modify.py
"""
# Modify
## Usage
```python
from tf.dataset import modify
modify(
location,
targetLocation,
mergeFeatures=None,
deleteFeatures=None,
addFeatures=None,
mergeTypes=None,
deleteTypes=None,
addTypes=None,
featureMeta=None,
silent=False,
)
```
"""
import collections
from ..fabric import Fabric
from ..parameters import WARP, OTYPE, OSLOTS, OTEXT
from ..core.timestamp import Timestamp
from ..core.helpers import itemize, fitemize, isInt, collectFormats, dirEmpty
VALTP = "valueType"
GENERATED = set(
"""
writtenBy
dateWritten
version
""".strip().split()
)
NODE = "node"
NODES = "nodes"
EDGE = "edge"
EDGES = "edges"
NFS = "nodeFeatures"
EFS = "edgeFeatures"
ADD_F_KEYS = {NFS, EFS}
NF = "nodeFrom"
NT = "nodeTo"
NS = "nodeSlots"
ADD_T_KEYS = {NF, NT, NS, NFS, EFS}
SE_TP = "sectionTypes"
SE_FT = "sectionFeatures"
ST_TP = "structureTypes"
ST_FT = "structureFeatures"
TM = Timestamp()
indent = TM.indent
info = TM.info
error = TM.error
isSilent = TM.isSilent
setSilent = TM.setSilent
def _rep(iterable):
return ", ".join(sorted(iterable))
def modify(
location,
targetLocation,
mergeFeatures=None,
deleteFeatures=None,
addFeatures=None,
mergeTypes=None,
deleteTypes=None,
addTypes=None,
featureMeta=None,
silent=False,
):
"""Modifies the supply of node types and features in a single data set.
Dependent on the presence of the parameters, the following steps will be
executed before the result is written out as a new TF dataset:
* merge existing features into an other feature, removing the features
that went in;
* delete any number of existing features;
* add any number of features and their data;
* merge existing node types into a new one, removing the
types that went in, without loss of nodes;
So far, no new nodes have been added or removed. But then:
* delete any number of node types with their nodes;
* add any number of new node types, with nodes and features.
The last two actions lead to a shifting of nodes, and all features that map
them, will be shifted accordingly.
You can also pass meta data to be merged in.
Finally, the resulting features will be written to disk.
!!! hint "Only added/merged features"
It is possible to output only the added and merged features instead
of a complete dataset. Just pass the boolean value `True` to `deleteFeatures`
below.
Parameters
----------
location: string
You can pass just the location of the original dataset in the file system,
i.e. the directory that contains the .tf files.
targetLocation: string
The directory into which the result dataset will be written.
mergeFeatures: dict, optional `None`
You can merge several features into one. This is especially useful if there
are many features each operating on different node types, and you want to
unify them into one feature.
The situation may occur that several of the features to be merged supply
conflicting values for a node. Then the last feature in the merge list wins.
The result feature may exist already. Also then there is a risk of conflict.
Again, the merge result wins.
Example
-------
mergeFeatures=dict(
resultFeature1=[feat1, feat2],
resultFeature2="feat3, feat4",
),
If the resulting feature is new, or needs a new description, you can
provide metadata in the `featureMeta` argument.
For new features you may want to set the `valueType`, although we try
hard to deduce it from the data available.
deleteFeatures: boolean | string | iterable, optional `None`
This should be either a boolean value `True` or an iterable or space/comma
separated string of features that you want to delete from the result.
`True` means: all features will be deleted that are not the result of merging
or adding features (see `mergeFeatures` above and `addFeatures` below.
addFeatures: dict, optional `None`
You can add as many features as you want, assigning values to all types,
including new nodes of new types that have been generated in the steps before.
You can also use this parameter to override existing features:
if a feature that you are adding already exists, the new data will be merged
in, overriding assignments of the existing feature if there is a conflict.
The meta data of the old and new feature will also be merged.
