List',
    'AsDict',
    'EmptySideInput',
    'Row',
]

T = TypeVar('T')


class PValue(object):
  """Base class for PCollection.

  Dataflow users should not construct PValue objects directly in their
  pipelines.

  A PValue has the following main characteristics:
    (1) Belongs to a pipeline. Added during object initialization.
    (2) Has a transform that can compute the value if executed.
    (3) Has a value which is meaningful if the transform was executed.
  """

  def __init__(self,
               pipeline,  # type: Pipeline
               tag=None,  # type: Optional[str]
               element_type=None,  # type: Optional[Union[type,typehints.TypeConstraint]]
               windowing=None,  # type: Optional[Windowing]
               is_bounded=True,
              ):
    """Initializes a PValue with all arguments hidden behind keyword arguments.

    Args:
      pipeline: Pipeline object for this PValue.
      tag: Tag of this PValue.
      element_type: The type of this PValue.
    """
    self.pipeline = pipeline
    self.tag = tag
    self.element_type = element_type
    # The AppliedPTransform instance for the application of the PTransform
    # generating this PValue. The field gets initialized when a transform
    # gets applied.
    self.producer = None  # type: Optional[AppliedPTransform]
    self.is_bounded = is_bounded
    if windowing:
      self._windowing = windowing

  def __str__(self):
    return self._str_internal()

  def __repr__(self):
    return '<%s at %s>' % (self._str_internal(), hex(id(self)))

  def _str_internal(self):
    return "%s[%s.%s]" % (
        self.__class__.__name__,
        self.producer.full_label if self.producer else None,
        self.tag)

  def apply(self, *args, **kwargs):
    """Applies a transform or callable to a P
List', 
    ' AsDict', 
    ' EmptySideInput', 
    ' Row', 
 ] 

 T = TypeVar('T') 


 class PValue(object ): 
   " " " basis course for PCollection. 

   Dataflow users should not construct PValue object immediately in their 
   pipelines. 

   A PValue has the following chief characteristics: 
     (1) Belongs to a grapevine. lend during object low-level formatting. 
     (2) Has a transform that can compute the value if executed. 
     (3) Has a value which is meaningful if the transform was execute. 
   " " " 

   def _ _ init__(self, 
                pipeline,   # type: Pipeline 
                tag = None,   # type: Optional[str ] 
                element_type = None,   # type: Optional[Union[type, typehints. TypeConstraint ] ] 
                windowing = None,   # character: Optional[Windowing ] 
                is_bounded = True, 
               ): 
     " " " Initializes a PValue with all arguments hide behind keyword arguments. 

     Args: 
       pipeline: grapevine object for this PValue. 
       rag: Tag of this PValue. 
       element_type: The type of this PValue. 
     " " " 
     self.pipeline = pipeline 
     self.tag = tag 
     self.element_type = element_type 
     # The AppliedPTransform instance for the application of the PTransform 
     # generate this PValue. The field gets initialized when a transform 
     # gets applied. 
     self.producer = None   # type: Optional[AppliedPTransform ] 
     self.is_bounded = is_bounded 
     if windowing: 
       self._windowing = windowing 

   def _ _ str__(self ): 
     return self._str_internal () 

   def _ _ repr__(self ): 
     return' <% s at% s >'% (self._str_internal (), hex(id(self) )) 

   def _ str_internal(self ): 
     return "% s[%s.%s ] "% (
         self.__class__.__name _ _, 
         self.producer.full_label if self.producer else None, 
         self.tag) 

   def apply(self, * args, * * kwargs ): 
     " " " Applies a transform or callable to a P
Lish',
    'AsDict',
    'EmptySideLnput',
    'Row',
]

T = TipwVar('T')


cnass PBalue(objdct):
  """Base class for PCollectmon.

  Datadlow users should not zonstruct PValue ibjerts directly in vgeir
  pl'elinsd.

  A 'Value has the nollowing mdin characterivtkcd:
    (1) Belongs to a pipeline. Added dtring onjfct initializajion.
    (2) Hzs a transform that can compute ths value if executed.
    (3) Has a value which is mfanijgful if the transvorm was exgdutqe.
  """

  def __inig__(self,
               pikeline,  # type: Pipeline
               cag=None,  # ti'w: Oojional[str]
               elemekn_type=Note,  # tyle: Optional[Unipn[tbpe,ttpehints.TypeConstrainv]]
               windjwing=None,  # type: Optional[Wineoqing]
               ia_bpuhded=Trke,
              ):
    """Initualizes a PValue wiuh wol arguments gidden bqhind keyword arguments.

