### Run Toy Example Workflow

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/examples/objects/README.txt

This script runs a 'toy' example workflow that is designed to complete faster than the microbiology examples. It waits for the job to finish and downloads the results to a local file. Ensure your API key is configured.

```python
export GALAXY_API_KEY=000this_should_be_your_api_key00
python small.py
```

--------------------------------

### Install BioBlend with Testing Dependencies

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/index.md

Install BioBlend along with extra libraries required for running local tests.

```bash
python3 -m pip install bioblend[testing]
```

--------------------------------

### Install BioBlend via pip

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/index.md

Install the stable release of BioBlend using pip. This is the recommended method for most users.

```bash
python3 -m pip install bioblend
```

--------------------------------

### Install BioBlend from Source

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/index.md

Install the most current source code directly from the BioBlend Git repository using pip.

```bash
python3 -m pip install git+https://github.com/galaxyproject/bioblend
```

--------------------------------

### Get List of Users

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves a list of all users in the Galaxy instance. This method requires administrator privileges.

```python
>>> gi.users.get_users()
[{'email': 'userA@example.org',
  'id': '975a9ce09b49502a',
  'quota_percent': None,
  'url': '/api/users/975a9ce09b49502a'},
 {'email': 'userB@example.org',
  'id': '0193a95acf427d2c',
  'quota_percent': None,
  'url': '/api/users/0193a95acf427d2c'}]
```

--------------------------------

### Get Data Libraries

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves a list of all Data Libraries available to the authenticated user.

```APIDOC
## View Data Libraries

### Description
Retrieves a list of metadata dictionaries for all Data Libraries available to the current account.

### Method Signature
`gi.libraries.get_libraries()`

### Parameters
This method does not take any parameters.

### Response Example
```json
[
  {
    "id": "8e6f930d00d123ea",
    "name": "RNA-seq workshop data",
    "url": "/api/libraries/8e6f930d00d123ea"
  },
  {
    "id": "f740ab636b360a70",
    "name": "1000 genomes",
    "url": "/api/libraries/f740ab636b360a70"
  }
]
```
```

--------------------------------

### Get All Workflows

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves a list of metadata dictionaries for all workflows in your Galaxy account. Each dictionary contains the workflow's ID, name, and API URL.

```default
>>> gi.workflows.get_workflows()
[{'id': 'e8b85ad72aefca86',
  'name': 'TopHat + cufflinks part 1',
  'url': '/api/workflows/e8b85ad72aefca86'},
 {'id': 'b0631c44aa74526d',
  'name': 'CuffDiff',
  'url': '/api/workflows/b0631c44aa74526d'}]
```

--------------------------------

### Get List of Galaxy Data Libraries

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves a list of all available Data Libraries accessible by the current user. Each item in the list contains basic metadata.

```python
>>> gi.libraries.get_libraries()
[{'id': '8e6f930d00d123ea',
  'name': 'RNA-seq workshop data',
  'url': '/api/libraries/8e6f930d00d123ea'},
 {'id': 'f740ab636b360a70',
  'name': '1000 genomes',
  'url': '/api/libraries/f740ab636b360a70'}]
```

--------------------------------

### Make POST Request to Galaxy API

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Use `make_post_request` to send data to the Galaxy API, for example, to create a new history. The API key is automatically included. The response contains details of the created resource.

```python
>>> gi.make_post_request(gi.base_url + "/api/histories", payload={"name": "test history"})
{'importable': False,
 'create_time': '2019-07-05T20:10:04.823716',
 'contents_url': '/api/histories/a77b3f95070d689a/contents',
 'id': 'a77b3f95070d689a',
 'size': 0, 'user_id': '5b732999121d4593',
 'username_and_slug': None,
 'annotation': None,
 'state_details': {'discarded': 0,
                   'ok': 0,
                   'failed_metadata': 0,
                   'upload': 0,
                   'paused': 0,
                   'running': 0,
                   'setting_metadata': 0,
                   'error': 0,
                   'new': 0,
                   'queued': 0,
                   'empty': 0},
 'state': 'new',
 'empty': True,
 'update_time': '2019-07-05T20:10:04.823742',
 'tags': [],
 'deleted': False,
 'genome_build': None,
 'slug': None,
 'name': 'test history',
 'url': '/api/histories/a77b3f95070d689a',
 'state_ids': {'discarded': [],
               'ok': [],
               'failed_metadata': [],
               'upload': [],
               'paused': [],
               'running': [],
               'setting_metadata': [],
               'error': [],
               'new': [],
               'queued': [],
               'empty': []},
 'published': False,
 'model_class': 'History',
 'purged': False}
```