This parameter must have this shape:
Example
-------
addFeatures=dict(
nodeFeatures=dict(
feat1=data1,
feat2=data2,
),
edgeFeatures=dict(
feat3=data3,
feat4=data4,
),
If the resulting features are new, or need a new description, you can
provide metadata in the `featureMeta` argument.
For new features you may want to set the `valueType`, although we try
hard to deduce it from the data available.
mergeTypes: dict, optional `None`
You can merge several node types into one.
The merged node type will have the union of nodes of the types that are merged.
All relevant features will stay the same, except the `otype` feature of course.
You can pass additional information to be added as features to nodes
of the new node type.
These features can be used to discriminate between the merged types.
This parameter must have this shape:
Example
-------
mergeTypes=dict(
outTypeA=(
'inType1',
'inType2',
),
outTypeB="inType3, inType4",
)
Example
-------
mergeTypes=dict(
outTypeA=dict(
inType1=dict(
featureI=valueI,
featureK=valueK,
),
inType2=dict(
featureL=valueL,
featureM=valueM,
),
),
outTypeB=dict(
inType3=dict(
featureN=valueN,
featureO=valueO,
),
inType4=dict(
featureP=valueP,
featureQ=valueQ,
),
),
)
It does not matter if these types and features already occur.
The outTypes may be existing types of really new types.
The new features may be existing or new features.
Do not forget to provide meta data for new features in the `featureMeta` argument.
This will migrate nodes of type `inType1` or `inType2` to nodes of `outTypeA`.
In the extended form, when there are feature specifications associated
with the old types, after merging the following assignments will be made:
`featureI = valueI` to nodes coming from `inType1`
and
`featureK = valueK` to nodes coming from `inType2`.
No nodes will be removed!
!!! caution "slot types"
Merging is all about non-slot types.
It is an error if a new type or an old type is a slot type.
deleteTypes: string | iterable, optional `None`
You can delete node types from the result altogether.
You can specify a list of node types as an iterable or as a space
separated string.
If a node type has to be deleted, all nodes in that type
will be removed, and features that assign values to these nodes will have
those assignments removed.
Example
-------
deleteTypes=('line', 'sentence')
Example
-------
deleteTypes="line sentence"
!!! caution "slot types"
Deleting is all about non-slot types.
It is an error to attempt to delete slot type.
addTypes: dict, optional `None`
You may add as many node types as you want.
Per node type that you add, you need to specify the current boundaries of
that type and how all those nodes map to slots.
You can also add features that assign values to those nodes:
Example
-------
dict(
nodeType1=dict(
nodeFrom=from1,
nodeTo=to1,
nodeSlots=slots1,
nodeFeatures=nFeatures1,
edgeFeatures=eFeatures1,
),
nodeType2=dict(
nodeFrom=from2,
nodeTo=to2,
nodeSlots=slots2,
nodeFeatures=nFeatures2,
edgeFeatures=eFeatures2,
),
),
The boundaries may be completely arbitrary, so if you get your nodes from another
TF data source, you do not need to align their values.
If you also add features about those nodes, the only thing that matters is
that the features assign the right values to the nodes within the boundaries.
Assignments to nodes outside the boundaries will be ignored.
The slots that you link the new nodes to, must exist in the original.
You cannot use this function to add slots to your data set.
!!! caution "existing node types"
It is an error if a new node type already exists in the original.
!!! info "nodeFeatures, edgeFeatures"
You can add any number of features.
Per feature you have to provide the mapping that defines the feature.
These features may be new,
or they may already be present in the original data.
If these features have values to nodes that are not within the boundaries
of the new node type,
those values will not be assigned but silently discarded.
