Skip to main content

Speedb Python Binding

Project description

SpeeDict

Key-value storage supporting any python object

CI PyPI PyPI Support python versions

Introduction

This library has two purposes.

  1. As an on-disk key-value storage solution for Python.
  2. As a SpeeDB interface.

These two purposes operate in different modes:

  • Default mode, which allows storing int, float, bool, str, bytes, and other python objects (with Pickle).

  • Raw mode (options=Options(raw_mode=True)), which allows storing only bytes.

Installation

Wheels available, just pip install speedict.

Examples

A minimal example

from speedict import Rdict
import numpy as np
import pandas as pd

path = str("./test_dict")

# create a Rdict with default options at `path`
db = Rdict(path)
db[1.0] = 1
db["huge integer"] = 2343546543243564534233536434567543
db["good"] = True
db["bytes"] = b"bytes"
db["this is a list"] = [1, 2, 3]
db["store a dict"] = {0: 1}
db[b"numpy"] = np.array([1, 2, 3])
db["a table"] = pd.DataFrame({"a": [1, 2], "b": [2, 1]})

# reopen Rdict from disk
db.close()
db = Rdict(path)
assert db[1.0] == 1
assert db["huge integer"] == 2343546543243564534233536434567543
assert db["good"] == True
assert db["bytes"] == b"bytes"
assert db["this is a list"] == [1, 2, 3]
assert db["store a dict"] == {0: 1}
assert np.all(db[b"numpy"] == np.array([1, 2, 3]))
assert np.all(db["a table"] == pd.DataFrame({"a": [1, 2], "b": [2, 1]}))

# iterate through all elements
for k, v in db.items():
    print(f"{k} -> {v}")

# batch get:
print(db[["good", "bad", 1.0]])
# [True, False, 1]
 
# delete Rdict from dict
db.close()
Rdict.destroy(path)

An Example of Raw Mode

This mode allows only bytes as keys and values.

from speedict import Rdict, Options

PATH_TO_ROCKSDB = str("path")

# open raw_mode, which allows only bytes
db = Rdict(path=PATH_TO_ROCKSDB, options=Options(raw_mode=True))

db[b'a'] = b'a'
db[b'b'] = b'b'
db[b'c'] = b'c'
db[b'd'] = b'd'

for k, v in db.items():
    print(f"{k} -> {v}")

# close and delete
db.close()
Rdict.destroy(PATH_TO_ROCKSDB)

New Feature Since v0.3.3

Loading Options from RocksDict Path.

Load Options and add A New ColumnFamily

from speedict import Options, Rdict
path = str("./rocksdict_path")

opts, cols = Options.load_latest(path)
opts.create_missing_column_families(True)
cols["bytes"] = Options()
self.test_dict = Rdict(path, options=opts, column_families=cols)

Reopening RocksDB Reads DB Options Automatically

import shutil

from speedict import Rdict, Options, SliceTransform, PlainTableFactoryOptions
import os

def db_options():
    opt = Options()
    # create table
    opt.create_if_missing(True)
    # config to more jobs
    opt.set_max_background_jobs(os.cpu_count())
    # configure mem-table to a large value (256 MB)
    opt.set_write_buffer_size(0x10000000)
    opt.set_level_zero_file_num_compaction_trigger(4)
    # configure l0 and l1 size, let them have the same size (1 GB)
    opt.set_max_bytes_for_level_base(0x40000000)
    # 256 MB file size
    opt.set_target_file_size_base(0x10000000)
    # use a smaller compaction multiplier
    opt.set_max_bytes_for_level_multiplier(4.0)
    # use 8-byte prefix (2 ^ 64 is far enough for transaction counts)
    opt.set_prefix_extractor(SliceTransform.create_max_len_prefix(8))
    # set to plain-table
    opt.set_plain_table_factory(PlainTableFactoryOptions())
    return opt


# create DB
db = Rdict("./some_path", db_options())
db[0] = 1
db.close()

# automatic reloading all options on reopening
db = Rdict("./some_path")
assert db[0] == 1

# destroy
db.close()
Rdict.destroy("./some_path")

More Examples on BatchWrite, SstFileWrite, Snapshot, RocksDB Options, and etc.