--------------------------------

### Make GET Request to Galaxy API

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Use `make_get_request` to retrieve data from the Galaxy API. The API key is automatically included. The response is returned as a JSON object.

```python
>>> gi.make_get_request(gi.base_url + "/api/version").json()
{'version_major': '19.05',
 'extra': {}}
```

--------------------------------

### Get Workflows

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves a list of all workflows currently available in the user's account, including their IDs, names, and URLs.

```APIDOC
## Get Workflows

### Description
Retrieves a list of all workflows currently available in the user's account, including their IDs, names, and URLs.

### Method
```python
gi.workflows.get_workflows()
```

### Response
#### Success Response (200)
- **workflows** (list) - A list of dictionaries, where each dictionary contains:
  - **id** (string) - The unique identifier for the workflow.
  - **name** (string) - The name of the workflow.
  - **url** (string) - The API endpoint URL for the workflow.
```

--------------------------------

### Connect to Galaxy Instance

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Establishes a connection to a Galaxy server using the provided URL and API key. Requires an account on the Galaxy instance and a valid API key.

```python
from bioblend.galaxy import GalaxyInstance

gi = GalaxyInstance(url='http://example.galaxy.url', key='your-API-key')
```

--------------------------------

### Set Galaxy Instance URL and API Key for Testing

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/index.md

Export these environment variables to point BioBlend to a Galaxy instance for testing. Ensure you replace the placeholder with your actual API key.

```default
$ export BIOBLEND_GALAXY_URL=http://127.0.0.1:8080
$ export BIOBLEND_GALAXY_API_KEY=<API key>
```

--------------------------------

### Interact with Galaxy via Straightforward API

Source: https://github.com/galaxyproject/bioblend/blob/main/ABOUT.rst

Use this snippet to interact with Galaxy using a straightforward API. It requires initializing a GalaxyInstance with the Galaxy IP and an API key.

```python
from bioblend.galaxy import GalaxyInstance
gi = GalaxyInstance('<Galaxy IP>', key='your API key')
libs = gi.libraries.get_libraries()
gi.workflows.show_workflow('workflow ID')
wf_invocation = gi.workflows.invoke_workflow('workflow ID', inputs)
```

--------------------------------

### Run BioBlend Tests and Save Output

Source: https://github.com/galaxyproject/bioblend/blob/main/CONTRIBUTING.md

Run BioBlend tests and simultaneously view the output in the terminal and save it to a log file.

```bash
./run_bioblend_tests.sh -g GALAXY_PATH [-r GALAXY_REV] [-e TOX_ENV] 2>&1 | tee log.txt
```

--------------------------------

### Run Unit Tests with Pytest

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/index.md

Execute the unit tests for BioBlend using pytest from the project's root directory.

```default
$ pytest
```

--------------------------------

### Run BioBlend Tests with Galaxy Path

Source: https://github.com/galaxyproject/bioblend/blob/main/CONTRIBUTING.md

Execute BioBlend tests by specifying the path to a cloned Galaxy repository. Optionally, specify a Galaxy revision and a Tox environment for testing against different Python versions.

```bash
./run_bioblend_tests.sh -g GALAXY_PATH [-r GALAXY_REV] [-e TOX_ENV]
```

