Database Abstraction Library

Navigation

Verified details

These details have been verified by PyPI
Owner
organization icon SQLAlchemy
Maintainers
Avatar for CaselIT from gravatar.com CaselIT

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Mike Bayer
  • Requires: Python !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, >=2.7
Classifiers

Project description

PyPI PyPI - Python Version PyPI - Downloads

The Python SQL Toolkit and Object Relational Mapper

Introduction

SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL. SQLAlchemy provides a full suite of well known enterprise-level persistence patterns, designed for efficient and high-performing database access, adapted into a simple and Pythonic domain language.

Major SQLAlchemy features include:

  • An industrial strength ORM, built from the core on the identity map, unit of work, and data mapper patterns. These patterns allow transparent persistence of objects using a declarative configuration system. Domain models can be constructed and manipulated naturally, and changes are synchronized with the current transaction automatically.

  • A relationally-oriented query system, exposing the full range of SQL’s capabilities explicitly, including joins, subqueries, correlation, and most everything else, in terms of the object model. Writing queries with the ORM uses the same techniques of relational composition you use when writing SQL. While you can drop into literal SQL at any time, it’s virtually never needed.

  • A comprehensive and flexible system of eager loading for related collections and objects. Collections are cached within a session, and can be loaded on individual access, all at once using joins, or by query per collection across the full result set.

  • A Core SQL construction system and DBAPI interaction layer. The SQLAlchemy Core is separate from the ORM and is a full database abstraction layer in its own right, and includes an extensible Python-based SQL expression language, schema metadata, connection pooling, type coercion, and custom types.

  • All primary and foreign key constraints are assumed to be composite and natural. Surrogate integer primary keys are of course still the norm, but SQLAlchemy never assumes or hardcodes to this model.

  • Database introspection and generation. Database schemas can be “reflected” in one step into Python structures representing database metadata; those same structures can then generate CREATE statements right back out - all within the Core, independent of the ORM.

SQLAlchemy’s philosophy:

  • SQL databases behave less and less like object collections the more size and performance start to matter; object collections behave less and less like tables and rows the more abstraction starts to matter. SQLAlchemy aims to accommodate both of these principles.

  • An ORM doesn’t need to hide the “R”. A relational database provides rich, set-based functionality that should be fully exposed. SQLAlchemy’s ORM provides an open-ended set of patterns that allow a developer to construct a custom mediation layer between a domain model and a relational schema, turning the so-called “object relational impedance” issue into a distant memory.

  • The developer, in all cases, makes all decisions regarding the design, structure, and naming conventions of both the object model as well as the relational schema. SQLAlchemy only provides the means to automate the execution of these decisions.

  • With SQLAlchemy, there’s no such thing as “the ORM generated a bad query” - you retain full control over the structure of queries, including how joins are organized, how subqueries and correlation is used, what columns are requested. Everything SQLAlchemy does is ultimately the result of a developer- initiated decision.

  • Don’t use an ORM if the problem doesn’t need one. SQLAlchemy consists of a Core and separate ORM component. The Core offers a full SQL expression language that allows Pythonic construction of SQL constructs that render directly to SQL strings for a target database, returning result sets that are essentially enhanced DBAPI cursors.

  • Transactions should be the norm. With SQLAlchemy’s ORM, nothing goes to permanent storage until commit() is called. SQLAlchemy encourages applications to create a consistent means of delineating the start and end of a series of operations.

  • Never render a literal value in a SQL statement. Bound parameters are used to the greatest degree possible, allowing query optimizers to cache query plans effectively and making SQL injection attacks a non-issue.

Documentation

Latest documentation is at:

https://www.sqlalchemy.org/docs/

Installation / Requirements

Full documentation for installation is at Installation.

Getting Help / Development / Bug reporting

Please refer to the SQLAlchemy Community Guide.

Code of Conduct

Above all, SQLAlchemy places great emphasis on polite, thoughtful, and constructive communication between users and developers. Please see our current Code of Conduct at Code of Conduct.

License

SQLAlchemy is distributed under the MIT license.

