A sample interactive session using TeaFiles api for Python.
>>> from teafiles import *
>>> with TeaFile.create('acme.tea', 'Time Price Volume', 'qdq', 'acme prices', {'exchange': 'nyse', 'decimals': 2}) as tf:
... for t in range(DateTime(2000), DateTime(2001), Duration(weeks=1)):
... import random
... tf.write(t, random.random() * 100, random.randint(1, 10000))
...
>>> TeaFile.printsnapshot('acme.tea')
TeaFile('acme.tea') 53 items
ItemDescription
Name: TPV
Size: 24
Fields:
[Time Type: Int64 Offset: 0 IsTime:1 IsEventTime:1,
Price Type: Double Offset: 8 IsTime:0 IsEventTime:0,
Volume Type: Int64 Offset:16 IsTime:0 IsEventTime:0]
ContentDescription
acme prices
NameValues
{u'decimals': 2, u'exchange': u'nyse'}
TimeScale
Epoch: 719162
Ticks per Day: 86400000
Wellknown Scale: Java
Items
TPV(Time=2000-01-01 00:00:00:000, Price=37.579128977028674, Volume=8047)
TPV(Time=2000-01-08 00:00:00:000, Price=10.618929589509186, Volume=232)
TPV(Time=2000-01-15 00:00:00:000, Price=73.08506970525428, Volume=1711)
TPV(Time=2000-01-22 00:00:00:000, Price=73.7749103916519, Volume=4397)
TPV(Time=2000-01-29 00:00:00:000, Price=10.323610234110403, Volume=3376)
>>> tf = TeaFile.openread('acme.tea')
>>> from pprint import pprint
>>> pprint(list(tf.items(50)))
[TPV(Time=2000-12-16 00:00:00:000, Price=62.654885677497305, Volume=8097),
TPV(Time=2000-12-23 00:00:00:000, Price=28.267048873450907, Volume=9226),
TPV(Time=2000-12-30 00:00:00:000, Price=34.48653142780683, Volume=7790)]
>>> pprint(list(tf.items(0, 10)))
[TPV(Time=2000-01-01 00:00:00:000, Price=37.579128977028674, Volume=8047),
TPV(Time=2000-01-08 00:00:00:000, Price=10.618929589509186, Volume=232),
TPV(Time=2000-01-15 00:00:00:000, Price=73.08506970525428, Volume=1711),
TPV(Time=2000-01-22 00:00:00:000, Price=73.7749103916519, Volume=4397),
TPV(Time=2000-01-29 00:00:00:000, Price=10.323610234110403, Volume=3376),
TPV(Time=2000-02-05 00:00:00:000, Price=5.253065316994842, Volume=3213),
TPV(Time=2000-02-12 00:00:00:000, Price=77.30547456663894, Volume=1740),
TPV(Time=2000-02-19 00:00:00:000, Price=70.41257838854919, Volume=3450),
TPV(Time=2000-02-26 00:00:00:000, Price=26.454005280919326, Volume=8699),
TPV(Time=2000-03-04 00:00:00:000, Price=18.6317489603937, Volume=8166)]
>>> def showdecimals():
... for filename in os.listdir('.'):
... with TeaFile.openread(filename) as tf:
... nvs = tf.description.namevalues
... print('{} {} {}'.format(filename, nvs.get('Decimals'), nvs.get('DisplayName')))
...
>>> showdecimals()
AA.day.tea 2 Alcoa, Inc.
AA.tick.tea 2 Alcoa, Inc.
AXP.day.tea 2 American Express Co.
BA.day.tea 2 Boeing Co. (The)
BAC.day.tea 2 Bank of America Corp.
CAT.day.tea 2 Caterpillar Inc.
CSCO.day.tea 2 Cisco Systems, Inc.
CVX.day.tea 2 Chevron Corporation
DD.day.tea 2 Du Pont (E.I.) de Nemours & Co
DIS.day.tea 2 WALT DISNEY-DISNEY C
GE.day.tea 2 General Electric Co
HD.day.tea 2 HOME DEPOT INC
HPQ.day.tea 2 Hewlett-Packard Co
IBM.day.tea 2 International Business Machines Corp.
INTC.day.tea 2 Intel Corporation
JNJ.day.tea 2 Johnson & Johnson
JPM.day.tea 2 JPMorgan Chase & Co.
KFT.day.tea 2 Kraft Foods, Inc.
KO.day.tea 2 Coca-Cola Co (The)
MCD.day.tea 2 McDonald's Corp
MMM.day.tea 2 3M Co
MRK.day.tea 2 Merck & Co., Inc
MSFT.day.tea 2 Microsoft Corporation
PFE.day.tea 2 PFIZER INC
PG.day.tea 2 Procter & Gamble Co.
T.day.tea 2 AT&T Inc
TRV.day.tea 2 Travelers Companies Inc (The)
UTX.day.tea 2 United Technologies Corp.
VZ.day.tea 2 Verizon Communications Inc
WMT.day.tea 2 Wal-Mart Stores, Inc.
XOM.day.tea 2 Exxon Mobil Corp.
>>>