def plantden_pk(dimapath):
"""
DEPRECATED
returns a dataframe with tblplots, tbllines, tblplantdenheader and tblplantdenDetail
joined. PrimaryKey field is made using formdate and plotkey
"""
arc = arcno()
denhead = arcno.MakeTableView('tblPlantDenHeader', dimapath)
dendet = arcno.MakeTableView('tblPlantDenDetail', dimapath)
# dendet = arcno.MakeTableView(fam['plantden'][0], dimapath)
# denhead = arcno.MakeTableView(fam['plantden'][1], dimapath)
plantden = pd.merge(denhead,dendet, how="inner", on="RecKey")
if 'tblLPIDetail' in ins.actual_list:
allpks = lpi_pk(dimapath)
elif 'tblGapDetail' in ins.actual_list:
allpks = gap_pk(dimapath)
else:
print("a difficult one! no source of easy source of PK's in this dima!")
# where to pull them from will depend on which table needs em, and
# what that table has in terms of fields (plotkey, reckey, linekey etc.)
pks = allpks.loc[:,["PrimaryKey", "EstablishDate", "FormDate", "RecKey","LineKey"]].copy()
iso = arc.isolateFields(pks,'LineKey','PrimaryKey').copy()
premerge = pd.merge(plantden,iso,how="inner", on="LineKey").drop_duplicates().copy()
if tablename=="tblPlantDenHeader":
iso = arc.isolateFields(premerge,'LineKey','PrimaryKey').copy()
merge = pd.merge(denhead,iso, how="inner", on="LineKey")
return merge
elif tablename=="tblPlantDenDetail":
iso = arc.isolateFields(premerge,'RecKey','PrimaryKey').copy()
merge = pd.merge(dendet,iso, how="inner", on="RecKey")
return merge
def gap_pk(dimapath):
"""
returns a dataframe with tblplots, tbllines, tblgapheader and tblgapDetail
joined. PrimaryKey field is made using formdate and plotkey
"""
arc = arcno()
gap_header = arcno.MakeTableView('tblGapHeader', dimapath)
gap_detail = arcno.MakeTableView('tblGapDetail', dimapath)
lines = arcno.MakeTableView('tblLines', dimapath)
plots = arcno.MakeTableView('tblPlots', dimapath)
# joins
plot_line = pd.merge(plots, lines, how="inner", on="PlotKey")
gaphead_detail = pd.merge(gap_header, gap_detail, how="inner", on="RecKey")
plot_line_det = pd.merge(plot_line,
gaphead_detail,
how="inner",
on="LineKey")
# fixing dup fields
# tmp1 = fix_fields(plot_line_det, 'DateModified')
# tmp2 = fix_fields(tmp1, 'ElevationType')
plot_line_det.FormDate = pd.to_datetime(
plot_line_det.FormDate) if platform.system(
) == 'Linux' else plot_line_det.FormDate
plot_pk = arc.CalculateField(plot_line_det, "PrimaryKey", "PlotKey",
"FormDate")
return plot_pk
def sperich_pk(dimapath, tablename):
"""
returns a dataframe with tblplots, tbllines, tblsperichheader and tblsperichDetail
joined. PrimaryKey field is made using formdate and plotkey
"""
arc = arcno()
spe_header = arcno.MakeTableView('tblSpecRichHeader', dimapath)
spe_detail = arcno.MakeTableView('tblSpecRichDetail', dimapath)
lines = arcno.MakeTableView('tblLines', dimapath)
plots = arcno.MakeTableView('tblPlots', dimapath)
# joins
plot_line = pd.merge(plots, lines, how="inner", on="PlotKey")
spehead_detail = pd.merge(spe_header, spe_detail, how="inner", on="RecKey")
plot_line_det = pd.merge(plot_line,
spehead_detail,
how="inner",
on="LineKey")
plot_line_det.FormDate = pd.to_datetime(
plot_line_det.FormDate) if platform.system(
) == 'Linux' else plot_line_det.FormDate
plot_pk = arc.CalculateField(plot_line_det, "PrimaryKey", "PlotKey",
"FormDate")
if tablename == "tblSpecRichHeader":
iso = arc.isolateFields(plot_pk, "LineKey", "PrimaryKey")
merge = pd.merge(spe_header, iso, how="inner", on="LineKey")
return merge
elif tablename == "tblSpecRichDetail":
iso = arc.isolateFields(plot_pk, "RecKey", "PrimaryKey")
merge = pd.merge(spe_detail, iso, how="inner", on="RecKey")
return merge
def table_check(tablename, path):
"""
returns true if table is present in a particular dima
uses "arcno.actual_list" to compile a list of tables
then checks if the chosen table is present in that list
"""
instance = arcno(path)
tablelist = [i for i, j in instance.actual_list.items()]
return True if tablename in tablelist else False
def bsne_pk(dimapath):
"""
returns a dataframe with tblplots, tblBSNE_Box, tblBSNE_Stack and
tblBSNE_BoxCollection and tblBSNE_TrapCollection joined. if tblBSNE_TrapCollection
does not exist in networkdima, skip it and join: box, stack and boxcollection.