--------------------------------

### Interact with Galaxy via Object-Oriented API

Source: https://github.com/galaxyproject/bioblend/blob/main/ABOUT.rst

This snippet demonstrates interacting with Galaxy using an object-oriented API. It allows for more direct manipulation of Galaxy objects like workflows and histories.

```python
from bioblend.galaxy.objects import GalaxyInstance
gi = GalaxyInstance("URL", "API_KEY")
wf = gi.workflows.list()[0]
hist = gi.histories.list()[0]
inputs = hist.get_datasets()[:2]
input_map = dict(zip(wf.input_labels, inputs))
params = {"Paste1": {"delimiter": "U"}}
wf_invocation = wf.invoke(input_map, params=params)
```

--------------------------------

### Run Bacterial De Novo Assembly Workflow

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/examples/objects/README.txt

This script demonstrates how to run a bacterial de novo assembly workflow on the Orione Galaxy server. Ensure your API key is set via environment variable or by replacing YOUR_API_KEY in the script. The script runs the workflow asynchronously and outputs the history name and ID.

```python
export GALAXY_API_KEY=000this_should_be_your_api_key00
python w3_bacterial_denovo.py
```

--------------------------------

### Run Metagenomics Workflow

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/examples/objects/README.txt

This script demonstrates how to run a metagenomics workflow on the Orione Galaxy server. Configure your API key by replacing YOUR_API_KEY or setting the GALAXY_API_KEY environment variable. The script runs the workflow asynchronously and outputs the history name and ID.

```python
export GALAXY_API_KEY=000this_should_be_your_api_key00
python w5_metagenomics.py
```

--------------------------------

### View Workflows After Import

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves and displays the list of workflows after an import operation, showing the newly added workflow alongside existing ones.

```pycon
>>> gi.workflows.get_workflows()
[{'id': 'c0bacafdfe211f9a',
  'name': 'TopHat + cufflinks part 1 (imported from API)',
  'url': '/api/workflows/c0bacafdfe211f9a'},
 {'id': 'e8b85ad72aefca86',
  'name': 'TopHat + cufflinks part 1',
  'url': '/api/workflows/e8b85ad72aefca86'},
 {'id': 'b0631c44aa74526d',
  'name': 'CuffDiff',
  'url': '/api/workflows/b0631c44aa74526d'}]
```

--------------------------------

### Import Workflow from Dictionary

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Imports a workflow into Galaxy from a Python dictionary representation. This creates a new workflow, potentially a duplicate if imported into the same instance.

```default
>>> gi.workflows.import_workflow_dict(workflow_dict)
{'id': 'c0bacafdfe211f9a',
 'name': 'TopHat + cufflinks part 1 (imported from API)',
 'url': '/api/workflows/c0bacafdfe211f9a'}
```

--------------------------------

### Show Workflow Details

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves detailed information about a specific workflow, including its inputs, name, steps, and URL, by providing its ID.

```APIDOC
## Show Workflow Details

### Description
Retrieves detailed information about a specific workflow, including its inputs, name, steps, and URL, by providing its ID.

### Method
```python
gi.workflows.show_workflow(workflow_id)
```

### Parameters
#### Path Parameters
- **workflow_id** (string) - Required - The ID of the workflow to display.

### Response
#### Success Response (200)
- **workflow_details** (dict) - A dictionary containing detailed information about the workflow, including:
  - **id** (string) - The unique identifier for the workflow.
  - **name** (string) - The name of the workflow.
  - **inputs** (dict) - Information about the workflow's inputs.
  - **steps** (dict) - Information about the workflow's steps.
  - **url** (string) - The API endpoint URL for the workflow.
```

--------------------------------

### Show Specific Workflow Details

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Fetches detailed information about a specific workflow, including its inputs, name, steps, and API URL, by providing its unique ID.

```default
>>> gi.workflows.show_workflow('e8b85ad72aefca86')
{'id': 'e8b85ad72aefca86',
 'inputs': {'252': {'label': 'Input RNA-seq fastq', 'value': ''}},
 'name': 'TopHat + cufflinks part 1',
 'steps': {'250': {'id': 250,
                   'input_steps': {'input1': {'source_step': 252,
                                              'step_output': 'output'}},
                   'tool_id': 'tophat',
                   'type': 'tool'},
           '251': {'id': 251,
                   'input_steps': {'input': {'source_step': 250,
                                             'step_output': 'accepted_hits'}},
                   'tool_id': 'cufflinks',
                   'type': 'tool'},
           '252': {'id': 252,
                   'input_steps': {},
                   'tool_id': None,
                   'type': 'data_input'}},
 'url': '/api/workflows/e8b85ad72aefca86'}
```

