| Name | nextmv JSON |
| Version |
0.13.1
JSON |
| download |
| home_page | None |
| Summary | The Python SDK for Nextmv |
| upload_time | 2024-10-17 05:34:09 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. 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| keywords |
decision engineering
decision science
decisions
nextmv
operations research
optimization
shift scheduling
solver
vehicle routing problem
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# Nextmv Python SDK
This is the Python SDK for the Nextmv Platform.
## Installation
Requires Python `>=3.8`. Install using `pip`:
```bash
pip install nextmv
```
## Usage
The Nextmv Python SDK is used to interact with various parts of the Nextmv
Platform:
- [Working with a Decision Model][working-with-a-decision-model]: Get to know
the functionality for running decision models. These API functions work
the same way in any machine (local or hosted).
- [Cloud][cloud]: Interact with the Nextmv Cloud API.
### Working with a Decision Model
To run a model, you can use the various helper functionality provided by the
SDK. Note that when you create an app that runs locally in your machine, it
will run in the same way in a Nextmv Cloud-hosted machine.
#### Options
Use options to capture parameters (i.e.: configurations) for the run:
```python
import nextmv
options = nextmv.Options(
nextmv.Parameter("str_option", str, "default value", "A string option", required=True),
nextmv.Parameter("int_option", int, 1, "An int option", required=False),
nextmv.Parameter("float_option", float, 1.0, "A float option", required=False),
nextmv.Parameter("bool_option", bool, True, "A bool option", required=True),
)
print(options.str_option)
print(options.int_option)
print(options.float_option)
print(options.bool_option)
print(options.to_dict())
```
By using options, you are able to pass in the values of the parameters with CLI
arguments or environment variables.
<!-- markdownlint-disable -->
```bash
$ python main.py --help
usage: main.py [options]
Options for main.py. Use command-line arguments (highest precedence) or environment variables.
optiTo exclude the `markdownlint` rule start and end block, you can use the
following syntax in your markdown file:STR_OPTION
[env var: STR_OPTION] (required) (default: default value) (type: str): A string option
-int_optRemember to replace `Your markdown content here` with your actual markdown
content.(type: int): An int option
-float_option FLOAT_OPTION, --float_option FLOAT_OPTION
[env var: FLOAT_OPTION] (default: 1.0) (type: float): A float option
-bool_option BOOL_OPTION, --bool_option BOOL_OPTION
[env var: BOOL_OPTION] (required) (default: True) (type: bool): A bool option
```
<!-- markdownlint-enable -->
#### Input
Capture the input data for the run.
- Work with `JSON`inputs.
```python
import nextmv
# Read JSON from stdin.
json_input_1 = nextmv.load_local()
print(json_input_1.data)
# Can also specify JSON format directly, and read from a file.
json_input_2 = nextmv.load_local(input_format=nextmv.InputFormat.JSON, path="input.json")
print(json_input_2.data)
```
- Work with plain, `utf-8` encoded, text inputs.
```python
import nextmv
# Read text from stdin.
text_input_1 = nextmv.load_local(input_format=nextmv.InputFormat.TEXT)
print(text_input_1.data)
# Can also read from a file.
text_input_2 = nextmv.load_local(input_format=nextmv.InputFormat.TEXT, path="input.txt")
print(text_input_2.data)
```
<!-- markdownlint-disable -->
- Work with multiple `CSV` files.
```python
import nextmv
# Read multiple CSV files from a dir named "input".
csv_archive_input_1 = nextmv.load_local(input_format=nextmv.InputFormat.CSV_ARCHIVE)
print(csv_archive_input_1.data)
# Read multiple CSV files from a custom dir.
csv_archive_input_2 = nextmv.load_local(input_format=nextmv.InputFormat.CSV_ARCHIVE, path="custom_dir")
print(csv_archive_input_2.data)
```
<!-- markdownlint-enable -->
#### Logging
The Nextmv platform captures logs via `stderr`. Use the provided functionality
to record logs.
```python
import sys
import nextmv
print("0. I do nothing")
nextmv.redirect_stdout()
nextmv.log("1. I log a message to stderr")
print("2. I print a message to stdout")
nextmv.reset_stdout()
print("3. I print another message to stdout")
print("4. I print yet another message to stderr without the logger", file=sys.stderr)
nextmv.log("5. I log a message to stderr using the nextmv module directly")
print("6. I print a message to stdout, again")
```
After executing it, here are the messages printed to the different streams.