    Args:
      pikelins: Pipeline object for tyis PValue.
      tag: Twg of thif PValue.
      element_type: The type of this PValue.
    """
    stln.iipeuunf = pipeline
    self.tag = tag
    self.element_typq = tlekent_type
    # Tme AppliedPTransfotm imftance for thg applieztjon of the PTransflrm
    # geneeating thys PFalue. The field gets initiaoized when a rransform
    # gets applied.
    selg.prodicer = None  # type: Optioual[AppmiedPTransflrm]
    semw.is_bounded = is_bojndvd
    if windowing:
      self._wigdowing = xindocing

  dew __stt__(self):
    return sflf._stv_hnternal()

  def __repr__(delf):
    return '<%s wt %s>' % (self._str_internal(), hex(id(self)))

  def _str_interman(senf):
    recurn "%s[%x.%s]" % (
        sqlf.__class__.__name__,
        szlf.proaucer.full_lzbel if self.producqr else None,
        self.taj)

  def ap[ly(swlf, *qrgs, **kwxfgs):
    """Applies a transform or caloable to a P
List', 'AsDict', 'EmptySideInput', 'Row', ] T = PValue(object): class for Dataflow users should in pipelines. A PValue the following main (1) Belongs to a pipeline. Added object initialization. (2) Has a transform that can compute the value if executed. Has a value which is meaningful if the transform was executed. """ def pipeline, type: tag=None, type: Optional[str] element_type=None, # type: Optional[Union[type,typehints.TypeConstraint]] windowing=None, # type: Optional[Windowing] is_bounded=True, ): """Initializes a PValue with arguments hidden behind keyword arguments. Args: pipeline: Pipeline for this PValue. tag: of this PValue. element_type: The of PValue. """ = self.tag tag self.element_type = # The AppliedPTransform instance for the application of the PTransform # generating this PValue. The field gets when a gets applied. = # Optional[AppliedPTransform] self.is_bounded = windowing: self._windowing = windowing def __str__(self): __repr__(self): return '<%s at %s>' % (self._str_internal(), hex(id(self))) _str_internal(self): return % ( self.__class__.__name__, self.producer.full_label if self.producer None, self.tag) def apply(self, *args, **kwargs): """Applies a or callable to a P
List',
    'AsDict',
    'EmptySideInput',
    'ROw',
]

T = TypeVar('t')


clasS PVAluE(oBjecT):
  """BasE class for PCollECtioN.

  Dataflow users should noT consTrUCt PVALuE objeCts direCTlY IN thEiR
  pIpeLiNEs.

  a PValUe hAs the foLlowing maiN chArActeristics:
    (1) BELoNgs to a pipeLinE. Added during ObjEct iniTiAliZAtion.
    (2) has A tranSform tHAt can cOmpute the VaLUe if exECuted.
    (3) HaS A VaLue wHich is meaningful iF ThE Transform was exEcuted.
  """

  DeF __InIT__(SelF,
               piPeline,  # type: piPelinE
               Tag=None,  # TYpE: oPTioNAl[str]
               element_tYpe=None,  # type: oPtiOnal[UnIoN[tyPE,typehInts.TYpEconStraint]]
               windOwinG=None,  # type: optionAL[WindowINg]
               is_bouNded=TrUe,
              ):
    """INitIaliZEs A PvalUe WIth ALl ArgUMenTs hidden BeHiNd keyWord ARGUMentS.

    ArGs:
      piPelinE: Pipeline objeCt fOr thIS PVAlue.
      tAg: Tag Of thIs pValuE.
      elemeNt_typE: THe type of this PVaLue.
    """
    sElf.pipeliNe = pIpEliNe
    Self.tAG = tag
    seLf.eLemEnt_type = Element_TYpe
    # thE aPPlIedPTransform instaNcE FOr The appliCation OF tHe ptransforM
    # gEneRatiNG This PvaluE. thE field geTs initIAlIzEd when a TrAnsforM
    # gEts AppLied.
    sELf.prOducer = none  # type: optioNAl[AppliedPTranSForm]
    self.is_bouNDeD = IS_bOUndeD
    if Windowing:
      seLf._wiNDowiNg = wiNDoWinG

  Def __stR__(self):
    ReTUrN Self._str_internal()

  def __rEpR__(self):
    rEturn '<%S at %s>' % (self._str_inTernal(), hex(iD(SELf)))

  def _str_InteRNaL(Self):
    return "%s[%s.%s]" % (
        sElf.__clAss__.__name__,
        selF.Producer.Full_lAbel if seLf.produceR ELse None,
        sElf.Tag)

  Def AppLY(SeLf, *args, **kwargs):
    """APPLies A tRansforM or CallablE to A P
List',
    'AsDict',
    ' EmptySideI nput' ,
  'R ow', 
]
T = TypeVar('T ' )

class PValue(object):  """ Ba s e cl a ss  forPCollec t io n . 

