Module tf.convert.mql
MQL
You can interchange with MQL data. Text-Fabric can read and write MQL dumps. An MQL dump is a text file, like an SQL dump. It contains the instructions to create and fill a complete database.
Correspondence TF and MQL
After exporting a TF dataset to MQL, the resulting MQL database has the following properties with respect to the TF dataset it comes from:
- the TF slots correspond exactly with the MQL monads and have the same numbers; provided the monad numbers in the MQL dump are consecutive. In MQL this is not obligatory. Even if there gaps in the monads sequence, we will fill the holes during conversion, so the slots are tightly consecutive;
- the TF nodes correspond exactly with the MQL objects and have the same numbers
Node features in MQL
The values of TF features are of two types, int and str, and they translate
to corresponding MQL types integer and string. The actual values do not
undergo any transformation.
That means that in MQL queries, you use quotes if the feature is a string feature. Only if the feature is a number feature, you may omit the quotes:
[word sp='verb']
[verse chapter=1 and verse=1]
Enumeration types
It is attractive to use eumeration types for the values of a feature, whereever
possible, because then you can query those features in MQL with IN and without
quotes:
[chapter book IN (Genesis, Exodus)]
We will generate enumerations for eligible features.
Integer values can already be queried like this, even if they are not part of an enumeration. So we restrict ourselves to node features with string values. We put the following extra restrictions:
- the number of distinct values is less than 1000
- all values must be legal C names, in practice: starting with a letter,
followed by letters, digits, or
_. The letters can only be plain ASCII letters, uppercase and lowercase.
Features that comply with these restrictions will get an enumeration type. Currently, we provide no ways to configure this in more detail.
Instead of creating separate enumeration types for individual features, we collect all enumerated values for all those features into one big enumeration type.
The reason is that MQL considers equal values in different types as distinct values. If we had separate types, we could never compare values for different features.
There is no place for edge values in
MQL. There is only one concept of feature in MQL: object features,
which are node features.
But TF edges without values can be seen as node features: nodes are
mapped onto sets of nodes to which the edges go. And that notion is supported by
MQL:
edge features are translated into MQL features of type LIST OF id_d,
i.e. lists of object identifiers.
Legal names in MQL
MQL names for databases, object types and features must be valid C identifiers (yes, the computer language C).
The requirements are for names are:
- start with a letter (ASCII, upper-case or lower-case)
- follow by any sequence of ASCII upper/lower-case letters or digits or
underscores (
_) - avoid being a reserved word in the C language
So, we have to change names coming from TF if they are invalid in MQL. We do
that by replacing illegal characters by _, and, if the result does not start
with a letter, we prepend an x. We do not check whether the name is a reserved
C word.
With these provisos:
- the given
dbNamecorrespond to the MQL database name - the TF otypes correspond to the MQL objects
- the TF features correspond to the MQL features
The MQL export is usually quite massive (500 MB for the Hebrew Bible).
It can be compressed greatly, especially by the program bzip2.
Exisiting database
If you try to import an MQL file in Emdros, and there exists already a file or directory with the same name as the MQL database, your import will fail spectacularly. So do not do that.
A good way to prevent clashes:
- export the MQL to outside your
text-fabric-datadirectory, e.g. to~/Downloads; - before importing the MQL file, delete the previous copy;
Delete existing copy:
cd ~/Downloads
rm dataset ; mql -b 3 < dataset.mql
Expand source code Browse git
"""
# MQL
You can interchange with [MQL data](https://emdros.org).
Text-Fabric can read and write MQL dumps.
An MQL dump is a text file, like an SQL dump.
It contains the instructions to create and fill a complete database.
## Correspondence TF and MQL
After exporting a TF dataset to MQL, the resulting MQL database has the
following properties with respect to the TF dataset it comes from:
* the TF *slots* correspond exactly with the MQL *monads* and have the same
numbers; provided the monad numbers in the MQL dump are consecutive. In MQL
this is not obligatory. Even if there gaps in the monads sequence, we will
fill the holes during conversion, so the slots are tightly consecutive;
* the TF *nodes* correspond exactly with the MQL *objects* and have the same
numbers
## Node features in MQL
The values of TF features are of two types, `int` and `str`, and they translate
to corresponding MQL types `integer` and `string`. The actual values do not
undergo any transformation.
That means that in MQL queries, you use quotes if the feature is a string feature.
Only if the feature is a number feature, you may omit the quotes:
```
[word sp='verb']
[verse chapter=1 and verse=1]
```
## Enumeration types
It is attractive to use eumeration types for the values of a feature, whereever
possible, because then you can query those features in MQL with `IN` and without
quotes:
```
[chapter book IN (Genesis, Exodus)]
```
We will generate enumerations for eligible features.
Integer values can already be queried like this, even if they are not part of an
enumeration. So we restrict ourselves to node features with string values. We
put the following extra restrictions:
* the number of distinct values is less than 1000
* all values must be legal C names, in practice: starting with a letter,
followed by letters, digits, or `_`. The letters can only be plain ASCII
letters, uppercase and lowercase.
Features that comply with these restrictions will get an enumeration type.
Currently, we provide no ways to configure this in more detail.
Instead of creating separate enumeration types for individual features,
we collect all enumerated values for all those features into one
big enumeration type.
The reason is that MQL considers equal values in different types as
distinct values. If we had separate types, we could never compare
values for different features.
There is no place for edge values in
MQL. There is only one concept of feature in MQL: object features,
which are node features.
But TF edges without values can be seen as node features: nodes are
mapped onto sets of nodes to which the edges go. And that notion is supported by
MQL:
edge features are translated into MQL features of type `LIST OF id_d`,
i.e. lists of object identifiers.
!!! caution "Legal names in MQL"
MQL names for databases, object types and features must be valid C identifiers
(yes, the computer language C).