Go to example folder.

Limitations

Currently, do not support merge operation and custom comparator.

Full Documentation

See rocksdict documentation.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

speedict-0.3.12-cp312-none-win_amd64.whl (2.8 MB view details)

Uploaded CPython 3.12 Windows x86-64

speedict-0.3.12-cp312-none-win32.whl (2.4 MB view details)

Uploaded CPython 3.12 Windows x86

speedict-0.3.12-cp312-cp312-manylinux_2_28_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.28+ x86-64

speedict-0.3.12-cp312-cp312-manylinux_2_28_aarch64.whl (5.0 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.28+ ARM64

speedict-0.3.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.2 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

speedict-0.3.12-cp312-cp312-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl (7.0 MB view details)

Uploaded CPython 3.12 macOS 10.14+ universal2 (ARM64, x86-64) macOS 10.14+ x86-64 macOS 11.0+ ARM64

speedict-0.3.12-cp311-none-win_amd64.whl (2.8 MB view details)

Uploaded CPython 3.11 Windows x86-64

speedict-0.3.12-cp311-none-win32.whl (2.4 MB view details)

Uploaded CPython 3.11 Windows x86

speedict-0.3.12-cp311-cp311-manylinux_2_28_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.28+ x86-64

speedict-0.3.12-cp311-cp311-manylinux_2_28_aarch64.whl (5.0 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.28+ ARM64

speedict-0.3.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.2 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

speedict-0.3.12-cp311-cp311-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl (7.0 MB view details)

Uploaded CPython 3.11 macOS 10.14+ universal2 (ARM64, x86-64) macOS 10.14+ x86-64 macOS 11.0+ ARM64

speedict-0.3.12-cp310-none-win_amd64.whl (2.8 MB view details)

Uploaded CPython 3.10 Windows x86-64

speedict-0.3.12-cp310-none-win32.whl (2.4 MB view details)

Uploaded CPython 3.10 Windows x86

speedict-0.3.12-cp310-cp310-manylinux_2_28_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.28+ x86-64

speedict-0.3.12-cp310-cp310-manylinux_2_28_aarch64.whl (5.0 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.28+ ARM64

speedict-0.3.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.2 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

speedict-0.3.12-cp310-cp310-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl (7.0 MB view details)

Uploaded CPython 3.10 macOS 10.14+ universal2 (ARM64, x86-64) macOS 10.14+ x86-64 macOS 11.0+ ARM64

speedict-0.3.12-cp39-none-win_amd64.whl (2.8 MB view details)

Uploaded CPython 3.9 Windows x86-64

speedict-0.3.12-cp39-none-win32.whl (2.4 MB view details)

Uploaded CPython 3.9 Windows x86

speedict-0.3.12-cp39-cp39-manylinux_2_28_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.28+ x86-64

speedict-0.3.12-cp39-cp39-manylinux_2_28_aarch64.whl (5.0 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.28+ ARM64

speedict-0.3.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.2 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

speedict-0.3.12-cp39-cp39-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl (7.0 MB view details)

Uploaded CPython 3.9 macOS 10.14+ universal2 (ARM64, x86-64) macOS 10.14+ x86-64 macOS 11.0+ ARM64

speedict-0.3.12-cp38-none-win_amd64.whl (2.8 MB view details)

Uploaded CPython 3.8 Windows x86-64

speedict-0.3.12-cp38-none-win32.whl (2.4 MB view details)

Uploaded CPython 3.8 Windows x86

speedict-0.3.12-cp38-cp38-manylinux_2_28_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.28+ x86-64

speedict-0.3.12-cp38-cp38-manylinux_2_28_aarch64.whl (5.0 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.28+ ARM64

speedict-0.3.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.2 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

speedict-0.3.12-cp38-cp38-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl (7.0 MB view details)

