Skip to main content

ODPS Python SDK and data analysis framework

Project description

PyPI version Docs License Implementation

Elegent way to access ODPS API. Documentation

Installation

The quick way:

pip install pyodps[full]

To integrate with Mars:

pip install pyodps#egg=pyodps[mars]

If you don’t need to use Jupyter, just type

pip install pyodps

The dependencies will be installed automatically.

Or from source code:

$ virtualenv pyodps_env
$ source pyodps_env/bin/activate
$ git clone <git clone URL> pyodps
$ cd pyodps
$ python setup.py install

Dependencies

  • Python (>=2.6), including Python 3+, pypy, Python 2.7 recommended

  • setuptools (>=3.0)

  • requests (>=2.4.0)

Run Unittest

  • copy conf/test.conf.template to odps/tests/test.conf, and fill it with your account

  • run python -m unittest discover

Usage

>>> from odps import ODPS
>>> o = ODPS('**your-access-id**', '**your-secret-access-key**',
...          project='**your-project**', endpoint='**your-end-point**')
>>> dual = o.get_table('dual')
>>> dual.name
'dual'
>>> dual.table_schema
odps.Schema {
  c_int_a                 bigint
  c_int_b                 bigint
  c_double_a              double
  c_double_b              double
  c_string_a              string
  c_string_b              string
  c_bool_a                boolean
  c_bool_b                boolean
  c_datetime_a            datetime
  c_datetime_b            datetime
}
>>> dual.creation_time
datetime.datetime(2014, 6, 6, 13, 28, 24)
>>> dual.is_virtual_view
False
>>> dual.size
448
>>> dual.table_schema.columns
[<column c_int_a, type bigint>,
 <column c_int_b, type bigint>,
 <column c_double_a, type double>,
 <column c_double_b, type double>,
 <column c_string_a, type string>,
 <column c_string_b, type string>,
 <column c_bool_a, type boolean>,
 <column c_bool_b, type boolean>,
 <column c_datetime_a, type datetime>,
 <column c_datetime_b, type datetime>]

DataFrame API

>>> from odps.df import DataFrame
>>> df = DataFrame(o.get_table('pyodps_iris'))
>>> df.dtypes
odps.Schema {
  sepallength           float64
  sepalwidth            float64
  petallength           float64
  petalwidth            float64
  name                  string
}
>>> df.head(5)
|==========================================|   1 /  1  (100.00%)         0s
   sepallength  sepalwidth  petallength  petalwidth         name
0          5.1         3.5          1.4         0.2  Iris-setosa
1          4.9         3.0          1.4         0.2  Iris-setosa
2          4.7         3.2          1.3         0.2  Iris-setosa
3          4.6         3.1          1.5         0.2  Iris-setosa
4          5.0         3.6          1.4         0.2  Iris-setosa
>>> df[df.sepalwidth > 3]['name', 'sepalwidth'].head(5)
|==========================================|   1 /  1  (100.00%)        12s
          name  sepalwidth
0  Iris-setosa         3.5
1  Iris-setosa         3.2
2  Iris-setosa         3.1
3  Iris-setosa         3.6
4  Iris-setosa         3.9

Command-line and IPython enhancement

In [1]: %load_ext odps

In [2]: %enter
Out[2]: <odps.inter.Room at 0x10fe0e450>

In [3]: %sql select * from pyodps_iris limit 5
|==========================================|   1 /  1  (100.00%)         2s
Out[3]:
   sepallength  sepalwidth  petallength  petalwidth         name
0          5.1         3.5          1.4         0.2  Iris-setosa
1          4.9         3.0          1.4         0.2  Iris-setosa
2          4.7         3.2          1.3         0.2  Iris-setosa
3          4.6         3.1          1.5         0.2  Iris-setosa
4          5.0         3.6          1.4         0.2  Iris-setosa

Python UDF Debugging Tool

#file: plus.py
from odps.udf import annotate

@annotate('bigint,bigint->bigint')
class Plus(object):
    def evaluate(self, a, b):
        return a + b
$ cat plus.input
1,1
3,2
$ pyou plus.Plus < plus.input
2
5

Contributing

For a development install, clone the repository and then install from source:

git clone https://github.com/aliyun/aliyun-odps-python-sdk
cd pyodps
pip install -r requirements.txt -e .