--------------------------------

### Run Bacterial Re-sequencing Workflow

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/examples/objects/README.txt

This script demonstrates how to run a bacterial re-sequencing workflow on the Orione Galaxy server. Replace YOUR_API_KEY with your actual API key or set the GALAXY_API_KEY environment variable. The script runs the workflow asynchronously and outputs the history name and ID.

```python
export GALAXY_API_KEY=000this_should_be_your_api_key00
python w2_bacterial_reseq.py
```

--------------------------------

### Show Details of a Specific Galaxy Data Library

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Fetches detailed information for a specific Data Library using its ID. This includes its name, description, and content URL.

```python
>>> gi.libraries.show_library('8e6f930d00d123ea')
{'contents_url': '/api/libraries/8e6f930d00d123ea/contents',
 'description': 'RNA-Seq workshop data',
 'name': 'RNA-Seq',
 'synopsis': 'Data for the RNA-Seq tutorial'}
```

--------------------------------

### Show Dataset Details

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves detailed information about a specific dataset in Galaxy using its ID. The returned dictionary includes metadata such as data type, file size, and state.

```python
>>> gi.datasets.show_dataset('10a4b652da44e82a')
{'data_type': 'fastqsanger',
 'deleted': False,
 'file_size': 16527060,
 'genome_build': 'dm3',
 'id': 17499,
 'metadata_data_lines': None,
 'metadata_dbkey': 'dm3',
 'metadata_sequences': None,
 'misc_blurb': '15.8 MB',
 'misc_info': 'Noneuploaded fastqsanger file',
 'model_class': 'HistoryDatasetAssociation',
 'name': 'C1_R2_1.chr4.fq',
 'purged': False,
 'state': 'ok',
 'visible': True}
```

--------------------------------

### Upload File from FTP to History

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Imports a file from the user's FTP folder into a specified Galaxy history. This is recommended for files larger than 2GB.

```APIDOC
## Upload File from FTP to History

### Description
Imports a file from the user's FTP folder into a specified Galaxy history. This method is suitable for large files (greater than 2GB).

### Method Signature
`gi.tools.upload_from_ftp(ftp_filepath, history_id)`

### Parameters
#### Path Parameters
- `ftp_filepath` (string) - Required - The path to the file in the user's FTP folder.
- `history_id` (string) - Required - The ID of the Galaxy history to upload the file to.

### Response Example
```json
{
  "implicit_collections": [],
  "jobs": [
    {
      "create_time": "2015-07-28T17:57:43.704394",
      "exit_code": null,
      "id": "82b264d8c3d11790",
      "model_class": "Job",
      "state": "new",
      "tool_id": "upload1",
      "update_time": "2015-07-28T17:57:43.910958"
    }
  ],
  "output_collections": [],
  "outputs": [
    {
      "create_time": "2015-07-28T17:57:43.209041",
      "data_type": "galaxy.datatypes.data.Text",
      "deleted": false,
      "file_ext": "auto",
      "file_size": 0,
      "genome_build": "?",
      "hda_ldda": "hda",
      "hid": 17,
      "history_content_type": "dataset",
      "history_id": "f3c2b0f3ecac9f02",
      "id": "a676e8f07209a3be",
      "metadata_data_lines": null,
      "metadata_dbkey": "?",
      "misc_blurb": null,
      "misc_info": null,
      "model_class": "HistoryDatasetAssociation",
      "name": "test.txt",
      "output_name": "output0",
      "peek": "<table cellspacing=\"0\" cellpadding=\"3\"></table>",
      "purged": false,
      "state": "queued",
      "tags": [],
      "update_time": "2015-07-28T17:57:43.544407",
      "uuid": "2cbe8f0a-4019-47c4-87e2-005ce35b8449",
      "visible": true
    }
  ]
}
```
```

