Module tf.advanced.app
Expand source code Browse git
import types
import traceback
from ..parameters import ORG, RELATIVE, OMAP, OTYPE
from ..fabric import Fabric
from ..lib import readSets
from ..core.helpers import console, mergeDict
from ..core.files import (
normpath,
abspath,
APIREF,
APP_CODE,
APP_APP,
TEMP_DIR,
expanduser as ex,
setDir,
prefixSlash,
splitPath,
isDir,
getLocation,
backendRep,
)
from ..core.timestamp import SILENT_D, AUTO, DEEP, TERSE, VERBOSE, silentConvert
from .find import findAppConfig, findAppClass
from .helpers import getText, runsInNotebook, dm, dh
from .settings import setAppSpecs, setAppSpecsApi
from .zipdata import zipApi
from .volumes import volumesApi
from .interchange import interchangeApi
from .links import linksApi, outLink
from .text import textApi
from .sections import sectionsApi
from .display import displayApi
from .search import searchApi
from .annotate import annotateApi
from .data import getModulesData
from .repo import checkoutRepo, publishRelease
# SET UP A TF API FOR AN APP
FROM_TF_METHODS = """
banner
silentOn
silentOff
isSilent
setSilent
info
warning
error
indent
featuresOnly
footprint
""".strip().split()
class App:
def __init__(
self,
cfg,
appName,
appPath,
commit,
release,
local,
backend,
_browse,
hoist=False,
version=None,
versionOverride=False,
checkout="",
mod=[],
locations=None,
modules=None,
volume=None,
collection=None,
api=None,
setFile="",
silent=SILENT_D,
loadData=True,
_withGc=True,
**configOverrides,
):
"""Set up the advanced TF API.
The parameters are explained in `tf.about.usefunc`.
Parameters
----------
appName, appPath, checkout, version: string
commit, release, local: string
backend: string
checkout: string, optional ""
mod: string or iterable, optional []
version: string, optional None
versionOverride: boolean, optional False
locations, modules: string, optional None
collection, volume: string, optional None
api: object, optional, `None`
setFile: string, optional, `None`
silent: string, optional tf.core.timestamp.SILENT_D
See `tf.core.timestamp.Timestamp`
hoist: dict, optional False
configOverrides: list of tuple
_withGc: boolean, optional True
If False, it disables the Python garbage collector before
loading features. Used to experiment with performance.
"""
silent = silentConvert(silent)
self.context = None
"""Result of interpreting all configuration options in `config.yaml`.
"""
self.inNb = runsInNotebook()
mergeDict(cfg, configOverrides)
self.cfgSpecs = cfg
for key, value in dict(
isCompatible=cfg.get("isCompatible", None),
backend=backend,
appName=appName,
api=api,
version=version,
versionOverride=versionOverride,
volume=volume,
collection=collection,
silent=silent,
loadData=loadData,
_browse=_browse,
).items():
setattr(self, key, value)
def mydm(md, unexpand=False):
dm(md, inNb=self.inNb, unexpand=unexpand)
def mydh(html, unexpand=False):
dh(html, inNb=self.inNb, unexpand=unexpand)
setattr(self, "dm", mydm)
setattr(self, "dh", mydh)
setAppSpecs(self, cfg)
aContext = self.context
version = aContext.version
setDir(self)
self.sets = None
if not self.api:
self.sets = None
if setFile:
sets = readSets(setFile)
if sets:
self.sets = sets
console(f'Sets from {setFile}: {", ".join(sets)}')
specs = getModulesData(
self, backend, mod, locations, modules, version, checkout, silent
)
if specs:
(locations, modules) = specs
self.tempDir = f"{self.repoLocation}/{TEMP_DIR}"
TF = Fabric(
locations=locations,
modules=modules,
volume=volume,
collection=collection,
silent=silent,
_withGc=_withGc,
)
self.TF = TF
if loadData:
api = TF.load("", silent=silent)
if api:
self.api = api
excludedFeatures = aContext.excludedFeatures
allFeatures = TF.explore(silent=DEEP, show=True)
loadableFeatures = allFeatures["nodes"] + allFeatures["edges"]
useFeatures = [
f
for f in loadableFeatures
if f not in excludedFeatures and not f.startswith(OMAP)
]
result = TF.load(useFeatures, add=True, silent=silent)
if result is False:
self.api = None
else:
self.api = None
console(
"""
No data has been loaded.
