%global _empty_manifest_terminate_build 0
Name:		python-pyfunctional
Version:	1.4.3
Release:	1
Summary:	Package for creating data pipelines with chain functional programming
License:	MIT
URL:		https://github.com/EntilZha/PyFunctional
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/65/b8/134bf0187d5db42641e93a23c90e0ea20dcda2a8c148147ccc07ecde56e4/PyFunctional-1.4.3.tar.gz
BuildArch:	noarch

Requires:	python3-dill
Requires:	python3-tabulate
Requires:	python3-pandas

%description
`map(func)/select(func)` | Maps `func` onto elements of sequence | transformation
`starmap(func)/smap(func)` | Apply `func` to sequence with `itertools.starmap` | transformation
`filter(func)/where(func)` | Filters elements of sequence to only those where `func(element)` is `True` | transformation
`filter_not(func)` | Filters elements of sequence to only those where `func(element)` is `False` | transformation
`flatten()` | Flattens sequence of lists to a single sequence | transformation
`flat_map(func)` | `func` must return an iterable. Maps `func` to each element, then merges the result to one flat sequence | transformation
`group_by(func)` | Groups sequence into `(key, value)` pairs where `key=func(element)` and `value` is from the original sequence | transformation
`group_by_key()` | Groups sequence of `(key, value)` pairs by `key` | transformation
`reduce_by_key(func)` | Reduces list of `(key, value)` pairs using `func` | transformation
`count_by_key()` | Counts occurrences of each `key` in list of `(key, value)` pairs | transformation
`count_by_value()` | Counts occurrence of each value in a list | transformation
`union(other)` | Union of unique elements in sequence and `other` | transformation
`intersection(other)` | Intersection of unique elements in sequence and `other` | transformation
`difference(other)` | New sequence with unique elements present in sequence but not in `other` | transformation
`symmetric_difference(other)` | New sequence with unique elements present in sequence or `other`, but not both | transformation
`distinct()` | Returns distinct elements of sequence. Elements must be hashable | transformation
`distinct_by(func)` | Returns distinct elements of sequence using `func` as a key | transformation
`drop(n)` | Drop the first `n` elements of the sequence | transformation
`drop_right(n)` | Drop the last `n` elements of the sequence | transformation
`drop_while(func)` | Drop elements while `func` evaluates to `True`, then returns the rest | transformation
`take(n)` | Returns sequence of first `n` elements | transformation
`take_while(func)` | Take elements while `func` evaluates to `True`, then drops the rest | transformation
`init()` | Returns sequence without the last element | transformation
`tail()` | Returns sequence without the first element | transformation
`inits()` | Returns consecutive inits of sequence | transformation
`tails()` | Returns consecutive tails of sequence | transformation
`zip(other)` | Zips the sequence with `other` | transformation
`zip_with_index(start=0)` | Zips the sequence with the index starting at `start` on the right side | transformation
`enumerate(start=0)` | Zips the sequence with the index starting at `start` on the left side | transformation
`cartesian(*iterables, repeat=1)` | Returns cartesian product from itertools.product | transformation
`inner_join(other)` | Returns inner join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`outer_join(other)` | Returns outer join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`left_join(other)` | Returns left join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`right_join(other)` | Returns right join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`join(other, join_type='inner')` | Returns join of sequence with other as specified by `join_type`. Must be a sequence of `(key, value)` pairs | transformation
`partition(func)` | Partitions the sequence into elements which satisfy `func(element)` and those that don't | transformation
`grouped(size)` | Partitions the elements into groups of size `size` | transformation
`sorted(key=None, reverse=False)/order_by(func)` | Returns elements sorted according to python `sorted` | transformation
`reverse()` | Returns the reversed sequence | transformation
`slice(start, until)` | Sequence starting at `start` and including elements up to `until` | transformation
`head()` / `first()` | Returns first element in sequence | action
`head_option()` | Returns first element in sequence or `None` if its empty | action
`last()` | Returns last element in sequence | action
`last_option()` | Returns last element in sequence or `None` if its empty | action
`len()` / `size()` | Returns length of sequence | action
`count(func)` | Returns count of elements in sequence where `func(element)` is True | action
`empty()` | Returns `True` if the sequence has zero length | action
`non_empty()` | Returns `True` if sequence has non-zero length | action