The requirements are for names are:
* start with a letter (ASCII, upper-case or lower-case)
* follow by any sequence of ASCII upper/lower-case letters or digits or
underscores (`_`)
* avoid being a reserved word in the C language
So, we have to change names coming from TF if they are invalid in MQL. We do
that by replacing illegal characters by `_`, and, if the result does not start
with a letter, we prepend an `x`. We do not check whether the name is a reserved
C word.
With these provisos:
* the given `dbName` correspond to the MQL *database name*
* the TF *otypes* correspond to the MQL *objects*
* the TF *features* correspond to the MQL *features*
The MQL export is usually quite massive (500 MB for the Hebrew Bible).
It can be compressed greatly, especially by the program `bzip2`.
!!! caution "Exisiting database"
If you try to import an MQL file in Emdros, and there exists already a file or
directory with the same name as the MQL database, your import will fail
spectacularly. So do not do that.
A good way to prevent clashes:
* export the MQL to outside your `text-fabric-data` directory, e.g. to
`~/Downloads`;
* before importing the MQL file, delete the previous copy;
Delete existing copy:
```sh
cd ~/Downloads
rm dataset ; mql -b 3 < dataset.mql
```
"""
import os
import re
from itertools import chain
from ..parameters import WARP, OTYPE, OSLOTS
from ..core.helpers import (
cleanName,
isClean,
specFromRanges,
rangesFromList,
setFromSpec,
nbytes,
console,
normpath,
)
# If a feature, with type string, has less than ENUM_LIMIT values,
# an enumeration type for it will be created
# provided all values of that feature are a valid name for MQL.
ENUM_LIMIT = 1000
ONE_ENUM_TYPE = True
class MQL(object):
def __init__(self, mqlDir, mqlName, tfFeatures, tmObj):
error = tmObj.error
mqlDir = normpath(mqlDir)
self.mqlDir = mqlDir
cleanDb = cleanName(mqlName)
if cleanDb != mqlName:
error(f'db name "{mqlName}" => "{cleanDb}"')
self.mqlName = cleanDb
self.tfFeatures = tfFeatures
self.tmObj = tmObj
self.enums = {}
self._check()
def write(self):
tmObj = self.tmObj
error = tmObj.error
info = tmObj.info
indent = tmObj.indent
if not self.good:
return
if not os.path.exists(self.mqlDir):
try:
os.makedirs(self.mqlDir, exist_ok=True)
except Exception:
error(f'Cannot create directory "{self.mqlDir}"')
self.good = False
return
mqlPath = f"{self.mqlDir}/{self.mqlName}.mql"
try:
fm = open(mqlPath, "w", encoding="utf8")
except Exception:
error(f"Could not write to {mqlPath}")
self.good = False
return
info(f"Loading {len(self.featureList)} features")
for ft in self.featureList:
fObj = self.features[ft]
fObj.load()
self.fm = fm
self._writeStartDb()
self._writeEnums()
self._writeTypes()
self._writeDataAll()
self._writeEndDb()
indent(level=0)
info("Done")
def _check(self):
tmObj = self.tmObj
error = tmObj.error
info = tmObj.info
indent = tmObj.indent
info(f"Checking features of dataset {self.mqlName}")
self.features = {}
self.featureList = []
indent(level=1)
for (f, fo) in sorted(self.tfFeatures.items()):
if fo.method is not None or f in WARP:
continue
fo.load(metaOnly=True)
if fo.isConfig:
continue
cleanF = cleanName(f)
if cleanF != f:
error(f'feature "{f}" => "{cleanF}"')
self.featureList.append(cleanF)
self.features[cleanF] = fo
good = True
for feat in (OTYPE, OSLOTS, "__levels__"):
if feat not in self.tfFeatures:
error(
"{} feature {} is missing from data set".format(
"Warp"
if feat in WARP
else "Computed"
if feat.startswith("__")
else "Data",
feat,
)
)
good = False
else:
fObj = self.tfFeatures[feat]
if not fObj.load():
good = False
indent(level=0)
if not good:
error("Export to MQL aborted")
else:
info(f"{len(self.featureList)} features to export to MQL ...")
