Skip to main content

DB API Module for ODBC

Project description

A Python DB API 2 module for ODBC. This project provides an up-to-date, convenient interface to ODBC using native data types like datetime and decimal.

Project details


Download files

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

Source Distribution

pyodbc-4.0.18.tar.gz (214.1 kB view details)

Uploaded Source

Built Distributions

pyodbc-4.0.18-cp36-cp36m-win_amd64.whl (60.3 kB view details)

Uploaded CPython 3.6m Windows x86-64

pyodbc-4.0.18-cp36-cp36m-win32.whl (51.5 kB view details)

Uploaded CPython 3.6m Windows x86

pyodbc-4.0.18-cp36-cp36m-macosx_10_6_intel.whl (119.2 kB view details)

Uploaded CPython 3.6m macOS 10.6+ intel

pyodbc-4.0.18-cp35-cp35m-win_amd64.whl (60.3 kB view details)

Uploaded CPython 3.5m Windows x86-64

pyodbc-4.0.18-cp35-cp35m-win32.whl (51.5 kB view details)

Uploaded CPython 3.5m Windows x86

pyodbc-4.0.18-cp35-cp35m-macosx_10_6_intel.whl (119.3 kB view details)

Uploaded CPython 3.5m macOS 10.6+ intel

pyodbc-4.0.18-cp34-cp34m-win_amd64.whl (53.8 kB view details)

Uploaded CPython 3.4m Windows x86-64

pyodbc-4.0.18-cp34-cp34m-win32.whl (49.1 kB view details)

Uploaded CPython 3.4m Windows x86

pyodbc-4.0.18-cp34-cp34m-macosx_10_6_intel.whl (119.2 kB view details)

Uploaded CPython 3.4m macOS 10.6+ intel

pyodbc-4.0.18-cp27-none-macosx_10_13_intel.whl (116.5 kB view details)

Uploaded CPython 2.7 macOS 10.13+ intel

pyodbc-4.0.18-cp27-cp27m-win_amd64.whl (55.2 kB view details)

Uploaded CPython 2.7m Windows x86-64

pyodbc-4.0.18-cp27-cp27m-win32.whl (50.3 kB view details)

Uploaded CPython 2.7m Windows x86

File details

Details for the file pyodbc-4.0.18.tar.gz.

File metadata

  • Download URL: pyodbc-4.0.18.tar.gz
  • Upload date:
  • Size: 214.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for pyodbc-4.0.18.tar.gz
Algorithm Hash digest
SHA256 6ebc1279b237cf45d3652ceaf502da8c0eaa45fc047ded35f6c2f72086e656b9
MD5 b157ae41a539b846691aba5f86189b48
BLAKE2b-256 7c9b7391a27b4c948b9ef15a4373715b1ea042008b2b4a21ca8638f946f2c8d9

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 3f709c77249658e6966b412e9996324ced972c3338b7e3ff1be77752fddf4432
MD5 f38805f3b7fbcaf4fa245bf4fe8a9e89
BLAKE2b-256 fcb9e794382f99845a69ef73af579ab13e70d0260067666016793fca47e896b5

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp36-cp36m-win32.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 43c298520280123a14c070390526449cf49b6ac34e6b46bc9a30d7722515d979
MD5 cc316f3f9cb7c038930999f7686f8dfb
BLAKE2b-256 933fd46b17a7480bb9cdeb6861c0dca0b9b80e905e2c0a8e1ec92e4cfb1789d5

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp36-cp36m-macosx_10_6_intel.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp36-cp36m-macosx_10_6_intel.whl
Algorithm Hash digest
SHA256 75264f97cdf3df5454ac597ed07c0159450bc80ade0378d7346af4cafe385cbd
MD5 446187381961fc12c3255349cef8af08
BLAKE2b-256 883ea7fc6afd4e43d327b661451e144c6e580bfba18e6e48f963ca60efdbc47d

