Merge pull request #11 from portfoliome/fix-intraday

Fix intraday

Author: pmart123

README.md

@@ -4,6 +4,14 @@
 
 alphavantage is a Python wrapper for the Alpha Vantage API.
 
+The API wrapper can be used to retrieve historical prices such as intraday or daily prices for global equities and ETFs.
+
+## Status
+
+The API aims to support equity time-series data as a first step.
+
+The package is currently in alpha status. It has not been used extensively yet and therefore mainly of the potential quirks of Alpha Vantage's actual API may not be accounted for. 
+
 ## Design Consideration
 
 This library is intended to provide a simple wrapper with minimal dependencies, and does not intend to introduce pydata stack dependencies (numpy, pandas, etc.) in the future. Differences with existing wrappers for the Alpha Vantage API include:
@@ -19,23 +27,38 @@ The library carries out some conveniences versus using the API without a wrapper
 
 ### Conveniences
 
-* converting timestamps to UTC time when applicable
-* Simplifies record field names i.e. "4. close" -> "close"
-* appends timestamp field to record vs. having timestamp act as dictionary key
-* Uses time ascending list/array versus dictionary/hash for price record data structure.
-* Mapping ticker symbology from other vendors
- 
+* Converts timestamps to UTC time when applicable.
+* Simplifies record field names i.e. "4. close" -> "close".
+* Appends the timestamp field to record vs. having the timestamp act as dictionary key.
+* Uses time ascending list versus a dictionary for price record data structure.
+* Returns multiple tickers over a given parameter set using threads.
+* Maps ticker symbology from other vendors.
+* Excludes intraday data in daily price history requests.
+
 ## Examples
 ```python
-from alphavantage.price_history import PriceHistory, IntradayPriceHistory, filter_dividends
+from alphavantage.price_history import (
+  AdjustedPriceHistory, get_results, PriceHistory, IntradayPriceHistory,
+  filter_dividends
+)
+
+# weekly prices
+history = PriceHistory(period='W', output_size='compact')
+results = history.get('AAPL')
 
-history = PriceHistory(output_size='compact')
+# intraday prices, 5 minute interval
+history = IntradayPriceHistory(utc=True, interval=5)
 results = history.get('AAPL')
 
-history = IntradayPriceHistory(utc=True)
+# adjusted daily prices
+history = AdjustedPriceHistory(period='D')
 results = history.get('AAPL')
 dividends = list(filter_dividends(results.records))
 
+# Return multiple tickers
+parameters = {'output_size': 'compact', 'period': 'D'}
+tickers = ['AAPL', 'MSFT']
+results = dict(get_results(PriceHistory, tickers, parameters))
 ```
 
 ## Contributing

alphavantage/_version.py

@@ -1,4 +1,4 @@
 
-version_info = (0, 0, 9)
+version_info = (0, 0, 10)
 
 __version__ = '.'.join(map(str, version_info))

alphavantage/price_history.py

@@ -7,7 +7,10 @@
 """
 
 import os
+from concurrent.futures import ThreadPoolExecutor, as_completed
 from operator import itemgetter
+from json import JSONDecodeError
+from urllib.error import HTTPError
 
 import requests
 from foil.formatters import format_repr_info
@@ -130,10 +133,14 @@ def get(self, ticker):
         return self.get_results(ticker, response, retrieved_at)
 
     def get_results(self, ticker, response, retrieved_at):
-        updated_at, timezone = self.transform_meta_data(response['Meta Data'])
+        updated_at, timezone, is_intraday = self.transform_meta_data(response['Meta Data'])
         records = self.transform_records(response[self.data_key])
         records = self.sort_records(self.convert_timezones(records, timezone))
 
+        # remove intraday record in daily series
+        if is_intraday:
+            records = records[0:-1]
+
         return Results(ticker, records, timezone,
                        updated_at=updated_at, retrieved_at=retrieved_at)
 
@@ -182,10 +189,23 @@ def transform_meta_data(self, response_meta):
         tz_key = next(
             key for key in response_meta if key.endswith('Time Zone')
         )
-        updated_at = self.parse_time(response_meta[refresh_key])
+        updated_at, is_intraday = self.parse_refresh_time(
+            response_meta[refresh_key]
+        )
         timezone = response_meta[tz_key]
 
-        return updated_at, timezone
+        return updated_at, timezone, is_intraday
+
+    def parse_refresh_time(self, dt):
+        is_intraday = False
+
+        try:
+            updated_at = self.parse_time(dt)
+        except ValueError:
+            updated_at = self.parse_time(dt[0:10])
+            is_intraday = True
+
+        return updated_at, is_intraday
 
 
 class AdjustedPriceHistory(PriceHistory):
@@ -236,12 +256,12 @@ def convert_timezones(self, records, timezone):
                 yield record
 
     def transform_meta_data(self, response_meta):
-        updated_at, timezone = super().transform_meta_data(response_meta)
+        updated_at, timezone, _ = super().transform_meta_data(response_meta)
 
         if self.utc:
             updated_at = convert_to_utc(updated_at, timezone)
 
-        return updated_at, timezone
+        return updated_at, timezone, None
 
 
 def get_time_series_function(period, adjusted=False):
@@ -280,3 +300,21 @@ def filter_dividends(records):
     for record in records:
         if record[DIVIDEND] != 0:
             yield record[DATE], record[DIVIDEND]
+
+
+def get_results(cls: PriceHistory, tickers: list, parameters: dict):
+    """Return multiple results using threads."""
+
+    with ThreadPoolExecutor(max_workers=4) as executor:
+        future_to_ticker = {
+            executor.submit(cls(**parameters).get, ticker): ticker
+            for ticker in tickers
+        }
+
+        for future in as_completed(future_to_ticker):
+            ticker = future_to_ticker[future]
+
+            try:
+                yield ticker, future.result()
+            except (HTTPError, JSONDecodeError, KeyError):
+                pass

tests/test_price_history.py

@@ -108,7 +108,7 @@ def test_sort_records(self):
         self.assertEqual(expected, result)
 
     def test_transform_meta_data(self):
-        expected = (self.updated_at, self.timezone)
+        expected = (self.updated_at, self.timezone, False)
         result = self.price_history.transform_meta_data(MOCK_META)
 
         self.assertEqual(expected, result)