Most of the TF API has not been loaded.
"""
)
else:
self.TF = None
self.api = None
if self.api:
self.TF = self.api.TF
volumesApi(self)
if self.api:
for m in FROM_TF_METHODS:
setattr(self, m, getattr(self.TF, m))
zipApi(self)
interchangeApi(self)
self.publishRelease = types.MethodType(publishRelease, self)
featuresOnly = self.featuresOnly
if not featuresOnly:
self.getText = types.MethodType(getText, self)
linksApi(self, silent=silent)
if not featuresOnly:
searchApi(self)
sectionsApi(self)
setAppSpecsApi(self, cfg)
displayApi(self, silent=silent)
textApi(self)
annotateApi(self)
setattr(self, "isLoaded", self.api.isLoaded)
if hoist:
self.hoist(hoist)
self.api.makeAvailableIn(hoist)
silentOff = self.silentOff
silentOff()
else:
if not _browse and loadData:
console(
f"""
There were problems with loading data.
The TF API has not been loaded!
The app "{appName}" will not work!
""",
error=True,
)
def hoist(self, hoist, silent=None):
"""Hoist the API handles of this TF app to the global scope.
You can use this if you have loaded a dataset without the `hoist=globals()`
parameter, and want to hoist the API handles in the global scope after all,
without loading the data.
Or, if you have multiple datasets loaded, you can switch for which dataset
you have the API handles in global scope.
Parameters
----------
hoist: dict
A dict of variables.
It makes only sense if you provide `globals()` for this parameter.
That is the dict of global variables in the scope where you call this
method.
silent: string, optional None
If passed, it is the verbosity. Otherwise the verbosity will be taken
from `self`.
"""
if silent is None:
silent = self.silent
if self.api:
self.api.makeAvailableIn(hoist)
if silent in {VERBOSE, AUTO, TERSE}:
if self.inNb:
dh(
"<div><b>TF API:</b> names "
+ outLink(
"N F E L T S C TF Fs Fall Es Eall Cs Call",
APIREF,
title="doc",
asHtml=True,
)
+ " directly usable</div><hr>"
)
else:
console("No api activated for this dataset. No hoisting will take place")
def load(self, features, silent=SILENT_D):
"""Loads extra features in addition to the main dataset.
This is the same as `tf.fabric.Fabric.load` when called with `add=True`.
Parameters
----------
features: string | iterable
Either a string containing space separated feature names, or an
iterable of feature names.
The feature names are just the names of `.tf` files
without directory information and without extension.
silent: string, optional tf.core.timestamp.SILENT_D
See `tf.core.timestamp.Timestamp`
Returns
-------
boolean
Whether the feature has been successfully loaded.
"""
TF = self.TF
silent = silentConvert(silent)
return TF.load(features, add=True, silent=silent)
def reinit(self):
"""TF Apps may override this method.
It is called by `reuse`. Hence it needs to be present.
"""
pass
def reuse(self, hoist=False):
"""Re-initialize the app.
The app's settings are read again, the app's code is re-imported,
the app's stylesheets are applied again.
But the data is left untouched, and no time-consuming reloading of data
takes place.
Handy when you are developing a new app and want to experiment with it
without the costly re-loading of the data in every cycle.
Parameters
----------
hoist: boolean, optional False
Same as in `App`.
!!! hint "the effect of the configuration settings"
If you are developing a TF app and need to see the effects of
the configuration settings in detail, you can conveniently
call `reuse`.