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp35-cp35m-win_amd64.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 8bec859780689f9eb4109c944b1f6159eaa0b9b46ad6898a5b40821d9f589b31
MD5 e3c919e90bf3571370ba33ac12b31d4d
BLAKE2b-256 c9e5f69fcbf4da738eb362c3fbde6d056cbde00693dfe838d7a2c598dc5b7bad

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp35-cp35m-win32.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp35-cp35m-win32.whl
Algorithm Hash digest
SHA256 88e05b009bfcf9adb887769579a474f10f7424b845b5be8068522d6baec568ec
MD5 0dd446f7726af0b9fc68d29e6ee528e8
BLAKE2b-256 46d4cef9209bce931cb1172afa39708f40158789eac56cca87203a6130e2963a

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp35-cp35m-macosx_10_6_intel.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp35-cp35m-macosx_10_6_intel.whl
Algorithm Hash digest
SHA256 3eedbbfabfba86e183e6a930c296403eabe7cc1298fa8381fd5108e7890af65e
MD5 ec23ccdcd0a35d071126630831e7b972
BLAKE2b-256 ef1367c3ed07602ea4546b4db15eea8b0b8ffa0cdf4fa1f19cffe4e456321415

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp34-cp34m-win_amd64.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp34-cp34m-win_amd64.whl
Algorithm Hash digest
SHA256 e5b6361f9c576cb321464176defdb5cace027cd8680ac3e6c79b74f6657f5abd
MD5 7e9a1dc269005a98b87b9e54db964e7d
BLAKE2b-256 e0c4732b9bbf2bf010689bbf9a15d019dd444144a0feb06c7ff2a1c23d1e0f38

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp34-cp34m-win32.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp34-cp34m-win32.whl
Algorithm Hash digest
SHA256 d454b4d1996abb1cdd04d2e8e18d4b5cecab4b64d91736468af0c2582cceb011
MD5 7f1346f82e13ed7ba13d7267fa0a35ce
BLAKE2b-256 4148720dead002cbc2d415563d625b7c32918c5ec9e3bbadcd7941f0d54e7b18

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp34-cp34m-macosx_10_6_intel.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp34-cp34m-macosx_10_6_intel.whl
Algorithm Hash digest
SHA256 e426b416602f934b43864a7483fa00b26567bf20d29cde69f518f53aa62381e1
MD5 932887ef22f1e149255cb2c1b1f5e441
BLAKE2b-256 3b6f253fc7f99c90e1a6c4802000bc89ec8979b5b20f113cfb5af3952abdf2d6

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp27-none-macosx_10_13_intel.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp27-none-macosx_10_13_intel.whl
Algorithm Hash digest
SHA256 764476887856f5dd1029b829537e2e22e9834de4ec8c78e4a9f818e064e565bb
MD5 015b8b9cc3c3407aae37954e1237791c
BLAKE2b-256 cfe5d565e8e10478453f51d0fcb904c1e798faaf60d718102f91ad4069a519e9

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp27-cp27m-win_amd64.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 382a985970d4be0cc86b50a818a03287cf2a879549c24f6b62065e166316cd2f
MD5 bb21fae17d2b61a4f28612e6c364fe93
BLAKE2b-256 94b78165a343b8aa591e8c523e62d418f1c1398cefc6628ec57f7cad0c416b12

See more details on using hashes here.

Provenance

File details

Details for the file pyodbc-4.0.18-cp27-cp27m-win32.whl.

File metadata

File hashes

Hashes for pyodbc-4.0.18-cp27-cp27m-win32.whl
Algorithm Hash digest
SHA256 e283eb7d77be80809817e10d0c42d88a490ab96929b8c443310850773a64d470
MD5 0d768237da3cce5493b51e038546fd6f
BLAKE2b-256 5c45e914b540a334a4756e78d8baed01c5fd8122612a429cbe770e389301fbcc

See more details on using hashes here.

Provenance

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