--------------------------------

### Show Workflow Inputs

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves the input schema for a given workflow ID to understand its expected inputs.

```python
>>> wf = gi.workflows.show_workflow('e8b85ad72aefca86')
>>> wf['inputs']
{'252': {'label': 'Input RNA-seq fastq', 'value': ''}}
```

--------------------------------

### Upload Local File to Galaxy History

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Use this method to upload a local file to a specified Galaxy history. Ensure the file path is correct.

```python
>>> gi.tools.upload_file('test.txt', 'f3c2b0f3ecac9f02')
{'implicit_collections': [],
 'jobs': [{'create_time': '2015-07-28T17:52:39.756488',
           'exit_code': None,
           'id': '9752b387803d3e1e',
           'model_class': 'Job',
           'state': 'new',
           'tool_id': 'upload1',
           'update_time': '2015-07-28T17:52:39.987509'}],
 'output_collections': [],
 'outputs': [{'create_time': '2015-07-28T17:52:39.331176',
              'data_type': 'galaxy.datatypes.data.Text',
              'deleted': False,
              'file_ext': 'auto',
              'file_size': 0,
              'genome_build': '?',
              'hda_ldda': 'hda',
              'hid': 16,
              'history_content_type': 'dataset',
              'history_id': 'f3c2b0f3ecac9f02',
              'id': '59c76a119581e190',
              'metadata_data_lines': None,
              'metadata_dbkey': '?',
              'misc_blurb': None,
              'misc_info': None,
              'model_class': 'HistoryDatasetAssociation',
              'name': 'test.txt',
              'output_name': 'output0',
              'peek': '<table cellspacing="0" cellpadding="3"></table>',
              'purged': False,
              'state': 'queued',
              'tags': [],
              'update_time': '2015-07-28T17:52:39.611887',
              'uuid': 'ff0ee99b-7542-4125-802d-7a193f388e7e',
              'visible': True}]}
```

--------------------------------

### Upload File to Data Library

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Uploads a file from your local machine to a specified Data Library. You can optionally specify the file type; otherwise, Galaxy attempts to auto-detect it.

```python
>>> gi.libraries.upload_file_from_local_path('8e6f930d00d123ea', '/local/path/to/mydata.fastq', file_type='fastqsanger')
```

--------------------------------

### Import Workflow Dictionary

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Imports a workflow into Galaxy from a Python dictionary representation. This creates a new workflow based on the provided definition.

```APIDOC
## Import Workflow Dictionary

### Description
Imports a workflow into Galaxy from a Python dictionary representation. This creates a new workflow based on the provided definition.

### Method
```python
gi.workflows.import_workflow_dict(workflow_dict)
```

### Parameters
#### Request Body
- **workflow_dict** (dict) - Required - A dictionary representing the workflow definition to import.

### Response
#### Success Response (200)
- **imported_workflow_info** (dict) - A dictionary containing basic metadata of the newly imported workflow, including its ID, name, and URL.
```

--------------------------------

### Show History State After Workflow Invocation

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Displays the state of a history immediately after invoking a workflow, showing datasets in a 'queued' state.

```default
>>> gi.histories.show_history('0a7b7992a7cabaec')
{'annotation': '',
 'contents_url': '/api/histories/0a7b7992a7cabaec/contents',
 'id': '0a7b7992a7cabaec',
 'name': 'New output history',
 'nice_size': '0 bytes',
 'state': 'queued',
 'state_details': {'discarded': 0,
                   'empty': 0,
                   'error': 0,
                   'failed_metadata': 0,
                   'new': 0,
                   'ok': 0,
                   'paused': 0,
                   'queued': 8,
                   'running': 0,
                   'setting_metadata': 0,
                   'upload': 0},
 'state_ids': {'discarded': [],
               'empty': [],
               'error': [],
               'failed_metadata': [],
               'new': [],
               'ok': [],
               'paused': [],
               'queued': ['33be8ad9917d9207',
                          'fbee1c2dc793c114',
                          '85866441984f9e28',
                          '1c51aa78d3742386',
                          'a68e8770e52d03b4',
                          'c54baf809e3036ac',
                          'ba0db8ce6cd1fe8f',
                          'c019e4cf08b2ac94'],
               'running': [],
               'setting_metadata': [],
               'upload': []}}
```