if it exists, join trapcollection and stack.
PrimaryKey field is made using formdate and plotkey
"""
ddt = arcno.MakeTableView("tblBSNE_TrapCollection", dimapath)
arc = arcno()
if ddt.shape[0] > 0:
ddt = arcno.MakeTableView("tblBSNE_TrapCollection", dimapath)
stack = arcno.MakeTableView("tblBSNE_Stack", dimapath)
# df = arc.AddJoin(stack, ddt, "StackID", "StackID")
df = pd.merge(stack, ddt, how="inner", on="StackID")
# df.collectDate = pd.to_datetime(df.collectDate) if platform.system()=='Linux' else df.collectDate
if "collectDate" in df.columns:
df.collectDate = pd.to_datetime(df.collectDate)
df2 = arc.CalculateField(df, "PrimaryKey", "PlotKey", "collectDate")
df2tmp = fix_fields(df2, "Notes")
df2tmp2 = fix_fields(df2tmp, "DateModified")
df2tmp3 = fix_fields(df2tmp2, "DateEstablished")
return df2tmp3
else:
box = arcno.MakeTableView("tblBSNE_Box", dimapath)
stack = arcno.MakeTableView("tblBSNE_Stack", dimapath)
boxcol = arcno.MakeTableView('tblBSNE_BoxCollection', dimapath)
# differences 1
# dfx = pd.merge(stack, box[cols_dif1], left_index=True, right_index=True, how="outer")
df = pd.merge(box, stack, how="inner", on="StackID")
# df.collectDate = pd.to_datetime(df.collectDate) if platform.system()=='Linux' else df.collectDate
df2 = pd.merge(df, boxcol, how="inner", on="BoxID")
df2.collectDate = pd.to_datetime(df2.collectDate) if platform.system(
) == 'Linux' else df2.collectDate
# fix
df2 = arc.CalculateField(df2, "PrimaryKey", "PlotKey", "collectDate")
df2tmp = fix_fields(df2, "Notes")
df2tmp2 = fix_fields(df2tmp, "DateModified")
df2tmp3 = fix_fields(df2tmp2, "DateEstablished")
return df2tmp3
def set_model(self,fields=None, tablename=None, pg=None):
if self.projectswitch=='tall':
self.fields = fields
self.tablename = tablename
self.modelhandler = model_handler(self.path, self.fields, self.tablename)
elif self.projectswitch=='dima':
arc = arcno(self.path)
for i,j in arc.actual_list.items():
if 'Box' not in i:
pg_send(i,self.path) if pg==None else pg_send(i,self.path,1)
else:
print('handling not implemented')
def table_collector(path2mdbs):
"""
returns a list of all tables present in a folder of dimas
because dimas may each have a different set of tables, this function
goes through the list of tables per dima and appends any table not previously
seen into an internal list which is ultimately returned.