`all()` | Returns `True` if all elements in sequence are truthy | action
`exists(func)` | Returns `True` if `func(element)` for any element in the sequence is `True` | action
`for_all(func)` | Returns `True` if `func(element)` is `True` for all elements in the sequence | action
`find(func)` | Returns the element that first evaluates `func(element)` to `True` | action
`any()` | Returns `True` if any element in sequence is truthy | action
`max()` | Returns maximal element in sequence | action
`min()` | Returns minimal element in sequence | action
`max_by(func)` | Returns element with maximal value `func(element)` | action
`min_by(func)` | Returns element with minimal value `func(element)` | action
`sum()/sum(projection)` | Returns the sum of elements possibly using a projection | action
`product()/product(projection)` | Returns the product of elements possibly using a projection | action
`average()/average(projection)` | Returns the average of elements possibly using a projection | action
`aggregate(func)/aggregate(seed, func)/aggregate(seed, func, result_map)` | Aggregate using `func` starting with `seed` or first element of list then apply `result_map` to the result | action
`fold_left(zero_value, func)` | Reduces element from left to right using `func` and initial value `zero_value` | action
`fold_right(zero_value, func)` | Reduces element from right to left using `func` and initial value `zero_value` | action
`make_string(separator)` | Returns string with `separator` between each `str(element)` | action
`dict(default=None)` / `to_dict(default=None)` | Converts a sequence of `(Key, Value)` pairs to a `dictionary`. If `default` is not None, it must be a value or zero argument callable which will be used to create a `collections.defaultdict` | action
`list()` / `to_list()` | Converts sequence to a list | action
`set() / to_set()` | Converts sequence to a set | action
`to_file(path)` | Saves the sequence to a file at path with each element on a newline | action
`to_csv(path)` | Saves the sequence to a csv file at path with each element representing a row | action
`to_jsonl(path)` | Saves the sequence to a jsonl file with each element being transformed to json and printed to a new line | action
`to_json(path)` | Saves the sequence to a json file. The contents depend on if the json root is an array or dictionary | action
`to_sqlite3(conn, tablename_or_query, *args, **kwargs)` | Save the sequence to a SQLite3 db. The target table must be created in advance. | action
`to_pandas(columns=None)` | Converts the sequence to a pandas DataFrame | action
`cache()` | Forces evaluation of sequence immediately and caches the result | action
`for_each(func)` | Executes `func` on each element of the sequence | action
### Lazy Execution
Whenever possible, `PyFunctional` will compute lazily. This is accomplished by tracking the list
of transformations that have been applied to the sequence and only evaluating them when an action is
called. In `PyFunctional` this is called tracking lineage. This is also responsible for the
ability for `PyFunctional` to cache results of computation to prevent expensive re-computation.
This is predominantly done to preserve sensible behavior and used sparingly. For example, calling
`size()` will cache the underlying sequence. If this was not done and the input was an iterator,
then further calls would operate on an expired iterator since it was used to compute the length.
Similarly, `repr` also caches since it is most often used during interactive sessions where its
undesirable to keep recomputing the same value. Below are some examples of inspecting lineage.
```python
def times_2(x):
    print(x)
    return 2 * x
elements = seq(1, 1, 2, 3, 4).map(times_2).distinct()
elements._lineage
# Lineage: sequence -> map(times_2) -> distinct
l_elements = elements.to_list()
# Prints: 1
# Prints: 1
# Prints: 2
# Prints: 3
# Prints: 4
elements._lineage
# Lineage: sequence -> map(times_2) -> distinct -> cache
l_elements = elements.to_list()
# The cached result is returned so times_2 is not called and nothing is printed
```
Files are given special treatment if opened through the `seq.open` and related APIs.
`functional.util.ReusableFile` implements a wrapper around the standard python file to support
multiple iteration over a single file object while correctly handling iteration termination and
file closing.
## Road Map Idea
* SQL based query planner and interpreter
* `_` lambda operator
## Contributing and Bug Fixes
Any contributions or bug reports are welcome. Thus far, there is a 100% acceptance rate for pull
requests and contributors have offered valuable feedback and critique on code. It is great to hear
from users of the package, especially what it is used for, what works well, and what could be
improved.
To contribute, create a fork of `PyFunctional`, make your changes, then make sure that they pass.