Example
-------
dict(
feat1=dict(
n1=val1,
n2=val2,
),
feat2=dict(
n1=val1,
n2=val2,
),
),
Edge features without values are specified like this:
Example
-------
dict(
feat1=dict(
n1={m1, m2},
n2={m3, m4},
),
feat2=dict(
n1={m5, m6},
n2={m7, m8},
),
),
Edge features with values are specified like this:
Example
-------
dict(
feat1=dict(
n1={m1: v1, m2: v2},
n2={m3: v3, m4: v4},
),
feat2=dict(
n1={m5: v5, m6: v6},
n2={m7: v7, m8: v8},
),
),
featureMeta: dict, optional `None`
If the features you have specified in one of the paramers above are new,
do not forget to pass metadata for them in this parameter
It is especially important to state the value type:
Example
-------
featureMeta=dict(
featureI=dict(
valueType='int',
description='level of node'
),
featureK=dict(
valueType='str',
description='subtype of node'
),
),
You can also tweak the section/structure configuration and the
text-formats that are specified in the `otext` feature.
Just specify them as keys and values to the `otext` feature.
The logic of tweaking meta data is this: what you provide in this
parameter will be merged into existing meta data.
If you want to remove a key from a feature, give it the value None.
silent: boolean, optional `False`
Suppress or enable informational messages.
"""
addFeatures = addFeatures or {}
onlyDeliverUpdatedFeatures = False
if type(deleteFeatures) is bool and deleteFeatures:
deleteFeatures = set()
onlyDeliverUpdatedFeatures = True
deleteFeatures = set(fitemize(deleteFeatures))
mergeFeatures = mergeFeatures or {}
addTypes = addTypes or {}
deleteTypes = set(fitemize(deleteTypes))
mergeTypes = mergeTypes or {}
featureMeta = featureMeta or {}
origMaxNode = None
origNodeTypes = None
origNodeFeatures = None
origEdgeFeatures = None
origFeatures = None
shift = {}
shiftNeeded = False
slotType = None
maxNode = None
nodeFeatures = {}
edgeFeatures = {}
deletedTypes = set()
deletedFeatures = set()
nodeTypes = {}
nodeFeaturesOut = {}
edgeFeaturesOut = {}
metaDataOut = {}
api = None
good = True
ePrefix = ""
eItem = ""
def err(msg):
nonlocal good
error(f"{ePrefix}{eItem}{msg}", tm=False)
good = False
def inf(msg):
info(f"{ePrefix}{eItem}{msg}", tm=False)
def meta(feat):
return api.TF.features[feat].metaData
def valTp(feat):
return meta(feat).get(VALTP, None)
def otextInfo():
orig = meta(OTEXT)
custom = featureMeta.get(OTEXT, {})
combi = {}
for key in set(custom) | set(orig):
origVal = orig.get(key, "")
customVal = custom.get(key, "")
combi[key] = customVal or origVal
ensureTypes = set()
ensureFeatures = set()
for kind in (SE_TP, ST_TP):
ensureTypes |= set(itemize(combi.get(kind, ""), sep=","))
for kind in (SE_FT, ST_FT):
ensureFeatures |= set(itemize(combi.get(kind, ""), sep=","))
ensureFeatures |= set(collectFormats(combi)[1])
return (ensureTypes, ensureFeatures)
def allInt(values):
return all(isInt(v) for v in values)
def prepare():
nonlocal api
nonlocal origNodeTypes
nonlocal origFeatures
nonlocal origNodeFeatures
nonlocal origEdgeFeatures
nonlocal origMaxNode
nonlocal maxNode
nonlocal shift
nonlocal ePrefix
nonlocal eItem
indent(level=0, reset=True)
info("preparing and checking ...")
