Merge pull request #1436 from bug-or-feature/issue-1435-minor-issues-11

Minor issues 11

docs/backtesting.md

@@ -3997,13 +3997,12 @@ of forecasts.
 
 ### Working out net costs (both instrument and forecast weights)
 
-Again I recommend you check out this [blog
-post](https://qoppac.blogspot.com/2016/05/optimising-weights-with-costs.html).
+Again I recommend you check out this [blog post](https://qoppac.blogspot.com/2016/05/optimising-weights-with-costs.html).
 
 ```
 forecast_weight_estimate:  ## can also be applied to instrument weights
    equalise_gross: False ## equalise gross returns so that only costs are used for optimisation
-   cost_multiplier: 0.0 ## multiply costs by this number. Zero means grosss returns used. Higher than 1 means costs will be inflated. Use zero if apply_cost_weight=True (see later)
+   cost_multiplier: 0.0 ## multiply costs by this number. Zero means gross returns used. Higher than 1 means costs will be inflated. Use zero if apply_cost_weight=True (see later)
 ```
 
 

docs/dashboard_and_monitor.md

@@ -2,7 +2,7 @@ This document describes how to monitor pysystemtrade in a production environment
 
 It will make no sense unless you've already read:
 
-- [Using pysystemtrade in production(/docs/production.md)
+- [Using pysystemtrade in production](/docs/production.md)
 
 Table of Contents
 =================

docs/instruments.md

@@ -4,7 +4,7 @@ It will make no sense unless you've already read:
 
 - [Backtesting with pysystemtrade](/docs/backtesting.md)
 - [Storing futures and spot FX data](/docs/data.md)
-- [Using pysystemtrade in production(/docs/production.md)
+- [Using pysystemtrade in production](/docs/production.md)
 
 Table of Contents
 =================
@@ -350,7 +350,7 @@ Operating in the production environment is a bit more complex, due to the intera
 
 When you're running in simulation things are relatively simple; configuration items are defined in defaults_yaml, but can be overridden by your private_config.yaml, and then also by your own backtest.yaml file.
 
-Importantly, once we're out of the 'backtesting'' part of a production system, we can't see the backtest configuration (which after all is system specific, whereas generally in the production environment we're working with global parameters). So the priority order is `defaults.yaml`, overridden by `private_config.yaml`. The downstream code that produces strategy orders once the production backtest has generated optimal positions, and then trades those orders, will operate only on the configuration in `private_config.yaml` and `defaults.yaml`. 
+Importantly, once we're out of the 'backtesting' part of a production system, we can't see the backtest configuration (which after all is system specific, whereas generally in the production environment we're working with global parameters). So the priority order is `defaults.yaml`, overridden by `private_config.yaml`. The downstream code that produces strategy orders once the production backtest has generated optimal positions, and then trades those orders, will operate only on the configuration in `private_config.yaml` and `defaults.yaml`. 
 
 ## Reduce only and other constraints in static systems
 

docs/production.md

@@ -1964,7 +1964,7 @@ We can set the maximum allowable position that can be held in a given instrument
 
 Autopopulate uses current levels of risk to estimate the appropriate position limit. So it will make position limits smaller when risk is higher, and vice versa. It makes a lot of assumptions when setting limits: that all your strategies have the same risk limit (which you can set), and the same IDM (also can be modified), and that all instruments have the same instrument weight (which you can set). It does not use actual instrument weights, and it only sets limits that are global for a particular instrument.
 
-The dynamic optimisation strategy will also use position limits in it's optimisation in production (not in backtests, since fixed position limits make no sense for a historical backtest).
+The dynamic optimisation strategy will also use position limits in its optimisation in production (not in backtests, since fixed position limits make no sense for a historical backtest).
 
 #### Trade control / override
 
@@ -2845,7 +2845,7 @@ The following are .csv configurations used in both production and sim:
 ### Set up configuration
 
 
-The following are used when initialising the database with it's initial configuration, but will also be used in the simulation environment:
+The following are used when initialising the database with its initial configuration, but will also be used in the simulation environment:
 
 - [/data/futures/csvconfig/spreadcosts.csv](/data/futures/csvconfig/spreadcosts.csv) 
 

sysbrokers/IB/ib_orders.py

@@ -1,9 +1,5 @@
 from ib_insync import Trade as ibTrade
 
-from copy import copy
-
-import datetime
-
 from sysbrokers.IB.ib_futures_contracts_data import ibFuturesContractData
 from sysbrokers.IB.ib_instruments_data import ibFuturesInstrumentData
 from sysbrokers.IB.ib_translate_broker_order_objects import (
@@ -456,7 +452,7 @@ def modify_limit_price_given_control_object(
         """
         NOTE this does not update the internal state of orders, which will retain the original order
 
