def sExport(self, mode, dialog):
print "I: ", self.name, ": export"
if (mode == self.eTABLE):
format = "Csv"
elif mode == self.eWWW:
format = "Htm"
elif mode == self.eDB:
format = "Db"
else:
print "sExport: ERROR"
'''get filename, gui dialog, save path to datastore'''
if dialog:
print "as", "dir_export_"+format.lower()
filename = uiAccesories.getSaveFileName("Export table "+self.name+" to "+format.upper(),"dir_export_"+format.lower(), format.upper()+" Files (*."+format.lower()+")", self.name+"."+format.lower())
else:
filename = utils.get_filename("export/"+format.lower()+"/"+self.name+"_"+dstore.GetItem("racesettings-app",['race_name'])+"."+format.lower())
if(filename == ""):
return
title = "Table '"+self.name + "'"+format.upper()+" Export"
'''Write to the file'''
if format == "Csv":
#export times (with collumn's names)
try:
self.model.df.to_csv(filename, ";", mode="w", index = False, encoding = "utf8", float_format = "%g")
except IOError:
uiAccesories.showMessage(self.name+" Export warning", "File "+filename+"\nPermission denied!")
elif format == "Htm":
'''Write to HTML file'''
try:
html_page = ew_html.Page_table(filename, title = dstore.GetItem("racesettings-app", ['race_name']), styles= ["css/results.css",], lists = exportRows, keys = exportHeader)
html_page.save()
uiAccesories.showMessage(title, "Succesfully ("+filename+") : "+ time.strftime("%H:%M:%S", time.localtime()), msgtype = MSGTYPE.statusbar)
except IOError:
uiAccesories.showMessage(title, "NOT succesfully \n\nCannot write into the file ("+filename+")")
def ExportToHtmFiles(dfs, type):
print "ExportToHtmFiles"
#return info
exported = {}
#get filename, gui dialog
racename = dstore.GetItem("racesettings-app", ['race_name'])
dirname = utils.get_filename("export/www/")
for i in range(0, NUMBER_OF.EXPORTS):
if (tabExportColumns.IsEnabled(i, "htm") == False):
continue
df = pd.DataFrame()
if(type == eHTM_EXPORT):
df = dfs[i]
#filter to checked columns
columns = GetExportCollumns(df, i)
if(len(df) != 0):
#get winner and compute GAPs
for nr in range(0, NUMBER_OF.TIMESCOLUMNS):
df = AddGap(df, nr)
df = df[columns]
else:
df = pd.DataFrame(columns=columns)
css_filename = dstore.GetItem("export_www", [i, "css_filename"])
js_filename = dstore.GetItem("export_www", [i, "js_filename"])
title = dstore.GetItem("racesettings-app", ['race_name'])
elif(type == eHTM_EXPORT_LOGO):
df = pd.DataFrame()
css_filename = u"css/logo.css"
js_filename = u""
title = "Časomíra Ewitis - <i>Vy závodíte, my měříme..</i>"
else:
print "Error: This export is not defined!", type
return
#complete export
#if(len(df) != 0) or (type == self.eHTM_EXPORT_LOGO):
filename = utils.get_filename(dirname+"e"+str(i+1)+"_"+racename+".htm")
#convert header EN => CZ
tocz_dict = dstore.GetItem("export", ["names", i])
df = df.rename(columns = tocz_dict)
#firsttimes
nr = dstore.GetItem("export_www", [i, "firsttimes"])
if nr != 0:
df = df.head(nr)
#lasttimes
nr = dstore.GetItem("export_www", [i, "lasttimes"])
if nr != 0:
df = df.tail(nr)
#transpose
if dstore.GetItem("export_www", [i, "transpose"]):
aux_columns = df.columns
df = df.T
df.insert(0,"", aux_columns)
ExportToHtmFile(filename, Columns2Cz(df, i), css_filename, js_filename, title)
exported["total"] = len(df)
return exported
def Export(utDf, export_type = eCSV_EXPORT):
# 3DFs for 3 exports
exportDf = [pd.DataFrame()] * NUMBER_OF.EXPORTS
if len(utDf) != 0:
#update export df
for i in range(0, NUMBER_OF.EXPORTS):
aux_df = utDf.copy()
if (tabExportColumns.IsEnabled(i) == False):
continue
#get export filtersort
filtersort = dstore.GetItem('export_filtersort', [i])
filter = filtersort['filter']
sort1 = filtersort['sort1'].lower()
sort2 = filtersort['sort2'].lower()
sortorder1 = True if(filtersort['sortorder1'].lower() == "asc") else False
sortorder2 = True if(filtersort['sortorder2'].lower() == "asc") else False
#filter
aux_df = df_utils.FilterEmptyColumns(aux_df, filter.split(" "))
#aux_df = self.joinedDf[(aux_df[column1].notnull()) & (self.joinedDf['user_id']!=0)]
#last time from each user?
