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awkward1-1.0.0rc1
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مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
Manipulate JSON-like data with NumPy-like idioms.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | awkward1-1.0.0rc1 |
| نام | awkward1 |
| نسخه کتابخانه | 1.0.0rc1 |
| نگهدارنده | ['Jim Pivarski'] |
| ایمیل نگهدارنده | ['pivarski@princeton.edu'] |
| نویسنده | Jim Pivarski |
| ایمیل نویسنده | pivarski@princeton.edu |
| آدرس صفحه اصلی | https://github.com/scikit-hep/awkward-1.0 |
| آدرس اینترنتی | https://pypi.org/project/awkward1/ |
| مجوز | BSD 3-clause |
<a href="https://github.com/scikit-hep/awkward-1.0#readme"><img src="https://github.com/scikit-hep/awkward-1.0/raw/main/docs-img/logo/logo-300px.png"></a>
Awkward Array is a library for **nested, variable-sized data**, including arbitrary-length lists, records, mixed types, and missing data, using **NumPy-like idioms**.
Arrays are **dynamically typed**, but operations on them are **compiled and fast**. Their behavior coincides with NumPy when array dimensions are regular and generalizes when they're not.
# Motivating example
Given an array of objects with `x`, `y` fields and variable-length nested lists like
```python
array = ak.Array([
[{"x": 1.1, "y": [1]}, {"x": 2.2, "y": [1, 2]}, {"x": 3.3, "y": [1, 2, 3]}],
[],
[{"x": 4.4, "y": {1, 2, 3, 4]}, {"x": 5.5, "y": [1, 2, 3, 4, 5]}]
])
```
the following slices out the `y` values, drops the first element from each inner list, and runs NumPy's `np.square` function on everything that is left:
```python
output = np.square(array["y", ..., 1:])
```
The result is
```python
[
[[], [4], [4, 9]],
[],
[[4, 9, 16], [4, 9, 16, 25]]
]
```
The equivalent using only Python is
```python
output = []
for sublist in array:
tmp1 = []
for record in sublist:
tmp2 = []
for number in record["y"][1:]:
tmp2.append(np.square(number))
tmp1.append(tmp2)
output.append(tmp1)
```
Not only is the expression using Awkward Arrays more concise, using idioms familiar from NumPy, but it's much faster and uses less memory.
For a similar problem 10 million times larger than the one above (on a single-threaded 2.2 GHz processor),
* the Awkward Array one-liner takes **4.6 seconds** to run and uses **2.1 GB** of memory,
* the equivalent using Python lists and dicts takes **138 seconds** to run and uses **22 GB** of memory.
Speed and memory factors in the double digits are common because we're replacing Python's dynamically typed, pointer-chasing virtual machine with type-specialized, precompiled routines on contiguous data. (In other words, for the same reasons as NumPy.) Even higher speedups are possible when Awkward Array is paired with [Numba](https://numba.pydata.org/).
Our [presentation at SciPy 2020](https://youtu.be/WlnUF3LRBj4) provides a good introduction, showing how to use these arrays in a real analysis.
# Installation
Awkward Array can be installed [from PyPI](https://pypi.org/project/awkward) using pip:
```bash
pip install awkward
```
You will likely get a precompiled binary (wheel), depending on your operating system and Python version. If not, pip attempts to compile from source (which requires a C++ compiler, make, and CMake).
Awkward Array is also available using [conda](https://anaconda.org/conda-forge/awkward), which always installs a binary:
```bash
conda install -c conda-forge awkward
```
If you have already added `conda-forge` as a channel, the `-c conda-forge` is unnecessary. Adding the channel is recommended because it ensures that all of your packages use compatible versions:
```bash
conda config --add channels conda-forge
conda update --all
```
## Getting help
<table>
<tr>
<td width="66%" valign="top">
<a href="https://awkward-array.org">
<img src="https://github.com/scikit-hep/awkward-1.0/raw/main/docs-img/panel-tutorials.png" width="570">
</a>
<p align="center"><b>
<a href="https://awkward-array.org">
How-to tutorials
</a>
</b></p>
</td>
<td width="33%" valign="top">
<a href="https://awkward-array.readthedocs.io/en/latest/index.html">
<img src="https://github.com/scikit-hep/awkward-1.0/raw/main/docs-img/panel-sphinx.png" width="268">
</a>
<p align="center"><b>
<a href="https://awkward-array.readthedocs.io/en/latest/index.html">
Python API reference
</a>
</b></p>
<a href="https://awkward-array.readthedocs.io/en/latest/_static/index.html">
<img src="https://github.com/scikit-hep/awkward-1.0/raw/main/docs-img/panel-doxygen.png" width="268">
</a>
<p align="center"><b>
<a href="https://awkward-array.readthedocs.io/en/latest/_static/index.html">
C++ API reference
</a>
</b></p>
</td>
</tr>
</table>
* Report bugs, request features, and ask for additional documentation on [GitHub Issues](https://github.com/scikit-hep/awkward-1.0/issues).
* If you have a "How do I...?" question, ask about it on [StackOverflow with the [awkward-array] tag](https://stackoverflow.com/questions/tagged/awkward-array). Be sure to include tags for any other libraries that you use, such as Pandas or PyTorch.
* To ask questions in real time, try the Gitter [Scikit-HEP/awkward-array](https://gitter.im/Scikit-HEP/awkward-array) chat room.
نیازمندی
| مقدار | نام |
|---|---|
| >=1.0.0 | awkward |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.* | Python |
نحوه نصب
نصب پکیج whl awkward1-1.0.0rc1:
pip install awkward1-1.0.0rc1.whl
نصب پکیج tar.gz awkward1-1.0.0rc1:
pip install awkward1-1.0.0rc1.tar.gz