- `stdout`
```txt
1. I do nothing
2. I print another message to stdout
3. I print a message to stdout, again
```
- `stderr`
```txt
1. I log a message to stderr
2. I print a message to stdout
3. I print yet another message to stderr without the logger
4. I log a message to stderr using the nextmv module directly
```
#### Output
Write the output data after a run is completed.
- Work with `JSON` outputs.
```python
import nextmv
output = nextmv.Output(
solution={"foo": "bar"},
statistics=nextmv.Statistics(
result=nextmv.ResultStatistics(
duration=1.0,
value=2.0,
custom={"custom": "result_value"},
),
run=nextmv.RunStatistics(
duration=3.0,
iterations=4,
custom={"custom": "run_value"},
),
),
)
# Write to stdout.
nextmv.write_local(output)
# Write to a file.
nextmv.write_local(output, path="output.json")
```
- Work with multple `CSV` files.
```python
import nextmv
output = nextmv.Output(
output_format=nextmv.OutputFormat.CSV_ARCHIVE,
solution={
"output": [
{"name": "Alice", "age": 30},
{"name": "Bob", "age": 40},
],
},
statistics=nextmv.Statistics(
result=nextmv.ResultStatistics(
duration=1.0,
value=2.0,
custom={"custom": "result_value"},
),
run=nextmv.RunStatistics(
duration=3.0,
iterations=4,
custom={"custom": "run_value"},
),
),
)
# Write multiple CSV fiules to a dir named "output".
nextmv.write_local(output)
# Write multiple CSV files to a custom dir.
nextmv.write_local(output, "custom_dir")
```
### Cloud
Before starting:
1. [Sign up][signup] for a Nextmv account.
2. Get your API key. Go to [Team > API Key][api-key].
Visit the [docs][docs] for more information. Make sure that you have your API
key set as an environment variable:
```bash
export NEXTMV_API_KEY="<YOUR-API-KEY>"
```
Additionally, you must have a valid app in Nextmv Cloud.
#### Push an application
Place the following script in the root of your app directory and run it to push
your app to the Nextmv Cloud. This is equivalent to using the Nextmv CLI and
running `nextmv app push`.
```python
import os
from nextmv import cloud
client = cloud.Client(api_key=os.getenv("NEXTMV_API_KEY"))
app = cloud.Application(client=client, id="<YOUR-APP-ID>")
app.push() # Use verbose=True for step-by-step output.
```
#### Run an application
Make a run and get the results.
```python
import os
from nextmv import cloud
input = {
"defaults": {"vehicles": {"speed": 20}},
"stops": [
{
"id": "Nijō Castle",
"location": {"lon": 135.748134, "lat": 35.014239},
"quantity": -1,
},
{
"id": "Kyoto Imperial Palace",
"location": {"lon": 135.762057, "lat": 35.025431},
"quantity": -1,
},
],
"vehicles": [
{
"id": "v2",
"capacity": 2,
"start_location": {"lon": 135.728898, "lat": 35.039705},
},
],
}
client = cloud.Client(api_key=os.getenv("NEXTMV_API_KEY"))
app = cloud.Application(client=client, id="<YOUR-APP-ID>")
result = app.new_run_with_result(
input=input,
instance_id="latest",
run_options={"solve.duration": "1s"},
polling_options=cloud.PollingOptions(), # Customize the polling options.