"""
containing_folder = path2mdbs
contained_files = os.listdir(containing_folder)
table_list = []
for mdb_path in contained_files:
if os.path.splitext(mdb_path)[1] == '.mdb' or os.path.splitext(
mdb_path)[1] == '.accdb':
instance = arcno(os.path.join(containing_folder, mdb_path))
for tablename, size in instance.actual_list.items():
if tablename not in table_list:
table_list.append(tablename)
return table_list
def qual_pk(dimapath):
"""
returns a dataframe with tblplots, tbllines, tblgapheader and tblgapDetail
joined. PrimaryKey field is made using formdate and plotkey
no dup fields
"""
arc = arcno()
header = arcno.MakeTableView('tblQualHeader', dimapath)
detail = arcno.MakeTableView('tblQualDetail', dimapath)
# joins
head_detail = pd.merge(header, detail, how="inner", on="RecKey")
head_detail.FormDate = pd.to_datetime(
head_detail.FormDate) if platform.system(
) == 'Linux' else head_detail.FormDate
plot_pk = arc.CalculateField(head_detail, "PrimaryKey", "PlotKey",
"FormDate")
return plot_pk
def lpi_pk(dimapath):
"""
returns a dataframe with tblplots, tbllines, tbllpiheader and tblLPIDetail
joined. PrimaryKey field is made using formdate and plotkey
"""
lpi_header = arcno.MakeTableView('tblLPIHeader', dimapath)
lpi_detail = arcno.MakeTableView('tblLPIDetail', dimapath)
lines = arcno.MakeTableView('tblLines', dimapath)
plots = arcno.MakeTableView('tblPlots', dimapath)
# joins
plot_line = pd.merge(plots, lines, how="inner", on="PlotKey")
plot_line.LineKey
lpihead_detail = pd.merge(lpi_header, lpi_detail, how="inner", on="RecKey")
len(lpihead_detail.PointLoc.unique())
plot_line_det = pd.merge(plot_line,
lpihead_detail,
how="inner",
on="LineKey")
plot_line_det.loc[:, ['FormDate', "RecKey", "LineKey"]]
arc = arcno()
#
# tmp1 = fix_fields(plot_line_det, 'DateModified').copy()
# tmp2 = fix_fields(tmp1,'ElevationType').copy()
plot_line_det.FormDate = pd.to_datetime(
plot_line_det.FormDate) if platform.system(
) == 'Linux' else plot_line_det.FormDate
plot_pk = arc.CalculateField(plot_line_det, "PrimaryKey", "PlotKey",
"FormDate")
# plot_pk.drop_duplicates(["PrimaryKey", "PlotKey", "FormDate"])
return plot_pk
def main_translate(tablename: str, dimapath: str, debug=None):
""" Translates between tables and different function argument strategies
This function will map the tablename to an appropriate tuple of arguments.
first block of 'a' argument tuple will check if the dima has 'BSNE' tables
within the DIMA. It could still be a vegetation dima however, that will be
checked further along on the no_pk function.
Parameters
----------
tablename : str
Name of the table in DIMA. example: 'tblLines'
dimapath : str
Physical path to DIMA Access file. example: 'c://Folder/dima_file.mdb'
debug : any character or None (default value: None)
Prints out how trayectory of the mapping process throughout the function.
"""
no_primary_key = ['tblPlots', 'tblLines', 'tblSpecies','tblSpeciesGeneric',\
'tblSites','tblPlotNotes', 'tblSites']
soil_stab_primary_key = ['tblSoilStabDetail', 'tblSoilStabHeader']
soil_pit_primary_key = ['tblSoilPits', 'tblSoilPitHorizons']
plant_prod_primary_key = ['tblPlantProdDetail', 'tblPlantProdHeader']
bsne_primary_keys = ['tblBSNE_Box', 'tblBSNE_Stack','tblBSNE_BoxCollection',\
'tblBSNE_TrapCollection']
switcher_arguments = {
'no_pk': (None, dimapath, tablename),
'no_pk_soilstab': ('soilstab', dimapath, None),
'no_pk_soilpits': ('soilpits', dimapath, None),
'no_pk_plantprod': ('plantprod', dimapath, None),
'yes_pk': dimapath,