self.good = good
def _writeStartDb(self):
self.fm.write(
"""
CREATE DATABASE '{name}'
GO
USE DATABASE '{name}'
GO
""".format(
name=self.mqlName
)
)
def _writeEndDb(self):
self.fm.write(
"""
VACUUM DATABASE ANALYZE
GO
"""
)
self.fm.close()
def _writeEnums(self):
tmObj = self.tmObj
info = tmObj.info
indent = tmObj.indent
indent(level=0)
info("Writing enumerations")
indent(level=1)
for ft in self.featureList:
fObj = self.features[ft]
if fObj.isEdge or fObj.dataType == "int":
continue
fMap = fObj.data
fValues = sorted(set(fMap.values()))
if len(fValues) > ENUM_LIMIT:
continue
eligible = all(isClean(fVal) for fVal in fValues)
if not eligible:
unclean = [fVal for fVal in fValues if not isClean(fVal)]
console(
"\t{:<15}: {:>4} values, {} not a name, e.g. «{}»".format(
ft,
len(fValues),
len(unclean),
unclean[0],
)
)
continue
self.enums[ft] = fValues
if ONE_ENUM_TYPE:
self._writeEnumsAsOne()
else:
for ft in sorted(self.enums):
self._writeEnum(ft)
indent(level=0)
info(f"Written {len(self.enums)} enumerations")
def _writeEnumsAsOne(self):
tmObj = self.tmObj
info = tmObj.info
fValues = sorted(
set(chain.from_iterable((set(fV) for fV in self.enums.values())))
)
if len(fValues):
info(f"Writing an all-in-one enum with {len(fValues):>4} values")
fValuesEnumerated = ",\n\t".join(
"{} = {}".format(fVal, i) for (i, fVal) in enumerate(fValues)
)
self.fm.write(
f"""
CREATE ENUMERATION all_enum = {{
{fValuesEnumerated}
}}
GO
"""
)
def _writeEnum(self, ft):
tmObj = self.tmObj
info = tmObj.info
fValues = self.enums[ft]
if len(fValues):
info(f"enum {ft:<15} with {len(fValues):>4} values")
fValuesEnumerated = ",\n\t".join(
f"{fVal} = {i}" for (i, fVal) in enumerate(fValues)
)
self.fm.write(
f"""
CREATE ENUMERATION {ft}_enum = {{
{fValuesEnumerated}
}}
GO
"""
)
def _writeTypes(self):
def valInt(n):
return str(n)
def valStr(s):
if "'" in s:
return '"{}"'.format(s.replace('"', '\\"'))
else:
return "'{}'".format(s)
def valIds(ids):
return "({})".format(",".join(str(i) for i in ids))
tmObj = self.tmObj
error = tmObj.error
info = tmObj.info
indent = tmObj.indent
self.levels = self.tfFeatures["__levels__"].data[::-1]
indent(level=0)
info(
"Mapping {} features onto {} object types".format(
len(self.featureList),
len(self.levels),
)
)
otypeSupport = {}
for (otype, av, start, end) in self.levels:
cleanOtype = cleanName(otype)
if cleanOtype != otype:
error(f'otype "{otype}" => "{cleanOtype}"')
otypeSupport[cleanOtype] = set(range(start, end + 1))
self.otypes = {}
self.featureTypes = {}
self.featureMethods = {}
for ft in self.featureList:
fObj = self.features[ft]
if fObj.isEdge:
dataType = "LIST OF id_d"
method = valIds
else:
if fObj.dataType == "str":
dataType = 'string DEFAULT ""'
method = valInt if ft in self.enums else valStr
elif fObj.dataType == "int":
dataType = "integer DEFAULT 0"
method = valInt
else:
dataType = 'string DEFAULT ""'
method = valStr
self.featureTypes[ft] = dataType
self.featureMethods[ft] = method
support = set(fObj.data.keys())
for otype in otypeSupport:
if len(support & otypeSupport[otype]):
self.otypes.setdefault(otype, []).append(ft)
for otype in (cleanName(x[0]) for x in self.levels):
self._writeType(otype)
def _writeType(self, otype):
self.fm.write(
f"""
CREATE OBJECT TYPE
[{otype}
"""
)
for ft in self.otypes[otype]:
fType = (
"{}_enum".format("all" if ONE_ENUM_TYPE else ft)
if ft in self.enums
else self.featureTypes[ft]
)
self.fm.write(f" {ft}:{fType};\n")
self.fm.write(
"""
]
GO
"""
)
def _writeDataAll(self):
tmObj = self.tmObj
info = tmObj.info
info(
"Writing {} features as data in {} object types".format(
len(self.featureList),
len(self.levels),
)
)
oslotsData = self.tfFeatures[OSLOTS].data
self.oslots = oslotsData[0]
self.maxSlot = oslotsData[1]
for (otype, av, start, end) in self.levels:
self._writeData(otype, start, end)
def _writeData(self, otype, start, end):
tmObj = self.tmObj
info = tmObj.info
indent = tmObj.indent
fm = self.fm
indent(level=1, reset=True)
info(f"{otype} data ...")
oslots = self.oslots
maxSlot = self.maxSlot
oFeats = self.otypes[otype]
features = self.features
featureMethods = self.featureMethods
fm.write(
"""
DROP INDEXES ON OBJECT TYPE[{o}]
GO
CREATE OBJECTS
WITH OBJECT TYPE[{o}]
""".format(
o=otype
)
)
curSize = 0
LIMIT = 50000
t = 0
j = 0
indent(level=2, reset=True)
for n in range(start, end + 1):
oMql = """
CREATE OBJECT
FROM MONADS= {{ {m} }}
WITH ID_D={i} [
""".format(
m=n
if n <= maxSlot
else specFromRanges(rangesFromList(oslots[n - maxSlot - 1])),
i=n,
)
for ft in oFeats:
method = featureMethods[ft]
fMap = features[ft].data
if n in fMap:
oMql += f"{ft}:={method(fMap[n])};\n"
oMql += """
]
"""
fm.write(oMql)
curSize += len(bytes(oMql, encoding="utf8"))
t += 1
j += 1
if j == LIMIT:
fm.write(
"""
GO
CREATE OBJECTS
WITH OBJECT TYPE[{o}]
""".format(
o=otype
)
)
info(
f"batch of size {nbytes(curSize):>20} with {j:>7} of {t:>7} {otype}s"
)
j = 0
curSize = 0
info(f"batch of size {nbytes(curSize):>20} with {j:>7} of {t:>7} {otype}s")
fm.write(
"""
GO
CREATE INDEXES ON OBJECT TYPE[{o}]
GO
""".format(
o=otype
)
)
indent(level=1)
info("{} data: {} objects".format(otype, t))
# MQL IMPORT
uniscan = re.compile(r"(?:\\x..)+")
def makeuni(match):
"""Make proper unicode of a text that contains byte escape codes
such as backslash xb6
"""
byts = eval('"' + match.group(0) + '"')
return byts.encode("latin1").decode("utf-8")
def uni(line):
return uniscan.sub(makeuni, line)
def tfFromMql(mqlFile, tmObj, slotType=None, otext=None, meta=None):
"""Generate TF from MQL
Parameters
----------
tmObj: object
A `tf.core.timestamp.Timestamp` object
mqlFile, slotType, otype, meta: various
See `tf.core.fabric.Fabric.importMQL
"""
mqlFile = normpath(mqlFile)
error = tmObj.error
if slotType is None:
error("ERROR: no slotType specified")
return (False, {}, {}, {})
(good, objectTypes, tables, edgeF, nodeF) = parseMql(mqlFile, tmObj)
if not good:
return (False, {}, {}, {})
return tfFromData(tmObj, objectTypes, tables, edgeF, nodeF, slotType, otext, meta)
def parseMql(mqlFile, tmObj):
info = tmObj.info
error = tmObj.error
info("Parsing mql source ...")