)
print(result.to_dict())
```
[signup]: https://cloud.nextmv.io
[docs]: https://nextmv.io/docs
[api-key]: https://cloud.nextmv.io/team/api-keys
[cloud]: #cloud
[working-with-a-decision-model]: #working-with-a-decision-model
Raw data
{
"_id": null,
"home_page": null,
"name": "nextmv",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": "Nextmv <tech@nextmv.io>",
"keywords": "decision engineering, decision science, decisions, nextmv, operations research, optimization, shift scheduling, solver, vehicle routing problem",
"author": null,
"author_email": "Nextmv <tech@nextmv.io>",
"download_url": "https://files.pythonhosted.org/packages/b0/95/0abbdd7603e89ecd530e6026b49ad77fe044c856a347142da3a4327c83a3/nextmv-0.13.1.tar.gz",
"platform": null,
"description": "# Nextmv Python SDK\n\nThis is the Python SDK for the Nextmv Platform.\n\n## Installation\n\nRequires Python `>=3.8`. Install using `pip`:\n\n```bash\npip install nextmv\n```\n\n## Usage\n\nThe Nextmv Python SDK is used to interact with various parts of the Nextmv\nPlatform:\n\n- [Working with a Decision Model][working-with-a-decision-model]: Get to know\n the functionality for running decision models. These API functions work\n the same way in any machine (local or hosted).\n- [Cloud][cloud]: Interact with the Nextmv Cloud API.\n\n### Working with a Decision Model\n\nTo run a model, you can use the various helper functionality provided by the\nSDK. Note that when you create an app that runs locally in your machine, it\nwill run in the same way in a Nextmv Cloud-hosted machine.\n\n#### Options\n\nUse options to capture parameters (i.e.: configurations) for the run:\n\n```python\nimport nextmv\n\noptions = nextmv.Options(\n nextmv.Parameter(\"str_option\", str, \"default value\", \"A string option\", required=True),\n nextmv.Parameter(\"int_option\", int, 1, \"An int option\", required=False),\n nextmv.Parameter(\"float_option\", float, 1.0, \"A float option\", required=False),\n nextmv.Parameter(\"bool_option\", bool, True, \"A bool option\", required=True),\n)\n\nprint(options.str_option)\nprint(options.int_option)\nprint(options.float_option)\nprint(options.bool_option)\nprint(options.to_dict())\n```\n\nBy using options, you are able to pass in the values of the parameters with CLI\narguments or environment variables.\n\n<!-- markdownlint-disable -->\n\n```bash\n$ python main.py --help\nusage: main.py [options]\n\nOptions for main.py. Use command-line arguments (highest precedence) or environment variables.\n\noptiTo exclude the `markdownlint` rule start and end block, you can use the\nfollowing syntax in your markdown file:STR_OPTION\n [env var: STR_OPTION] (required) (default: default value) (type: str): A string option\n -int_optRemember to replace `Your markdown content here` with your actual markdown\ncontent.(type: int): An int option\n -float_option FLOAT_OPTION, --float_option FLOAT_OPTION\n [env var: FLOAT_OPTION] (default: 1.0) (type: float): A float option\n -bool_option BOOL_OPTION, --bool_option BOOL_OPTION\n [env var: BOOL_OPTION] (required) (default: True) (type: bool): A bool option\n```\n\n<!-- markdownlint-enable -->\n\n#### Input\n\nCapture the input data for the run.\n\n- Work with `JSON`inputs.\n\n ```python\n import nextmv\n\n # Read JSON from stdin.\n json_input_1 = nextmv.load_local()\n print(json_input_1.data)\n\n # Can also specify JSON format directly, and read from a file.\n json_input_2 = nextmv.load_local(input_format=nextmv.InputFormat.JSON, path=\"input.json\")\n print(json_input_2.data)\n ```\n\n- Work with plain, `utf-8` encoded, text inputs.\n\n ```python\n import nextmv\n\n # Read text from stdin.\n text_input_1 = nextmv.load_local(input_format=nextmv.InputFormat.TEXT)\n print(text_input_1.data)\n\n # Can also read from a file.\n text_input_2 = nextmv.load_local(input_format=nextmv.InputFormat.TEXT, path=\"input.txt\")\n print(text_input_2.data)\n ```\n\n<!-- markdownlint-disable -->\n\n- Work with multiple `CSV` files.\n\n ```python\n import nextmv\n\n # Read multiple CSV files from a dir named \"input\".\n csv_archive_input_1 = nextmv.load_local(input_format=nextmv.InputFormat.CSV_ARCHIVE)\n print(csv_archive_input_1.data)\n\n # Read multiple CSV files from a custom dir.\n csv_archive_input_2 = nextmv.load_local(input_format=nextmv.InputFormat.CSV_ARCHIVE, path=\"custom_dir\")\n print(csv_archive_input_2.data)\n ```\n\n<!-- markdownlint-enable -->\n\n#### Logging\n\nThe Nextmv platform captures logs via `stderr`. Use the provided functionality\nto record logs.