/usr/share/pyshared/dballe/dbacsv.py is in python-dballe 5.18-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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"""
Export data from DB-All.e into CSV format
"""
import dballe
import csv
def intormiss(x):
if x == dballe.MISSING_INT:
return "-"
else:
return "%d" % x
class Exporter:
def __init__(self, db):
self.db = db
self.title = ""
self.cols = []
self.anaData = {}
self.attrData = {}
def getpaval (self, x, var):
id = x["ana_id"]
data = self.anaData[id]
#print "***********", id, av, data
if data.has_key(var):
return data[var].format("")
else:
return ""
def getattrval (self, x, v):
data = self.attrData["%d,%s"%(x["context_id"],x["var"])]
if v in data:
return data.getvar(v).format()
else:
return ""
def computeColumns(self, filter):
title = ""
cols = []
# Do one pass over the result set to compute the columns
stations = {}
idents = set()
anaVars = {}
reps = set()
rcod = {}
dates = set()
levels = set()
tranges = set()
vars = set()
attrs = {}
for d in self.db.query_data(filter):
# Add columns about the station
id = d["ana_id"]
stations[id] = [d["lat"], d["lon"], d.get("ident", None)]
idents.add(d.get("ident", None))
# Get info about the pseudoana extra data
if id not in self.anaData:
query = dballe.Record()
query["ana_id"] = id
query.set_ana_context()
items = {}
for record in self.db.query_data(query):
v = record["var"]
items[v] = dballe.Var(record.getvar(v))
val = record.getvar(v).format("");
if v in anaVars:
if anaVars[v] != val:
anaVars[v] = None
else:
anaVars[v] = val
#print id, v, items[v].format('none')
self.anaData[id] = items
# Add columns about the context
# Repcod
reps.add(d["rep_cod"])
rcod[d["rep_cod"]] = d["rep_memo"]
# Date
dates.add(d["date"])
# Level layer
levels.add(",".join([intormiss(x) for x in d["level"]]))
# Time range
tranges.add(",".join([intormiss(x) for x in d["trange"]]))
# Variables
vars.add(d["var"])
# Attributes
attributes = dballe.Record()
self.db.query_attrs(d["context_id"], d["var"], [], attributes)
self.attrData["%d,%s"%(d["context_id"], d["var"])] = attributes
for v in attributes:
#attrs.add(v.code())
code = v.code()
val = v.format("");
if code in attrs:
if attrs[code] != val:
attrs[code] = None
else:
attrs[code] = val
# Now that we have detailed info, compute the columns
if len(stations) == 1:
# Get the data on the station
for i in stations.itervalues():
data = i
break;
if data[2] == None:
title = title + "Fixed station, lat %f, lon %f. " % (data[0], data[1])
else:
title = title + "Mobile station %s, lat %f, lon %f. " % (data[2], data[0], data[1])
else:
cols.append(["Station", lambda x: x["ana_id"]])
cols.append(["Latitude", lambda x: x["lat"]])
cols.append(["Longitude", lambda x: x["lon"]])
if len(idents) > 1:
cols.append(["Ident", lambda x: x.get("ident", None) or ""])
# Repcod
if len(reps) == 1:
title = title + "Report: %s." % rcod[reps.pop()]
elif len(reps) > 1:
cols.append(["Report", lambda x: x["rep_memo"]])
# Date
if len(dates) == 1:
title = title + "Date: %s." % (dates.pop())
elif len(dates) > 1:
cols.append(["Date", lambda x: x["date"]])
# Level layer
if len(levels) == 1:
title = title + "Level: %s." % (levels.pop())
elif len(levels) > 1:
cols.append(["Level1", lambda x: intormiss(x["leveltype1"])])
cols.append(["L1", lambda x: intormiss(x["l1"])])
cols.append(["Level2", lambda x: intormiss(x["leveltype2"])])
cols.append(["L2", lambda x: intormiss(x["l2"])])
# Time range
if len(tranges) == 1:
title = title + "Time range: %s." % (tranges.pop())
elif len(tranges) > 1:
cols.append(["Time range", lambda x: intormiss(x["pindicator"])])
cols.append(["P1", lambda x: intormiss(x["p1"])])
cols.append(["P2", lambda x: intormiss(x["p2"])])
# Variables
for v in sorted(vars):
cols.append([v, lambda x, v=v: x.getvar(v).format("")])
# Column for special station ana data
for av in sorted(anaVars.keys()):
if anaVars[av] == None:
# Dirty workaround to compensate Python's lack of proper
# anonymous functions: see http://www.jnetworld.com/python.htm
cols.append(["Ana "+av, lambda a, av=av: self.getpaval(a, av)])
else:
title = title + "Ana %s: %s. " % (av, anaVars[av])
# Attributes
for v in sorted(attrs.keys()):
if attrs[v] == None:
# Dirty workaround to compensate Python's lack of proper
# anonymous functions: see http://www.jnetworld.com/python.htm
cols.append(["Attr "+v, lambda a, v=v: self.getattrval(a, v)])
else:
title = title + "Attr %s: %s. " % (v, attrs[v])
self.title = title
self.cols = cols
def output(self, filter, fd):
"""
Perform a DB-All.e query using the given filter and output the results
in CSV format on the given file object
"""
#writer = csv.writer(fd, dialect="excel")
writer = csv.writer(fd)
self.computeColumns(filter)
# Don't query an empty result set
if len(self.cols) == 0:
sys.stderr.write("Warning: result is empty.\n")
return
# Print the title if we have it
if len(self.title) > 0:
row = ["" for x in range(len(self.cols))]
row[0] = self.title
writer.writerow(row)
# Print the column titles
writer.writerow([x[0] for x in self.cols])
for result in self.db.query_data(filter):
fields = []
for c in self.cols:
fields.append(c[1](result))
writer.writerow(fields)
def export(db, query, file):
"""
Perform a DB-All.e query using the given db and query filter, and output
the results in CSV format on the given file object
"""
e = Exporter(db)
e.output(query, file)
# vim:set ts=4 sw=4 expandtab:
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