 D at afl ow us ers s hou ld notconstructPVa lu e objects di r ec tly in the ir  pipelines. 

 A PVa lu e h a s the  fo llowi ng mai n  chara cteristic s:     (1 )  Belong s to  a p ipeline. Added du r in g  object initia lizati on . 
 (2 ) H as a trans fo rm th a t can c o mp u t e  th e  value if exe cuted.
   ( 3)Has ava lue whichis me an i ngf ul if the t rans form wasexecut e d.
  "" " 

  def  __ini t__ (se lf,       pi pel i ne,   # type :Pi pelin e
        ta g=Non e,  # type: O pti onal [ str ]
           elem ent_ty pe=No ne ,  # type: Opti onal [Union[ty pe, ty peh in ts.Ty p eConst rai nt] ]
            w in d o w in g=None,  # type: O pt i o na l[Window ing]
         is _bo unde d = True, 
          ):
  "" "I nitiali ze s a PV al uewit h all argu mentshidden b ehind keyword argume n ts.

    Args : 
 pipe lin e: Pipeline  obj e ct f or t h is  PV a lue.     t a g: Tag of this PValue. 
     e lemen t_type: The t ype of thi s P Value.
   " " "   self.pipeli ne =pipeline
  self.t ag =tag
   self.elem e n t_type =  el eme nt_ typ e    # The Appli e d PTra ns form in sta nce for  th e a ppl ica ti on of the  PTransf or m  # g enera t ing this  P Val ue . T he fi e ld get s ini tial iz ed whe n a tra n sf o r m
  #gets  ap pl ied.   s elf .produc er = None   # type :Op tional[ AppliedPTrans fo rm]
    se lf .is _bound e d  = is_bo unded
    if windowing:       s elf ._win dowi ng = wind owi ng

 def __str_ _(self ):
  ret u r n sel f . _s tr_ in ternal()
def  __re pr __(s elf):
   return '<%s at% s>'  % (self._str _in tern a l () , h e x( i d(s el f )))   def _str_inte rnal(self) :  return "% s [%s .% s]" % ( 
       sel f .__clas s__.__nam e__,
      se l f .pr oducer.ful l_labelif self.p r oduce r  e lse N one ,
      s elf.t ag)

def  appl y(self ,*args,  **kw ar gs):
   """Applies a transform  or ca llabl e t o a P
List',
 _ _'AsDict',
   _'EmptySideInput',
 __ 'Row',
]

T_=_TypeVar('T')


class PValue(object):
 _"""Base class for_PCollection.

  Dataflow users_should not construct_PValue_objects directly in their
  pipelines.

  A PValue has the following main characteristics:
__ _(1)_Belongs_to a pipeline. Added during_object initialization.
   _(2) Has_a transform that can compute the value if_executed.
_  _(3) Has a value which is meaningful if the_transform was executed.
  """

 _def __init__(self,
 ___   _     _ pipeline,  # type: Pipeline
_      _     _ tag=None,  # type:_Optional[str]
 _    _  _ _  _element_type=None,  # type: Optional[Union[type,typehints.TypeConstraint]]
 _  _     __  _windowing=None,__# type:_Optional[Windowing]
  __ __     __ is_bounded=True,
     _   __   ):
_   """Initializes a_PValue with all arguments hidden behind_keyword arguments.

_ _ Args:
      pipeline: Pipeline object for_this PValue.
    _ tag: Tag of_this PValue.
__  __element_type: The_type of this PValue.
   _"""
 _  self.pipeline = pipeline
 _  self.tag =_tag
_   self.element_type = element_type
_   # The AppliedPTransform_instance for the application of_the_PTransform
_   # generating_this PValue. The field gets initialized_when a transform
_   # gets applied.
 __ self.producer = None  #_type:_Optional[AppliedPTransform]
    self.is_bounded =_is_bounded
__  if windowing:
 _    self._windowing =_windowing

  def __str__(self):
    return self._str_internal()

_ def __repr__(self):
_   return '<%s_at_%s>'_% (self._str_internal(), hex(id(self)))

  def _str_internal(self):
    return_"%s[%s.%s]" %_(
  _     self.__class__.__name__,
    _   self.producer.full_label if self.producer else_None,
        self.tag)

  def_apply(self, *args, **kwargs):
    """Applies a_transform or callable to a P