Project details

Verified details

These details have been verified by PyPI
Owner
organization icon SQLAlchemy
Maintainers
Avatar for CaselIT from gravatar.com CaselIT

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Mike Bayer
  • Requires: Python !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, >=2.7
Classifiers

Release history Release notifications | RSS feed

2.0.36

2.0.35

2.0.34

2.0.33

2.0.32

2.0.31

2.0.30

2.0.29

2.0.28

2.0.27

2.0.26

2.0.25

2.0.24

2.0.23

2.0.22

2.0.21

2.0.20

2.0.19

2.0.18

2.0.17

2.0.16

2.0.15

2.0.14

2.0.13

2.0.12

2.0.11

2.0.10

2.0.9

2.0.8

2.0.7

2.0.6

2.0.5.post1

2.0.5 yanked

Reason this release was yanked:

wheel files failed to build due to a test issue

2.0.4

2.0.3

2.0.2

2.0.1

2.0.0

2.0.0rc3 pre-release

2.0.0rc2 pre-release

2.0.0rc1 pre-release

2.0.0b4 pre-release

2.0.0b3 pre-release

2.0.0b2 pre-release

2.0.0b1 pre-release

1.4.54

1.4.53

1.4.52

1.4.51

1.4.50

1.4.49

1.4.48

1.4.47

1.4.46

1.4.45

1.4.44

1.4.43

1.4.42

1.4.41

1.4.40

1.4.39

1.4.38

1.4.37

1.4.36

1.4.35

1.4.34 yanked

Reason this release was yanked:

critical caching issue identified, 1.4.35 resolves

1.4.33 yanked

Reason this release was yanked:

Regression when inserting orm models using insert. See https://github.com/sqlalchemy/sqlalchemy/issues/7878