'f': ('fake', dimapath, tablename)
}
# first check if tablename exists in the particular dima
if table_check(tablename, dimapath):
if tablename in no_primary_key:
# no_pk branch
network_check = 0
inst = arcno(dimapath)
for i, j in inst.actual_list.items():
if any(
[True for i, j in inst.actual_list.items()
if 'BSNE' in i]):
network_check = 2
else:
network_check = 1
while network_check != 0:
if network_check == 1:
print('no_pk; netdima in path; line or plot'
) if debug else None
df = switcher[tablename](*switcher_arguments['f'])
network_check = 0
df = blank_fixer(df)
df = significant_digits_fix_pandas(df)
return df
elif network_check == 2:
print('no_pk; netdima in path; line or plot'
) if debug else None
df = switcher[tablename](*switcher_arguments['no_pk'])
network_check = 0
df = blank_fixer(df)
df = significant_digits_fix_pandas(df)
return df
elif tablename in soil_stab_primary_key:
# no_pk + soilstab branch
print('no_pk; soilstab') if debug else None
df = switcher[tablename](*switcher_arguments['no_pk_soilstab'])
df = blank_fixer(df)
df = significant_digits_fix_pandas(df)
return df
elif tablename in soil_pit_primary_key:
# no_pk + soilpits branch
print('no_pk; soilpits') if debug else None
df = switcher[tablename](*switcher_arguments['no_pk_soilpits'])
df = blank_fixer(df)
df = significant_digits_fix_pandas(df)
return df
elif tablename in plant_prod_primary_key:
# no_pk + plantprod branch
print('no_pk; plantprod') if debug else None
df = switcher[tablename](*switcher_arguments['no_pk_plantprod'])
df = blank_fixer(df)
df = significant_digits_fix_pandas(df)
return df
else:
# lpi_pk, gap_pk, sperich_pk, plantden_pk, bsne_pk branch
if tablename in bsne_primary_keys:
print('bsne collection') if debug else None
retdf = switcher[tablename](switcher_arguments['yes_pk'])
retdf = blank_fixer(retdf)
retdf = significant_digits_fix_pandas(retdf)
retdf = openingsize_fixer(retdf)
return retdf
else:
print('hmmm?') if debug else None
df = switcher[tablename](switcher_arguments['yes_pk'])
arc = arcno()
iso = arc.isolateFields(df, tableswitch[tablename],
"PrimaryKey").copy()
iso.drop_duplicates([tableswitch[tablename]], inplace=True)
target_table = arcno.MakeTableView(tablename, dimapath)
retdf = pd.merge(target_table,
iso,
how="inner",
on=tableswitch[tablename])
retdf = blank_fixer(retdf)
retdf = significant_digits_fix_pandas(retdf)
retdf = openingsize_fixer(retdf)
return retdf
else:
print(f'table not in {os.path.basename(dimapath)}')
pass
def no_pk(tablefam: str = None, dimapath: str = None, tablename: str = None):
"""
"""
arc = arcno()
ins = arcno(dimapath)
fam = {
'plantprod': ['tblPlantProdDetail', 'tblPlantProdHeader'],
'soilstab': ['tblSoilStabDetail', 'tblSoilStabHeader'],
'soilpit': ['tblSoilPits', 'tblSoilPitHorizons'],
'plantden': ['tblPlantDenDetail', 'tblPlantDenHeader'],
}
try:
if tablefam is not None and ('plantprod' in tablefam):
header = arcno.MakeTableView(fam['plantprod'][1], dimapath)
detail = arcno.MakeTableView(fam['plantprod'][0], dimapath)
head_det = pd.merge(header, detail, how="inner", on="RecKey")
head_det.FormDate = pd.to_datetime(
head_det.FormDate) if platform.system(
) == 'Linux' else head_det.FormDate
head_det = arc.CalculateField(head_det, "PrimaryKey", "PlotKey",
"FormDate")
if tablename == "tblPlantProdHeader":
iso = arc.isolateFields(head_det, 'PlotKey',
'PrimaryKey').copy()
merge = pd.merge(header, iso, how="inner", on="PlotKey")
return merge
elif tablename == "tblPlantProdDetail":
iso = arc.isolateFields(head_det, 'RecKey',