"""
backend = self.backend
aContext = self.context
appPath = aContext.appPath
appName = aContext.appName
local = aContext.local
commit = aContext.commit
release = aContext.release
version = aContext.version
api = self.api
cfg = findAppConfig(
appName,
appPath,
commit,
release,
local,
backend,
org=aContext.org,
repo=aContext.repo,
relative=prefixSlash(aContext.relative),
version=version,
)
findAppClass(appName, appPath)
setAppSpecs(self, cfg, reset=True)
if api:
TF = self.TF
TF._makeApi()
api = TF.api
self.api = api
self.reinit() # may be used by custom TF apps
linksApi(self, silent=DEEP)
searchApi(self)
sectionsApi(self)
setAppSpecsApi(self, cfg)
displayApi(self, silent=DEEP)
textApi(self)
if hoist:
api.makeAvailableIn(hoist)
def featureTypes(self, show=True):
"""For which node types is each feature defined?
It computes on the fly for each feature the node types for which
the feature has defined values.
Parameters
----------
show: boolean, optional True
Whether to output the result in pretty markdown.
Returns
-------
dict
If `show` is true, None is returned, but if `show` is false,
a dict is returned, keyed by features and the value for each feature
is the list of types for which it has defined values.
"""
if hasattr(self, "featureTypeMap"):
info = self.featureTypeMap
else:
api = self.api
F = api.F
Fs = api.Fs
Fall = api.Fall
nodesByType = {}
allFeatures = [p for p in Fall() if p != OTYPE]
allTypes = F.otype.all
for tp in allTypes:
nodesByType[tp] = set(F.otype.s(tp))
info = {}
for feat in allFeatures:
featNodes = {i[0] for i in Fs(feat).items()}
for tp in allTypes:
if len(featNodes & nodesByType[tp]) > 0:
info.setdefault(feat, []).append(tp)
self.featureTypeMap = info
if show:
md = []
md.extend(["""feature | node types""", """:- | :-"""])
for feat, tps in sorted(info.items()):
tpsRep = "*" + "*, *".join(tps) + "*"
md.append(f"""**{feat}** | {tpsRep}""")
self.dm("\n".join(md))
self.dm(
"To get this overview in a dict, "
"call `A.featureTypes(show=False)`\n"
)
else:
return info
def findApp(
appName,
checkoutApp,
dataLoc,
backend,
_browse,
*args,
silent=SILENT_D,
version=None,
legacy=False,
**kwargs,
):
"""Find a TF app by name and initialize an object of its main class.
Parameters
----------
appName: string or None
Either:
* None, but then `dataLoc` should have a value
* `app:path/to/tf/app` (not literally)
* `org/repo` (not literally)
* `org/repo/relative` (not literally)
* `app`, i.e. the plain name of an official TF app
(e.g. `bhsa`, `oldbabylonian`)
The last case is legacy: instead of `app`, pass `org/repo`.
dataLoc: string or None
Either:
* None, but then `appName` should have a value
* path to a local directory
* `org/repo`
* `org/repo/relative`
Except for the first two cases, a trailing checkout specifier
is allowed, like `:clone`, `:local`, `:latest`, `:hot`
It is assumed that the location is a TF data directory;
a vanilla app without extra configuration is initialized.
checkoutApp: string
The checkout specifier for the TF app. See `tf.advanced.app.App`.
args: mixed
Arguments that will be passed to the initializer of the `tf.advanced.app.App`
class.
backend: string
`github` or `gitlab` or a GitLab instance such as `gitlab.huc.knaw.nl`.
kwargs: mixed
Keyword arguments that will be passed to the initializer of the
`tf.advanced.app.App` class.
legacy: boolean, optional False
If true, accept that a legacy-app is called.
Do not give warning, and do not try to load the app in the non-legacy way.
