def pickleStock(ndays):
symbols = md.getAllPortfoliosSymbols()
dfnrow = getRowNDaysAgo(ndays, symbols)
if len(dfnrow.index.values) == 0:
print('{} {}'.format('Failed', ndays))
raise ConnectionError('{} {}'.format('Failed', ndays))
rdate = getRowYmdDate(dfnrow)
dfnrow.to_pickle(getPickleName(rdate))
def getMdbRowForDate(adate,db_coll):
try:
mdb_data = db_coll.find({'Date': adate})[0]
except:
print('index error',adate)
ndays = md.getNBusDaysFromDateStr(adate.strftime("%Y-%m-%d"))
df = md.getRowNDaysAgo(ndays, md.getAllPortfoliosSymbols())
mdb_data = addCloseVolumeRowToMdb(df,db_coll)
return md.MdbToDataframeForPercent(mdb_data)
def getMissingMarketRow(ndays, db_coll, symbols):
dbaction = None
df = md.getNdaysRowFromMdb(ndays, db_coll)
if df.size == 0: #missing whole row of data, missing all symbole
missing_symbols = md.getAllPortfoliosSymbols()
dbaction = 'ADD'
else:
dfs = set(df.columns)
missing_symbols = set(symbols).difference(dfs)
dbaction = 'UPDATE'
if len(missing_symbols) > 0:
return (md.getRowNDaysAgo(ndays, missing_symbols),dbaction)
else:
return (pd.DataFrame({}),dbaction)
from datetime import datetime
from pymongo import MongoClient
from bson import json_util
from pandas import json_normalize
import json
import pandas as pd
import market_data as md
import rh
client = MongoClient()
db = client['stock_market']
earnings_col = db['market_data_earnings']
symbols = md.getAllPortfoliosSymbols()
#symbols = ['HD','LOW','BEP','LU']
year, month, day = rh.getYearMonthDay()
current_month_dates = rh.getEarnings(symbols, year, month)
current_month_dates = filter(lambda x: x[1][8:10] >= day, current_month_dates)
df = pd.DataFrame(current_month_dates, columns=['symbol', 'earnings_date'])
df.drop_duplicates(inplace=True)
# delete current mdb records and insert new
result = earnings_col.delete_many({})
print(result.deleted_count, " documents deleted.")
try:
result = md.addRowToMdb(df, earnings_col)
print(len(result.inserted_ids), ' documents inserted')
except Exception as e:
print('error ', e)
def testrowndays(ndays):
symbols = md.getAllPortfoliosSymbols()
df = md.getRowNDaysAgo(ndays, symbols)
print(df)