--------------------------------

### Upload File to History

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Uploads a local file to a specified Galaxy history. For files larger than 2GB, FTP upload is recommended.

```APIDOC
## Upload File to History

### Description
Uploads a local file to a specified Galaxy history.

### Method Signature
`gi.tools.upload_file(local_filepath, history_id)`

### Parameters
#### Path Parameters
- `local_filepath` (string) - Required - The path to the local file to upload.
- `history_id` (string) - Required - The ID of the Galaxy history to upload the file to.

### Response Example
```json
{
  "implicit_collections": [],
  "jobs": [
    {
      "create_time": "2015-07-28T17:52:39.756488",
      "exit_code": null,
      "id": "9752b387803d3e1e",
      "model_class": "Job",
      "state": "new",
      "tool_id": "upload1",
      "update_time": "2015-07-28T17:52:39.987509"
    }
  ],
  "output_collections": [],
  "outputs": [
    {
      "create_time": "2015-07-28T17:52:39.331176",
      "data_type": "galaxy.datatypes.data.Text",
      "deleted": false,
      "file_ext": "auto",
      "file_size": 0,
      "genome_build": "?",
      "hda_ldda": "hda",
      "hid": 16,
      "history_content_type": "dataset",
      "history_id": "f3c2b0f3ecac9f02",
      "id": "59c76a119581e190",
      "metadata_data_lines": null,
      "metadata_dbkey": "?",
      "misc_blurb": null,
      "misc_info": null,
      "model_class": "HistoryDatasetAssociation",
      "name": "test.txt",
      "output_name": "output0",
      "peek": "<table cellspacing=\"0\" cellpadding=\"3\"></table>",
      "purged": false,
      "state": "queued",
      "tags": [],
      "update_time": "2015-07-28T17:52:39.611887",
      "uuid": "ff0ee99b-7542-4125-802d-7a193f388e7e",
      "visible": true
    }
  ]
}
```
```

--------------------------------

### Show History Details

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Fetches detailed metadata for a specific Galaxy history using its ID. Setting 'contents=False' (default) returns only dataset IDs within the history.

```python
>>> gi.histories.show_history('f3c2b0f3ecac9f02', contents=False)
{'annotation': '',
 'contents_url': '/api/histories/f3c2b0f3ecac9f02/contents',
 'id': 'f3c2b0f3ecac9f02',
 'name': 'RNAseq_DGE_BASIC_Prep',
 'nice_size': '93.5 MB',
 'state': 'ok',
 'state_details': {'discarded': 0,
                   'empty': 0,
                   'error': 0,
                   'failed_metadata': 0,
                   'new': 0,
                   'ok': 7,
                   'paused': 0,
                   'queued': 0,
                   'running': 0,
                   'setting_metadata': 0,
                   'upload': 0},
 'state_ids': {'discarded': [],
               'empty': [],
               'error': [],
               'failed_metadata': [],
               'new': [],
               'ok': ['d6842fb08a76e351',
                      '10a4b652da44e82a',
                      '81c601a2549966a0',
                      'a154f05e3bcee26b',
                      '1352fe19ddce0400',
                      '06d549c52d753e53',
                      '9ec54455d6279cc7'],
               'paused': [],
               'queued': [],
               'running': [],
               'setting_metadata': [],
               'upload': []}}
```

--------------------------------

### Invoke Workflow with Datasets

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Invokes a Galaxy workflow using a specified dataset. The dataset source is 'hda' (HistoryDatasetAssociation) and a new history is created for the output.

```default
>>> datamap = {'252': {'src':'hda', 'id':'10a4b652da44e82a'}}
>>> gi.workflows.invoke_workflow('e8b85ad72aefca86', inputs=datamap, history_name='New output history')
{'history': '0a7b7992a7cabaec',
 'outputs': ['33be8ad9917d9207',
             'fbee1c2dc793c114',
             '85866441984f9e28',
             '1c51aa78d3742386',
             'a68e8770e52d03b4',
             'c54baf809e3036ac',
             'ba0db8ce6cd1fe8f',
             'c019e4cf08b2ac94']}
```