In order to be merged, all pull requests must:
* Pass all the unit tests
* Pass all the pylint tests, or ignore warnings with explanation of why its correct to do so
* Not significantly reduce covrage without a good reason [coveralls.io](coveralls.io/github/EntilZha/PyFunctional))
* Edit the `CHANGELOG.md` file in the `Next Release` heading with changes
## Contact
[Gitter for chat](https://gitter.im/EntilZha/PyFunctional)
## Supported Python Versions
* `PyFunctional` 1.4 and above supports and is tested against Python 3.6, Python 3.7, and PyPy3
* `PyFunctional` 1.4 and above does not support python 2.7
* `PyFunctional` 1.4 and above works in Python 3.5, but is not tested against it
* `PyFunctional` 1.4 and above partially works in 3.8, parallel processing currently has issues, but other feature work fine
* `PyFunctional` 1.3 and below supports and was tested against Python 2.7, Python 3.5, Python 3.6, PyPy2, and PyPy3
## Changelog
[Changelog](https://github.com/EntilZha/PyFunctional/blob/master/CHANGELOG.md)
## About me
To learn more about me (the author) visit my webpage at
[pedro.ai](https://www.pedro.ai).
I created `PyFunctional` while using Python extensivel, and finding that I missed the
ease of use for manipulating data that Spark RDDs and Scala collections have. The project takes the
best ideas from these APIs as well as LINQ to provide an easy way to manipulate data when using
Scala is not an option or PySpark is overkill.
## Contributors
These people have generously contributed their time to improving `PyFunctional`
* [versae](https://github.com/versae)
* [adrian17](https://github.com/adrian17)
* [lucidfrontier45](https://github.com/lucidfrontier45)
* [Digenis](https://github.com/Digenis)
* [ChuyuHsu](https://github.com/ChuyuHsu)
* [jsemric](https://github.com/jsemric)

%package -n python3-pyfunctional
Summary:	Package for creating data pipelines with chain functional programming
Provides:	python-pyfunctional
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-pyfunctional
`map(func)/select(func)` | Maps `func` onto elements of sequence | transformation
`starmap(func)/smap(func)` | Apply `func` to sequence with `itertools.starmap` | transformation
`filter(func)/where(func)` | Filters elements of sequence to only those where `func(element)` is `True` | transformation
`filter_not(func)` | Filters elements of sequence to only those where `func(element)` is `False` | transformation
`flatten()` | Flattens sequence of lists to a single sequence | transformation
`flat_map(func)` | `func` must return an iterable. Maps `func` to each element, then merges the result to one flat sequence | transformation
`group_by(func)` | Groups sequence into `(key, value)` pairs where `key=func(element)` and `value` is from the original sequence | transformation
`group_by_key()` | Groups sequence of `(key, value)` pairs by `key` | transformation
`reduce_by_key(func)` | Reduces list of `(key, value)` pairs using `func` | transformation
`count_by_key()` | Counts occurrences of each `key` in list of `(key, value)` pairs | transformation
`count_by_value()` | Counts occurrence of each value in a list | transformation
`union(other)` | Union of unique elements in sequence and `other` | transformation
`intersection(other)` | Intersection of unique elements in sequence and `other` | transformation
`difference(other)` | New sequence with unique elements present in sequence but not in `other` | transformation
`symmetric_difference(other)` | New sequence with unique elements present in sequence or `other`, but not both | transformation
`distinct()` | Returns distinct elements of sequence. Elements must be hashable | transformation
`distinct_by(func)` | Returns distinct elements of sequence using `func` as a key | transformation
`drop(n)` | Drop the first `n` elements of the sequence | transformation
`drop_right(n)` | Drop the last `n` elements of the sequence | transformation
`drop_while(func)` | Drop elements while `func` evaluates to `True`, then returns the rest | transformation
`take(n)` | Returns sequence of first `n` elements | transformation
`take_while(func)` | Take elements while `func` evaluates to `True`, then drops the rest | transformation
`init()` | Returns sequence without the last element | transformation
`tail()` | Returns sequence without the first element | transformation
`inits()` | Returns consecutive inits of sequence | transformation
`tails()` | Returns consecutive tails of sequence | transformation
`zip(other)` | Zips the sequence with `other` | transformation
`zip_with_index(start=0)` | Zips the sequence with the index starting at `start` on the right side | transformation
`enumerate(start=0)` | Zips the sequence with the index starting at `start` on the left side | transformation
`cartesian(*iterables, repeat=1)` | Returns cartesian product from itertools.product | transformation