indent(level=1, reset=True)
TF = Fabric(locations=location, silent=silent)
origAllFeatures = TF.explore(silent=silent or True, show=True)
origNodeFeatures = set(origAllFeatures[NODES])
origEdgeFeatures = set(origAllFeatures[EDGES])
origFeatures = origNodeFeatures | origEdgeFeatures
api = TF.load("", silent=silent)
if not api:
return False
F = api.F
C = api.C
origNodeTypes = {x[0]: (x[2], x[3]) for x in C.levels.data}
origMaxSlot = F.otype.maxSlot
origMaxNode = F.otype.maxNode
maxNode = origMaxNode
addedTp = set()
addedFt = set()
deletedTp = set()
deletedFt = set()
# check mergeFeatures
ePrefix = "Merge features: "
for (outFeat, inFeats) in mergeFeatures.items():
eItem = f"{outFeat}: "
inFeats = fitemize(inFeats)
if outFeat in WARP:
err("Can not merge into standard features")
continue
if not inFeats:
err("Nothing to merge from")
continue
addedFt.add(outFeat)
for inFeat in inFeats:
if inFeat in WARP:
err(f"Can not merge from standard features: {inFeat}")
continue
deletedFt.add(inFeat)
missingIn = set(f for f in inFeats if f not in origFeatures)
if missingIn:
err(f"Missing features {_rep(missingIn)}")
allInIsNode = all(f in origNodeFeatures for f in inFeats)
allInIsEdge = all(f in origEdgeFeatures for f in inFeats)
outExists = outFeat in origFeatures
outIsNode = outExists and outFeat in origNodeFeatures
outIsEdge = outExists and outFeat in origEdgeFeatures
if outIsNode and not allInIsNode:
err("Node Feature can not be merged from an edge feature")
if outIsEdge and not allInIsEdge:
err("Edge Feature can not be merged from a node feature")
if not allInIsNode and not allInIsEdge:
err("Feature can not be merged from both node and edge features")
allInIsInt = all(valTp(f) == "int" for f in inFeats)
correctTp = "int" if allInIsInt else "str"
checkValType(outFeat, correctTp=correctTp)
# check deleteFeatures
ePrefix = "Delete features: "
for feat in deleteFeatures:
eItem = f"{feat}: "
if feat in WARP:
err("Can not delete standard features")
continue
if feat not in origFeatures:
err("Not in data set")
deletedFt.add(feat)
# check addFeatures
ePrefix = "Add features: "
eItem = ""
illegalKeys = set(addFeatures) - ADD_F_KEYS
if illegalKeys:
err(f"{_rep(illegalKeys)} unrecognized, expected {_rep(ADD_F_KEYS)}")
bothFeatures = set(addFeatures.get(NFS, {})) & set(addFeatures.get(EFS, {}))
if bothFeatures:
err(f"{_rep(bothFeatures)}: Both node and edge features")
for (kind, otherKind, origSet, origSetOther) in (
(NODE, EDGE, origNodeFeatures, origEdgeFeatures),
(EDGE, NODE, origEdgeFeatures, origNodeFeatures),
):
for (feat, data) in addFeatures.get(f"{kind}Features", {}).items():
eItem = f"{feat}: "
if feat in WARP:
err("Cannot add standard features")
continue
if feat in origSetOther:
err(f"{kind} feature already exists as {otherKind} feature")
checkValType(feat, vals=data.values())
addedFt.add(feat)
# check mergeTypes
ePrefix = "Merge types: "
mData = {}
for (outType, inTypes) in mergeTypes.items():
eItem = f"{outType}: "
if outType == slotType:
err("Result cannot be the slot type")
withFeatures = type(inTypes) is dict
addedTp.add(outType)
for inType in inTypes:
if inType == slotType:
err(f"Slot type {inType} is not mergeable")
continue
if inType not in origNodeTypes:
err(f"Cannot merge non-existing node type {inType}")
continue
deletedTp.add(inType)
mFeatures = inTypes[inType] if withFeatures else {}
for (feat, val) in mFeatures.items():
mData.setdefault(feat, set()).add(val)
addedFt.add(feat)
for (feat, vals) in mData.items():