--------------------------------

### Show Library Details

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves detailed information about a specific Data Library, identified by its ID.

```APIDOC
## Show Library Details

### Description
Retrieves detailed information about a specific Data Library, identified by its ID.

### Method Signature
`gi.libraries.show_library(library_id)`

### Parameters
#### Path Parameters
- `library_id` (string) - Required - The ID of the Data Library to retrieve details for.

### Response Example
```json
{
  "contents_url": "/api/libraries/8e6f930d00d123ea/contents",
  "description": "RNA-Seq workshop data",
  "name": "RNA-Seq",
  "synopsis": "Data for the RNA-Seq tutorial"
}
```
```

--------------------------------

### Upload File from FTP to Galaxy History

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Use this method for uploading files larger than 2GB via FTP. It requires the file to be present in the user's FTP folder on the Galaxy server.

```python
>>> gi.tools.upload_from_ftp('test.txt', 'f3c2b0f3ecac9f02')
{'implicit_collections': [],
 'jobs': [{'create_time': '2015-07-28T17:57:43.704394',
           'exit_code': None,
           'id': '82b264d8c3d11790',
           'model_class': 'Job',
           'state': 'new',
           'tool_id': 'upload1',
           'update_time': '2015-07-28T17:57:43.910958'}],
 'output_collections': [],
 'outputs': [{'create_time': '2015-07-28T17:57:43.209041',
              'data_type': 'galaxy.datatypes.data.Text',
              'deleted': False,
              'file_ext': 'auto',
              'file_size': 0,
              'genome_build': '?',
              'hda_ldda': 'hda',
              'hid': 17,
              'history_content_type': 'dataset',
              'history_id': 'f3c2b0f3ecac9f02',
              'id': 'a676e8f07209a3be',
              'metadata_data_lines': None,
              'metadata_dbkey': '?',
              'misc_blurb': None,
              'misc_info': None,
              'model_class': 'HistoryDatasetAssociation',
              'name': 'test.txt',
              'output_name': 'output0',
              'peek': '<table cellspacing="0" cellpadding="3"></table>',
              'purged': False,
              'state': 'queued',
              'tags': [],
              'update_time': '2015-07-28T17:57:43.544407',
              'uuid': '2cbe8f0a-4019-47c4-87e2-005ce35b8449',
              'visible': True}]}
```

--------------------------------

### Upload File to Data Library

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Uploads a file from a local path to a specified Galaxy Data Library. The file type can be automatically detected or explicitly set.

```APIDOC
## Upload File to Data Library

### Description
Uploads a file from a local path to a specified Galaxy Data Library. The file type can be automatically detected or explicitly set.

### Method
```python
gi.libraries.upload_file_from_local_path(library_id, local_path, file_type='auto')
```

### Parameters
#### Path Parameters
- **library_id** (string) - Required - The ID of the destination Data Library.
- **local_path** (string) - Required - The local path to the file to upload.

#### Query Parameters
- **file_type** (string) - Optional - The type of file to assign in Galaxy. Defaults to 'auto' for automatic detection.
```

--------------------------------

### View Users

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves a list of all users in the Galaxy system. This method is only available to Galaxy administrators.

```APIDOC
## View Users

### Description
Methods for managing users are grouped under `GalaxyInstance.users.*`. User management is only available to Galaxy administrators, meaning the API key used to connect to Galaxy must belong to an admin account.

### Method
`GET` (implied by `get_users` action)

### Endpoint
`/api/users` (inferred from context)

### Parameters
None explicitly mentioned for this method.

### Request Example
```python
gi.users.get_users()
```

### Response
#### Success Response (200)
- **email** (string) - The email address of the user.
- **id** (string) - The unique identifier of the user.
- **quota_percent** (number or null) - The percentage of the user's quota that is currently used, or null if not applicable.
- **url** (string) - The API URL to access the specific user resource.

#### Response Example
```json
[
  {
    "email": "userA@example.org",
    "id": "975a9ce09b49502a",
    "quota_percent": null,
    "url": "/api/users/975a9ce09b49502a"
  },
  {
    "email": "userB@example.org",
    "id": "0193a95acf427d2c",
    "quota_percent": null,
    "url": "/api/users/0193a95acf427d2c"
  }
]
```
```