\n\n```python\nimport sys\n\nimport nextmv\n\nprint(\"0. I do nothing\")\n\nnextmv.redirect_stdout()\n\nnextmv.log(\"1. I log a message to stderr\")\n\nprint(\"2. I print a message to stdout\")\n\nnextmv.reset_stdout()\n\nprint(\"3. I print another message to stdout\")\n\nprint(\"4. I print yet another message to stderr without the logger\", file=sys.stderr)\n\nnextmv.log(\"5. I log a message to stderr using the nextmv module directly\")\n\nprint(\"6. I print a message to stdout, again\")\n```\n\nAfter executing it, here are the messages printed to the different streams.\n\n- `stdout`\n\n ```txt\n 1. I do nothing\n 2. I print another message to stdout\n 3. I print a message to stdout, again\n ```\n\n- `stderr`\n\n ```txt\n 1. I log a message to stderr\n 2. I print a message to stdout\n 3. I print yet another message to stderr without the logger\n 4. I log a message to stderr using the nextmv module directly\n ```\n\n#### Output\n\nWrite the output data after a run is completed.\n\n- Work with `JSON` outputs.\n\n ```python\n import nextmv\n\n output = nextmv.Output(\n solution={\"foo\": \"bar\"},\n statistics=nextmv.Statistics(\n result=nextmv.ResultStatistics(\n duration=1.0,\n value=2.0,\n custom={\"custom\": \"result_value\"},\n ),\n run=nextmv.RunStatistics(\n duration=3.0,\n iterations=4,\n custom={\"custom\": \"run_value\"},\n ),\n ),\n )\n\n # Write to stdout.\n nextmv.write_local(output)\n\n # Write to a file.\n nextmv.write_local(output, path=\"output.json\")\n ```\n\n- Work with multple `CSV` files.\n\n ```python\n import nextmv\n\n output = nextmv.Output(\n output_format=nextmv.OutputFormat.CSV_ARCHIVE,\n solution={\n \"output\": [\n {\"name\": \"Alice\", \"age\": 30},\n {\"name\": \"Bob\", \"age\": 40},\n ],\n },\n statistics=nextmv.Statistics(\n result=nextmv.ResultStatistics(\n duration=1.0,\n value=2.0,\n custom={\"custom\": \"result_value\"},\n ),\n run=nextmv.RunStatistics(\n duration=3.0,\n iterations=4,\n custom={\"custom\": \"run_value\"},\n ),\n ),\n )\n\n # Write multiple CSV fiules to a dir named \"output\".\n nextmv.write_local(output)\n\n # Write multiple CSV files to a custom dir.\n nextmv.write_local(output, \"custom_dir\")\n ```\n\n### Cloud\n\nBefore starting:\n\n1. [Sign up][signup] for a Nextmv account.\n2. Get your API key. Go to [Team > API Key][api-key].\n\nVisit the [docs][docs] for more information. Make sure that you have your API\nkey set as an environment variable:\n\n```bash\nexport NEXTMV_API_KEY=\"<YOUR-API-KEY>\"\n```\n\nAdditionally, you must have a valid app in Nextmv Cloud.\n\n#### Push an application\n\nPlace the following script in the root of your app directory and run it to push\nyour app to the Nextmv Cloud. This is equivalent to using the Nextmv CLI and\nrunning `nextmv app push`.\n\n```python\nimport os\n\nfrom nextmv import cloud\n\nclient = cloud.Client(api_key=os.getenv(\"NEXTMV_API_KEY\"))\napp = cloud.Application(client=client, id=\"<YOUR-APP-ID>\")\napp.push() # Use verbose=True for step-by-step output.\n```\n\n#### Run an application\n\nMake a run and get the results.\n\n```python\nimport os\n\nfrom nextmv import cloud\n\ninput = {\n \"defaults\": {\"vehicles\": {\"speed\": 20}},\n \"stops\": [\n {\n \"id\": \"Nij\u014d Castle\",\n \"location\": {\"lon\": 135.748134, \"lat\": 35.014239},\n \"quantity\": -1,\n },\n {\n \"id\": \"Kyoto Imperial Palace\",\n \"location\": {\"lon\": 135.762057, \"lat\": 35.025431},\n \"quantity\": -1,\n },\n ],\n \"vehicles\": [\n {\n \"id\": \"v2\",\n \"capacity\": 2,\n \"start_location\": {\"lon\": 135.728898, \"lat\": 35.039705},\n },\n ],\n}\n\nclient = cloud.Client(api_key=os.getenv(\"NEXTMV_API_KEY\"))\napp = cloud.Application(client=client, id=\"<YOUR-APP-ID>\")\nresult = app.new_run_with_result(\n input=input,\n instance_id=\"latest\",\n run_options={\"solve.duration\": \"1s\"},\n polling_options=cloud.PollingOptions(), # Customize the polling options.\n)\nprint(result.to_dict())\n```\n\n[signup]: https://cloud.nextmv.io\n[docs]: https://nextmv.io/docs\n[api-key]: https://cloud.nextmv.io/team/api-keys\n[cloud]: #cloud\n[working-with-a-decision-model]: #working-with-a-decision-model\n",
"bugtrack_url": null,
"license": "Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. \"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. \"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. \"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. \"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License. \"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. \"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. \"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). \"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. 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