fh = open(mqlFile, encoding="utf8")
objectTypes = dict()
tables = dict()
edgeF = dict()
nodeF = dict()
curId = None
curEnum = None
curObjectType = None
curTable = None
curObject = None
curValue = None
curFeature = None
seeObjects = False
inObjectTypeFeatures = False
STRING_TYPES = {"ascii", "string"}
enums = dict()
chunkSize = 1000000
inThisChunk = 0
good = True
for (ln, line) in enumerate(fh):
inThisChunk += 1
if inThisChunk == chunkSize:
info(f"\tline {ln + 1:>9}")
inThisChunk = 0
if line.startswith("CREATE OBJECTS WITH OBJECT TYPE") or line.startswith(
"WITH OBJECT TYPE"
):
comps = line.rstrip().rstrip("]").split("[", 1)
curTable = comps[1]
info(f"\t\tobjects in {curTable}")
curObject = None
if curTable not in tables:
tables[curTable] = dict()
seeObjects = True
elif line == "CREATE OBJECT\n":
curObject = None
curObject = dict(feats=dict(), monads=None)
curId = None
seeObjects = True
elif curEnum is not None:
if line.startswith("}"):
curEnum = None
continue
comps = line.strip().rstrip(",").split("=", 1)
comp = comps[0].strip()
words = comp.split()
if words[0] == "DEFAULT":
enums[curEnum]["default"] = uni(words[1])
value = words[1]
else:
value = words[0]
enums[curEnum]["values"].append(value)
elif curObjectType is not None:
if line.startswith("]"):
curObjectType = None
inObjectTypeFeatures = False
continue
if curObjectType is True:
if line.startswith("["):
curObjectType = line.rstrip()[1:]
objectTypes[curObjectType] = dict()
info(f"\t\totype {curObjectType}")
inObjectTypeFeatures = True
continue
if inObjectTypeFeatures:
comps = line.strip().rstrip(";").split(":", 1)
feature = comps[0].strip()
fInfo = comps[1].strip()
fCleanInfo = fInfo.replace("FROM SET", "")
fInfoComps = fCleanInfo.split(" ", 1)
fMQLType = fInfoComps[0]
if len(fInfoComps) == 2:
fDefaultComps = fInfoComps[1].strip().split(" ", 1)
fDefault = fDefaultComps[1] if len(fDefaultComps) > 1 else None
else:
fDefault = None
if fDefault is not None and fMQLType in STRING_TYPES:
fDefault = uni(fDefault[1:-1])
default = enums.get(fMQLType, {}).get("default", fDefault)
ftype = (
"str"
if fMQLType in enums
else "int"
if fMQLType == "integer"
else "str"
if fMQLType in STRING_TYPES
else "int"
if fInfo == "id_d"
else "str"
)
isEdge = fMQLType == "id_d"
if isEdge:
edgeF.setdefault(curObjectType, set()).add(feature)
else:
nodeF.setdefault(curObjectType, set()).add(feature)
objectTypes[curObjectType][feature] = (ftype, default)
info(
"\t\t\tfeature {} ({}) =def= {} : {}".format(
feature, ftype, default, "edge" if isEdge else "node"
)
)
elif seeObjects:
if curObject is not None:
if line.startswith("]"):
objectType = objectTypes[curTable]
for (feature, (ftype, default)) in objectType.items():
if feature not in curObject["feats"] and default is not None:
curObject["feats"][feature] = default
tables[curTable][curId] = curObject
curObject = None
continue
elif line.startswith("["):
name = line.rstrip()[1:]
if len(name):
curTable = name
if curTable not in tables:
tables[curTable] = dict()
elif line.startswith("FROM MONADS"):
monads = (
line.split("=", 1)[1]
.replace("{", "")
.replace("}", "")
.replace(" ", "")
.strip()
)
curObject["monads"] = setFromSpec(monads)
elif line.startswith("WITH ID_D"):
comps = line.replace("[", "").rstrip().split("=", 1)
curId = int(comps[1])
elif line.startswith("GO"):
pass
elif line.strip() == "":
pass
else:
if curValue is not None:
toBeContinued = not line.rstrip().endswith('";')
if toBeContinued:
curValue += line
else:
curValue += line.rstrip().rstrip(";").rstrip('"')
curObject["feats"][curFeature] = uni(curValue)
curValue = None
curFeature = None
continue
if ":=" in line:
(featurePart, valuePart) = line.split("=", 1)
feature = featurePart[0:-1].strip()
valuePart = valuePart.lstrip()
isText = ':="' in line
toBeContinued = isText and not line.rstrip().endswith('";')
if toBeContinued:
# this happens if a feature value
# contains a new line
# we must continue scanning lines
# until we meet the end of the value
curFeature = feature
curValue = valuePart.lstrip('"')
else:
value = valuePart.rstrip().rstrip(";").strip('"')
curObject["feats"][feature] = (
uni(value) if isText else value
)
else:
error(f"ERROR: line {ln}: unrecognized line -->{line}<--")
good = False
break
else:
if line.startswith("CREATE OBJECT"):
curObject = dict(feats=dict(), monads=None)
curId = None
else:
if line.startswith("CREATE ENUMERATION"):
words = line.split()
curEnum = words[2]
enums[curEnum] = dict(default=None, values=[])
info(f"\t\tenum {curEnum}")
elif line.startswith("CREATE OBJECT TYPE"):
curObjectType = True
inObjectTypeFeatures = False
info(f"{ln + 1} lines parsed")
fh.close()
for table in tables:
info(f"{len(tables[table])} objects of type {table}")
if len(tables) == 0:
info("No objects found")
return (good, objectTypes, tables, nodeF, edgeF)
def tfFromData(tmObj, objectTypes, tables, nodeF, edgeF, slotType, otext, meta):
info = tmObj.info
info("Making TF data ...")