`inner_join(other)` | Returns inner join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`outer_join(other)` | Returns outer join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`left_join(other)` | Returns left join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`right_join(other)` | Returns right join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`join(other, join_type='inner')` | Returns join of sequence with other as specified by `join_type`. Must be a sequence of `(key, value)` pairs | transformation
`partition(func)` | Partitions the sequence into elements which satisfy `func(element)` and those that don't | transformation
`grouped(size)` | Partitions the elements into groups of size `size` | transformation
`sorted(key=None, reverse=False)/order_by(func)` | Returns elements sorted according to python `sorted` | transformation
`reverse()` | Returns the reversed sequence | transformation
`slice(start, until)` | Sequence starting at `start` and including elements up to `until` | transformation
`head()` / `first()` | Returns first element in sequence | action
`head_option()` | Returns first element in sequence or `None` if its empty | action
`last()` | Returns last element in sequence | action
`last_option()` | Returns last element in sequence or `None` if its empty | action
`len()` / `size()` | Returns length of sequence | action
`count(func)` | Returns count of elements in sequence where `func(element)` is True | action
`empty()` | Returns `True` if the sequence has zero length | action
`non_empty()` | Returns `True` if sequence has non-zero length | action
`all()` | Returns `True` if all elements in sequence are truthy | action
`exists(func)` | Returns `True` if `func(element)` for any element in the sequence is `True` | action
`for_all(func)` | Returns `True` if `func(element)` is `True` for all elements in the sequence | action
`find(func)` | Returns the element that first evaluates `func(element)` to `True` | action
`any()` | Returns `True` if any element in sequence is truthy | action
`max()` | Returns maximal element in sequence | action
`min()` | Returns minimal element in sequence | action
`max_by(func)` | Returns element with maximal value `func(element)` | action
`min_by(func)` | Returns element with minimal value `func(element)` | action
`sum()/sum(projection)` | Returns the sum of elements possibly using a projection | action
`product()/product(projection)` | Returns the product of elements possibly using a projection | action
`average()/average(projection)` | Returns the average of elements possibly using a projection | action
`aggregate(func)/aggregate(seed, func)/aggregate(seed, func, result_map)` | Aggregate using `func` starting with `seed` or first element of list then apply `result_map` to the result | action
`fold_left(zero_value, func)` | Reduces element from left to right using `func` and initial value `zero_value` | action
`fold_right(zero_value, func)` | Reduces element from right to left using `func` and initial value `zero_value` | action
`make_string(separator)` | Returns string with `separator` between each `str(element)` | action
`dict(default=None)` / `to_dict(default=None)` | Converts a sequence of `(Key, Value)` pairs to a `dictionary`. If `default` is not None, it must be a value or zero argument callable which will be used to create a `collections.defaultdict` | action
`list()` / `to_list()` | Converts sequence to a list | action
`set() / to_set()` | Converts sequence to a set | action
`to_file(path)` | Saves the sequence to a file at path with each element on a newline | action
`to_csv(path)` | Saves the sequence to a csv file at path with each element representing a row | action
`to_jsonl(path)` | Saves the sequence to a jsonl file with each element being transformed to json and printed to a new line | action
`to_json(path)` | Saves the sequence to a json file. The contents depend on if the json root is an array or dictionary | action
`to_sqlite3(conn, tablename_or_query, *args, **kwargs)` | Save the sequence to a SQLite3 db. The target table must be created in advance. | action
`to_pandas(columns=None)` | Converts the sequence to a pandas DataFrame | action
`cache()` | Forces evaluation of sequence immediately and caches the result | action
`for_each(func)` | Executes `func` on each element of the sequence | action
### Lazy Execution
Whenever possible, `PyFunctional` will compute lazily. This is accomplished by tracking the list
of transformations that have been applied to the sequence and only evaluating them when an action is
called. In `PyFunctional` this is called tracking lineage. This is also responsible for the
ability for `PyFunctional` to cache results of computation to prevent expensive re-computation.
This is predominantly done to preserve sensible behavior and used sparingly. For example, calling
`size()` will cache the underlying sequence. If this was not done and the input was an iterator,
then further calls would operate on an expired iterator since it was used to compute the length.
Similarly, `repr` also caches since it is most often used during interactive sessions where its
undesirable to keep recomputing the same value. Below are some examples of inspecting lineage.
