scoring=scoring,
year=year,
week=week)
file = os.path.join(
directory,
f'{year}_expert_list_week{week}_{pos.upper()}_{scoring.upper()}.csv'
)
utils.write_df(df=df, filepath=file, verbose=self.verbose)
if update_master:
combined_df = combined_df.append(df)
if update_master:
rank_id = f'{year}_week{week}'
combined_df = (combined_df.groupby(
['expert_id', 'expert_name', 'site'],
as_index=False).agg({'timestamp': 'min'}))
self._update_master(df=combined_df, rank_id=rank_id)
def write_weekly_rankings(self,
year=utils.get_current_season(),
week=utils.get_current_week(),
start_exp=0):
"""
Write the draft rankings for all available FantasyPros experts to CSV files. Available experts are read from
the expert master file. One CSV file per expert/position/scoring combination. For example:
./rankings/2019/weekly/2019_week1_9_Scott Pianowski_Yahoo! Sports_RB_STD.csv
Repeatedly calls the get_weekly_rankings method and writes the returned dataframe to CSV.
:param year: the season year to return rankings for (int) (defaults to current year)
:param week: the week number to return rankings for (int) (defaults to current week number)
:param start_exp: the expert ID number to start with (defaults to 0 to scrape all experts)
"""
if week == 0:
print(f"Writing draft rankings because 'week' was set to 0.")
# this won't return anything, but returning the value will prevent the rest of this method from running
return self.write_draft_rankings(year=year, start_exp=start_exp)
expert_df = self._get_all_experts()
for i, row in expert_df.iterrows():
expert_id = row['expert_id']
expert_name = row['expert_name']
site = row['site']
if expert_id < start_exp:
continue
for pos in _pos_scoring_dict.keys():
for scoring in _pos_scoring_dict[pos]:
rank_df = self.get_weekly_rankings(expert_id=expert_id,
scoring=scoring,
pos=pos,
year=year,
week=week)
# write to CSV if results were found
if rank_df.shape[0] > 0:
filename = f'{year}_week{week}_{expert_id}_{expert_name}_{site}_{pos}_{scoring}.csv'
path = os.path.join(self.ranking_dir, str(year),
'weekly', f'week{week}', filename)
utils.write_df(rank_df, path, verbose=self.verbose)
def get_draft_rankings(self,
expert_id,
scoring,
pos='ALL',
year=utils.get_current_season()):
"""
Simple wrapper around _scrape_rankings to get draft rankings for a single expert and the specified parameters.
Performs some basic input validation.
:param expert_id: expert ID (integer)
:param scoring: 'STD', 'HALF', or 'PPR'
:param pos: 'ALL' for overall, or one of 'QB', 'RB', 'WR', 'TE', 'FLEX', 'QB-FLEX', 'DST', 'K'
:param year: year (integer); defaults to current year
:return: dataframe with rankings for one expert
"""
_check_scoring(pos, scoring)
return self._scrape_rankings(expert_id=expert_id,
scoring=scoring,
pos=pos,
year=year,
week=0)
def get_weekly_rankings(self,
expert_id,
scoring,
pos,
year=utils.get_current_season(),
week=utils.get_current_week()):
"""
Simple wrapper around _scrape_rankings to get weekly rankings for a single expert and the specified parameters.
Performs some basic input validation.
:param expert_id: expert ID (integer)
:param scoring: 'STD', 'HALF', or 'PPR'
:param pos: 'ALL' for overall, or one of 'QB', 'RB', 'WR', 'TE', 'FLEX', 'QB-FLEX', 'DST', 'K'
:param year: year (integer); defaults to current year
:param week: week number (integer); defaults to current week
:return: dataframe with rankings for one expert
"""
if week == 0:
print(f"Returning draft rankings because 'week' was set to 0.")
return self.get_draft_rankings(expert_id=expert_id,
scoring=scoring,
pos=pos,
year=year)
if pos.upper() == 'ALL':
raise ValueError(
"'ALL' is not valid for weekly rankings. Overall rankings only available for draft."
)
_check_scoring(pos, scoring)
return self._scrape_rankings(expert_id=expert_id,
scoring=scoring,
pos=pos,
year=year,
week=week)