If you need to modify the frontend code, you need to install nodejs/npm. To build and install your frontend code, use

python setup.py build_js
python setup.py install_js

License

Licensed under the Apache License 2.0

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

pyodps-0.11.3b1.tar.gz (1.0 MB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

pyodps-0.11.3b1-cp310-cp310-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.10Windows x86-64

pyodps-0.11.3b1-cp310-cp310-win32.whl (1.6 MB view details)

Uploaded CPython 3.10Windows x86

pyodps-0.11.3b1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

pyodps-0.11.3b1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (4.6 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ ARM64

pyodps-0.11.3b1-cp310-cp310-macosx_10_9_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

pyodps-0.11.3b1-cp310-cp310-macosx_10_9_universal2.whl (1.9 MB view details)

Uploaded CPython 3.10macOS 10.9+ universal2 (ARM64, x86-64)

pyodps-0.11.3b1-cp39-cp39-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.9Windows x86-64

pyodps-0.11.3b1-cp39-cp39-win32.whl (1.6 MB view details)

Uploaded CPython 3.9Windows x86

pyodps-0.11.3b1-cp39-cp39-manylinux2014_aarch64.whl (4.7 MB view details)

Uploaded CPython 3.9

pyodps-0.11.3b1-cp39-cp39-manylinux1_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.9

pyodps-0.11.3b1-cp39-cp39-macosx_10_9_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

pyodps-0.11.3b1-cp39-cp39-macosx_10_9_universal2.whl (1.9 MB view details)

Uploaded CPython 3.9macOS 10.9+ universal2 (ARM64, x86-64)

pyodps-0.11.3b1-cp38-cp38-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.8Windows x86-64

pyodps-0.11.3b1-cp38-cp38-win32.whl (1.6 MB view details)

Uploaded CPython 3.8Windows x86

pyodps-0.11.3b1-cp38-cp38-manylinux2014_aarch64.whl (4.9 MB view details)

Uploaded CPython 3.8

pyodps-0.11.3b1-cp38-cp38-manylinux1_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.8

pyodps-0.11.3b1-cp38-cp38-macosx_10_9_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

pyodps-0.11.3b1-cp37-cp37m-win_amd64.whl (1.8 MB view details)

Uploaded CPython 3.7mWindows x86-64

pyodps-0.11.3b1-cp37-cp37m-win32.whl (1.7 MB view details)

Uploaded CPython 3.7mWindows x86

pyodps-0.11.3b1-cp37-cp37m-manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded CPython 3.7m

pyodps-0.11.3b1-cp37-cp37m-manylinux1_x86_64.whl (3.7 MB view details)

Uploaded CPython 3.7m

pyodps-0.11.3b1-cp37-cp37m-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

pyodps-0.11.3b1-cp36-cp36m-win_amd64.whl (1.8 MB view details)

Uploaded CPython 3.6mWindows x86-64

pyodps-0.11.3b1-cp36-cp36m-win32.whl (1.7 MB view details)

Uploaded CPython 3.6mWindows x86

pyodps-0.11.3b1-cp36-cp36m-manylinux1_x86_64.whl (3.7 MB view details)

Uploaded CPython 3.6m

pyodps-0.11.3b1-cp36-cp36m-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.6mmacOS 10.9+ x86-64

pyodps-0.11.3b1-cp35-cp35m-win_amd64.whl (1.8 MB view details)

Uploaded CPython 3.5mWindows x86-64

pyodps-0.11.3b1-cp35-cp35m-win32.whl (1.7 MB view details)

Uploaded CPython 3.5mWindows x86

pyodps-0.11.3b1-cp35-cp35m-manylinux1_x86_64.whl (3.6 MB view details)

Uploaded CPython 3.5m

pyodps-0.11.3b1-cp27-cp27mu-manylinux1_x86_64.whl (3.4 MB view details)

Uploaded CPython 2.7mu

pyodps-0.11.3b1-cp27-cp27m-manylinux1_x86_64.whl (3.4 MB view details)

Uploaded CPython 2.7m

pyodps-0.11.3b1-cp27-cp27m-macosx_10_9_x86_64.whl (1.8 MB view details)

Uploaded CPython 2.7mmacOS 10.9+ x86-64

File details

Details for the file pyodps-0.11.3b1.tar.gz.