```python
def times_2(x):
    print(x)
    return 2 * x
elements = seq(1, 1, 2, 3, 4).map(times_2).distinct()
elements._lineage
# Lineage: sequence -> map(times_2) -> distinct
l_elements = elements.to_list()
# Prints: 1
# Prints: 1
# Prints: 2
# Prints: 3
# Prints: 4
elements._lineage
# Lineage: sequence -> map(times_2) -> distinct -> cache
l_elements = elements.to_list()
# The cached result is returned so times_2 is not called and nothing is printed
```
Files are given special treatment if opened through the `seq.open` and related APIs.
`functional.util.ReusableFile` implements a wrapper around the standard python file to support
multiple iteration over a single file object while correctly handling iteration termination and
file closing.
## Road Map Idea
* SQL based query planner and interpreter
* `_` lambda operator
## Contributing and Bug Fixes
Any contributions or bug reports are welcome. Thus far, there is a 100% acceptance rate for pull
requests and contributors have offered valuable feedback and critique on code. It is great to hear
from users of the package, especially what it is used for, what works well, and what could be
improved.
To contribute, create a fork of `PyFunctional`, make your changes, then make sure that they pass.
In order to be merged, all pull requests must:
* Pass all the unit tests
* Pass all the pylint tests, or ignore warnings with explanation of why its correct to do so
* Not significantly reduce covrage without a good reason [coveralls.io](coveralls.io/github/EntilZha/PyFunctional))
* Edit the `CHANGELOG.md` file in the `Next Release` heading with changes
## Contact
[Gitter for chat](https://gitter.im/EntilZha/PyFunctional)
## Supported Python Versions
* `PyFunctional` 1.4 and above supports and is tested against Python 3.6, Python 3.7, and PyPy3
* `PyFunctional` 1.4 and above does not support python 2.7
* `PyFunctional` 1.4 and above works in Python 3.5, but is not tested against it
* `PyFunctional` 1.4 and above partially works in 3.8, parallel processing currently has issues, but other feature work fine
* `PyFunctional` 1.3 and below supports and was tested against Python 2.7, Python 3.5, Python 3.6, PyPy2, and PyPy3
## Changelog
[Changelog](https://github.com/EntilZha/PyFunctional/blob/master/CHANGELOG.md)
## About me
To learn more about me (the author) visit my webpage at
[pedro.ai](https://www.pedro.ai).
I created `PyFunctional` while using Python extensivel, and finding that I missed the
ease of use for manipulating data that Spark RDDs and Scala collections have. The project takes the
best ideas from these APIs as well as LINQ to provide an easy way to manipulate data when using
Scala is not an option or PySpark is overkill.
## Contributors
These people have generously contributed their time to improving `PyFunctional`
* [versae](https://github.com/versae)
* [adrian17](https://github.com/adrian17)
* [lucidfrontier45](https://github.com/lucidfrontier45)
* [Digenis](https://github.com/Digenis)
* [ChuyuHsu](https://github.com/ChuyuHsu)
* [jsemric](https://github.com/jsemric)

%package help
Summary:	Development documents and examples for pyfunctional
Provides:	python3-pyfunctional-doc
%description help
`map(func)/select(func)` | Maps `func` onto elements of sequence | transformation
`starmap(func)/smap(func)` | Apply `func` to sequence with `itertools.starmap` | transformation
`filter(func)/where(func)` | Filters elements of sequence to only those where `func(element)` is `True` | transformation
`filter_not(func)` | Filters elements of sequence to only those where `func(element)` is `False` | transformation
`flatten()` | Flattens sequence of lists to a single sequence | transformation
`flat_map(func)` | `func` must return an iterable. Maps `func` to each element, then merges the result to one flat sequence | transformation
`group_by(func)` | Groups sequence into `(key, value)` pairs where `key=func(element)` and `value` is from the original sequence | transformation
`group_by_key()` | Groups sequence of `(key, value)` pairs by `key` | transformation
`reduce_by_key(func)` | Reduces list of `(key, value)` pairs using `func` | transformation
`count_by_key()` | Counts occurrences of each `key` in list of `(key, value)` pairs | transformation
`count_by_value()` | Counts occurrence of each value in a list | transformation
`union(other)` | Union of unique elements in sequence and `other` | transformation
`intersection(other)` | Intersection of unique elements in sequence and `other` | transformation
`difference(other)` | New sequence with unique elements present in sequence but not in `other` | transformation
`symmetric_difference(other)` | New sequence with unique elements present in sequence or `other`, but not both | transformation
`distinct()` | Returns distinct elements of sequence. Elements must be hashable | transformation
`distinct_by(func)` | Returns distinct elements of sequence using `func` as a key | transformation
`drop(n)` | Drop the first `n` elements of the sequence | transformation
`drop_right(n)` | Drop the last `n` elements of the sequence | transformation
`drop_while(func)` | Drop elements while `func` evaluates to `True`, then returns the rest | transformation
`take(n)` | Returns sequence of first `n` elements | transformation
`take_while(func)` | Take elements while `func` evaluates to `True`, then drops the rest | transformation
`init()` | Returns sequence without the last element | transformation