Uploaded CPython 3.8 macOS 10.14+ universal2 (ARM64, x86-64) macOS 10.14+ x86-64 macOS 11.0+ ARM64

speedict-0.3.12-cp37-none-win_amd64.whl (2.8 MB view details)

Uploaded CPython 3.7 Windows x86-64

speedict-0.3.12-cp37-none-win32.whl (2.4 MB view details)

Uploaded CPython 3.7 Windows x86

speedict-0.3.12-cp37-cp37m-manylinux_2_28_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.28+ x86-64

speedict-0.3.12-cp37-cp37m-manylinux_2_28_aarch64.whl (5.0 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.28+ ARM64

speedict-0.3.12-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.2 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

speedict-0.3.12-cp37-cp37m-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl (7.0 MB view details)

Uploaded CPython 3.7m macOS 10.14+ universal2 (ARM64, x86-64) macOS 10.14+ x86-64 macOS 11.0+ ARM64

File details

Details for the file speedict-0.3.12-cp312-none-win_amd64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp312-none-win_amd64.whl
Algorithm Hash digest
SHA256 532aedcf448007d293debfbcb3b95f0a89f5837faf0e0481e785f5cdeca38ab1
MD5 1450313e6e7a5068d7ebd81dc986206c
BLAKE2b-256 6d98f447e467fa7c76b6d0874458973310784539c458bb8e6b543c4073fbb72e

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp312-none-win32.whl.

File metadata

  • Download URL: speedict-0.3.12-cp312-none-win32.whl
  • Upload date:
  • Size: 2.4 MB
  • Tags: CPython 3.12, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for speedict-0.3.12-cp312-none-win32.whl
Algorithm Hash digest
SHA256 e6e05472e7eea5e4ead607831a62ea0d8617bd5a3debe85b8bb9c615b85fd9c4
MD5 a0f67d9c179ab00f2ab41897aee60da9
BLAKE2b-256 9fe7a500a6f19874809679f37139b6cc2b69e8063d7a329cd41b8100ff88214f

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 5ec1a786ed17cefc0c3205b6ce29e4acebef9a3af61777eb0fb22b4ad9ac13ea
MD5 8bfc66c8df3ec4a11a5d0899a824d173
BLAKE2b-256 7cb05ae30606da3c0c49dff06317a56c4a32074da43d0d777311fc18ba98d2ad

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp312-cp312-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp312-cp312-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 aaf83944fee9dc115506d5fb2bc24049f91a088da32272ab8e7e28684a6abfac
MD5 b74c8ee10385a570eb57f57bb1a75d4a
BLAKE2b-256 152fa08ba64eaacb726aa715d2ab574be2adbe5f2cc3bca64d8f15422a778e08

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 10ed33d39fb247a879c13ed472fbe347cbf08109e8d96716455beff0d6200b69
MD5 d2de4747cd1ed8e786302b84ffe40b72
BLAKE2b-256 5c3a8729cac4fac0b3af6e91c5c5a542bfb0268cbdf53d0fe6fde7417b49de6f

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp312-cp312-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp312-cp312-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl
Algorithm Hash digest
SHA256 349558a553c32ac3fd8d8c8f3783f1029ffff67036b27857c1be54e1dc99f94f
MD5 f9e7aeb79c4ba19061303c6cd2a06a99
BLAKE2b-256 b62a1a5e1e04a1a8ccb4679aa4aa0d786a6a706fb2b99d5b23f6bddf83f8dda3

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp311-none-win_amd64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp311-none-win_amd64.whl
Algorithm Hash digest
SHA256 cf04e816ac9106fe48d5a8420a694accc25fa6afda0161c851ca8f62e107067f
MD5 7cac1b1cf1f03e3542be7b2a0c99e55b
BLAKE2b-256 191d7dd7faf70f0a64235519ed984ae04798fd18da3d97b68cc5c6fd3dd860e2

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp311-none-win32.whl.