File metadata

  • Download URL: pyodps-0.11.3b1.tar.gz
  • Upload date:
  • Size: 1.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.6

File hashes

Hashes for pyodps-0.11.3b1.tar.gz
Algorithm Hash digest
SHA256 d07096f83329808a3bae601c3081c8cad647fe6d4fca6e5189747a9d78ae9d68
MD5 60508bb0ace9cbcd436c37b6834e5a89
BLAKE2b-256 8aef4a0ff90b41fd909a8053d7f6063348fff298e7554c1763308c0f83e9e9d3

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 1dd12609494d3f4573bd7656245bda0c08d4059036ce6d29294407b5d39784a1
MD5 7a1c1aeae6e6cc0cb68100ef5e281243
BLAKE2b-256 f2eb33ded2989b0cabbdc189e0fc254bbd6fd42c3b1e039a5e8c63ab7e6237c1

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp310-cp310-win32.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp310-cp310-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 0184e0f401da09e3128afebc6a930d1e4a04edf50d0ede9b6b37a3c51e660a70
MD5 8a1f02138505a8a1fe926a4aed406f57
BLAKE2b-256 06650f6fc0ce154be917432099441e9c5d516320b9813cc2c9aa59b241a98fb0

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2ad1d5f3ef804d2063d5761bb2e279dc9b8ed026c4bfd41c4fe0a689a649dfcf
MD5 426db5d9db0a97790f0fca1b94aba74b
BLAKE2b-256 b4ca86a57c14a8f99fc52270bf8d3f87d88a06407576aa71cd02e93567138f9b

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 a166fa036d41d5423512f72ae5d5b78a0db452d6b78c8b714056c3ece56a2cbe
MD5 2a77c85acd1b0dc6d9511bce25cf1685
BLAKE2b-256 64703e7ad9c1767dab21690267bbd9f76399522f233292145aa0e77b62861bbe

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp310-cp310-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.10, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.8.3 requests/2.27.1 setuptools/44.1.1 requests-toolbelt/0.10.1 tqdm/4.64.1 CPython/2.7.18

File hashes

Hashes for pyodps-0.11.3b1-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 d30e4f57a3857928039221932e47db7227ceed8c12279e9acaf358ffe33fc564
MD5 564fb5579ecc6cd4ea3271cc7df87bc3
BLAKE2b-256 c3cd56d78f7305010882aa5ef2eea7ca208c56c2e1b8ceefefefdfec0f18fd72

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp310-cp310-macosx_10_9_universal2.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.10, macOS 10.9+ universal2 (ARM64, x86-64)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.8.3 requests/2.27.1 setuptools/41.2.0 requests-toolbelt/0.10.1 tqdm/4.64.1 CPython/2.7.18

File hashes

Hashes for pyodps-0.11.3b1-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 92c28d57f97502945379d9afb86d56af704b675dc5090536aeb53f2ae05a16c3
MD5 a4a820d192402b1800cda97530a5485d
BLAKE2b-256 f682bd9167fb9a7ac4f5d2a6c5b10271bf7e3503f53e166fb536f285765d645a

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 b3e48d5ad389f53d805a6d4d6aa72c6886a499720a5fd30dcf32c26a3ab1ed7c
MD5 fbc7048dd80a8af04722b43156bde3e2
BLAKE2b-256 fe1c70555ac7b790f7136331f51d8faeb23b9f57189250a87bc5d058aa4e9de9

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp39-cp39-win32.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp39-cp39-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 78c69ee20e35fa7fefa7085ebf70ce0eb7fa9efbbc30b6aa3b9764d57e3d655a
MD5 edc443a31a9aa3fe190f7013c310f985
BLAKE2b-256 3b094e76df92cd3e7d25c2c6d84f120f64d94619624b25a7ebf9f3ce84007ee7

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp39-cp39-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp39-cp39-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 b4926706b90fbcb2e7495aac5c363f155219239090185298818cd5583bb58005
MD5 ff7a43447ebde92fdaeed00913690997
BLAKE2b-256 995d29652fe21e5bb54cdffaa51e4d4c9c263c4e1e82b679d5e355d906357c21

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp39-cp39-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp39-cp39-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 95897e04cb3be0bd3eeb95ad2d66c4e13e5ff98a3cf5d24de9738bc21e29e67d
MD5 e798a56e600a4638a9d660b41c9ec222
BLAKE2b-256 c40cac604ede481f515e6b38df440184210096f4cf9cba0c9224df2c8be3f490

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp39-cp39-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.9, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.8.3 requests/2.27.1 setuptools/44.1.1 requests-toolbelt/0.10.1 tqdm/4.64.1 CPython/2.7.18