-        :param broker_orders_with_controls:
+        :param broker_order_with_controls:
         :param new_limit_price:
         :return:
         """

syscore/fileutils.py

@@ -8,7 +8,7 @@
 
 from syscore.dateutils import SECONDS_PER_DAY
 
-# DO NOTE DELETE: all these are unused: but are required to get the filename padding to work
+# DO NOT DELETE: all these are unused: but are required to get the filename padding to work
 
 
 """
@@ -103,7 +103,7 @@ def get_file_or_folder_age_in_days(full_filename_with_ext: str) -> float:
 
 
 def resolve_path_and_filename_for_package(
-    path_and_filename: str, seperate_filename=None
+    path_and_filename: str, separate_filename=None
 ) -> str:
     """
     A way of resolving relative and absolute filenames, and dealing with awkward OS specific things
@@ -135,10 +135,10 @@ def resolve_path_and_filename_for_package(
     """
 
     path_and_filename_as_list = transform_path_into_list(path_and_filename)
-    if seperate_filename is None:
+    if separate_filename is None:
         (
             path_as_list,
-            seperate_filename,
+            separate_filename,
         ) = extract_filename_from_combined_path_and_filename_list(
             path_and_filename_as_list
         )
@@ -147,7 +147,7 @@ def resolve_path_and_filename_for_package(
 
     resolved_pathname = get_pathname_from_list(path_as_list)
 
-    resolved_path_and_filename = os.path.join(resolved_pathname, seperate_filename)
+    resolved_path_and_filename = os.path.join(resolved_pathname, separate_filename)
 
     return resolved_path_and_filename
 
@@ -240,9 +240,9 @@ def extract_filename_from_combined_path_and_filename_list(
     extension = path_and_filename_as_list.pop()
     filename = path_and_filename_as_list.pop()
 
-    seperate_filename = ".".join([filename, extension])
+    separate_filename = ".".join([filename, extension])
 
-    return path_and_filename_as_list, seperate_filename
+    return path_and_filename_as_list, separate_filename
 
 
 def get_pathname_from_list(path_as_list: List[str]) -> str:

sysdata/csv/csv_futures_contract_prices.py

@@ -54,7 +54,7 @@ def _get_merged_prices_for_contract_object_no_checking(
         """
         Read back the prices for a given contract object
 
-        :param contract_object:  futuresContract
+        :param futures_contract_object:  futuresContract
         :return: data
         """
 

sysdata/futures/spread_costs.py

@@ -1,5 +1,5 @@
 ## Expected slippage eg half bid-ask spread
-## Used to be in instrument config, now seperate
+## Used to be in instrument config, now separate
 import pandas as pd
 from sysdata.base_data import baseData
 from syslogging.logger import *

sysdata/parquet/parquet_access.py

@@ -62,7 +62,7 @@ def _get_filename_given_data_type_and_identifier(
     ):
         path = self._get_pathname_given_data_type(data_type)
         return resolve_path_and_filename_for_package(
-            path, seperate_filename="%s.%s" % (identifier, EXTENSION)
+            path, separate_filename="%s.%s" % (identifier, EXTENSION)
         )
 
     def _get_pathname_given_data_type(self, data_type: str):

sysdata/production/capital.py

@@ -236,8 +236,10 @@ class totalCapitalCalculationData(object):
 
     def __init__(self, capital_data: capitalData, calc_method="full"):
         """
-        Calculation methods are: full- all profits and losses go to capital, half - profits past the HWM are not added,
-           fixed - capital is unaffected by profits and losses (not reccomended!)
+        Calculation methods are:
+          - full: all profits and losses go to capital
+          - half: profits past the HWM are not added
+          - fixed: capital is unaffected by profits and losses (not recommended!)
 
         :param capital_data: strategyCapitalData instance or something that inherits from it
         :param calc_method: method for going from profits to capital allocated

sysdata/sim/sim_data.py

@@ -270,7 +270,7 @@ def _get_fx_data(self, currency1: str, currency2: str) -> fxPrices:
         Get the FX rate currency1/currency2 between two currencies
         Or return None if not available
 
-        (Normally we'd over ride this with a specific source)
+        (Normally we'd override this with a specific source)
 
 
         """
@@ -287,7 +287,7 @@ def _get_fx_data_from_start_date(
         Get the FX rate currency1/currency2 between two currencies
         Or return None if not available
 
-        (Normally we'd over ride this with a specific source)
+        (Normally we'd override this with a specific source)
 