NIL = {"nil", "NIL", "Nil"}
tableOrder = [slotType] + [t for t in sorted(tables) if t != slotType]
iddFromMonad = dict()
slotFromMonad = dict()
nodeFromIdd = dict()
iddFromNode = dict()
nodeFeatures = dict()
edgeFeatures = dict()
metaData = dict()
# metadata that ends up in every feature
metaData[""] = meta.get("", {})
distinctFeatures = chain(chain.from_iterable(nodeF.values()), chain.from_iterable(edgeF.values()))
for f in distinctFeatures:
metaInfo = meta.get(f, None)
if metaInfo is not None:
metaData[f] = metaInfo
# the config feature otext
metaData["otext"] = otext
good = True
info("Monad - idd mapping ...")
for idd in tables.get(slotType, {}):
monad = list(tables[slotType][idd]["monads"])[0]
iddFromMonad[monad] = idd
info("Removing holes in the monad sequence")
# we set up a monad - slot mapping
curSlot = 0
otype = dict()
for monad in sorted(iddFromMonad):
curSlot += 1
slotFromMonad[monad] = curSlot
idd = iddFromMonad[monad]
nodeFromIdd[idd] = curSlot
iddFromNode[curSlot] = idd
otype[curSlot] = slotType
maxSlot = curSlot
info(f"maxSlot={maxSlot}")
info("Node mapping and otype ...")
node = maxSlot
for t in tableOrder[1:]:
for idd in sorted(tables[t]):
node += 1
nodeFromIdd[idd] = node
iddFromNode[node] = idd
otype[node] = t
nodeFeatures["otype"] = otype
metaData["otype"] = dict(valueType="str")
info("oslots ...")
oslots = dict()
for t in tableOrder[1:]:
for idd in tables.get(t, {}):
node = nodeFromIdd[idd]
monads = tables[t][idd]["monads"]
oslots[node] = {slotFromMonad[m] for m in monads}
edgeFeatures["oslots"] = oslots
metaData["oslots"] = dict(valueType="str")
info("metadata ...")
for t in nodeF:
for f in nodeF[t]:
ftype = objectTypes[t][f][0]
metaData.setdefault(f, {})["valueType"] = ftype
for t in edgeF:
for f in edgeF[t]:
metaData.setdefault(f, {})["valueType"] = "str"
info("features ...")
chunkSize = 100000
for t in tableOrder:
info(f"\tfeatures from {t}s")
inThisChunk = 0
thisTable = tables.get(t, {})
for (i, idd) in enumerate(thisTable):
inThisChunk += 1
if inThisChunk == chunkSize:
info(f"\t{i + 1:>9} {t}s")
inThisChunk = 0
node = nodeFromIdd[idd]
features = tables[t][idd]["feats"]
for (f, v) in features.items():
isEdge = f in edgeF.get(t, set())
if isEdge:
if v not in NIL:
edgeFeatures.setdefault(f, {}).setdefault(node, set()).add(
nodeFromIdd[int(v)]
)
else:
nodeFeatures.setdefault(f, {})[node] = v
info(f"\t{len(thisTable):>9} {t}s")
return (good, nodeFeatures, edgeFeatures, metaData)Functions
def makeuni(match)-
Make proper unicode of a text that contains byte escape codes such as backslash xb6
Expand source code Browse git
def makeuni(match): """Make proper unicode of a text that contains byte escape codes such as backslash xb6 """ byts = eval('"' + match.group(0) + '"') return byts.encode("latin1").decode("utf-8") def parseMql(mqlFile, tmObj)-
Expand source code Browse git
def parseMql(mqlFile, tmObj): info = tmObj.info error = tmObj.error info("Parsing mql source ...") fh = open(mqlFile, encoding="utf8") objectTypes = dict() tables = dict() edgeF = dict() nodeF = dict() curId = None curEnum = None curObjectType = None curTable = None curObject = None curValue = None curFeature = None seeObjects = False inObjectTypeFeatures = False STRING_TYPES = {"ascii", "string"} enums = dict() chunkSize = 1000000 inThisChunk = 0 good = True for (ln, line) in enumerate(fh): inThisChunk += 1 if inThisChunk == chunkSize: info(f"\tline {ln + 1:>9}") inThisChunk = 0 if line.startswith("CREATE OBJECTS WITH OBJECT TYPE") or line.startswith( "WITH OBJECT TYPE" ): comps = line.rstrip().rstrip("]").split("[", 1) curTable = comps[1] info(f"\t\tobjects in {curTable}") curObject = None if curTable not in tables: tables[curTable] = dict() seeObjects = True elif line == "CREATE OBJECT\n": curObject = None curObject = dict(feats=dict(), monads=None) curId = None seeObjects = True elif curEnum is not None: if line.startswith("}"): curEnum = None continue comps = line.strip().rstrip(",").split("=", 1) comp = comps[0].strip() words = comp.split() if words[0] == "DEFAULT": enums[curEnum]["default"] = uni(words[1]) value = words[1] else: value = words[0] enums[curEnum]["values"].append(value) elif curObjectType is not None: if line.startswith("]"): curObjectType = None inObjectTypeFeatures = False continue if curObjectType is True: if line.startswith("["): curObjectType = line.rstrip()[1:] objectTypes[curObjectType] = dict() info(f"\t\totype {curObjectType}") inObjectTypeFeatures = True continue if inObjectTypeFeatures: comps = line.strip().rstrip(";").split(":", 1) feature = comps[0].strip() fInfo = comps[1].strip() fCleanInfo = fInfo.replace("FROM SET", "") fInfoComps = fCleanInfo.split(" ", 1) fMQLType = fInfoComps[0] if len(fInfoComps) == 2: fDefaultComps = fInfoComps[1].strip().split(" ", 1) fDefault = fDefaultComps[1] if