"""
versionGiven = version
(commit, release, local) = (None, None, None)
extraMod = None
appLoc = None
if appName is not None and appName.startswith("app:"):
appLoc = normpath(appName[4:])
else:
appName = normpath(appName)
if dataLoc is None and appName is None:
console("No TF app and no data location specified", error=True)
return None
if dataLoc is not None and appName is not None:
console("Both a TF app and a data location are specified", error=True)
return None
dataOrg = None
dataRepo = None
dataFolder = None
inNb = runsInNotebook()
if silent not in {TERSE, DEEP}:
dm("**Locating corpus resources ...**", inNb=inNb)
if dataLoc is None:
if appLoc:
if ":" in appLoc:
console(
"When passing an app by `app:fullpath` you cannot use :-specifiers"
)
return None
appPath = ex(appLoc) if appLoc else ""
absPath = abspath(appPath)
if isDir(absPath):
appDir = absPath
appBase = ""
else:
console(f"{absPath} is not an existing directory", error=True)
appBase = False
appDir = None
appPath = appDir
elif "/" in appName:
(dataOrg, rest) = appName.split("/", maxsplit=1)
(dataRepo, *rest) = rest.split("/")
dataRelative = kwargs.get("relative", None) or RELATIVE
if len(rest) > 0 and rest[-1] == APP_APP:
appParts = rest
dataParts = rest[0:-1] + [dataRelative]
elif len(rest) > 0 and rest[-1] == RELATIVE:
appParts = rest[0:-1] + [APP_APP]
dataParts = rest
else:
dataParts = rest + [dataRelative]
appParts = rest + [APP_APP]
appFolder = prefixSlash("/".join(appParts))
dataFolder = prefixSlash("/".join(x for x in dataParts if x))
(commit, release, local, appBase, appDir) = checkoutRepo(
backend,
_browse=_browse,
org=dataOrg,
repo=dataRepo,
folder=appFolder,
checkout=checkoutApp,
withPaths=True,
keep=False,
silent=silent,
label="app",
)
appBaseRep = f"{appBase}/" if appBase else ""
appPath = f"{appBaseRep}{appDir}"
else:
(commit, release, local, appBase, appDir) = checkoutRepo(
backend,
_browse=_browse,
org=ORG,
repo=f"app-{appName}",
folder=APP_CODE,
checkout=checkoutApp,
withPaths=True,
keep=False,
silent=silent,
label="app",
)
appBaseRep = f"{appBase}/" if appBase else ""
appPath = f"{appBaseRep}{appDir}"
cfg = findAppConfig(appName, appPath, commit, release, local, backend)
provenanceSpec = kwargs.get("provenanceSpec", {})
if provenanceSpec:
for k in ("org", "repo", "relative"):
value = provenanceSpec.get(k, None)
if value:
if k == "relative":
value = prefixSlash(value)
cfg[k] = value
dataOrg = cfg.get("provenanceSpec", {}).get("org", None)
dataRepo = cfg.get("provenanceSpec", {}).get("repo", None)
if not legacy:
if dataOrg:
console(
(
"WARNING: in the future, pass "
f"`{dataOrg}/{appName}` instead of `{appName}`"
),
error=True,
)
(commit, release, local, appBase, appDir) = checkoutRepo(
backend,
_browse=_browse,
org=dataOrg,
repo=dataRepo,
folder=APP_APP,
checkout=checkoutApp,
withPaths=True,
keep=False,
silent=silent,
label="app",
)
appBaseRep = f"{appBase}/" if appBase else ""
appPath = f"{appBaseRep}{appDir}"
else:
parts = dataLoc.split(":", maxsplit=1)
if len(parts) == 1:
parts.append("")
(dataLoc, checkoutData) = parts
if checkoutData == "":
appPath = ex(dataLoc) if dataLoc else ""
absPath = abspath(appPath)
if isDir(absPath):
(appDir, appName) = splitPath(absPath)
appBase = ""
else:
console(f"{absPath} is not an existing directory", error=True)
appBase = False
appDir = None
appPath = appDir
else:
appBase = ""
appDir = ""
appPath = ""
extraMod = f"{dataLoc}:{checkoutData}"
cfg = findAppConfig(
appName,
appPath,
commit,
release,
local,
backend,
org=dataOrg,
repo=dataRepo,
relative=dataFolder,
version=version,
)
version = cfg["provenanceSpec"].get("version", None)
isCompatible = cfg["isCompatible"]
if isCompatible is None:
appClass = App
elif not isCompatible:
return None
else:
appBaseRep = f"{appBase}/" if appBase else ""
appPath = f"{appBaseRep}{appDir}"
appClass = findAppClass(appName, appPath) or App
mod = kwargs.get("mod", [])
mod = [] if mod is None else mod.split(",") if type(mod) is str else list(mod)
if extraMod:
if len(mod) > 0:
mod = [extraMod, *mod]
else:
mod = [extraMod]
kwargs["mod"] = mod
try:
app = appClass(
cfg,
appName,
appPath,
commit,
release,
local,
backend,
_browse,
*args,
version=version,
versionOverride=not not versionGiven,
silent=silent,
**kwargs,
)
except Exception as e:
if appClass is not App:
console(
f"There was an error loading corpus {appName}",
error=True,
)
console(repr(e), error=True)
traceback.print_exc()
console("TF is not loaded", error=True)
return None
return app
def useApp(appName, backend):
"""Make use of a corpus.