 
         """

sysexecution/algos/algo_limit_orders.py

@@ -1,20 +1,5 @@
-"""
-Simplest possible execution method, one market order
-"""
-from copy import copy
-from sysexecution.orders.named_order_objects import missing_order
-from sysproduction.data.broker import dataBroker
-
 from sysexecution.algos.algo import Algo, limit_price_from_input, limit_order_type
-from sysexecution.algos.common_functions import (
-    post_trade_processing,
-    MESSAGING_FREQUENCY,
-    cancel_order,
-)
-from sysdata.data_blob import dataBlob
-from sysexecution.orders.contract_orders import contractOrder
 from sysexecution.order_stacks.broker_order_stack import orderWithControls
-from sysexecution.orders.broker_orders import market_order_type
 
 
 class algoLimit(Algo):

sysexecution/algos/algo_market.py

@@ -60,7 +60,7 @@ def prepare_and_submit_trade(self):
 
         if cut_down_contract_order.trade != contract_order.trade:
             self.data.log.debug(
-                "Cut down order to size %s from %s because of algo size limit"
+                "Cut down order from size %s to %s because of algo size limit"
                 % (str(contract_order.trade), str(cut_down_contract_order.trade)),
                 **log_attrs,
             )

sysexecution/algos/algo_original_best.py

@@ -102,7 +102,7 @@ def prepare_and_submit_trade(self) -> orderWithControls:
         )
         if cut_down_contract_order.trade != contract_order.trade:
             data.log.debug(
-                "Cut down order to size %s from %s because of algo size limit"
+                "Cut down order from size %s to %s because of algo size limit"
                 % (str(contract_order.trade), str(cut_down_contract_order.trade)),
                 **log_attrs,
             )

sysexecution/stack_handler/create_broker_orders_from_contract_orders.py

@@ -201,7 +201,7 @@ def liquidity_size_contract_order(
 
         if liquid_qty != contract_order_after_trade_limits.trade:
             self.log.debug(
-                "Cut down order to size %s from %s because of liquidity"
+                "Cut down order from size %s to %s because of liquidity"
                 % (str(liquid_qty), str(contract_order_after_trade_limits.trade)),
                 **contract_order_after_trade_limits.log_attributes(),
                 method="temp",

sysinit/futures/barchart_futures_contract_prices.py

@@ -7,7 +7,7 @@
 from syscore.dateutils import month_from_contract_letter
 
 from sysinit.futures.contract_prices_from_csv_to_arctic import (
-    init_arctic_with_csv_futures_contract_prices,
+    init_db_with_csv_futures_contract_prices,
 )
 
 
@@ -100,9 +100,7 @@ def strip_file_names(pathname):
 
 def transfer_barchart_prices_to_arctic(datapath):
     strip_file_names(datapath)
-    init_arctic_with_csv_futures_contract_prices(
-        datapath, csv_config=barchart_csv_config
-    )
+    init_db_with_csv_futures_contract_prices(datapath, csv_config=barchart_csv_config)
 
 
 if __name__ == "__main__":

sysinit/futures/safely_modify_roll_parameters.py

@@ -148,7 +148,7 @@ def safely_modify_roll_parameters(data: dataBlob):
 
 
 def modified_roll_parameters(data: dataBlob, instrument_code) -> rollParameters:
-    print("Existing roll parameters: Must be defined in database config")
+    print("Existing roll parameters: Must be defined in CSV config")
     data_contracts = dataContracts(data)
     roll_parameters = data_contracts.get_roll_parameters(instrument_code)
     print(str(roll_parameters))

sysinit/futures/seed_price_data_from_IB.py

@@ -21,7 +21,7 @@ def seed_price_data_from_IB(instrument_code):
     ## This returns yyyymmdd strings, where we have the actual expiry date
 
     for contract_date in list_of_contracts:
-        ## We do this slightly tortorous thing because there are energy contracts
+        ## We do this slightly tortuous thing because there are energy contracts
         ## which don't expire in the month they are labelled with
         ## So for example, CRUDE_W 202106 actually expires on 20210528
 

sysproduction/data/risk.py

@@ -182,7 +182,7 @@ def get_daily_ts_stdev_of_prices(data, instrument_code):
 
     # volconfig contains 'func' and some other arguments
     # we turn func which could be a string into a function, and then
-    # call it with the other ags
+    # call it with the other args
 
     volfunction = resolve_function(volconfig.pop("func"))
     vol = volfunction(dailyreturns, **volconfig)

sysproduction/interactive_update_roll_status.py

@@ -566,7 +566,8 @@ def manually_update_roll_state_for_code(
     )
     if roll_state_suggested == ASK_FOR_STATE:
         print(
-            "No specific state suggested: recommend one of Force, Force_Outright or Close)"
+            "No specific state suggested: recommend one of Force, "
+            "Force_Outright or Close"
         )
         default_state = roll_data.original_roll_status.name
     else:

sysproduction/reporting/adhoc/dynamic_optimisation.py

@@ -303,7 +303,7 @@ def dynamic_optimisation_text(data: dataBlob, strategy_name: str):
 
 
 if __name__ == "__main__":
-    ### Do two seperate reports, one graphical, one text
+    ### Do two separate reports, one graphical, one text
 
     data = dataBlob()
     ## interactively get backtest to use

sysproduction/reporting/data/rolls.py

@@ -361,7 +361,7 @@ def get_or_infer_latest_price(new_multiple_prices, price_col: str = "PRICE"):
 