len(fDefaultComps) > 1 else None else: fDefault = None if fDefault is not None and fMQLType in STRING_TYPES: fDefault = uni(fDefault[1:-1]) default = enums.get(fMQLType, {}).get("default", fDefault) ftype = ( "str" if fMQLType in enums else "int" if fMQLType == "integer" else "str" if fMQLType in STRING_TYPES else "int" if fInfo == "id_d" else "str" ) isEdge = fMQLType == "id_d" if isEdge: edgeF.setdefault(curObjectType, set()).add(feature) else: nodeF.setdefault(curObjectType, set()).add(feature) objectTypes[curObjectType][feature] = (ftype, default) info( "\t\t\tfeature {} ({}) =def= {} : {}".format( feature, ftype, default, "edge" if isEdge else "node" ) ) elif seeObjects: if curObject is not None: if line.startswith("]"): objectType = objectTypes[curTable] for (feature, (ftype, default)) in objectType.items(): if feature not in curObject["feats"] and default is not None: curObject["feats"][feature] = default tables[curTable][curId] = curObject curObject = None continue elif line.startswith("["): name = line.rstrip()[1:] if len(name): curTable = name if curTable not in tables: tables[curTable] = dict() elif line.startswith("FROM MONADS"): monads = ( line.split("=", 1)[1] .replace("{", "") .replace("}", "") .replace(" ", "") .strip() ) curObject["monads"] = setFromSpec(monads) elif line.startswith("WITH ID_D"): comps = line.replace("[", "").rstrip().split("=", 1) curId = int(comps[1]) elif line.startswith("GO"): pass elif line.strip() == "": pass else: if curValue is not None: toBeContinued = not line.rstrip().endswith('";') if toBeContinued: curValue += line else: curValue += line.rstrip().rstrip(";").rstrip('"') curObject["feats"][curFeature] = uni(curValue) curValue = None curFeature = None continue if ":=" in line: (featurePart, valuePart) = line.split("=", 1) feature = featurePart[0:-1].strip() valuePart = valuePart.lstrip() isText = ':="' in line toBeContinued = isText and not line.rstrip().endswith('";') if toBeContinued: # this happens if a feature value # contains a new line # we must continue scanning lines # until we meet the end of the value curFeature = feature curValue = valuePart.lstrip('"') else: value = valuePart.rstrip().rstrip(";").strip('"') curObject["feats"][feature] = ( uni(value) if isText else value ) else: error(f"ERROR: line {ln}: unrecognized line -->{line}<--") good = False break else: if line.startswith("CREATE OBJECT"): curObject = dict(feats=dict(), monads=None) curId = None else: if line.startswith("CREATE ENUMERATION"): words = line.split() curEnum = words[2] enums[curEnum] = dict(default=None, values=[]) info(f"\t\tenum {curEnum}") elif line.startswith("CREATE OBJECT TYPE"): curObjectType = True inObjectTypeFeatures = False info(f"{ln + 1} lines parsed") fh.close() for table in tables: info(f"{len(tables[table])} objects of type {table}") if len(tables) == 0: info("No objects found") return (good, objectTypes, tables, nodeF, edgeF) def tfFromData(tmObj, objectTypes, tables, nodeF, edgeF, slotType, otext, meta)-
Expand source code Browse git
def tfFromData(tmObj, objectTypes, tables, nodeF, edgeF, slotType, otext, meta): info = tmObj.info info("Making TF data ...") NIL = {"nil", "NIL", "Nil"} tableOrder = [slotType] + [t for t in sorted(tables) if t != slotType] iddFromMonad = dict() slotFromMonad = dict() nodeFromIdd = dict() iddFromNode = dict() nodeFeatures = dict() edgeFeatures = dict() metaData = dict() # metadata that ends up in every feature metaData[""] = meta.get("", {}) distinctFeatures = chain(chain.from_iterable(nodeF.values()), chain.from_iterable(edgeF.values())) for f in distinctFeatures: metaInfo = meta.get(f, None) if metaInfo is not None: metaData[f] = metaInfo # the config feature otext metaData["otext"] = otext good = True info("Monad - idd mapping ...") for idd in tables.get(slotType, {}): monad = list(tables[slotType][idd]["monads"])[0] iddFromMonad[monad] = idd info("Removing holes in the monad sequence") # we set up a monad - slot mapping curSlot = 0 otype = dict() for monad in sorted(iddFromMonad): curSlot += 1 slotFromMonad[monad] = curSlot idd = iddFromMonad[monad] nodeFromIdd[idd] = curSlot iddFromNode[curSlot] = idd otype[curSlot] = slotType maxSlot = curSlot info(f"maxSlot={maxSlot}") info("Node mapping and otype ...") node = maxSlot for t in tableOrder[1:]: for idd in sorted(tables[t]): node += 1 nodeFromIdd[idd] = node iddFromNode[node] = idd otype[node] = t nodeFeatures["otype"] = otype metaData["otype"] = dict(valueType="str") info("oslots ...") oslots = dict() for t in tableOrder[1:]: for idd in tables.get(t, {}): node = nodeFromIdd[idd] monads = tables[t][idd]["monads"] oslots[node] = {slotFromMonad[m] for m in monads} edgeFeatures["oslots"] = oslots metaData["oslots"] = dict(valueType="str") info("metadata ...") for t in nodeF: for f in nodeF[t]: ftype = objectTypes[t][f][0] metaData.setdefault(f, {})["valueType"] = ftype for t in edgeF: for f in edgeF[t]: metaData.setdefault(f, {})["valueType"] = "str" info("features ...") chunkSize = 100000 for t in tableOrder: info(f"\tfeatures from {t}s") inThisChunk = 0 thisTable = tables.get(t, {}) for (i, idd) in enumerate(thisTable): inThisChunk += 1 if inThisChunk == chunkSize: info(f"\t{i + 1:>9} {t}s") inThisChunk = 0 node = nodeFromIdd[idd] features = tables[t][idd]["feats"] for (f, v) in features.items(): isEdge = f in edgeF.get(t, set()) if isEdge: if v not in NIL: edgeFeatures.setdefault(f, {}).setdefault(node, set()).add( nodeFromIdd[int(v)] ) else: nodeFeatures.setdefault(f, {})[node] = v info(f"\t{len(thisTable):>9} {t}s") return (good, nodeFeatures, edgeFeatures, metaData) def tfFromMql(mqlFile, tmObj, slotType=None, otext=None, meta=None)-
Generate TF from MQL
Parameters
tmObj:object- A
Timestampobject mqlFile,slotType,otype,meta:various- See `tf.core.fabric.Fabric.importMQL
Expand source code Browse git
def tfFromMql(mqlFile, tmObj, slotType=None, otext=None, meta=None): """Generate TF from MQL Parameters ---------- tmObj: object A `tf.core.timestamp.Timestamp` object mqlFile, slotType, otype, meta: various See `tf.core.fabric.Fabric.importMQL """ mqlFile = normpath(mqlFile) error = tmObj.error if slotType is None: error("ERROR: no slotType specified") return (False, {}, {}, {}) (good, objectTypes, tables, edgeF, nodeF) = parseMql(mqlFile, tmObj) if not good: return (False, {}, {}, {}) return tfFromData(tmObj, objectTypes, tables, edgeF, nodeF, slotType, otext, meta) def uni(line)-
Expand source code Browse git
def uni(line): return uniscan.sub(makeuni, line)
Classes
class MQL (mqlDir, mqlName, tfFeatures, tmObj)-
Expand source code Browse git
class MQL(object): def __init__(self, mqlDir, mqlName, tfFeatures, tmObj): error = tmObj.error mqlDir = normpath(mqlDir) self.mqlDir = mqlDir cleanDb = cleanName(mqlName) if cleanDb != mqlName: error(f'db name "{mqlName}" => "{cleanDb}"') self.mqlName = cleanDb self.tfFeatures = tfFeatures self.tmObj = tmObj self.enums = {} self._check() def write(self): tmObj = self.tmObj error = tmObj.error info = tmObj.info indent = tmObj.indent if not self.good: return if not os.path.exists(self.mqlDir): try: os.makedirs(self.mqlDir, exist_ok=True) except Exception: error(f'Cannot create directory "{self.mqlDir}"') self.good = False return mqlPath = f"{self.mqlDir}/{self.mqlName}.mql" try: fm = open(mqlPath, "w", encoding="utf8") except Exception: error(f"Could not write to {mqlPath}") self.good = False return info(f"Loading {len(self.featureList)} features") for ft in self.featureList: fObj = self.features[ft] fObj.load() self.fm = fm self._writeStartDb() self._writeEnums() self._writeTypes() self._writeDataAll() self._writeEndDb() indent(level=0) info("Done") def _check(self): tmObj = self.tmObj error = tmObj.error info = tmObj.info indent = tmObj.indent info(f"Checking features of dataset {self.mqlName}") self.features = {} self.featureList = [] indent(level=1) for (f, fo) in sorted(self.tfFeatures.items()): if fo.method is not None or f in WARP: continue fo.load(metaOnly=True) if fo.isConfig: continue cleanF = cleanName(f) if cleanF != f: error(f'feature "{f}" => "{cleanF}"') self.featureList.append(cleanF) self.features[cleanF] = fo good = True for feat in (OTYPE, OSLOTS, "__levels__"): if feat not in self.tfFeatures: error( "{} feature {} is missing from data set".format( "Warp" if feat in WARP else "Computed" if feat.startswith("__") else "Data", feat, ) ) good = False else: fObj = self.tfFeatures[feat] if not fObj.load(): good = False indent(level=0) if not good: error("Export to MQL aborted") else: info(f"{len(self.featureList)} features to export to MQL ...") self.good = good def _writeStartDb(self): self.fm.write( """ CREATE DATABASE '{name}' GO USE DATABASE '{name}' GO """.format( name=self.mqlName ) ) def _writeEndDb(self): self.fm.write( """ VACUUM DATABASE ANALYZE GO """ ) self.fm.close() def _writeEnums(self): tmObj = self.tmObj info = tmObj.info indent = tmObj.indent indent(level=0) info("Writing enumerations") indent(level=1) for ft in self.featureList: fObj = self.features[ft] if fObj.isEdge or fObj.dataType == "int": continue fMap = fObj.data fValues = sorted(set(fMap.values())) if len(fValues) > ENUM_LIMIT: continue eligible = all(isClean(fVal) for fVal in fValues) if not eligible: unclean = [fVal for fVal in fValues if not isClean(fVal)] console( "\t{:<15}: {:>4} values, {} not a name, e.g. «{}»".format( ft, len(fValues), len(unclean), unclean[0], ) ) continue self.enums[ft] = fValues if ONE_ENUM_TYPE: self._writeEnumsAsOne() else: for ft in sorted(self.enums): self._writeEnum(ft) indent(level=0) info(f"Written {len(self.enums)} enumerations") def _writeEnumsAsOne(self): tmObj = self.tmObj info = tmObj.info fValues = sorted( set(chain.from_iterable((set(fV) for fV in self.enums.values()))) ) if len(fValues): info(f"Writing an all-in-one enum with {len(fValues):>4} values") fValuesEnumerated = ",\n\t".join( "{} = {}".format(fVal, i) for (i, fVal) in enumerate(fValues) ) self.fm.write( f""" CREATE ENUMERATION all_enum = {{ {fValuesEnumerated} }} GO """ ) def _writeEnum(self, ft): tmObj = self.tmObj info = tmObj.info fValues = self.enums[ft] if len(fValues): info(f"enum {ft:<15} with {len(fValues):>4} values") fValuesEnumerated = ",\n\t".join( f"{fVal} = {i}" for (i, fVal) in enumerate(fValues) ) self.fm.write( f""" CREATE ENUMERATION {ft}_enum = {{ {fValuesEnumerated} }} GO """ ) def _writeTypes(self): def valInt(n): return str(n) def valStr(s): if "'" in s: return '"{}"'.format(s.replace('"', '\\"')) else: return "'{}'".format(s) def valIds(ids): return "({})".format(",".join(str(i) for i in ids)) tmObj = self.tmObj error = tmObj.error info = tmObj.info indent = tmObj.indent self.levels = self.tfFeatures["__levels__"].data[::-1] indent(level=0) info( "Mapping {} features onto {} object types".format( len(self.featureList), len(self.levels), ) ) otypeSupport = {} for (otype, av, start, end) in self.levels: cleanOtype = cleanName(otype) if cleanOtype != otype: error(f'otype "{otype}" => "{cleanOtype}"') otypeSupport[cleanOtype] = set(range(start, end + 1)) self.otypes = {} self.featureTypes = {} self.featureMethods = {} for ft in self.featureList: fObj = self.features[ft] if fObj.isEdge: dataType = "LIST OF id_d" method = valIds else: if fObj.dataType == "str": dataType = 'string DEFAULT ""' method = valInt if ft in self.enums else valStr elif fObj.dataType == "int": dataType = "integer DEFAULT 0" method = valInt else: dataType = 'string DEFAULT ""' method = valStr self.featureTypes[ft] = dataType self.featureMethods[ft] = method support = set(fObj.data.keys()) for otype in otypeSupport: if len(support & otypeSupport[otype]): self.otypes.setdefault(otype, []).append(ft) for otype in (cleanName(x[0]) for x in self.levels): self._writeType(otype) def _writeType(self, otype): self.fm.write( f""" CREATE OBJECT TYPE [{otype} """ ) for ft in self.otypes[otype]: fType = ( "{}_enum".format("all" if ONE_ENUM_TYPE else ft) if ft in self.enums else self.featureTypes[ft] ) self.fm.write(f" {ft}:{fType};\n") self.fm.write( """ ] GO """ ) def _writeDataAll(self): tmObj = self.tmObj info = tmObj.info info( "Writing {} features as data in {} object types".format( len(self.featureList), len(self.levels), ) ) oslotsData = self.tfFeatures[OSLOTS].data self.oslots = oslotsData[0] self.maxSlot = oslotsData[1] for (otype, av, start, end) in self.levels: self._writeData(otype, start, end) def _writeData(self, otype, start, end): tmObj = self.tmObj info = tmObj.info indent = tmObj.indent fm = self.fm indent(level=1, reset=True) info(f"{otype} data ...") oslots = self.oslots maxSlot = self.maxSlot oFeats = self.otypes[otype] features = self.features featureMethods = self.featureMethods fm.write( """ DROP INDEXES ON OBJECT TYPE[{o}] GO CREATE OBJECTS WITH OBJECT TYPE[{o}] """.format( o=otype ) ) curSize = 0 LIMIT = 50000 t = 0 j = 0 indent(level=2, reset=True) for n in range(start, end + 1): oMql = """ CREATE OBJECT FROM MONADS= {{ {m} }} WITH ID_D={i} [ """.format( m=n if n <= maxSlot else specFromRanges(rangesFromList(oslots[n - maxSlot - 1])), i=n, ) for ft in oFeats: method = featureMethods[ft] fMap = features[ft].data if n in fMap: oMql += f"{ft}:={method(fMap[n])};\n" oMql += """ ] """ fm.write(oMql) curSize += len(bytes(oMql, encoding="utf8")) t += 1 j += 1 if j == LIMIT: fm.write( """ GO CREATE OBJECTS WITH OBJECT TYPE[{o}] """.format( o=otype ) ) info( f"batch of size {nbytes(curSize):>20} with {j:>7} of {t:>7} {otype}s" ) j = 0 curSize = 0 info(f"batch of size {nbytes(curSize):>20} with {j:>7} of {t:>7} {otype}s") fm.write( """ GO CREATE INDEXES ON OBJECT TYPE[{o}] GO """.format( o=otype ) ) indent(level=1) info("{} data: {} objects".format(otype, t))Methods
def write(self)-
Expand source code Browse git
def write(self): tmObj = self.tmObj error = tmObj.error info = tmObj.info indent = tmObj.indent if not self.good: return if not os.path.exists(self.mqlDir): try: os.makedirs(self.mqlDir, exist_ok=True) except Exception: error(f'Cannot create directory "{self.mqlDir}"') self.good = False return mqlPath = f"{self.mqlDir}/{self.mqlName}.mql" try: fm = open(mqlPath, "w", encoding="utf8") except Exception: error(f"Could not write to {mqlPath}") self.good = False return info(f"Loading {len(self.featureList)} features") for ft in self.featureList: fObj = self.features[ft] fObj.load() self.fm = fm self._writeStartDb() self._writeEnums() self._writeTypes() self._writeDataAll() self._writeEndDb() indent(level=0) info("Done")