def test_fred_series_search(self):
fred.key('123')
fred.search('money stock')
expected = 'http://api.stlouisfed.org/fred/series/search'
params = {
'api_key': '123',
'search_text': 'money stock',
'file_type': 'json'
}
self.get.assert_called_with(expected, params=params)
def searchTitle(*args):
if not args: searchKey = raw_input("Enter search key: ")
else: searchKey = args[0]
response = fred.search(searchKey)
if response['seriess'] == []:
print 'No results found for: ', searchKey
return []
index = 1
l = ['']
i = 0
if not args: print '0) ALL'
while i < len(response['seriess']) and index < 51:
if not args: sys.stdout.write(str(index)), sys.stdout.write(') ')
more = True #necessary?
if i < len(response['seriess']):
try:
l.append((response['seriess'][i]['title'],
response['seriess'][i]['id']))
if args: break
print response['seriess'][i]['title']
i += 1
index += 1
except:
i += 1
if args: break
return l
def get_series_notes(series_term: str) -> pd.DataFrame:
"""Get Series notes. [Source: FRED]
Parameters
----------
series_term : str
Search for this series term
Returns
----------
pd.DataFrame
DataFrame of matched series
"""
fred.key(cfg.API_FRED_KEY)
d_series = fred.search(series_term)
df_fred = pd.DataFrame()
if "error_message" in d_series:
if "api_key" in d_series["error_message"]:
console.print("[red]Invalid API Key[/red]\n")
else:
console.print(d_series["error_message"])
else:
if "seriess" in d_series:
if d_series["seriess"]:
df_fred = pd.DataFrame(d_series["seriess"])
df_fred["notes"] = df_fred["notes"].fillna(
"No description provided.")
else:
console.print("No matches found. \n")
else:
console.print("No matches found. \n")
return df_fred
def get_series_ids(series_term: str, num: int) -> Tuple[List[str], List[str]]:
"""Get Series IDs. [Source: FRED]
Parameters
----------
series_term : str
Search for this series term
num : int
Maximum number of series IDs to output
Returns
----------
List[str]
List of series IDs
List[str]
List of series Titles
"""
fred.key(cfg.API_FRED_KEY)
d_series = fred.search(series_term)
if "seriess" not in d_series:
return [], []
if not d_series["seriess"]:
return [], []
df_series = pd.DataFrame(d_series["seriess"])
df_series = df_series.sort_values(by=["popularity"],
ascending=False).head(num)
return df_series["id"].values, df_series["title"].values
def set_dropdown_options(input_value):
##Search FRED and gets the top 100 results
search = {}
if input_value != '':
search = fred2.search(input_value)['seriess'][:100]
#Get series IDs and information of top 100 results
search_titles = [e['title'] for e in search]
search_frequency = [e['frequency'] for e in search]
search_units = [e['units'] for e in search]
search_seasonal_adjustment = [e['seasonal_adjustment'] for e in search]
search_IDs = [e['id'] for e in search]
search_observation_start = [e['observation_start'] for e in search]
search_observation_end = [e['observation_end'] for e in search]
#Return list of options
out_dict = [{
'label':
'{}, {}, {}, {}, {}, {} to {}'.format(title, frequency, units,
seasonal_adjustment, id,
observation_start,
observation_end),
'value':
id
} for title, frequency, units, seasonal_adjustment, id,
observation_start, observation_end in zip(
search_titles, search_frequency, search_units,
search_seasonal_adjustment, search_IDs,
search_observation_start, search_observation_end)]
return out_dict
def search_fred(search_string, page=1):
results_per_page = 15
api_call_result = fred.search(search_string)
total_pages = math.ceil(api_call_result['count'] / results_per_page)
upper_result_bound = page * results_per_page - 1
lower_result_bound = upper_result_bound - results_per_page + 1
search_results = api_call_result['seriess']
page_results = search_results[lower_result_bound:upper_result_bound]
page_data = _unpack_search_data(page_results)
metadata = {
'data': page_data,
'total_pages': total_pages,
'current_page': page
}
return metadata
def get_series_notes(series_term: str) -> pd.DataFrame:
"""Get Series notes. [Source: FRED]
Parameters
----------
series_term : str
Search for this series term
Returns
----------
pd.DataFrame
DataFrame of matched series
"""
fred.key(cfg.API_FRED_KEY)
d_series = fred.search(series_term)
if "seriess" not in d_series:
return pd.DataFrame()
if not d_series["seriess"]:
return pd.DataFrame()
df_fred = pd.DataFrame(d_series["seriess"])
df_fred["notes"] = df_fred["notes"].fillna("No description provided.")
return df_fred
def get_series_ids(series_term: str, num: int) -> Tuple[List[str], List[str]]:
"""Get Series IDs. [Source: FRED]
Parameters
----------
series_term : str
Search for this series term
num : int
Maximum number of series IDs to output
Returns
----------
List[str]
List of series IDs
List[str]
List of series Titles
"""
fred.key(cfg.API_FRED_KEY)
d_series = fred.search(series_term)
# Cover invalid api and empty search terms
if "error_message" in d_series:
if "api_key" in d_series["error_message"]:
console.print("[red]Invalid API Key[/red]\n")
else:
console.print(d_series["error_message"])
return [], []
if "seriess" not in d_series:
return [], []
if not d_series["seriess"]:
return [], []
df_series = pd.DataFrame(d_series["seriess"])
df_series = df_series.sort_values(by=["popularity"],
ascending=False).head(num)
return df_series["id"].values, df_series["title"].values
def get_series_notes(series_term: str, num: int) -> str:
"""Get Series notes. [Source: FRED]
Parameters
----------
series_term : str
Search for this series term
num : int
Maximum number of series notes to display
Returns
----------
notes : str
Series notes output
"""
fred.key(cfg.API_FRED_KEY)
d_series = fred.search(series_term)
if "seriess" not in d_series:
return "No Series found using this term!\n"
df_fred = pd.DataFrame(d_series["seriess"])
if df_fred.empty:
return "No Series found using this term!\n"
df_fred = df_fred.sort_values(by=["popularity"], ascending=False).head(num)
notes = ""
for _, series in df_fred.iterrows():
if series["notes"]:
notes += series["id"] + "\n"
notes += "-" * len(series["id"]) + "\n"
notes += series["notes"] + "\n\n"
if not notes:
return "Series notes not found!\n"
return notes
def test_fred_series_search(self):
fred.key('123')
fred.search('money stock')
expected = 'https://api.stlouisfed.org/fred/series/search'
params = {'api_key': '123', 'search_text': 'money stock', 'file_type': 'json'}
self.get.assert_called_with(expected, params=params)