1.4.32

1.4.31

1.4.30

1.4.29

1.4.28

1.4.27

This version

1.4.26

1.4.25

1.4.24

1.4.23

1.4.22

1.4.21

1.4.20

1.4.19

1.4.18

1.4.17

1.4.16

1.4.15

1.4.14

1.4.13

1.4.12

1.4.11

1.4.10

1.4.9

1.4.8

1.4.7

1.4.6

1.4.5

1.4.4

1.4.3

1.4.2

1.4.1

1.4.0

1.4.0b3 pre-release

1.4.0b2 pre-release

1.4.0b1 pre-release

1.3.24

1.3.23

1.3.22

1.3.21

1.3.20

1.3.19

1.3.18

1.3.17

1.3.16

1.3.15

1.3.14

1.3.13

1.3.12

1.3.11

1.3.10

1.3.9

1.3.8

1.3.7

1.3.6

1.3.5

1.3.4

1.3.3

1.3.2

1.3.1

1.3.0

1.3.0b3 pre-release

1.3.0b2 pre-release

1.3.0b1 pre-release

1.2.19

1.2.18

1.2.17

1.2.16

1.2.15

1.2.14

1.2.13

1.2.12

1.2.11

1.2.10

1.2.9

1.2.8

1.2.7

1.2.6

1.2.5

1.2.4

1.2.3

1.2.2

1.2.1

1.2.0

1.2.0b3 pre-release

1.2.0b2 pre-release

1.2.0b1 pre-release

1.1.18

1.1.17

1.1.16

1.1.15

1.1.14

1.1.13

1.1.12

1.1.11

1.1.10

1.1.9

1.1.8

1.1.7

1.1.6

1.1.5

1.1.4

1.1.3

1.1.2

1.1.1

1.1.0

1.1.0b3 pre-release

1.1.0b2 pre-release

1.1.0b1 pre-release

1.0.19

1.0.18

1.0.17

1.0.16

1.0.15

1.0.14

1.0.13

1.0.12

1.0.11

1.0.10

1.0.9

1.0.8

1.0.7

1.0.6

1.0.5

1.0.4

1.0.3

1.0.2

1.0.1

1.0.0

1.0.0b5 pre-release

1.0.0b4 pre-release

1.0.0b3 pre-release

1.0.0b2 pre-release

1.0.0b1 pre-release

0.9.10

0.9.9

0.9.8

0.9.7

0.9.6

0.9.5

0.9.4

0.9.3

0.9.2

0.9.1

0.9.0

0.8.7

0.8.6

0.8.5

0.8.4

0.8.3

0.8.2

0.8.1

0.8.0

0.8.0b2 pre-release

0.7.10

0.7.9

0.7.8

0.7.7

0.7.6

0.7.5

0.7.4

0.7.3

0.7.2

0.7.1

0.7.0

0.6.9

0.6.8

0.6.7

0.6.6

0.6.5

0.6.4

0.6.3

0.6.2

0.6.1

0.6.0

0.6beta3 pre-release

0.6beta2 pre-release

0.6beta1 pre-release

0.5.8

0.5.7

0.5.6

0.5.5

0.5.4

0.5.3

0.5.2

0.5.1

0.5.0

0.5.0rc4 pre-release

0.5.0rc3 pre-release

0.5.0rc2 pre-release

0.5.0rc1 pre-release

0.5.0beta3 pre-release

0.5.0beta2 pre-release

0.5.0beta1 pre-release

0.4.8

0.4.7

0.4.6

0.4.5

0.4.4

0.4.3

0.4.2

0.4.2b pre-release

0.4.2a pre-release

0.4.1

0.4.0

0.4.0beta6 pre-release

0.4.0beta5 pre-release

0.4.0beta4 pre-release

0.4.0beta3 pre-release

0.4.0beta2 pre-release

0.4.0beta1 pre-release

0.3.11

0.3.10

0.3.9

0.3.8

0.3.7

0.3.6

0.3.5

0.3.4

0.3.3

0.3.2

0.3.1

0.3.0

0.2.8

0.2.7

0.2.6

0.2.5

0.2.4

0.2.3

0.2.2

0.2.1

0.2.0

0.1.7

0.1.6

0.1.5

0.1.4

0.1.3

0.1.2

0.1.1

0.1.0

Download files

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

Source Distribution

SQLAlchemy-1.4.26.tar.gz (7.8 MB view details)

Uploaded Source

Built Distributions

SQLAlchemy-1.4.26-cp310-cp310-win_amd64.whl (1.5 MB view details)

Uploaded CPython 3.10 Windows x86-64

SQLAlchemy-1.4.26-cp310-cp310-win32.whl (1.5 MB view details)

Uploaded CPython 3.10 Windows x86

SQLAlchemy-1.4.26-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.26-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp310-cp310-macosx_10_14_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.10 macOS 10.14+ x86-64

SQLAlchemy-1.4.26-cp39-cp39-win_amd64.whl (1.5 MB view details)

Uploaded CPython 3.9 Windows x86-64

SQLAlchemy-1.4.26-cp39-cp39-win32.whl (1.5 MB view details)

Uploaded CPython 3.9 Windows x86

SQLAlchemy-1.4.26-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.26-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp39-cp39-macosx_10_14_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.9 macOS 10.14+ x86-64

SQLAlchemy-1.4.26-cp38-cp38-win_amd64.whl (1.5 MB view details)

Uploaded CPython 3.8 Windows x86-64

SQLAlchemy-1.4.26-cp38-cp38-win32.whl (1.5 MB view details)

Uploaded CPython 3.8 Windows x86

SQLAlchemy-1.4.26-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.26-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp38-cp38-macosx_10_14_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.8 macOS 10.14+ x86-64

SQLAlchemy-1.4.26-cp37-cp37m-win_amd64.whl (1.5 MB view details)

Uploaded CPython 3.7m Windows x86-64

SQLAlchemy-1.4.26-cp37-cp37m-win32.whl (1.5 MB view details)

Uploaded CPython 3.7m Windows x86

SQLAlchemy-1.4.26-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.26-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp37-cp37m-macosx_10_14_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.7m macOS 10.14+ x86-64

SQLAlchemy-1.4.26-cp36-cp36m-win_amd64.whl (1.5 MB view details)

Uploaded CPython 3.6m Windows x86-64

SQLAlchemy-1.4.26-cp36-cp36m-win32.whl (1.5 MB view details)

Uploaded CPython 3.6m Windows x86

SQLAlchemy-1.4.26-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.26-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp36-cp36m-macosx_10_14_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.6m macOS 10.14+ x86-64

SQLAlchemy-1.4.26-cp27-cp27mu-manylinux_2_5_x86_64.manylinux1_x86_64.whl (1.6 MB view details)

Uploaded CPython 2.7mu manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp27-cp27m-win_amd64.whl (1.5 MB view details)

Uploaded CPython 2.7m Windows x86-64

SQLAlchemy-1.4.26-cp27-cp27m-win32.whl (1.5 MB view details)

Uploaded CPython 2.7m Windows x86

SQLAlchemy-1.4.26-cp27-cp27m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (1.6 MB view details)

Uploaded CPython 2.7m manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.26-cp27-cp27m-macosx_10_14_x86_64.whl (1.5 MB view details)

Uploaded CPython 2.7m macOS 10.14+ x86-64

File details

Details for the file SQLAlchemy-1.4.26.tar.gz.