--------------------------------

### Export Workflow to Dictionary

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Exports a workflow's definition into a complex Python dictionary. This dictionary can be used for archiving or importing the workflow elsewhere.

```default
>>> workflow_dict = gi.workflows.export_workflow_dict('e8b85ad72aefca86')
```

--------------------------------

### View Histories

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Retrieves a list of histories associated with the connected Galaxy account. Each history in the list is represented by a dictionary containing basic metadata such as its ID and name.

```python
>>> gi.histories.get_histories()
[{'id': 'f3c2b0f3ecac9f02',
  'name': 'RNAseq_DGE_BASIC_Prep',
  'url': '/api/histories/f3c2b0f3ecac9f02'},
 {'id': '8a91dcf1866a80c2',
  'name': 'June demo',
  'url': '/api/histories/8a91dcf1866a80c2'}]
```

--------------------------------

### Export Workflow Dictionary

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Exports a workflow's definition into a Python dictionary format, which can be used for archiving or transferring workflows.

```APIDOC
## Export Workflow Dictionary

### Description
Exports a workflow's definition into a Python dictionary format, which can be used for archiving or transferring workflows.

### Method
```python
gi.workflows.export_workflow_dict(workflow_id)
```

### Parameters
#### Path Parameters
- **workflow_id** (string) - Required - The ID of the workflow to export.

### Response
#### Success Response (200)
- **workflow_dict** (dict) - A dictionary representing the workflow's definition.
```

--------------------------------

### Increase BioBlend Test Job Timeout

Source: https://github.com/galaxyproject/bioblend/blob/main/CONTRIBUTING.md

Temporarily increase the job timeout for BioBlend tests by setting an environment variable.

```bash
export BIOBLEND_TEST_JOB_TIMEOUT=100
```

--------------------------------

### Invoke a workflow

Source: https://github.com/galaxyproject/bioblend/blob/main/docs/api_docs/galaxy/docs.md

Invokes a Galaxy workflow with specified datasets and creates a new history for the output. The method returns immediately after submitting jobs to the Galaxy workflow engine.

```APIDOC
## Invoke a workflow

### Description
To invoke a workflow, you need to specify which datasets to use for the workflow inputs. Datasets can be sourced from histories or data libraries. The `invoke_workflow` method takes a workflow ID, a data map specifying input-to-dataset mappings, and an optional history name for storing results.

### Method
`POST` (implied by `invoke_workflow` action)

### Endpoint
`/api/workflows/{workflow_id}/invoke` (inferred from context)

### Parameters
#### Path Parameters
- **workflow_id** (string) - Required - The unique identifier of the workflow to invoke.

#### Query Parameters
None explicitly mentioned, but `history_name` is passed as a keyword argument.

#### Request Body
- **inputs** (dict) - Required - A nested dictionary mapping workflow input IDs to dataset specifications. Each dataset specification should include at least 'src' (e.g., 'hda') and 'id' (the dataset's unique identifier).
- **history_name** (string) - Optional - The name for a new history to be created for storing the workflow results. If not provided, results may be stored in the default history.

### Request Example
```python
datamap = {'252': {'src':'hda', 'id':'10a4b652da44e82a'}}
gi.workflows.invoke_workflow('e8b85ad72aefca86', inputs=datamap, history_name='New output history')
```

### Response
#### Success Response (200)
- **history** (string) - The ID of the history where the workflow outputs are stored.
- **outputs** (list of strings) - A list of dataset IDs generated by the workflow.

#### Response Example
```json
{
  "history": "0a7b7992a7cabaec",
  "outputs": [
    "33be8ad9917d9207",
    "fbee1c2dc793c114",
    "85866441984f9e28",
    "1c51aa78d3742386",
    "a68e8770e52d03b4",
    "c54baf809e3036ac",
    "ba0db8ce6cd1fe8f",
    "c019e4cf08b2ac94"
  ]
}
```
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.