File metadata

  • Download URL: speedict-0.3.12-cp311-none-win32.whl
  • Upload date:
  • Size: 2.4 MB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for speedict-0.3.12-cp311-none-win32.whl
Algorithm Hash digest
SHA256 fbf5cc085d9cd6eed7de55311970b6003367ccf476beb806fe5b82d9f0e2e123
MD5 2a15f44ce6cab0aa5bb565133f2ab1d6
BLAKE2b-256 8eaa2e2d39915125dea7ce945bc3654060501dea99075c10ae876e32837d423b

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 cdfa2cce2755d1bcfb955bf70adae1066565a4c3930d52c7dfede6fb07e37a53
MD5 1969bda5fe67fcff09a6f9825d0cf4c4
BLAKE2b-256 6df59a018c0c7a92e2578e0253b09e9aaf9d30dd28a4928060a551a1850addda

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp311-cp311-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp311-cp311-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 e530421a1156d6648acfe3831f79f7a9956c06c9039d973cf8d205b8fc570208
MD5 f7b1bc2711c4419c8aa2a52131066ed0
BLAKE2b-256 09112430205cba51ed7b3729eef142a80048fad9be97e4bcc7e228651e2dd9d4

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 820a856f94ed7fae6cf0df9a4e1d9273134e4f574bf81946a5f7ab8de6a43897
MD5 b9538b75b89fc212b4d48dcdf12f7571
BLAKE2b-256 126643af93a92af8beb02abf8714b0ea8a97e4a0f54a332e9817355903115148

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp311-cp311-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp311-cp311-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl
Algorithm Hash digest
SHA256 e7bdbb14d1ada7a9980d2ef93c2fe7c23ccbff449042d37f2aab59b73a775a12
MD5 d84d05c727b1c199bab91fa14aa4e154
BLAKE2b-256 7e4b5972cec4eb277b4484ff774325a5a6841999fa4d4c131759b1e42b1bd0c9

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp310-none-win_amd64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp310-none-win_amd64.whl
Algorithm Hash digest
SHA256 447f8177ea9b05f33f4928d8f87303cc285b49273c4e9bb3b7c24401a495e0ba
MD5 a598ddeee6b8dc2b0c56cb8002746438
BLAKE2b-256 69d14d23bd45af328e02374935458c385ab35954d4dd368fe22adaf2df61edfa

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp310-none-win32.whl.

File metadata

  • Download URL: speedict-0.3.12-cp310-none-win32.whl
  • Upload date:
  • Size: 2.4 MB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for speedict-0.3.12-cp310-none-win32.whl
Algorithm Hash digest
SHA256 9d1c119e4624fb11557647007a875dac99cdce7af441c5539f9ca64434d53cf2
MD5 0be486d72e75efbef25e663dbbefb176
BLAKE2b-256 3fd9466eecaa3348898348ac5c7bbfe2a86032301a43d1629a7fd8ea833ee464

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 7ad77167e30e1974a190ff388fb4b2cd90913bc3fc58f55371484e5d8870f5a5
MD5 77fe4bc9ca36b68f4f5b5700fbdcec3b
BLAKE2b-256 ab0182638ae1bff02885b567e9ba2b7c0a0cc5c68cd124d911fd35fc335cd56c

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp310-cp310-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp310-cp310-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 14c3f5618f131ac786a5e58dab7fc89e7c96e011eeef01fc191f3c9f08c08b2a
MD5 8fe6f6333f4a715ed82c038e105a9104
BLAKE2b-256 a65c86779993d2b71d67a07b120783cdcb24026b8fe0c118d3c475eadd68a5ce

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0ed7c5d713683dfaa49736363c647f2a627422efbad890f8531be2014e816666
MD5 a56112987b68a05e46e983f25abf55b6
BLAKE2b-256 88bfcc506602798a6ee578e9ea54b06f12ac01f084be39b0615569447e49673f

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp310-cp310-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp310-cp310-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl
Algorithm Hash digest
SHA256 8a8b9bbcd2bae9dcf6e233b79adccae253adfb0ac30c908aaf059eb5eb4c1ba4
MD5 7f0f9c3934da71a6a28484cbbb62c530
BLAKE2b-256 ef44eb508a9aa5e2c1a25626fb2cf24588505c0c71ac938ad481147bdb2caa59

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp39-none-win_amd64.whl.