File hashes

Hashes for pyodps-0.11.3b1-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 fba0feecd9115fe4bb8bb82a129c617ac67569d988fab4a13a277de5648b84c6
MD5 ee4a9dd0e64cfa867e4489125049f96f
BLAKE2b-256 4570802797b1ded1d0aeca6c288ff68ab508f4f674d8b49bfd19ed4613849078

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp39-cp39-macosx_10_9_universal2.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.9, macOS 10.9+ universal2 (ARM64, x86-64)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.8.3 requests/2.27.1 setuptools/41.2.0 requests-toolbelt/0.10.1 tqdm/4.64.1 CPython/2.7.18

File hashes

Hashes for pyodps-0.11.3b1-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 ee29d305a8ddff415ea308bc37a445da2132ce667aecadef0a343ac42d6993b0
MD5 7568fee00a18d6d18c34b34d6f73dd88
BLAKE2b-256 405cd1d39847aa4327b2d6c43dda3022a8c3ecef6cec135547a527f31c852193

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 a4bb832692944813e46ffb29325f17b5c07d542f78b5a3f073acd08a293a0a26
MD5 b893b60f9550fd74fe45f5fbf080e3da
BLAKE2b-256 86b6748fd5b0a1c78ae52f6085d9f69c212e0bfa85b53a3ba69c56dcce1afbf6

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp38-cp38-win32.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp38-cp38-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 6335fa0d0751d21babcdee3c156cbbf7bbd746335faff6e0721521bdf4e8c837
MD5 f2baf117914dc79d9da59cc0b8927200
BLAKE2b-256 8e56dc09b64ad8be2bf59a48da428e3c64ffe9d71af98ddc23c7915f6eaa1e18

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp38-cp38-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp38-cp38-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 9d45c67d2e3d3b98e3da5d157a0776004b72e23e223dfd4da098f08ea76400d7
MD5 93fa625bfe366d1871b9e00e381cb8af
BLAKE2b-256 d427e4df435af5d1eddd1d936ddd203587b20f00b236b4ac6920fb2889c13b7e

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp38-cp38-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 57191687115749318e67e2b28b444ce6b5c0a4b1a2bb2ce41ea2b6c83bcd430f
MD5 279d66637b3f1b97df2f8b35887a18db
BLAKE2b-256 7411874f1ac4d518838c1c8e339f07fc9f6ffaaf5474b8af4f03834c43cb34f2

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.8.3 requests/2.27.1 setuptools/44.1.1 requests-toolbelt/0.10.1 tqdm/4.64.1 CPython/2.7.18

File hashes

Hashes for pyodps-0.11.3b1-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 5ee956474dfa2fd8cf97f68f2177754bc52d096da55f6b9a06de70a3b36b5dc2
MD5 97e9b4bef2d21824883266393511b0c6
BLAKE2b-256 0fd1bfd937df6b79de2df6a2d6a42cf03e3d491e6c05bfeb187eb90cc47f32ca

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 9a67c29c6bead78617ec1efb20a044fa41b6dd43b17e786df4536b1f1fcb11f8
MD5 3c72c5a4a93e6b2703cac21f57e46d9b
BLAKE2b-256 12dc3c2effa7ee1677113a8cdf9ff8a0f121f141dbba1b4563bb46da12f1e5bb

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp37-cp37m-win32.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 9819380012c1d579381d904cf8ba63f54dccc1fe33c0cd3b65393404529348f6
MD5 78b1cc91c7cffc29599ae5fc5a221417
BLAKE2b-256 a8cde4cbf3ef19b4253427d266213af8bfd3c1de4c0be3b83e43d550d1683ca8

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp37-cp37m-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp37-cp37m-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 546a1276b95e159aed942c7774c5ea7e77171663590a40d5b60ec9644884743e
MD5 d8acc18770bcc995ad9b35e567148ce1
BLAKE2b-256 217156aeacc4ca28654a61d20d7150bc0bddd7f14b1d39e1401843ba91cc8e86

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 7891db71196bb39830330eaeb53e844e482ae2da42572809696e97a125338eb2
MD5 10039c00c0512e3ec1016b6a85bd5b63
BLAKE2b-256 864fcf93355fd030f3694470193bfd95c57f4bf1c339aba86d7d52b206643634

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.8.3 requests/2.27.1 setuptools/44.1.1 requests-toolbelt/0.10.1 tqdm/4.64.1 CPython/2.7.18

