You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: docs/source/install.rst
+35-53Lines changed: 35 additions & 53 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -1,16 +1,16 @@
1
1
Install
2
2
=======
3
3
4
-
**AWS Data Wrangler** runs with Python ``3.7``, ``3.8``, ``3.9`` and ``3.10``.
4
+
**AWS Data Wrangler** runs on Python ``3.7``, ``3.8``, ``3.9`` and ``3.10``,
5
5
and on several platforms (AWS Lambda, AWS Glue Python Shell, EMR, EC2,
6
6
on-premises, Amazon SageMaker, local, etc).
7
7
8
-
Some good practices for most of the methods below are:
8
+
Some good practices to follow for options below are:
9
9
10
-
- Use new and individual Virtual Environments for each project (`venv <https://docs.python.org/3/library/venv.html>`_).
11
-
- On Notebooks, always restart your kernel after installations.
10
+
- Use new and isolated Virtual Environments for each project (`venv <https://docs.python.org/3/library/venv.html>`_).
11
+
- On Notebooks, always restart your kernel after installations.
12
12
13
-
.. note:: If you want to use ``awswrangler`` for connecting to Microsoft SQL Server, some additional configuration is needed. Please have a look at the corresponding section below.
13
+
.. note:: If you want to use ``awswrangler`` to connect to Microsoft SQL Server, some additional configuration is needed. Please have a look at the corresponding section below.
14
14
15
15
PyPI (pip)
16
16
----------
@@ -28,60 +28,45 @@ AWS Lambda Layer
28
28
Managed Layer
29
29
^^^^^^^^^^^^^^
30
30
31
-
AWS Data Wrangler is available as an AWS Lambda Managed layer in the following regions:
31
+
.. note:: There is a one week minimum delay between version release and layers being available in the AWS Lambda console.
32
32
33
-
- ap-northeast-1
34
-
- ap-southeast-2
35
-
- eu-central-1
36
-
- eu-west-1
37
-
- us-east-1
38
-
- us-east-2
39
-
- us-west-2
33
+
AWS Data Wrangler is available as an AWS Lambda Managed layer in all AWS commercial regions.
40
34
41
35
It can be accessed in the AWS Lambda console directly:
Or via its ARN: ``arn:aws:lambda:<region>:336392948345:layer:AWSDataWrangler-Python<python-version>:<layer-version>``.
42
+
43
+
For example: ``arn:aws:lambda:us-east-1:336392948345:layer:AWSDataWrangler-Python37:1``.
44
+
45
+
The full list of ARNs is available `here <layers.rst>`__.
61
46
62
47
Custom Layer
63
48
^^^^^^^^^^^^^^
64
49
65
-
For AWS regions not in the above list, you can create your own Lambda layer following these instructions:
50
+
You can also create your own Lambda layer with these instructions:
66
51
67
52
1 - Go to `GitHub's release section <https://github.com/awslabs/aws-data-wrangler/releases>`_
68
-
and download the layer zip related to the desired version. Alternatively, you can download the zip from the `public artifacts bucket <https://aws-data-wrangler.readthedocs.io/en/latest/install.html#public-artifacts>`_.
53
+
and download the zipped layer for to the desired version. Alternatively, you can download the zip from the `public artifacts bucket <https://aws-data-wrangler.readthedocs.io/en/latest/install.html#public-artifacts>`_.
69
54
70
-
2 - Go to the AWS Lambda Panel, open the layer section (left side)
55
+
2 - Go to the AWS Lambda console, open the layer section (left side)
71
56
and click **create layer**.
72
57
73
-
3 - Set name and python version, upload your fresh downloaded zip file
74
-
and press **create** to create the layer.
58
+
3 - Set name and python version, upload your downloaded zip file
59
+
and press **create**.
75
60
76
-
4 - Go to your Lambda and select your new layer!
61
+
4 - Go to your Lambda function and select your new layer!
77
62
78
63
Serverless Application Repository (SAR)
79
64
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
80
65
81
66
Starting version `2.12.0`, AWS Data Wrangler layers are also available in the `AWS Serverless Application Repository <https://serverlessrepo.aws.amazon.com/applications>`_ (SAR).
82
67
83
68
The app deploys the Lambda layer version in your own AWS account and region via a CloudFormation stack.
84
-
This option provides the ability to use semantic versions (i.e. library version) instead of Lambda layer versions.
69
+
This option provides the ability to use semantic versions (i.e. library version) instead of Lambda layer versions.
85
70
86
71
.. list-table:: AWS Data Wrangler Layer Apps
87
72
:widths: 25 25 50
@@ -135,34 +120,33 @@ Here is an example of how to create and use the AWS Data Wrangler Lambda layer i
135
120
AWS Glue Python Shell Jobs
136
121
--------------------------
137
122
138
-
.. note:: Glue Python Shell only supports Python3.6, for which support was dropped in version 2.15.0 of Wrangler. Please use version 2.14.0 or below.
123
+
.. note:: Glue Python Shell runs on Python3.6, for which support was dropped in version 2.15.0 of Wrangler. Please use version 2.14.0 of the library or below.
139
124
140
125
1 - Go to `GitHub's release page <https://github.com/awslabs/aws-data-wrangler/releases>`_ and download the wheel file
141
126
(.whl) related to the desired version. Alternatively, you can download the wheel from the `public artifacts bucket <https://aws-data-wrangler.readthedocs.io/en/latest/install.html#public-artifacts>`_.
142
127
143
-
2 - Upload the wheel file to any Amazon S3 location.
128
+
2 - Upload the wheel file to the Amazon S3 location of your choice.
144
129
145
-
3 - Go to your Glue Python Shell job and point to the wheel file on S3 in
130
+
3 - Go to your Glue Python Shell job and point to the S3 wheel file in
0 commit comments