aux_df = aux_df.sort("timeraw")
if("last" in filter):
aux_df = aux_df.groupby("nr", as_index = False).last()
#beautify
aux_df = aux_df.where(pd.notnull(aux_df), None)
aux_df.set_index('id', drop=False, inplace = True)
#sort
if(sort2 in aux_df.columns):
aux_df = aux_df.sort([sort1, sort2], ascending = [sortorder1, sortorder2])
else:
aux_df = aux_df.sort(sort1, ascending = sortorder1)
#add "order in category" -> "3./Kategorie XY"
for oc in range(0, NUMBER_OF.EXPORTS):
ordercatX = 'ordercat'+str(oc+1)
orderX = 'order'+str(oc+1)
#aux_df[ordercatX] = aux_df[orderX].astype(str)+"./"+aux_df.category
aux_df[ordercatX] = aux_df[orderX].astype(float).map('{:,g}'.format)+"./"+aux_df.category
# #get winner and compute GAPs
for nr in range(0, NUMBER_OF.TIMESCOLUMNS):
gapX = 'gap'+str(nr+1)
lapX = 'lap'+str(nr+1)
timeX = 'time'+str(nr+1)
try:
winnerX = aux_df.sort([lapX,timeX], ascending = [False, True]).iloc[0]
if (lapX in winnerX) and (timeX in winnerX):
aux_df[gapX] = aux_df.apply(lambda row: GetGap(row[timeX],row[lapX], winnerX[timeX], winnerX[lapX]), axis = 1)
else:
aux_df[gapX] = None
except:
aux_df[gapX] = None
#lapsexport
if (dstore.GetItem('export_filtersort', [i, "onerow"]) != 0):
aux_df = ToLapsExport(aux_df)
#print "PRED",i, aux_df.head(2), aux_df.dtypes
ConvertToInt(aux_df)
#print "PO",i, aux_df.head(2), aux_df.dtypes
#add missing users with DNS status
if export_type == eCSV_EXPORT_DNS:
#print "==========================AddMissingUsers", i
aux_df = AddMissingUsers(aux_df)
#beautify once again
aux_df = aux_df.where(pd.notnull(aux_df), None)
aux_df.set_index('id', drop=False, inplace = True)
ConvertToInt(aux_df)
exportDf[i] = aux_df
#export complete/ category and group results from export DFs
exported = {}
if (export_type == eCSV_EXPORT) or (export_type == eCSV_EXPORT_DNS):
#get dirname
racename = dstore.GetItem("racesettings-app", ['race_name'])
dirname = utils.get_filename("export/"+timeutils.getUnderlinedDatetime()+"_"+racename+"/")
try:
os.makedirs(dirname)
except WindowsError:
pass
exported = ExportToCsvFiles(exportDf, dirname)
exported.update(ExportToSmsFiles(exportDf, dirname))
elif (export_type == eHTM_EXPORT) or (export_type == eHTM_EXPORT_LOGO):
exported = ExportToHtmFiles(exportDf, export_type)
else:
print "Error: This export is not defined!"
return exported
def ExportToCsvFiles(dfs, dirname):
#ret = uiAccesories.showMessage("Results Export", "Choose format of results", MSGTYPE.question_dialog, "NOT finally results", "Finally results")
#if ret == False: #cancel button
# return
#return info
exported = {}
#get dirname
racename = dstore.GetItem("racesettings-app", ['race_name'])
#dirname = utils.get_filename("export/"+timeutils.getUnderlinedDatetime()+"_"+racename+"/")
#print "DN", dirname
#os.makedirs(dirname)
for i in range(0, NUMBER_OF.EXPORTS):
if (tabExportColumns.IsEnabled(i, "csv") == False):
continue
#get df
df = dfs[i]
filtersort = dstore.GetItem('export_filtersort', [i])
#get firstline (racename, time)
header = dstore.GetItem("export_header", [i])
racename = header["racename"].replace("%race%", dstore.GetItem("racesettings-app", ['race_name']))
headertext = header["headertext"].replace("%time%", timeutils.getCurrentDateTime())
firstline = [racename, headertext]
#filter to checked columns
columns = GetExportCollumns(df, i)
#workarround
#replace time with DNF for long times
#df = self.DNF_workarround(df)
#total export
if "total" in filtersort["type"]:
#print i, "TOTAL"
if(len(df) != 0):
#df = AddOrderToMissingUsers(df)
#get winner and compute GAPs
for nr in range(0, NUMBER_OF.TIMESCOLUMNS):
#print df.columns
#df = AddGap(df, nr)
pass
#print df[["nr","gap1"]]
#print "================"
#
filename = utils.get_filename("e"+str(i+1)+"_t_"+racename)
ExportToCsvFile(dirname+filename+".csv", Columns2Cz(df[columns], i), firstline)
exported[filename] = len(df)
#category export
if "categories" in filtersort["type"]:
#print i, "CATEGORIES"
c_df = dfs[i]
c_df = c_df.set_index("category", drop = False)
category_groupby = c_df.groupby(c_df.index)
for c_name, c_df in category_groupby:
c_df = AddOrderToMissingUsers(c_df)
if(len(c_df) != 0):
#get winner and compute GAPs
for nr in range(0, NUMBER_OF.TIMESCOLUMNS):
c_df = AddGap(c_df, nr)
category = tableCategories.model.getCategoryParName(c_name)
category = category.to_dict()
#get secondline (!!c_name used also for filename!!)