File metadata

  • Download URL: SQLAlchemy-1.4.26.tar.gz
  • Upload date:
  • Size: 7.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.9.1 pkginfo/1.7.0 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.9.7

File hashes

Hashes for SQLAlchemy-1.4.26.tar.gz
Algorithm Hash digest
SHA256 6bc7f9d7d90ef55e8c6db1308a8619cd8f40e24a34f759119b95e7284dca351a
MD5 f023eaf3d126d4357eefc136da6a2fbb
BLAKE2b-256 ef92598c80e2818bf2cbf41741af022197c04a1089a95daaebb3c1825dc4c9c2

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 908fad32c53b17aad12d722379150c3c5317c422437e44032256a77df1746292
MD5 45bfa1bef8668e71181d62ee2cbab0d3
BLAKE2b-256 1edcb283289be422c846e1c2e1fdcd9646897d1749f56de6ff482f6cc7484af0

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp310-cp310-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp310-cp310-win32.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 7ef421c3887b39c6f352e5022a53ac18de8387de331130481cb956b2d029cad6
MD5 99cef3a9f8143cd7b751d7c253bf486f
BLAKE2b-256 3697635f90b4669ca00336fcbdb7c2587be582a4dd600e6ddaa558b7d9787291

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c46f013ff31b80cbe36410281675e1fb4eaf3e25c284fd8a69981c73f6fa4cb4
MD5 bcdf24bcc2a3e479eaff9074f135fb04
BLAKE2b-256 4b5a5730d9786697ad26f6196b0795021c296ea1e2758ec5c3f3a8bb63b04a93

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ad7e403fc1e3cb76e802872694e30d6ca6129b9bc6ad4e7caa48ca35f8a144f8
MD5 9b6bd837917a1a37d512860daf23f0bf
BLAKE2b-256 14da2b49dfd7699140d7cd2afa1a7a0c9dc9c13517a3df08b60bc4e7b9d87135

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 fb2aa74a6e3c2cebea38dd21633671841fbe70ea486053cba33d68e3e22ccc0a
MD5 0a4a90aebb318380949f70cecb9c500a
BLAKE2b-256 2c1eb1ee71f4b4bb74bc9a015a21eb18ff40f3072da5a8e8d4a23d18bf50813e

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp310-cp310-macosx_10_14_x86_64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp310-cp310-macosx_10_14_x86_64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.10, macOS 10.14+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12

File hashes

Hashes for SQLAlchemy-1.4.26-cp310-cp310-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 c24c01dcd03426a5fe5ee7af735906bec6084977b9027a3605d11d949a565c01
MD5 596d799b3e9694ca288f625cd5bd6fa8
BLAKE2b-256 371e234467c622463f43af83b1c87b17522a870557f313c09557f8ea7b3bb9eb

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 5c6774b34782116ad9bdec61c2dbce9faaca4b166a0bc8e7b03c2b870b121d94
MD5 d73d6fa563b7b864b67927855d6706e8
BLAKE2b-256 39eb2d9bdbd7dd2fe0ba5360658d84ad4e8995e313777cc81c7d6ecc01d0c973

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp39-cp39-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp39-cp39-win32.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 b86f762cee3709722ab4691981958cbec475ea43406a6916a7ec375db9cbd9e9
MD5 18072015addece9c94d7a6807da10d9d
BLAKE2b-256 2cdb49ec914fac60894bcf71ec33742778b0251d5587f3c099ee14e49de8ba7b

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 4a882dedb9dfa6f33524953c3e3d72bcf518a5defd6d5863150a821928b19ad3
MD5 6d16cedcd59afd2024c4faf57cba25ec
BLAKE2b-256 7a5bb533b9aec369271722cbeeea50ff3214b6a4aecf32301d3bb509d8f7b54e

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3c0c5f54560a92691d54b0768d67b4d3159e514b426cfcb1258af8c195577e8f
MD5 e2867c36b3195fa0740256bbfd2bc61a
BLAKE2b-256 395b8bfcc5e762f6d4ff4ad303aca4e909d2948cf28103d172b1427b5bdc2587

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 1dee515578d04bc80c4f9a8c8cfe93f455db725059e885f1b1da174d91c4d077
MD5 a757fec0ae9b9df56daadf7ad824975f
BLAKE2b-256 74dcc04d4912077df7ff4f5fab90ea0bdaaf0b3b8148a9dc4a9b9d66f6c56e9f

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp39-cp39-macosx_10_14_x86_64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp39-cp39-macosx_10_14_x86_64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.9, macOS 10.14+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12