eItem = f"{feat}: "
checkValType(feat, vals=vals)
# check deleteTypes
ePrefix = "Delete types: "
for nodeType in deleteTypes:
eItem = f"{nodeType}: "
if nodeType not in origNodeTypes:
err("Not in data set")
continue
deletedTp.add(nodeType)
# check addTypes
ePrefix = "Add types: "
for (nodeType, typeInfo) in sorted(addTypes.items()):
eItem = f"{nodeType}: "
illegalKeys = set(typeInfo) - ADD_T_KEYS
if illegalKeys:
err(f"{_rep(illegalKeys)} unrecognized, expected {_rep(ADD_T_KEYS)}")
continue
if nodeType in origNodeTypes:
err("Already occurs")
continue
addedTp.add(nodeType)
nodeSlots = typeInfo.get(NS, {})
if not nodeSlots:
err("No slot information given")
nF = typeInfo.get(NF, None)
if not nF:
err("No lower bound given")
nT = typeInfo.get(NT, None)
if not nT:
err("No upper bound given")
if nF is not None and nT is not None:
unlinked = 0
badlinked = 0
for n in range(nF, nT + 1):
slots = nodeSlots.get(n, ())
if not slots:
unlinked += 1
else:
slotGood = True
for slot in slots:
if slot < 1 or slot > origMaxSlot:
slotGood = False
if not slotGood:
badlinked += 1
if unlinked:
err(f"{unlinked} nodes not linked to slots")
if badlinked:
err(f"{badlinked} nodes linked to non-slot nodes")
for kind in (NODE, EDGE):
for (feat, data) in typeInfo.get(f"{kind}Features", {}).items():
eItem = f"{feat}: "
checkValType(feat, vals=data.values())
addedFt.add(feat)
(otextTypes, otextFeatures) = otextInfo()
problemTypes = addedTp & deletedTp
if problemTypes:
ePrefix = "Add and then delete: "
eItem = "types: "
err(f"{_rep(problemTypes)}")
problemTypes = otextTypes - ((set(origNodeTypes) | addedTp) - deletedTp)
if problemTypes:
ePrefix = "Missing for text API: "
eItem = "types: "
err(f"{_rep(problemTypes)}")
problemFeats = addedFt & deletedFt
if problemFeats:
ePrefix = "Add and then delete: "
eItem = "features: "
err(f"{_rep(problemFeats)}")
problemFeats = otextFeatures - ((origFeatures | addedFt) - deletedFt)
if problemFeats:
ePrefix = "Missing for text API: "
eItem = "features: "
err(f"{_rep(problemFeats)}")
if not dirEmpty(targetLocation):
ePrefix = "Output directory: "
eItem = "not empty: "
err("Clean it or remove it or choose another location")
if not good:
return False
api = TF.loadAll()
info("done")
return True
def checkValType(feat, vals=None, correctTp=None):
origTp = valTp(feat) if feat in origFeatures else None
customTp = featureMeta.get(feat, {}).get(VALTP, None)
assignedTp = origTp or customTp
if correctTp is None:
correctTp = "int" if allInt(vals) else "str"
newTp = customTp or correctTp
if newTp != assignedTp:
featureMeta.setdefault(feat, {})[VALTP] = newTp
if customTp and customTp != correctTp and customTp == "int":
err("feature values are declared to be int but some values are not int")
if assignedTp != newTp:
rep1 = f"feature of type {newTp}"
rep2 = f" (was {assignedTp})" if assignedTp else ""
inf(f"{rep1}{rep2}")
def shiftx(vs, offset=None, nF=None, nT=None):
if offset is None:
return (
{shift[m]: v for (m, v) in vs.items()}
if type(vs) is dict
else {shift[m] for m in vs}
)
else:
return (
{m + offset: v for (m, v) in vs.items() if nF <= m <= nT}
if type(vs) is dict
else {m + offset for m in vs if nF <= m <= nT}
)
def shiftFeature(kind, feat, data):
return (
{shift[n]: v for (n, v) in data.items() if n in shift}
if kind == NODE
else {shift[n]: shiftx(v) for (n, v) in data.items() if n in shift}
)
def mergeF():
nonlocal deletedFeatures
Fs = api.Fs
Es = api.Es
indent(level=0)
if mergeFeatures:
info("merge features ...")
