tensorbay.client.lazy

Lazy evaluation related classes.

class tensorbay.client.lazy.LazyItem(page: tensorbay.client.lazy.LazyPage[tensorbay.client.lazy._T], data: tensorbay.client.lazy._T)[source]

Bases: Generic[tensorbay.client.lazy._T]

In paging lazy evaluation system, a LazyItem instance represents an element in a pagination.

If user wants to access the elememt, LazyItem will trigger the paging request to pull a page of elements and return the required element. All the pulled elements will be stored in different LazyItem instances and will not be requested again.

Parameters: page – The page the item belongs to.

page: The parent LazyPage of this item.

data: The actual element stored in this item.

classmethod from_page(page: tensorbay.client.lazy.LazyPage[tensorbay.client.lazy._T]) → tensorbay.client.lazy.LazyItem[tensorbay.client.lazy._T][source]

Create a LazyItem instance from page.

Parameters: page – The page of the element.
Returns: The LazyItem instance which stores the input page.

classmethod from_data(data: tensorbay.client.lazy._T) → tensorbay.client.lazy.LazyItem[tensorbay.client.lazy._T][source]

Create a LazyItem instance from data.

Parameters: data – The actual data needs to be stored in LazyItem.
Returns: The LazyItem instance which stores the input data.

get() → tensorbay.client.lazy._T[source]

Access the actual element represented by LazyItem.

If the element is already pulled from web, it will be return directly, otherwise this function will request for a page of elements to get the required elememt.

Returns: The actual element this LazyItem instance represents.

class tensorbay.client.lazy.ReturnGenerator(generator: Generator[tensorbay.client.lazy._T, Any, tensorbay.client.lazy._R])[source]

Bases: Generic[tensorbay.client.lazy._T, tensorbay.client.lazy._R]

ReturnGenerator is a generator wrap to get the return value easily.

Parameters: generator – The generator needs to be wrapped.

value

The return value of the input generator.

Type: tensorbay.client.lazy._R

class tensorbay.client.lazy.LazyPage(offset: int, limit: int, func: Callable[[int, int], Generator[tensorbay.client.lazy._T, None, int]])[source]

Bases: Generic[tensorbay.client.lazy._T]

In paging lazy evaluation system, a LazyPage instance represents a page with elements.

LazyPage is used for sending paging request to pull a page of elements and storing them in different LazyItem instances.

Parameters

offset – The offset of the page.
limit – The limit of the page.
func – A paging generator function, which takes offset<int> and limit<int> as inputs and returns a generator. The returned generator should yield the element user needs, and return the total count of the elements in the paging request.

items: The LazyItem list which represents a page of elements.

pull() → None[source]: Send paging request to pull a page of elements and store them in LazyItem.

class tensorbay.client.lazy.InitPage(offset: int, limit: int, func: Callable[[int, int], Generator[tensorbay.client.lazy._T, None, int]])[source]

Bases: tensorbay.client.lazy.LazyPage[tensorbay.client.lazy._T]

In paging lazy evaluation system, InitPage is the page for initializing PagingList.

InitPage will send a paging request to pull a page of elements and storing them in different LazyItem instances when construction. And the totalCount of the page will also be stored in the instance.

Parameters

offset – The offset of the page.
limit – The limit of the page.
func – A paging generator function, which takes offset<int> and limit<int> as inputs and returns a generator. The returned generator should yield the element user needs, and return the total count of the elements in the paging request.

items: The LazyItem list which represents a page of elements.

total_count: The totalCount of the paging request.

class tensorbay.client.lazy.PagingList(func: Callable[[int, int], Generator[tensorbay.client.lazy._T, None, int]], limit: int)[source]

Bases: MutableSequence[tensorbay.client.lazy._T], tensorbay.utility.repr.ReprMixin

PagingList is a wrap of web paging request.

It follows the python MutableSequence protocal, which means it can be used like a python builtin list. And it provides features like lazy evaluation and cache.

Parameters

func – A paging generator function, which takes offset<int> and limit<int> as inputs and returns a generator. The returned generator should yield the element user needs, and return the total count of the elements in the paging request.
limit – The page size of each paging request.

insert(index: int, value: tensorbay.client.lazy._T) → None[source]

Insert object before index.

Parameters

index – Position of the PagingList.
value – Element to be inserted into the PagingList.

append(value: tensorbay.client.lazy._T) → None[source]

Append object to the end of the PagingList.

Parameters: value – Element to be appended to the PagingList.

reverse() → None[source]: Reverse the items of the PagingList in place.

pop(index: int = - 1) → tensorbay.client.lazy._T[source]

Return the item at index (default last) and remove it from the PagingList.

Parameters: index – Position of the PagingList.
Returns: Element to be removed from the PagingList.

index(value: Any, start: int = 0, stop: Optional[int] = None) → int[source]

Return the first index of the value.

Parameters

value – The value to be found.
start – The start index of the subsequence.
stop – The end index of the subsequence.

Raises

ValueError – When the value is not in the PagingList

Returns

The first index of the value.

count(value: Any) → int[source]

Return the number of occurrences of value.

Parameters: value – The value needs to be counted.
Returns: The number of occurrences of value.

extend(values: Iterable[tensorbay.client.lazy._T]) → None[source]

Extend PagingList by appending elements from the iterable.

Parameters: values – Elements to be extended into the PagingList.