File metadata

  • Download URL: speedict-0.3.12-cp39-none-win_amd64.whl
  • Upload date:
  • Size: 2.8 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for speedict-0.3.12-cp39-none-win_amd64.whl
Algorithm Hash digest
SHA256 52556bf1b8222dc1a06b8861fcf8ee3d437673ad2d25a535f2cf0f11ee1e0b5d
MD5 a0eda6aeb9b75fb05e9bca1f9f9b5ce0
BLAKE2b-256 60394dc4fb55f37947b6bf4526dd97f530678d33ed5008f572f6aa786f159a4e

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp39-none-win32.whl.

File metadata

  • Download URL: speedict-0.3.12-cp39-none-win32.whl
  • Upload date:
  • Size: 2.4 MB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for speedict-0.3.12-cp39-none-win32.whl
Algorithm Hash digest
SHA256 5331a5b9640d61ac76951f8ce3cc58313d3e20fbc338ba55aca32c82d592fe89
MD5 3a75be6fc4ba7f86ee47ab076b133211
BLAKE2b-256 66882f50297cfe506fb682a6cf50556477859ba22f7f8db72fbffd2b77abc340

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 70984623badd07fef80d076bc8c24c083d73e9288262899ba79bf822067740b9
MD5 3ef316b8f5f89540b04421576b3e2318
BLAKE2b-256 93b9f9ab84082a16d5c60039c8487323423c6affc8f59202e529edc23606506e

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp39-cp39-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp39-cp39-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 7ab409d6ab915097ebaf42f3b581ab8efd56685d9854a23ade8a60ec2189e352
MD5 ff4515bbb339d143651a91e62a35f7c0
BLAKE2b-256 b6bde319dd5187b7d2a62eb7c802433240342266b4046259fc76cf5b04c16893

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fcca71dbe3b7a368511ffd72bdef3ee7ad44c22f7c808133aa0b87e02608774e
MD5 ea2630a9f9e3c5d7a731f8e65131526a
BLAKE2b-256 3497d6eed12c73bd960ca842645335d5f17eb69379ae8d1960649ea55152596e

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp39-cp39-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp39-cp39-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl
Algorithm Hash digest
SHA256 73c8011367bb3367ad96117a0bf96889283a8fa6514247f5f34ae10cf5cb8ec2
MD5 cba7c32587137984edb373b11e8a9b35
BLAKE2b-256 6d1a41f809a3b433eac4a9275fa0997d3fd94dbc5853c94717ce78fcae56fc91

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp38-none-win_amd64.whl.

File metadata

  • Download URL: speedict-0.3.12-cp38-none-win_amd64.whl
  • Upload date:
  • Size: 2.8 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for speedict-0.3.12-cp38-none-win_amd64.whl
Algorithm Hash digest
SHA256 b8d2d589256e8ddf8e4bdba4c8197190d6666775165769622ca3949c7f13b447
MD5 bce3f46b487d5bfa4a84bc9ef8601875
BLAKE2b-256 7528a7370e79c2fd103fca724c92d9e2d6291e3f389fd6717a50f6204ebd401f

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp38-none-win32.whl.

File metadata

  • Download URL: speedict-0.3.12-cp38-none-win32.whl
  • Upload date:
  • Size: 2.4 MB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for speedict-0.3.12-cp38-none-win32.whl
Algorithm Hash digest
SHA256 8537c4a95e9e66159c47cc3c731d9c0ba14e0154990cc9435d20609014d81e05
MD5 1ec59f3ec5348cc97b94bdd995ae4722
BLAKE2b-256 00fa348136887d35cd04670a82d5d676d877574ef910a2732cdd22ff76c8a2c1

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp38-cp38-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp38-cp38-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1e1f603efd634fa584cbb1566e3be30755ad59aec687ff8510775c0c46cd8b48
MD5 6d2ee9ee61d326dd0a1d2157922ea2cb
BLAKE2b-256 55afbd2293156f7e095c3980adbc05eac800d257068cecf2ee5c3128524e6381