File hashes

Hashes for SQLAlchemy-1.4.26-cp39-cp39-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 a6506c17b0b6016656783232d0bdd03fd333f1f654d51a14d93223f953903646
MD5 2f1b84da36a3c7d799aedb3a021bd1f3
BLAKE2b-256 97a265b33a3bacba081a87f6fd0f0b018c4b041724c0d3ded7936072e527791d

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 dbf588ab09e522ac2cbd010919a592c6aae2f15ccc3cd9a96d01c42fbc13f63e
MD5 d8281c1870b99b3ac2e4d519a43a5e36
BLAKE2b-256 f3b527617902569ae05e5c4b1a3108b856891a8e2bbef8ea9dd471bb84a3082f

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp38-cp38-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp38-cp38-win32.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 2ce42ad1f59eb85c55c44fb505f8854081ee23748f76b62a7f569cfa9b6d0604
MD5 ee5cc55ffe9fc0b3af5defcb24dd4538
BLAKE2b-256 9ff40112ecb72e6b4bf1067c15044a0dade168e1e1122fc5f7c5987405b8dc06

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 7e8ef103eaa72a857746fd57dda5b8b5961e8e82a528a3f8b7e2884d8506f0b7
MD5 cf86feba75c2caf51ab9271b1a5db47b
BLAKE2b-256 5e6a5c1700ff527f4af10228507ceea59f7c9542dc3b64109f206a76da670569

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2feb028dc75e13ba93456a42ac042b255bf94dbd692bf80b47b22653bb25ccf8
MD5 0546a6ef907dd51ffc0ba6965d800ec7
BLAKE2b-256 88ace46cf142b0fdcfd5368e3fb539ebdc5c9bd8a787eaf6dd61d34b02773ee8

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 31f4426cfad19b5a50d07153146b2bcb372a279975d5fa39f98883c0ef0f3313
MD5 5e07c748a2c7ae75c4cf27da62da3626
BLAKE2b-256 d7f8246217ce22dc47a0d57cdcad9922fe654f6d0f4eb18a7b47f60e9f74ec01

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp38-cp38-macosx_10_14_x86_64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp38-cp38-macosx_10_14_x86_64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.8, macOS 10.14+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12

File hashes

Hashes for SQLAlchemy-1.4.26-cp38-cp38-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 5039faa365e7522a8eb4736a54afd24a7e75dcc33b81ab2f0e6c456140f1ad64
MD5 5199301eb8398fcefcde248bd3a3a7e5
BLAKE2b-256 4d5d69244c7a28be5585650d1af023a1e9bdce9f32edd7c0ee568f300762911b

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 07ac4461a1116b317519ddf6f34bcb00b011b5c1370ebeaaf56595504ffc7e84
MD5 d78c7f44c99e879aa3811c137bdddb40
BLAKE2b-256 7cdcef6733fa0eb12ca1a9cf235d2a05095196dd66e471cebed62db459750714

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp37-cp37m-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 a95bf9c725012dcd7ea3cac16bf647054e0d62b31d67467d228338e6a163e4ff
MD5 cd4daa9f447a186554931ac7e2834532
BLAKE2b-256 2f9c484e6ecc206c99c20743055475d17031714ee9c4519ad2edb161af1fd137

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 4c185c928e2638af9bae13acc3f70e0096eac76471a1101a10f96b80666b8270
MD5 d55828352eecbaf3536d567ec89a534f
BLAKE2b-256 576b02c3a11ce005b2a77d80a22c6c6455d8bbe2bf9c03f16652d7f3603f68a8

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ff8f91a7b1c4a1c7772caa9efe640f2768828897044748f2458b708f1026e2d4
MD5 fb00eae2a1b5cbdc763097ee52593302
BLAKE2b-256 0b0d90ade42ef6219c77f8786538b55c19e736a45b3a9fc1e3bb7b91a85f85b0

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 bca660b76672e15d70a7dba5e703e1ce451a0257b6bd2028e62b0487885e8ae9
MD5 e1b5a8703a78646f9e097a3a5365f6cf
BLAKE2b-256 3b72ab3b7c24acdb5a0ec797b4b94e24e5367709bf03e9df7731b6bd62908cd8

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp37-cp37m-macosx_10_14_x86_64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp37-cp37m-macosx_10_14_x86_64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.7m, macOS 10.14+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12

File hashes

Hashes for SQLAlchemy-1.4.26-cp37-cp37m-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 f1e97c5f36b94542f72917b62f3a2f92be914b2cf33b80fa69cede7529241d2a
MD5 2c2061ea7431c3d290cc4c7587e14902
BLAKE2b-256 0906a4acfb7b9938515983826f0769e4c0462a56c18ab4ebd2b22b10432f9c3d