`tail()` | Returns sequence without the first element | transformation
`inits()` | Returns consecutive inits of sequence | transformation
`tails()` | Returns consecutive tails of sequence | transformation
`zip(other)` | Zips the sequence with `other` | transformation
`zip_with_index(start=0)` | Zips the sequence with the index starting at `start` on the right side | transformation
`enumerate(start=0)` | Zips the sequence with the index starting at `start` on the left side | transformation
`cartesian(*iterables, repeat=1)` | Returns cartesian product from itertools.product | transformation
`inner_join(other)` | Returns inner join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`outer_join(other)` | Returns outer join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`left_join(other)` | Returns left join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`right_join(other)` | Returns right join of sequence with other. Must be a sequence of `(key, value)` pairs | transformation
`join(other, join_type='inner')` | Returns join of sequence with other as specified by `join_type`. Must be a sequence of `(key, value)` pairs | transformation
`partition(func)` | Partitions the sequence into elements which satisfy `func(element)` and those that don't | transformation
`grouped(size)` | Partitions the elements into groups of size `size` | transformation
`sorted(key=None, reverse=False)/order_by(func)` | Returns elements sorted according to python `sorted` | transformation
`reverse()` | Returns the reversed sequence | transformation
`slice(start, until)` | Sequence starting at `start` and including elements up to `until` | transformation
`head()` / `first()` | Returns first element in sequence | action
`head_option()` | Returns first element in sequence or `None` if its empty | action
`last()` | Returns last element in sequence | action
`last_option()` | Returns last element in sequence or `None` if its empty | action
`len()` / `size()` | Returns length of sequence | action
`count(func)` | Returns count of elements in sequence where `func(element)` is True | action
`empty()` | Returns `True` if the sequence has zero length | action
`non_empty()` | Returns `True` if sequence has non-zero length | action
`all()` | Returns `True` if all elements in sequence are truthy | action
`exists(func)` | Returns `True` if `func(element)` for any element in the sequence is `True` | action
`for_all(func)` | Returns `True` if `func(element)` is `True` for all elements in the sequence | action
`find(func)` | Returns the element that first evaluates `func(element)` to `True` | action
`any()` | Returns `True` if any element in sequence is truthy | action
`max()` | Returns maximal element in sequence | action
`min()` | Returns minimal element in sequence | action
`max_by(func)` | Returns element with maximal value `func(element)` | action
`min_by(func)` | Returns element with minimal value `func(element)` | action
`sum()/sum(projection)` | Returns the sum of elements possibly using a projection | action
`product()/product(projection)` | Returns the product of elements possibly using a projection | action
`average()/average(projection)` | Returns the average of elements possibly using a projection | action
`aggregate(func)/aggregate(seed, func)/aggregate(seed, func, result_map)` | Aggregate using `func` starting with `seed` or first element of list then apply `result_map` to the result | action
`fold_left(zero_value, func)` | Reduces element from left to right using `func` and initial value `zero_value` | action
`fold_right(zero_value, func)` | Reduces element from right to left using `func` and initial value `zero_value` | action
`make_string(separator)` | Returns string with `separator` between each `str(element)` | action
`dict(default=None)` / `to_dict(default=None)` | Converts a sequence of `(Key, Value)` pairs to a `dictionary`. If `default` is not None, it must be a value or zero argument callable which will be used to create a `collections.defaultdict` | action
`list()` / `to_list()` | Converts sequence to a list | action
`set() / to_set()` | Converts sequence to a set | action
`to_file(path)` | Saves the sequence to a file at path with each element on a newline | action
`to_csv(path)` | Saves the sequence to a csv file at path with each element representing a row | action
`to_jsonl(path)` | Saves the sequence to a jsonl file with each element being transformed to json and printed to a new line | action
`to_json(path)` | Saves the sequence to a json file. The contents depend on if the json root is an array or dictionary | action
`to_sqlite3(conn, tablename_or_query, *args, **kwargs)` | Save the sequence to a SQLite3 db. The target table must be created in advance. | action
`to_pandas(columns=None)` | Converts the sequence to a pandas DataFrame | action
`cache()` | Forces evaluation of sequence immediately and caches the result | action
`for_each(func)` | Executes `func` on each element of the sequence | action
### Lazy Execution
Whenever possible, `PyFunctional` will compute lazily. This is accomplished by tracking the list
of transformations that have been applied to the sequence and only evaluating them when an action is
called. In `PyFunctional` this is called tracking lineage. This is also responsible for the
ability for `PyFunctional` to cache results of computation to prevent expensive re-computation.