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp38-cp38-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp38-cp38-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 086547048c06875cc0c87f4eb940ed64e34b1d001df460a95524d4460706656b
MD5 1d8c3e2cdff0dbc9bdbe5bf1d4f876f9
BLAKE2b-256 3711a32e9ffc662a3cc5244a13b70b57241036e8b60ec51b1e424dfb89ecbac9

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 220ea77095fe2f0b40fa371c0cdec8c68ec0d3bd7989bf3b142b450bdea1fd2a
MD5 560b464bf1f30a7bff5388e9cc48f28b
BLAKE2b-256 b26b3fa0684fd868d586e0819549fededf3f8e554692cadd4cc974b6e187544e

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp38-cp38-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp38-cp38-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl
Algorithm Hash digest
SHA256 4321e211c32b0f982a8a83e0d3416835d1a6b5d5b249bf497e0b93d27b972e19
MD5 54bffdbef238baa866ad200371085e70
BLAKE2b-256 40b480278c73dc78b22c79f9a5b1ad71a0d840b556ac362a28a1966a05e2e7b7

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp37-none-win_amd64.whl.

File metadata

  • Download URL: speedict-0.3.12-cp37-none-win_amd64.whl
  • Upload date:
  • Size: 2.8 MB
  • Tags: CPython 3.7, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for speedict-0.3.12-cp37-none-win_amd64.whl
Algorithm Hash digest
SHA256 540d40c9e1806f96048218f33b201553758f233d057a51dd40d2937a892dcfd1
MD5 64dfe508d85b207403aa50e9a37f1307
BLAKE2b-256 5491cedc2a4d7adda8c5277f9b1ec52596921e8552423acb567bcdbfce7c36df

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp37-none-win32.whl.

File metadata

  • Download URL: speedict-0.3.12-cp37-none-win32.whl
  • Upload date:
  • Size: 2.4 MB
  • Tags: CPython 3.7, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for speedict-0.3.12-cp37-none-win32.whl
Algorithm Hash digest
SHA256 7f12ef6f26cb23bba799ece8113c78a03dfbe9eb02f3112406d9be13789fb929
MD5 ba2fc5316858905bbf7e7b5ef0beac1c
BLAKE2b-256 2270a43763b4bd271e1f654aaafc2672bd4df08b248fb4e2b328b2010b1aef63

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp37-cp37m-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp37-cp37m-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 228e852d1e5359f6412829ad54fbb9a1eecee1d94753d4d348041a0b85ede187
MD5 efc721366e205cdbaa55e532c444a3b4
BLAKE2b-256 b2c1ecb3f3f9bbb55117dc5a0259de232d3d522b521092794fd35f712d640997

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp37-cp37m-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp37-cp37m-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 f7f785898e286498936ac5b61bb2d53603986e45f5917f67f2a07d2ee5704f20
MD5 8e9537da23f2ebbbfa7db2c145d197db
BLAKE2b-256 6eb763985a92e8566160dd02f675b0b9cf2d779cb3b88d0b7e986320f00b2f83

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d12160a1d8ba132fe64ecda42a1930c9db003b62413bef07f2dc71ba4abba977
MD5 808cc761f3a59f07b124a14f40849059
BLAKE2b-256 7583ea68ac22feaea5a89ed231cd02ce82c5006d99ab4ca1578d3be65be1837f

See more details on using hashes here.

File details

Details for the file speedict-0.3.12-cp37-cp37m-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl.

File metadata

File hashes

Hashes for speedict-0.3.12-cp37-cp37m-macosx_10_14_x86_64.macosx_11_0_arm64.macosx_10_14_universal2.whl
Algorithm Hash digest
SHA256 e9404b51e351a2357051bf7145463d95ee1ecfb6e8f9ce08c4e6b2f2be2e9282
MD5 962698c28e70d12dc3e412ff29d0496d
BLAKE2b-256 3900e6c7cbf55c86e7b88acedf24662209d4f24eba67653e796359585747f8ca

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page