File hashes

Hashes for pyodps-0.11.3b1-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 53323d575e1e641e90731e9bc8f0db2e4d3ff2651f63c8d93ab4b043a77ccd8d
MD5 7982ad0abcc15f66641fca9f740240f9
BLAKE2b-256 953262286095ef15043525587f91620c52d5caed264568a6795d2d441b5286c7

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 fe4f6a5e05bb94dfee838d0e0f30cd11acb2b2bc10cb2f42579ce3d61ff33ed2
MD5 2f5504839e852c82d15a4f9c30bba314
BLAKE2b-256 c05dea4a519f739ce88865b61874e74cd3ee164ea15db8715ae0f75018fbd085

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp36-cp36m-win32.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 0afdd93ddd9a535ffa7091ebbac4df7bf59b2df4051568629936956b2fd8579d
MD5 1ad1108df2d3337956647d0126231bd9
BLAKE2b-256 ab2f6f588ca872a58965795e4b8e81af681f5fff37850342438f9e4780d6d7e9

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 4aaf2be5320b5257cca5ea16e91fdfedf3faef1d72cd40bfb2796b2eaa6f7e7f
MD5 2068e07084cb0484274635a49ae3f01c
BLAKE2b-256 3c6e3cacf93a9f209584762a83da11a45c196e6275e3f05dc5ddf6a862114abb

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp36-cp36m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.6m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.8.3 requests/2.27.1 setuptools/44.1.1 requests-toolbelt/0.10.1 tqdm/4.64.1 CPython/2.7.18

File hashes

Hashes for pyodps-0.11.3b1-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 4e0f26fac80d4cb59b7ebe779dc18e998c763dfeebc1a206549d16d6e370b069
MD5 31578db9705e6c45f26f39010bc8abab
BLAKE2b-256 1cc6c690d489f6e24335583c99a6d531ca2a5fa4da9ba5626aa4f6b0d4fda3ac

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 5b534364ba6effeab7b5761d9e2fdcdb538c7c61881e86ead2e7859e2a21b920
MD5 bb5d3bec5f0db918cbc144017dcd71f8
BLAKE2b-256 c7500239a325413c1a7d4a2d91b845a701ba271f31eb509f8fdaef6489033f12

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp35-cp35m-win32.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp35-cp35m-win32.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: CPython 3.5m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pyodps-0.11.3b1-cp35-cp35m-win32.whl
Algorithm Hash digest
SHA256 7d460359bb523cb01091e7ba7d1132522e7fd5d3144512614aca4b275a158a33
MD5 aaec512bfef0491c3111113eddcf594e
BLAKE2b-256 669ca038b9eddae94ebe75836d297c41cbcb936e1258c4bea60a9953503d582a

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp35-cp35m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp35-cp35m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 f8b7e23e19f9e807e5afee914db05ce9f232694601f11dce7be0c7d8a3ba188c
MD5 52a9747345a561245c1620fa8dfde358
BLAKE2b-256 a513a8c3321210875dc2305dd8e3a826b7d23a1a792664d1d2d6318e49fd2159

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp27-cp27mu-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp27-cp27mu-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 7c46a5755117a78433e43b8a63f4e741d0c27470d335c3062fd933194af7e657
MD5 bf726fe0610c19043cb4515c40211b84
BLAKE2b-256 ff5f64292110be6b61b4e3ac041ce2410caeec7773434e6576f245784a47648b

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp27-cp27m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyodps-0.11.3b1-cp27-cp27m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 8143342a8b739b56699c3077e2f48d185ce371baab7853b15b7cbe83d13b5fc0
MD5 42d8d1da14cd453722ecb8eef874c64b
BLAKE2b-256 d705432c43c4fe3222e0437bf1b8d41d74995de128a9ea0e1d12d1dfa6291e80

See more details on using hashes here.

File details

Details for the file pyodps-0.11.3b1-cp27-cp27m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pyodps-0.11.3b1-cp27-cp27m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 2.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.8.3 requests/2.27.1 setuptools/44.1.1 requests-toolbelt/0.10.1 tqdm/4.64.1 CPython/2.7.18

File hashes

Hashes for pyodps-0.11.3b1-cp27-cp27m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 5663d1c33086e3550882145a249c2c136b53af485a461ea0e985894389ae4413
MD5 836cda237e28453a34139aae6a7bd4b6
BLAKE2b-256 4c9dcbfe1dfa79702e16db0e6d5d7d4fd5decb00536de84cc704ab7f0938bb5a

See more details on using hashes here.

Supported by

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