     If one can't be found, infer (There will always be a price in some column)
 
-    :param current_multiple_prices: futuresMultiplePrices
+    :param new_multiple_prices: futuresMultiplePrices
     :param price_col: one of 'PRICE','CARRY','FORWARD'
     :return: tuple: float, bool. Bool is true if the price is inferred, otherwise False
     """

sysproduction/update_total_capital.py

@@ -50,7 +50,7 @@ def update_margin(self):
         margin_data.add_total_margin_entry(margin_in_base_currency)
         margin_series = margin_data.get_series_of_total_margin()
 
-        log.debug("Recent margin\n %s" % str(margin_series.tail(10)))
+        log.debug("Recent margin\n%s" % str(margin_series.tail(10)))
 
     def update_capital(self):
         data = self.data

sysquant/estimators/correlations.py

@@ -196,10 +196,10 @@ def without_missing_data(self):
 
     def quantize(self, quant_factor=0.2):
         as_pd = self.as_pd()
-        multipier = 1 / quant_factor
-        multiplied_pd = as_pd * multipier
+        multiplier = 1 / quant_factor
+        multiplied_pd = as_pd * multiplier
         multiplied_pd_rounded = multiplied_pd.round()
-        pd_quantized = multiplied_pd_rounded / multipier
+        pd_quantized = multiplied_pd_rounded / multiplier
 
         return correlationEstimate(
             values=pd_quantized.values, columns=pd_quantized.columns

sysquant/estimators/pooled_correlation.py

@@ -23,7 +23,7 @@ def pooled_correlation_estimator(
     ## Will need to keep this to adjust lookbacks
     length_adjustment = len(downsampled_data)
 
-    ## We do this to ensure same frequency throughout once concatendate
+    ## We do this to ensure same frequency throughout once concatenated
     data_at_common_frequency = downsampled_data.reindex_to_common_index()
 
     # Make into one giant dataframe

systems/accounts/account_buffering_subsystem.py

@@ -117,17 +117,17 @@ def apply_buffer(
 
     If we're rounding positions, then we floor and ceiling the buffers.
 
-    :param position: optimal position
-    :type position: pd.Series
+    :param optimal_position: optimal position
+    :type optimal_position: pd.Series
 
     :param pos_buffers:
     :type pos_buffers: Tx2 pd.dataframe, top_pos and bot_pos
 
-    :param trade_to_edge: Trade to the edge (TRue) or the optimal (False)
+    :param trade_to_edge: Trade to the edge (True) or the optimal (False)
     :type trade_to_edge: bool
 
-    :param round_positions: Produce rounded positions
-    :type round_positions: bool
+    :param roundpositions: Produce rounded positions
+    :type roundpositions: bool
 
     :returns: pd.Series
     """
@@ -185,7 +185,7 @@ def apply_buffer_single_period(
     :param bot_pos: bottom of buffer
     :type bot_pos: float
 
-    :param trade_to_edge: Trade to the edge (TRue) or the optimal (False)
+    :param trade_to_edge: Trade to the edge (True) or the optimal (False)
     :type trade_to_edge: bool
 
     :returns: float

systems/accounts/account_costs.py

@@ -29,7 +29,7 @@ def get_SR_cost_for_instrument_forecast(
 
         KEY OUTPUT
         """
-        ## Calculate holding and transaction seperately, as the former could be pooled
+        ## Calculate holding and transaction separately, as the former could be pooled
         transaction_cost = self.get_SR_transaction_cost_for_instrument_forecast(
             instrument_code=instrument_code, rule_variation_name=rule_variation_name
         )
@@ -184,7 +184,7 @@ def get_SR_holding_cost_only(self, instrument_code: str) -> float:
         cost_per_trade = self.get_SR_cost_per_trade_for_instrument(instrument_code)
         hold_turnovers = self.get_rolls_per_year(instrument_code) * 2.0
 
-        ## Assumes no benefit from spread trades i.e. do two seperate trades
+        ## Assumes no benefit from spread trades i.e. do two separate trades
         SR_cost_holding = hold_turnovers * cost_per_trade
 
         return SR_cost_holding