For a detailed description, see `tf.about.usefunc`.
Parameters
----------
appName: string
backend: string, optional None
If present, it is `github` or `gitlab`
or a GitLab instance such as `gitlab.huc.knaw.nl`.
If absent, `None` or empty, it is `github`.
args: mixed
Do not pass any other positional argument!
kwargs: mixed
Used to initialize the corpus app that we use.
That is either an uncustomised `tf.advanced.app.App` or
a customization of it.
Returns
-------
A: object
The object whose attributes and methods constitute the advanced API.
See Also
--------
tf.advanced.app.App
"""
if appName.startswith("data:"):
dataLoc = appName[5:]
appName = None
checkoutApp = None
elif appName.startswith("app:"):
dataLoc = None
checkoutApp = None
else:
dataLoc = None
parts = appName.split(":", maxsplit=1)
if len(parts) == 1:
parts.append("")
(appName, checkoutApp) = parts
backend = backendRep(backend, "norm")
return (appName, checkoutApp, dataLoc, backend)
def loadApp(silent=DEEP):
"""Loads a given TF app or loads the TF app based on the working directory.
It assumes that the dataset sits in a clone from a back-end (`github` / `gitlab`),
and it will load this data.
Parameters
----------
silent: string, optional "deep"
The level of silence in which the loading will happen.
The default is as silent as possible.
Returns
-------
app: object|void
The handle to the loaded TF dataset, if it is successfully loaded, else `None`.
"""
(backend, org, repo, relative) = getLocation()
if any(s is None for s in (backend, org, repo, relative)):
console(
"Not working in a repo: "
f"backend={backend} org={org} repo={repo} relative={relative}"
)
return None
(appName, checkoutApp, dataLoc, backend) = useApp(
f"{org}/{repo}{relative}:clone", backend
)
return findApp(
appName, checkoutApp, dataLoc, backend, False, checkout="clone", silent=silent
)
Functions
def findApp(appName, checkoutApp, dataLoc, backend, _browse, *args, silent='auto', version=None, legacy=False, **kwargs)
-
Find a TF app by name and initialize an object of its main class.
Parameters
appName
:string
orNone
-
Either:
- None, but then
dataLoc
should have a value app:path/to/tf/app
(not literally)org/repo
(not literally)org/repo/relative
(not literally)app
, i.e. the plain name of an official TF app (e.g.bhsa
,oldbabylonian
)
The last case is legacy: instead of
app
, passorg/repo
. - None, but then
dataLoc
:string
orNone
-
Either:
- None, but then
appName
should have a value - path to a local directory
org/repo
org/repo/relative
Except for the first two cases, a trailing checkout specifier is allowed, like
:clone
,:local
,:latest
,:hot
It is assumed that the location is a TF data directory; a vanilla app without extra configuration is initialized.
- None, but then
checkoutApp
:string
- The checkout specifier for the TF app. See
App
. args
:mixed
- Arguments that will be passed to the initializer of the
App
class. backend
:string
github
orgitlab
or a GitLab instance such asgitlab.huc.knaw.nl
.kwargs
:mixed
- Keyword arguments that will be passed to the initializer of the
App
class. legacy
:boolean
, optionalFalse
- If true, accept that a legacy-app is called. Do not give warning, and do not try to load the app in the non-legacy way.
def loadApp(silent='deep')
-
Loads a given TF app or loads the TF app based on the working directory.
