Пример #1
0
def download_weekly_bars(instrument, year, csvFile):
    """Download weekly bars from Yahoo! Finance for a given year.

    :param instrument: Instrument identifier.
    :type instrument: string.
    :param year: The year.
    :type year: int.
    :param csvFile: The path to the CSV file to write.
    :type csvFile: string.
    """

    begin = dt.get_first_monday(year)
    end = dt.get_last_monday(year) + datetime.timedelta(days=6)
    bars = download_csv(instrument, begin, end, "w")
    f = open(csvFile, "w")
    f.write(bars)
    f.close()
Пример #2
0
def download_weekly_bars(instrument, year, csvFile):
    """Download weekly bars from Yahoo! Finance for a given year.

    :param instrument: Instrument identifier.
    :type instrument: string.
    :param year: The year.
    :type year: int.
    :param csvFile: The path to the CSV file to write.
    :type csvFile: string.
    """

    begin = dt.get_first_monday(year)
    end = dt.get_last_monday(year) + datetime.timedelta(days=6)
    bars = download_csv(instrument, begin, end, "w")
    f = open(csvFile, "w")
    f.write(bars)
    f.close()
Пример #3
0
def download_weekly_bars(sourceCode, tableCode, year, csvFile, authToken=None):
    """Download weekly bars from Quandl for a given year.

    :param sourceCode: The dataset's source code.
    :type sourceCode: string.
    :param tableCode: The dataset's table code.
    :type tableCode: string.
    :param year: The year.
    :type year: int.
    :param csvFile: The path to the CSV file to write.
    :type csvFile: string.
    :param authToken: Optional. An authentication token needed if you're doing more than 50 calls per day.
    :type authToken: string.
    """

    begin = dt.get_first_monday(year) - datetime.timedelta(days=1)  # Start on a sunday
    end = dt.get_last_monday(year) - datetime.timedelta(days=1)  # Start on a sunday
    bars = download_csv(sourceCode, tableCode, begin, end, "weekly", authToken)
    f = open(csvFile, "w")
    f.write(bars)
    f.close()
Пример #4
0
def download_weekly_bars(sourceCode, tableCode, year, csvFile, authToken=None):
    """Download weekly bars from Quandl for a given year.

    :param sourceCode: The dataset's source code.
    :type sourceCode: string.
    :param tableCode: The dataset's table code.
    :type tableCode: string.
    :param year: The year.
    :type year: int.
    :param csvFile: The path to the CSV file to write.
    :type csvFile: string.
    :param authToken: Optional. An authentication token needed if you're doing more than 50 calls per day.
    :type authToken: string.
    """

    begin = dt.get_first_monday(year) - datetime.timedelta(days=1)  # Start on a sunday
    end = dt.get_last_monday(year) - datetime.timedelta(days=1)  # Start on a sunday
    bars = download_csv(sourceCode, tableCode, begin, end, "weekly", authToken)
    f = open(csvFile, "w")
    f.write(bars)
    f.close()
Пример #5
0
 def testGetLastMonday(self):
     self.assertEquals(dt.get_last_monday(2010),
                       datetime.date(2010, 12, 27))
     self.assertEquals(dt.get_last_monday(2011),
                       datetime.date(2011, 12, 26))
Пример #6
0
 def testGetLastMonday(self):
     self.assertEquals(dt.get_last_monday(2010), datetime.date(2010, 12, 27))
     self.assertEquals(dt.get_last_monday(2011), datetime.date(2011, 12, 26))
Пример #7
0
nasdaq_df = nasdaq_df[nasdaq_df.Industry != 'n/a']

#amex
amex_df = pd.read_csv("data/amex.csv")
amex_df = amex_df[amex_df.Industry != 'n/a']

#ntse

nyse_df = pd.read_csv("data/nyse.csv")
nyse_df = nyse_df[nyse_df.Industry != 'n/a']

now = datetime.datetime.now() 
year = now.year

begin = dt.get_first_monday(year-3)
end = dt.get_last_monday(year) + datetime.timedelta(days=6)


data = nasdaq_df['Symbol'].tolist() + amex_df['Symbol'].tolist() + nyse_df['Symbol'].tolist()


def callback(request, result):
    symbol = request.args[0]
    csvFile = "result/%s.csv"%(symbol)
    if result is not None:
        f = open(csvFile, "w")
        f.write(result)
        f.close()
    
def run(symbol):
    try:
Пример #8
0
nasdaq_df = nasdaq_df[nasdaq_df.Industry != 'n/a']

#amex
amex_df = pd.read_csv("data/amex.csv")
amex_df = amex_df[amex_df.Industry != 'n/a']

#ntse

nyse_df = pd.read_csv("data/nyse.csv")
nyse_df = nyse_df[nyse_df.Industry != 'n/a']

now = datetime.datetime.now()
year = now.year

BEGIN = dt.get_first_monday(year - 3)
END = dt.get_last_monday(year) + datetime.timedelta(days=6)

DATA = nasdaq_df['Symbol'].tolist() + amex_df['Symbol'].tolist(
) + nyse_df['Symbol'].tolist()


def callback(request, result):
    symbol = request.args[0]
    csvFile = "result/%s.csv" % (symbol)
    if result is not None:
        f = open(csvFile, "w")
        f.write(result)
        f.close()


def run(symbol):