Suggest to use pandas capabilities

[rkahun]

First of all, thanks for your effort. I'd like to suggest using of pandas data reading capabilities rather than using loops. What do you think of something like this? Cheers

--

import io

TZ_SERVER = 'Europe/Tallinn' # EET
TZ_LOCAL  = 'Europe/Budapest'
TZ_UTC    = 'UTC'

# get all open positions
ok, resp = MT.send_command("F061#0#")
if ok==True and resp[0:5]=="F061#" and resp[-1]=="!":
    df = pd.read_table(io.StringIO(resp[resp.index('#',5)+1:-1]), sep='$', lineterminator='#',
                       header=None,
                       names=np.array(MT.columnsOpenPositions[1:])[:,0],
                       dtype=MT.columnsOpenPositions[1:]
    ).fillna('')
    df.open_time = pd.to_datetime(df.open_time, unit='s').dt.tz_localize(TZ_SERVER).dt.tz_convert(TZ_UTC)
else:
    pass

[Branly76]

@rhahun,

Hi i will have a look at it. Python is a new language for me. So it is a discovery all the time. Python is very different from all the languages I did in the last 40 years.

BR

[Branly76]

Appreciated.

BR

[rkahun]

In this case I give a bit more universal, although not optimized example. BTW I like your code. ;) Cheers

updated:

import sys

commands = {
    'get_open_orders':      ('F060#', 'columnsOpenOrders', 'open_time'),
    'get_open_positions':   ('F061#', 'columnsOpenPositions', 'open_time'),
    'get_deleted_orders':   ('F065#', 'columnsDeletedOrders', 'delete_time'),
    'get_closed_positions': ('F063#', 'columnsClosedPositions', 'close_time'),
}   

def get_table(command, cols, field, tz=TZ_UTC, **kwargs):
    ok, resp = MT.send_command(command)
    if ok==True and resp[0:5]==command[0:5] and resp[-1]=="!":

        t0 = datetime(1970,1,1)
        t1 = datetime.now()
        if 'date_from' in kwargs.keys():
            t0 = kwargs['date_from']
        if 'date_to' in kwargs.keys():
            t1 = kwargs['date_to']

        df = pd.read_table(io.StringIO(resp[resp.index('#',5)+1:-1]), sep='$', lineterminator='#',
                           header=None,
                           names=np.array(getattr(MT,cols)[1:])[:,0],
                           dtype=getattr(MT, cols)[1:]
        ).fillna('')
        df.index.name = getattr(MT,cols)[0][0]
        for f in df.columns[df.columns.str.contains('_time')]:
            df[f] = pd.to_datetime(df[f], unit='s').dt.tz_localize(TZ_SERVER).dt.tz_convert(tz)
        filter = ((df[field] >= t0.astimezone()) & (df[field] <= t1.astimezone()))
        df = df.loc[filter]
    else:
        df = None

    return df

def get_open_orders(**kwargs):
    command, cols, field = commands[sys._getframe().f_code.co_name]
    df = get_table(command, cols, field, **kwargs)
    return df

def get_deleted_orders(**kwargs):
    command, cols, field = commands[sys._getframe().f_code.co_name]
    df = get_table(command, cols, field, **kwargs)
    return df

def get_open_positions(**kwargs):
    command, cols, field = commands[sys._getframe().f_code.co_name]
    df = get_table(command, cols, field, **kwargs)
    return df

def get_closed_positions(**kwargs):
    command, cols, field = commands[sys._getframe().f_code.co_name]
    df = get_table(command, cols, field, **kwargs)
    return df

display(
    get_open_orders(tz=TZ_LOCAL,
                    date_from=(datetime.now()+timedelta(seconds=-86400)).astimezone(),
                    date_to  =(datetime.now()+timedelta(seconds=-8000)).astimezone()),
    get_deleted_orders(tz=TZ_LOCAL, date_from=(datetime.now()+timedelta(days=-2)).astimezone()),
    get_open_positions(tz=TZ_SERVER),
    get_closed_positions(),
    get_open_orders(),
)

[rkahun]

I see, you've revised it. Cheers