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 ba84026e84379326bbf2f0c50792f2ae56ab9c01937df5597b6893810b8ca369
MD5 ba891767f9306c827cf4e6210a980f6e
BLAKE2b-256 02b6fa23a921e093148275fab495bd6edff87628dc0d4d5474e18229e392c251

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp36-cp36m-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 cc6b21f19bc9d4cd77cbcba5f3b260436ce033f1053cea225b6efea2603d201e
MD5 02a0d614a736171e0fe1b9c0bfc58434
BLAKE2b-256 66f37265bcab23ed127768a36f2a897abceb2085f859c2a38370c8f24b74d452

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 090536fd23bf49077ee94ff97142bc5ee8bad24294c3d7c8d5284267c885dde7
MD5 5642fe39b275d4c69ce65ecb22fb8590
BLAKE2b-256 874ac0eb6a3155360b689e928dcf6a80e0752946b23bdc5700b668ed1385d7e9

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 295b90efef1278f27fe27d94a45460ae3c17f5c5c2b32c163e29c359740a1599
MD5 ba62eac7dac5c7dc0408c77482bc3bfa
BLAKE2b-256 18d5b2279610584462c0ad999f231099df50ffd9e1c32754e3153ce6d3508faa

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 e700d48056475d077f867e6a36e58546de71bdb6fdc3d34b879e3240827fefab
MD5 66d9b5fa7cff2980220d2bcc9bd8bfab
BLAKE2b-256 e2a05a63e8ff102332ad9523a3498302250c5184bba59162f0bb4b096e8dcaa8

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp36-cp36m-macosx_10_14_x86_64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp36-cp36m-macosx_10_14_x86_64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.6m, macOS 10.14+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12

File hashes

Hashes for SQLAlchemy-1.4.26-cp36-cp36m-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 1ef37c9ec2015ce2f0dc1084514e197f2f199d3dc3514190db7620b78e6004c8
MD5 7fb65761b9a556995209860610c04f27
BLAKE2b-256 ebac5a33d7a73f45d5c64e2a5a77da4476c240cd187c6b4668acab8a9af246a5

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp27-cp27mu-manylinux_2_5_x86_64.manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp27-cp27mu-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 c757ba1279b85b3460e72e8b92239dae6f8b060a75fb24b3d9be984dd78cfa55
MD5 00ea5eea92c789dc410176638e319060
BLAKE2b-256 0916a1130d63651f0a02824c38af3ba3b0fdeec0cab8fa900f613c48d49c23f1

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp27-cp27m-win_amd64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp27-cp27m-win_amd64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 2.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 463ef692259ff8189be42223e433542347ae17e33f91c1013e9c5c64e2798088
MD5 f36d32f6e9fa819eabe529d2e2a3996d
BLAKE2b-256 e375577084f4fcdc5c891390cf381b80877553be8907c5aef62fcba8ef83217b

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp27-cp27m-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp27-cp27m-win32.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 2.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.26-cp27-cp27m-win32.whl
Algorithm Hash digest
SHA256 de996756d894a2d52c132742e3b6d64ecd37e0919ddadf4dc3981818777c7e67
MD5 6a9735f7dfcf6506f8a3d58a2c9bb02a
BLAKE2b-256 99f3a4ea5d43dcc7f50b02cc1db14af922d73973229f6f22465227f4b4478f0f

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp27-cp27m-manylinux_2_5_x86_64.manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.26-cp27-cp27m-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 91efbda4e6d311812f23996242bad7665c1392209554f8a31ec6db757456db5c
MD5 c9393d806a19d83fea9565ccc149245e
BLAKE2b-256 36c6f1a39992f6636ac732ce884bb066224b89953762e5eca306f5a19d665dc7

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.26-cp27-cp27m-macosx_10_14_x86_64.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.26-cp27-cp27m-macosx_10_14_x86_64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 2.7m, macOS 10.14+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12

File hashes

Hashes for SQLAlchemy-1.4.26-cp27-cp27m-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 c2f2114b0968a280f94deeeaa31cfbac9175e6ac7bd3058b3ce6e054ecd762b3
MD5 a26b38daf4a44ea778fa85e2a9a09390
BLAKE2b-256 b49d06d4a64e648d3213bc6a719f3a5cc1d2a4ef2caf93df92d98110c0d01f87

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