It assumes that the dataset sits in a clone from a back-end (
github
/gitlab
), and it will load this data.Parameters
silent
:string
, optional"deep"
- The level of silence in which the loading will happen. The default is as silent as possible.
Returns
app
:object|void
- The handle to the loaded TF dataset, if it is successfully loaded, else
None
.
def useApp(appName, backend)
-
Make use of a corpus.
For a detailed description, see
tf.about.usefunc
.Parameters
appName
:string
backend
:string
, optionalNone
- If present, it is
github
orgitlab
or a GitLab instance such asgitlab.huc.knaw.nl
. If absent,None
or empty, it isgithub
. args
:mixed
- Do not pass any other positional argument!
kwargs
:mixed
- Used to initialize the corpus app that we use.
That is either an uncustomised
App
or a customization of it.
Returns
A
:object
- The object whose attributes and methods constitute the advanced API.
See Also
Classes
class App (cfg, appName, appPath, commit, release, local, backend, _browse, hoist=False, version=None, versionOverride=False, checkout='', mod=[], locations=None, modules=None, volume=None, collection=None, api=None, setFile='', silent='auto', loadData=True, **configOverrides)
-
Set up the advanced TF API.
The parameters are explained in
tf.about.usefunc
.Parameters
appName
,appPath
,checkout
,version
:string
commit
,release
,local
:string
backend
:string
checkout
:string
, optional""
mod
:string
oriterable
, optional[]
version
:string
, optionalNone
versionOverride
:boolean
, optionalFalse
locations
,modules
:string
, optionalNone
collection
,volume
:string
, optionalNone
api
:object
, optional,
None``setFile
:string
, optional,
None``silent
:string
, optionalSILENT_D
- See
Timestamp
hoist
:dict
, optionalFalse
configOverrides
:list
oftuple
_withGc
:boolean
, optionalTrue
- If False, it disables the Python garbage collector before loading features. Used to experiment with performance.
Expand source code Browse git
class App: def __init__( self, cfg, appName, appPath, commit, release, local, backend, _browse, hoist=False, version=None, versionOverride=False, checkout="", mod=[], locations=None, modules=None, volume=None, collection=None, api=None, setFile="", silent=SILENT_D, loadData=True, _withGc=True, **configOverrides, ): """Set up the advanced TF API. The parameters are explained in `tf.about.usefunc`. Parameters ---------- appName, appPath, checkout, version: string commit, release, local: string backend: string checkout: string, optional "" mod: string or iterable, optional [] version: string, optional None versionOverride: boolean, optional False locations, modules: string, optional None collection, volume: string, optional None api: object, optional, `None` setFile: string, optional, `None` silent: string, optional tf.core.timestamp.SILENT_D See `tf.core.timestamp.Timestamp` hoist: dict, optional False configOverrides: list of tuple _withGc: boolean, optional True If False, it disables the Python garbage collector before loading features. Used to experiment with performance. """ silent = silentConvert(silent) self.context = None """Result of interpreting all configuration options in `config.yaml`. """ self.inNb = runsInNotebook() mergeDict(cfg, configOverrides) self.cfgSpecs = cfg for key, value in dict( isCompatible=cfg.get("isCompatible", None), backend=backend, appName=appName, api=api, version=version, versionOverride=versionOverride, volume=volume, collection=collection, silent=silent, loadData=loadData, _browse=_browse, ).items(): setattr(self, key, value) def mydm(md, unexpand=False): dm(md, inNb=self.inNb, unexpand=unexpand) def mydh(html, unexpand=False): dh(html, inNb=self.inNb, unexpand=unexpand) setattr(self, "dm", mydm) setattr(self, "dh", mydh) setAppSpecs(self, cfg) aContext = self.context version = aContext.version setDir(self) self.sets = None if not self.api: self.sets = None if setFile: sets = readSets(setFile) if sets: self.sets = sets console(f'Sets from {setFile}: {", ".join(sets)}') specs = getModulesData( self, backend, mod, locations, modules, version, checkout, silent ) if specs: (locations, modules) = specs self.tempDir = f"{self.repoLocation}/{TEMP_DIR}" TF = Fabric( locations=locations, modules=modules, volume=volume, collection=collection, silent=silent, _withGc=_withGc, ) self.TF = TF if loadData: api = TF.load("", silent=silent) if api: self.api = api excludedFeatures = aContext.excludedFeatures allFeatures = TF.explore(silent=DEEP, show=True) loadableFeatures = allFeatures["nodes"] + allFeatures["edges"] useFeatures = [ f for f in loadableFeatures if f not in excludedFeatures and not f.startswith(OMAP) ] result = TF.load(useFeatures, add=True, silent=silent) if result is False: self.api = None else: self.api = None console( """ No data has been loaded. Most of the TF API has not been loaded. """ ) else: self.TF = None self.api = None if self.api: self.TF = self.api.TF volumesApi(self) if self.api: for m in FROM_TF_METHODS: setattr(self, m, getattr(self.TF, m)) zipApi(self) interchangeApi(self) self.publishRelease = types.MethodType(publishRelease, self) featuresOnly = self.featuresOnly if not featuresOnly: self.getText = types.MethodType(getText, self) linksApi(self, silent=silent) if not featuresOnly: searchApi(self) sectionsApi(self) setAppSpecsApi(self, cfg) displayApi(self, silent=silent) textApi(self) annotateApi(self) setattr(self, "isLoaded", self.api.isLoaded) if hoist: self.hoist(hoist) self.api.makeAvailableIn(hoist) silentOff = self.silentOff silentOff() else: if not _browse and loadData: console( f""" There were problems with loading data. The TF API has not been loaded! The app "{appName}" will not work! """, error=True, ) def hoist(self, hoist, silent=None): """Hoist the API handles of this TF app to the global scope. You can use this if you have loaded a dataset without the `hoist=globals()` parameter, and want to hoist the API handles in the global scope after all, without loading the data. Or, if you have multiple datasets loaded, you can switch for which dataset you have the API handles in global scope. Parameters ---------- hoist: dict A dict of variables. It makes only sense if you provide `globals()` for this parameter. That is the dict of global variables in the scope where you call this method. silent: string, optional None If passed, it is the verbosity. Otherwise the verbosity will be taken from `self`. """ if silent is None: silent = self.silent if self.api: self.api.makeAvailableIn(hoist) if silent in {VERBOSE, AUTO, TERSE}: if self.inNb: dh( "<div><b>TF API:</b> names " + outLink( "N F E L T S C TF Fs Fall Es Eall Cs Call", APIREF, title="doc", asHtml=True, ) + " directly usable</div><hr>" ) else: console("No api activated for this dataset. No hoisting will take place") def load(self, features, silent=SILENT_D): """Loads extra features in addition to the main dataset. This is the same as `tf.fabric.Fabric.load` when called with `add=True`. Parameters ---------- features: string | iterable Either a string containing space separated feature names, or an iterable of feature names. The feature names are just the names of `.tf` files without directory information and without extension. silent: string, optional tf.core.timestamp.SILENT_D See `tf.core.timestamp.Timestamp` Returns ------- boolean Whether the feature has been successfully loaded. """ TF = self.TF silent = silentConvert(silent) return TF.load(features, add=True, silent=silent) def reinit(self): """TF Apps may override this method. It is called by `reuse`. Hence it needs to be present. """ pass def reuse(self, hoist=False): """Re-initialize the app. The app's settings are read again, the app's code is re-imported, the app's stylesheets are applied again. But the data is left untouched, and no time-consuming reloading of data takes place. Handy when you are developing a new app and want to experiment with it without the costly re-loading of the data in every cycle. Parameters ---------- hoist: boolean, optional False Same as in `App`. !!! hint "the effect of the configuration settings" If you are developing a TF app and need to see the effects of the configuration settings in detail, you can conveniently call `reuse`. """ backend = self.backend aContext = self.context appPath = aContext.appPath appName = aContext.appName local = aContext.local commit = aContext.commit release = aContext.release version = aContext.version api = self.api cfg = findAppConfig( appName, appPath, commit, release, local, backend, org=aContext.org, repo=aContext.repo, relative=prefixSlash(aContext.relative), version=version, ) findAppClass(appName, appPath) setAppSpecs(self, cfg, reset=True) if api: TF = self.TF TF._makeApi() api = TF.api self.api = api self.reinit() # may be used by custom TF apps linksApi(self, silent=DEEP) searchApi(self) sectionsApi(self) setAppSpecsApi(self, cfg) displayApi(self, silent=DEEP) textApi(self) if hoist: api.makeAvailableIn(hoist) def featureTypes(self, show=True): """For which node types is each feature defined? It computes on the fly for each feature the node types for which the feature has defined values. Parameters ---------- show: boolean, optional True Whether to output the result in pretty markdown. Returns ------- dict If `show` is true, None is returned, but if `show` is false, a dict is returned, keyed by features and the value for each feature is the list of types for which it has defined values. """ if hasattr(self, "featureTypeMap"): info = self.featureTypeMap else: api = self.api F = api.F Fs = api.Fs Fall = api.Fall nodesByType = {} allFeatures = [p for p in Fall() if p != OTYPE] allTypes = F.otype.all for tp in allTypes: nodesByType[tp] = set(F.otype.s(tp)) info = {} for feat in allFeatures: featNodes = {i[0] for i in Fs(feat).items()} for tp in allTypes: if len(featNodes & nodesByType[tp]) > 0: info.setdefault(feat, []).append(tp) self.featureTypeMap = info if show: md = [] md.extend(["""feature | node types""", """:- | :-"""]) for feat, tps in sorted(info.items()): tpsRep = "*" + "*, *".join(tps) + "*" md.append(f"""**{feat}** | {tpsRep}""") self.dm("\n".join(md)) self.dm( "To get this overview in a dict, " "call `A.featureTypes(show=False)`\n" ) else: return info
Subclasses
Instance variables
var context
-
Result of interpreting all configuration options in
config.yaml
.
Methods
def featureTypes(self, show=True)
-
For which node types is each feature defined?
It computes on the fly for each feature the node types for which the feature has defined values.
Parameters
show
:boolean
, optionalTrue
- Whether to output the result in pretty markdown.
Returns
dict
- If
show
is true, None is returned, but ifshow
is false, a dict is returned, keyed by features and the value for each feature is the list of types for which it has defined values.
def hoist(self, hoist, silent=None)
-
Hoist the API handles of this TF app to the global scope.
You can use this if you have loaded a dataset without the
hoist=globals()
parameter, and want to hoist the API handles in the global scope after all, without loading the data.Or, if you have multiple datasets loaded, you can switch for which dataset you have the API handles in global scope.
Parameters
hoist
:dict
- A dict of variables.
It makes only sense if you provide
globals()
for this parameter. That is the dict of global variables in the scope where you call this method. silent
:string
, optionalNone
- If passed, it is the verbosity. Otherwise the verbosity will be taken
from
self
.
def load(self, features, silent='auto')
-
Loads extra features in addition to the main dataset.
This is the same as
FabricCore.load()
when called withadd=True
.Parameters
features
:string | iterable
- Either a string containing space separated feature names, or an
iterable of feature names.
The feature names are just the names of
.tf
files without directory information and without extension. silent
:string
, optionalSILENT_D
- See
Timestamp
Returns
boolean
- Whether the feature has been successfully loaded.
def reinit(self)
-
TF Apps may override this method. It is called by
reuse
. Hence it needs to be present. def reuse(self, hoist=False)
-
Re-initialize the app.
The app's settings are read again, the app's code is re-imported, the app's stylesheets are applied again. But the data is left untouched, and no time-consuming reloading of data takes place.
Handy when you are developing a new app and want to experiment with it without the costly re-loading of the data in every cycle.
Parameters
hoist
:boolean
, optionalFalse
- Same as in
App
.
the effect of the configuration settings
If you are developing a TF app and need to see the effects of the configuration settings in detail, you can conveniently call
reuse
.