indent(level=1, reset=True)
inF = set()
for (outFeat, inFeats) in mergeFeatures.items():
data = {}
inFeats = fitemize(inFeats)
if all(f in origNodeFeatures for f in inFeats):
featSrc = Fs
featDst = nodeFeatures
else:
featSrc = Es
featDst = edgeFeatures
for inFeat in inFeats:
for (n, val) in featSrc(inFeat).data.items():
data[n] = val
featDst.setdefault(outFeat, {}).update(data)
for inFeat in inFeats:
inF.add(inFeat)
if inFeat in featDst:
del featDst[inFeat]
deletedFeatures |= inF
if mergeFeatures:
info(f"done (deleted {len(inF)} and added {len(mergeFeatures)} features)")
indent(level=2)
info(f"deleted {_rep(inF)}", tm=False)
info(f"added {_rep(mergeFeatures)}", tm=False)
return True
def deleteF():
indent(level=0)
if deleteFeatures:
info("delete features ...")
indent(level=1, reset=True)
for feat in deleteFeatures:
dest = (
nodeFeatures
if feat in origNodeFeatures
else edgeFeatures
if feat in origEdgeFeatures
else None
)
if dest and feat in dest:
del dest[feat]
deletedFeatures.add(feat)
if deleteFeatures:
info(f"done ({len(deleteFeatures)} features)")
indent(level=2)
info(_rep(deleteFeatures), tm=False)
return True
def addF():
indent(level=0)
if addFeatures:
info("add features ...")
indent(level=1, reset=True)
added = collections.defaultdict(set)
for (kind, dest) in (
(NODE, nodeFeatures),
(EDGE, edgeFeatures),
):
for (feat, data) in addFeatures.get(f"{kind}Features", {}).items():
dest.setdefault(feat, {}).update(data)
added[kind].add(feat)
if addFeatures:
info(
f'done (added {len(added["node"])} node + {len(added["edge"])} edge features)'
)
indent(level=2)
for (kind, feats) in sorted(added.items()):
info(f"{kind} features: {_rep(feats)}")
return True
def mergeT():
nonlocal deletedTypes
indent(level=0)
if mergeTypes:
info("merge types ...")
indent(level=1, reset=True)
inT = set()
for (outType, inTypes) in mergeTypes.items():
info(f"Merging {outType}")
withFeatures = type(inTypes) is dict
for inType in inTypes:
addFeatures = inTypes[inType] if withFeatures else {}
addFeatures[OTYPE] = outType
(nF, nT) = origNodeTypes[inType]
for (feat, val) in addFeatures.items():
for n in range(nF, nT + 1):
nodeFeatures.setdefault(feat, {})[n] = val
inT.add(inType)
deletedTypes |= inT
if mergeTypes:
info(f"done (merged {len(mergeTypes)} node types)")
indent(level=2)
info(f"deleted {_rep(inT)}", tm=False)
info(f"added {_rep(mergeTypes)}", tm=False)
return True
def deleteT():
nonlocal maxNode
nonlocal shiftNeeded
indent(level=0)
if deleteTypes:
info("delete types ...")
indent(level=1, reset=True)
curShift = 0
for (nType, (nF, nT)) in sorted(origNodeTypes.items(), key=lambda x: x[1][0]):
if nType in deleteTypes:
curShift -= nT - nF + 1
deletedTypes.add(nType)
else:
nodeTypes[nType] = (nF + curShift, nT + curShift)
for n in range(nF, nT + 1):
shift[n] = n - curShift
for (kind, upd) in (
(NODE, nodeFeatures),
(EDGE, edgeFeatures),
):
for (feat, uData) in upd.items():
upd[feat] = shiftFeature(kind, feat, uData)
maxNode = origMaxNode - curShift
shiftNeeded = curShift != 0
if deleteTypes:
info(f"done ({len(deleteTypes)} types)")
indent(level=2)
info(_rep(deleteTypes), tm=False)
return True
def addT():
nonlocal maxNode
indent(level=0)
if addTypes:
info("add types ...")
