A blazingly fast datadict library
Project description
Teapy
Blazingly fast datadict library in Python
Teapy is a high-performance data dictionary library implemented in Rust, designed for blazingly fast operations. It offers the following features:
- Lazy evaluation
- Handling of NaN values
- Multi-threaded processing
- Support for any dimensionality
Setup
Install the latest teapy version with:
pip install teapy
Basic Usage
Creating Expressions
# Expressions can be created in various ways
import numpy as np
import pandas as pd
import polars as pl
import teapy as tp
e1 = tp.Expr([1, 2, 3]) # Create from a list
e2 = tp.Expr((1, 2, 3)) # Create from a tuple
e3 = tp.Expr(np.array([1, 2, 3]), 'e3') # Create from a numpy.ndarray, name is e3
e4 = tp.Expr(pd.Series([1, 2, 3])) # Create from a pandas.Series
e5 = tp.Expr(pl.Series([1, 2, 3])) # Create from a polars.Series
Creating DataDicts
# DataDicts can be created in different ways
dd1 = tp.DataDict({'a': [1, 2], 'b': [2, 3]}, c=[3, 4]) # Create from a dictionary
dd2 = tp.DataDict([tp.Expr([1, 2], 'a'), tp.Expr([2, 3], 'b')]) # Create from a list of expressions
dd3 = tp.DataDict(a=[1, 2], b=[2, 3], c=np.array([3, 6, 2])) # Create by specifying key-value pairs
Evaluating Expressions and DataDicts
# Evaluating Expressions
e = tp.Expr([1, 2, 3]).mean()
e.eval() # Execute the expression
e.view # View the memory of the array
e.eview() # Execute the expression and view the memory of the array
e.value() # Execute the expression and copy the memory of the array to a new numpy.ndarray
# Evaluating DataDicts
dd = tp.DataDict({'a': [1, 2]*10, 'b': [2, 3]*10}, c=[3, 4])
dd = dd.select([
dd['a'].ts_mean(3).alias('d'),
dd['b'].ts_std(4).alias('e')
])
dd.eval(['d', 'e']) # Evaluate specific keys in parallel
dd.eval() # Or evaluate all expressions in parallel
print(dd['d'])
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
teapy-0.4.18.tar.gz
(161.2 kB
view hashes)
Built Distributions
Close
Hashes for teapy-0.4.18-cp38-abi3-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b1b5b93a780a05e2b4ddff61ee90711e8ded9d2ec87edb3c55cc515d189a9409 |
|
MD5 | 3cf2d54d8fa5eaf5c9a5481e40a7232f |
|
BLAKE2b-256 | 320b3c615384c5de612d8df1e51f25e9470d0db6c13cb593c0f128bd9af366df |
Close
Hashes for teapy-0.4.18-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9d57f4d764863377df15a455b69d5526f165e2e92fc78618501ffbb73c45e50a |
|
MD5 | 4389e248c3145a3701cde6ed62846d04 |
|
BLAKE2b-256 | 69e8230e0684f4ff4f908b695b6a654266edd13e6f176f6092aa96da82a8cff5 |
Close
Hashes for teapy-0.4.18-cp38-abi3-macosx_11_0_arm64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1dd0e0fa1bff92faf10077bf0a19727b05f7d52b66475be69fa26850bc1263d3 |
|
MD5 | 1551efb783005cfbb12d6513bd7ebe6d |
|
BLAKE2b-256 | fc5d0689dae025fd656bf9be1920053c1c9e5533f39e0b1fc363a26b932f3cc0 |
Close
Hashes for teapy-0.4.18-cp38-abi3-macosx_10_7_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 71adb00cbebcb5c7cd524c46c83e9dece6026a87cf23963d8e356fb7d8016773 |
|
MD5 | ea1f57ba877c6f179de11bff530f0923 |
|
BLAKE2b-256 | c9c48a0825ae56a874af9856bb250d0b0bb48d27201e346f5cf09f0eb9907012 |