c_name = header["categoryname"].replace("%category%", c_name)
secondline = [c_name, header["description"].replace("%description%", category["description"])]
#write to file
filename = utils.get_filename("e"+str(i+1)+"_c_"+c_name)
ExportToCsvFile(dirname+filename+".csv", Columns2Cz(c_df[columns], i), firstline, secondline)
exported[filename] = len(c_df)
#group export
if "groups" in filtersort["type"]:
#print i, "GROUPS"
g_df = dfs[i]
for x in range(1,11):
g_label = "g"+str(x)
categories = tableCategories.model.getCategoriesParGroupLabel(g_label)
aux_df = g_df[g_df["category"].isin(categories["name"])]
if(aux_df.empty == False):
#get winner and compute GAPs
for nr in range(0, NUMBER_OF.TIMESCOLUMNS):
aux_df = AddGap(aux_df, nr)
group = tableCGroups.model.getCGrouptParLabel(g_label)
filename = utils.get_filename("e"+str(i+1)+"_"+g_label+"__"+group["name"])
ExportToCsvFile(dirname+filename+".csv", Columns2Cz(aux_df[columns], i), firstline, [group["name"], group["description"]])
exported[filename] = len(aux_df)
return exported
def ExportToSmsFiles(dfs, dirname):
exported = {}
# #get dirname
racename = dstore.GetItem("racesettings-app", ['race_name'])
# dirname = utils.get_filename("export/"+timeutils.getUnderlinedDatetime()+"_"+racename+"/")
# try:
# os.makedirs(dirname)
# except WindowsError:
# pass
for i in range(0, NUMBER_OF.EXPORTS):
if (tabExportColumns.IsEnabled(i, "sms") == False):
continue
#get df
df = dfs[i]
if(len(df) != 0):
#add sms-text as additional column
mystr = dstore.GetItem("export_sms", ['text',i])
mystr = mystr.replace("%racename%", dstore.GetItem("racesettings-app", ['race_name']))
df["sms_text"] = df.apply(lambda row: replaceSmsTags(mystr, row), axis = 1)
#create empty frame
df_sms = pd.DataFrame(columns=["phone_nr", "prio", "sms_text"])
#phone numbers are in phonecol (o1/o2/o3/o4)
for phonecol in dstore.GetItem("export_sms", ['phone_column']):
if phonecol in df:
#drop empty rows
df_temp = df[df[phonecol] != u""]
#replace # => '
df_temp = df_temp.copy() #SettingWithCopyWarning:
df_temp[phonecol] = df_temp[phonecol].str.replace("#","'")
#add forward sms
df_forwards = pd.DataFrame()
for forward in dstore.GetItem("export_sms", ['forward']):
if (forward["phone_nr"] != 0):
df_forward = df_temp[df_temp.nr == forward["user_nr"]].copy()
df_forward[phonecol] = forward["phone_nr"]
df_forwards = df_forwards.append(df_forward, ignore_index=True)
#df_forwards["sms_text"] = "Fwd:" + df_forwards["sms_text"]
df_temp = df_temp.append(df_forwards, ignore_index=True)
#reduce to 2 columns and rename phonecol (o1/o2/o3/o4 -> phone_nr)
df_temp = df_temp[[phonecol, "sms_text"]]
df_temp.columns = ["phone_nr", "sms_text"]
#append numbers from this collumn
df_sms = df_sms.append(df_temp, ignore_index=True)
#
filename = utils.get_filename("e"+str(i+1)+"_sms_"+racename)
ExportToCsvFile(dirname+filename+".csv", df_sms, firstline = None, secondline = None)
exported[filename] = len(df_sms)
return exported