This is predominantly done to preserve sensible behavior and used sparingly. For example, calling
`size()` will cache the underlying sequence. If this was not done and the input was an iterator,
then further calls would operate on an expired iterator since it was used to compute the length.
Similarly, `repr` also caches since it is most often used during interactive sessions where its
undesirable to keep recomputing the same value. Below are some examples of inspecting lineage.
```python
def times_2(x):
    print(x)
    return 2 * x
elements = seq(1, 1, 2, 3, 4).map(times_2).distinct()
elements._lineage
# Lineage: sequence -> map(times_2) -> distinct
l_elements = elements.to_list()
# Prints: 1
# Prints: 1
# Prints: 2
# Prints: 3
# Prints: 4
elements._lineage
# Lineage: sequence -> map(times_2) -> distinct -> cache
l_elements = elements.to_list()
# The cached result is returned so times_2 is not called and nothing is printed
```
Files are given special treatment if opened through the `seq.open` and related APIs.
`functional.util.ReusableFile` implements a wrapper around the standard python file to support
multiple iteration over a single file object while correctly handling iteration termination and
file closing.
## Road Map Idea
* SQL based query planner and interpreter
* `_` lambda operator
## Contributing and Bug Fixes
Any contributions or bug reports are welcome. Thus far, there is a 100% acceptance rate for pull
requests and contributors have offered valuable feedback and critique on code. It is great to hear
from users of the package, especially what it is used for, what works well, and what could be
improved.
To contribute, create a fork of `PyFunctional`, make your changes, then make sure that they pass.
In order to be merged, all pull requests must:
* Pass all the unit tests
* Pass all the pylint tests, or ignore warnings with explanation of why its correct to do so
* Not significantly reduce covrage without a good reason [coveralls.io](coveralls.io/github/EntilZha/PyFunctional))
* Edit the `CHANGELOG.md` file in the `Next Release` heading with changes
## Contact
[Gitter for chat](https://gitter.im/EntilZha/PyFunctional)
## Supported Python Versions
* `PyFunctional` 1.4 and above supports and is tested against Python 3.6, Python 3.7, and PyPy3
* `PyFunctional` 1.4 and above does not support python 2.7
* `PyFunctional` 1.4 and above works in Python 3.5, but is not tested against it
* `PyFunctional` 1.4 and above partially works in 3.8, parallel processing currently has issues, but other feature work fine
* `PyFunctional` 1.3 and below supports and was tested against Python 2.7, Python 3.5, Python 3.6, PyPy2, and PyPy3
## Changelog
[Changelog](https://github.com/EntilZha/PyFunctional/blob/master/CHANGELOG.md)
## About me
To learn more about me (the author) visit my webpage at
[pedro.ai](https://www.pedro.ai).
I created `PyFunctional` while using Python extensivel, and finding that I missed the
ease of use for manipulating data that Spark RDDs and Scala collections have. The project takes the
best ideas from these APIs as well as LINQ to provide an easy way to manipulate data when using
Scala is not an option or PySpark is overkill.
## Contributors
These people have generously contributed their time to improving `PyFunctional`
* [versae](https://github.com/versae)
* [adrian17](https://github.com/adrian17)
* [lucidfrontier45](https://github.com/lucidfrontier45)
* [Digenis](https://github.com/Digenis)
* [ChuyuHsu](https://github.com/ChuyuHsu)
* [jsemric](https://github.com/jsemric)

%prep
%autosetup -n pyfunctional-1.4.3

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-pyfunctional -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 1.4.3-1
- Package Spec generated