'PrimaryKey').copy()
merge = pd.merge(detail, iso, how="inner", on="RecKey")
return merge
elif tablefam is not None and ('soilstab' in tablefam):
header = arcno.MakeTableView(fam['soilstab'][1], dimapath)
detail = arcno.MakeTableView(fam['soilstab'][0], dimapath)
head_det = pd.merge(header, detail, how="inner", on="RecKey")
head_det.FormDate = pd.to_datetime(
head_det.FormDate) if platform.system(
) == 'Linux' else head_det.FormDate
head_det = arc.CalculateField(head_det, "PrimaryKey", "PlotKey",
"FormDate")
if tablename == "tblSoilStabHeader":
iso = arc.isolateFields(head_det, 'PlotKey',
'PrimaryKey').copy()
merge = pd.merge(header, iso, how="inner",
on="PlotKey").drop_duplicates()
return merge
elif tablename == "tblSoilStabDetail":
iso = arc.isolateFields(head_det, 'RecKey',
'PrimaryKey').copy()
merge = pd.merge(
detail, iso, how="inner",
on="RecKey").drop_duplicates(subset=["BoxNum"])
return merge
elif tablefam is not None and ('soilpit' in tablefam):
# print("soilpit")
pits = arcno.MakeTableView(fam['soilpit'][0], dimapath)
horizons = arcno.MakeTableView(fam['soilpit'][1], dimapath)
pits_horizons = pd.merge(pits, horizons, how="inner", on="SoilKey")
if 'tblLPIDetail' in ins.actual_list:
allpks = lpi_pk(dimapath)
elif 'tblGapDetail' in ins.actual_list:
allpks = gap_pk(dimapath)
else:
print(
"a difficult one! no source of easy source of PK's in this dima!"
)
# where to pull them from will depend on which table needs em, and
# what that table has in terms of fields (plotkey, reckey, linekey etc.)
pks = allpks.loc[:, [
"PrimaryKey", "EstablishDate", "FormDate", "DateModified",
"PlotKey"
]].copy()
iso = arc.isolateFields(pks, 'PlotKey', 'PrimaryKey').copy()
premerge = pd.merge(pits_horizons, iso, how="inner",
on="PlotKey").drop_duplicates().copy()
if tablename == "tblSoilPits":
iso = arc.isolateFields(premerge, 'PlotKey',
'PrimaryKey').drop_duplicates().copy()
merge = pd.merge(pits, iso, how="inner", on="PlotKey")
return merge
elif tablename == "tblSoilPitHorizons":
iso = arc.isolateFields(premerge, 'HorizonKey',
'PrimaryKey').drop_duplicates().copy()
merge = pd.merge(horizons, iso, how="inner", on="HorizonKey")
return merge
elif tablefam is not None and ('plantden' in tablefam):
dendet = arcno.MakeTableView(fam['plantden'][0], dimapath)
denhead = arcno.MakeTableView(fam['plantden'][1], dimapath)
plantden = pd.merge(denhead, dendet, how="inner", on="RecKey")
plantden = arc.CalculateField(plantden, "PrimaryKey", "LineKey",
"FormDate")
if tablename == "tblPlantDenHeader":
iso = arc.isolateFields(plantden, 'LineKey',
'PrimaryKey').copy()
merge = pd.merge(denhead, iso, how="inner", on="LineKey")
return merge
elif tablename == "tblPlantDenDetail":
iso = arc.isolateFields(plantden, 'RecKey',
'PrimaryKey').copy()
merge = pd.merge(dendet, iso, how="inner", on="RecKey")
return merge
else:
no_pk_df = arcno.MakeTableView(tablename, dimapath)
# print('netdima in path')
if ('Network_DIMAs' in dimapath) and (tablefam == None):
if ('tblPlots' in tablename) or ('tblLines' in tablename):
print("lines,plots; networkdima in the path")
fulldf = bsne_pk(dimapath)
iso = arc.isolateFields(fulldf, 'PlotKey',
'PrimaryKey').copy()
no_pk_df = pd.merge(
no_pk_df, iso, how="inner",
on=["PlotKey"]).drop_duplicates([
"LineKey", "PrimaryKey"
]) if "tblLines" in tablename else pd.merge(
no_pk_df, iso, how="inner",
on=["PlotKey"]).drop_duplicates(["PrimaryKey"])
return no_pk_df
else:
print("network, but not line or plot, no pk")
if 'Sites' in tablename:
no_pk_df = no_pk_df[(no_pk_df.SiteKey != '888888888') &