indent(level=1, reset=True)
for (nodeType, typeInfo) in sorted(addTypes.items()):
nF = typeInfo[NF]
nT = typeInfo[NT]
offset = maxNode - nF + 1
nodeSlots = typeInfo[NS]
data = {}
for n in range(nF, nT + 1):
data[offset + n] = nodeType
nodeFeatures.setdefault(OTYPE, {}).update(data)
data = {}
for n in range(nF, nT + 1):
data[offset + n] = set(nodeSlots[n])
edgeFeatures.setdefault(OSLOTS, {}).update(data)
for (feat, addData) in typeInfo.get(NFS, {}).items():
data = {}
for n in range(nF, nT + 1):
value = addData.get(n, None)
if value is not None:
data[offset + n] = value
nodeFeatures.setdefault(feat, {}).update(data)
for (feat, addData) in typeInfo.get(EFS, {}).items():
data = {}
for n in range(nF, nT + 1):
value = addData.get(n, None)
if value:
newValue = shiftx(value, offset=offset, nF=nF, nT=nT)
if newValue:
data[offset + n] = newValue
edgeFeatures.setdefault(feat, {}).update(data)
maxNode += nT - nF + 1
if addTypes:
info(f"done ({len(addTypes)} types)")
indent(level=2)
info(_rep(addTypes), tm=False)
return True
def applyUpdates():
Fs = api.Fs
Es = api.Es
indent(level=0)
info("applying updates ...")
indent(level=1, reset=True)
mFeat = 0
for (kind, featSet, featSrc, featUpd, featOut) in (
(NODE, origNodeFeatures, Fs, nodeFeatures, nodeFeaturesOut),
(EDGE, origEdgeFeatures, Es, edgeFeatures, edgeFeaturesOut),
):
allFeatSet = set() if onlyDeliverUpdatedFeatures else set(featSet)
for feat in (allFeatSet | set(featUpd)) - deletedFeatures:
outData = {}
outMeta = {}
if feat in featSet:
featObj = featSrc(feat)
outMeta.update(featObj.meta)
if shiftNeeded:
outData.update(shiftFeature(kind, feat, featObj))
mFeat += 1
else:
outData.update(featObj.items())
if feat in featUpd:
outData.update(featUpd[feat])
if kind == EDGE:
aVal = next(iter(featUpd[feat].values()))
hasValues = type(aVal) is dict
if outMeta.get("edgeValues", False) != hasValues:
outMeta["edgeValues"] = hasValues
if feat in featureMeta:
for (k, v) in featureMeta[feat].items():
if v is None:
if k in outMeta:
del outMeta[k]
else:
outMeta[k] = v
featOut[feat] = outData
metaDataOut[feat] = outMeta
otextMeta = {}
otextMeta.update(meta(OTEXT))
mK = 0
if OTEXT in featureMeta:
for (k, v) in featureMeta[OTEXT].items():
if v is None:
if k in otextMeta:
del otextMeta[k]
mK += 1
else:
if k not in otextMeta or otextMeta[k] != v:
otextMeta[k] = v
mK += 1
metaDataOut[OTEXT] = otextMeta
if mFeat or mK:
fRep = f" (shifted {mFeat} features)" if mFeat else ""
kRep = f" (adapted {mK} keys in otext)" if mK else ""
info(f"done{fRep}{kRep}")
return True
def writeTf():
indent(level=0)
info("write TF data ...")
indent(level=1, reset=True)
TF = Fabric(locations=targetLocation, silent=silent)
TF.save(
metaData=metaDataOut,
nodeFeatures=nodeFeaturesOut,
edgeFeatures=edgeFeaturesOut,
)
return True
def finalize():
indent(level=0)
info("all done")
return True
def process():
for step in (
prepare,
mergeF,
deleteF,
addF,
mergeT,
deleteT,
addT,
applyUpdates,
writeTf,
finalize,
):
if not step():
return False
return True
wasSilent = isSilent()
setSilent(silent)
result = process()
setSilent(wasSilent)
return result