(no_pk_df.SiteKey != '999999999')]
return no_pk_df
else:
return no_pk_df
elif ('Network_DIMAs' in dimapath) and ('fake' in tablefam):
if ('tblPlots' in tablename) or ('tblLines' in tablename):
fulldf = lpi_pk(dimapath)
iso = arc.isolateFields(fulldf, 'PlotKey',
'PrimaryKey').copy()
no_pk_df = pd.merge(
no_pk_df, iso, how="inner",
on=["PlotKey"]).drop_duplicates([
"LineKey", "PrimaryKey"
]) if "tblLines" in tablename else pd.merge(
no_pk_df, iso, how="inner",
on=["PlotKey"]).drop_duplicates(["PrimaryKey"])
return no_pk_df
else:
print("network, but not line or plot, no pk --fakebranch")
if 'Sites' in tablename:
no_pk_df = no_pk_df[(no_pk_df.SiteKey != '888888888') &
(no_pk_df.SiteKey != '999999999')]
return no_pk_df
else:
return no_pk_df
else:
if ('tblPlots' in tablename) or ('tblLines' in tablename):
print('not network, no tablefam')
fulldf = lpi_pk(dimapath)
iso = arc.isolateFields(fulldf, 'PlotKey',
'PrimaryKey').copy()
no_pk_df = pd.merge(
no_pk_df, iso, how="inner",
on=["PlotKey"]).drop_duplicates([
"LineKey", "PrimaryKey"
]) if "tblLines" in tablename else pd.merge(
no_pk_df, iso, how="inner",
on=["PlotKey"]).drop_duplicates(["PrimaryKey"])
return no_pk_df
else:
print("not network, not line or plot, no pk")
if 'Sites' in tablename:
no_pk_df = no_pk_df[(no_pk_df.SiteKey != '888888888') &
(no_pk_df.SiteKey != '999999999')]
return no_pk_df
else:
return no_pk_df
# return no_pk_df
except Exception as e:
print(e)
def looper(path2mdbs, tablename, projk=None, csv=False):
"""
goes through all the files(.mdb or .accdb extensions) inside a folder,
create a dataframe of the chosen table using the 'main_translate' function,
adds the dataframe into a dictionary,a
finally appends all the dataframes
and returns the entire appended dataframe
"""
containing_folder = path2mdbs
contained_files = os.listdir(containing_folder)
df_dictionary = {}
count = 1
basestring = 'file_'
for i in contained_files:
if os.path.splitext(os.path.join(
containing_folder, i))[1] == '.mdb' or os.path.splitext(
os.path.join(containing_folder, i))[1] == '.accdb':
countup = basestring + str(count)
# df creation/manipulation starts here
arc = arcno(os.path.join(containing_folder, i))
print(i)
df = main_translate(tablename, os.path.join(containing_folder, i))
# if its gapheader, this deals with different versions (the fun alt_gapheader_check)
if "tblGapHeader" in tablename:
if tablename in arc.actual_list:
df = alt_gapheader_check(df)
else:
df = None
if df is not None:
if 'DateLoadedInDB' in df.columns:
df['DateLoadedInDB'] = df['DateLoadedInDB'].astype(
'datetime64')
df['DateLoadedInDB'] = datetime.now().strftime(
"%d-%m-%Y %H:%M:%S")
else:
df['DateLoadedInDB'] = datetime.now().strftime(
"%d-%m-%Y %H:%M:%S")
df['DBKey'] = os.path.split(os.path.splitext(i)[0])[1].replace(
" ", "")
# df add to dictionary list
df_dictionary[countup] = df.copy()
else:
pass
count += 1
# return df_dictionary
if len(df_dictionary) > 0:
final_df = pd.concat([j for i, j in df_dictionary.items()],
ignore_index=True).drop_duplicates()
final_df = dateloadedcheck(final_df)
# final_df = northing_round(final_df)
if (tablename == 'tblPlots') and (projk is not None):
final_df["ProjectKey"] = projk
if "tblLines" in tablename:
for i in final_df.columns:
if "PrimaryKey" in i:
final_df[i] = final_df[i].astype("object")
return final_df if csv == False else final_df.to_csv(
os.path.join(containing_folder, tablename + '.csv'))
else:
print(f"table '{tablename}' not found within this dima batch")
