pywikipathways

https://github.com/wikipathways/pywikipathways
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pywikipathways is a Python client package that provides programmatic access to WikiPathways content...
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### Install Development Version

Source: https://github.com/wikipathways/pywikipathways/blob/main/AGENTS.md

Use a virtual environment and install the package in editable mode for quick iteration.

```bash
pip install -e .
```

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

### Get Help for list_pathways Function

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Use the `help()` function to understand the parameters, return types, and see examples for the `list_pathways` function.

```python
help(pwpw.list_pathways)
```

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

### Install pywikipathways

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Install the package from PyPI using pip. For the development version, install directly from GitHub.

```bash
pip install pywikipathways
```

```bash
pip install git+https://github.com/kozo2/pywikipathways.git
```

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

### Install Pywikipathways

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Install the pywikipathways package using pip. This is a prerequisite for using the library.

```python
!pip install pywikipathways
```

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

### Develop pywikipathways with uv

Source: https://github.com/wikipathways/pywikipathways/blob/main/README.md

Instructions for setting up a development environment and installing pywikipathways using uv for dependency management. Includes creating a virtual environment, activating it, installing the package in editable mode, and running tests.

```bash
uv venv
source .venv/bin/activate  # or .venv\Scripts\activate on Windows
uv pip install -e .
uv run pytest
```

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

### Install pywikipathways Package

Source: https://github.com/wikipathways/pywikipathways/blob/main/README.md

Use this command to install the pywikipathways package using pip.

```bash
pip install pywikipathways
```

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

### Install with uv

Source: https://github.com/wikipathways/pywikipathways/blob/main/AGENTS.md

uv can manage dependencies and run commands, mirroring the pip workflow.

```bash
uv pip install -e .
uv run pytest
```

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

### Install pywikipathways and bridgedbpy

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-bridgedbpy.ipynb

Install the necessary packages for accessing WikiPathways and BridgeDb functionalities. This is a prerequisite for using the libraries.

```python
!pip install pywikipathways bridgedbpy
```

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

### Install Development Version of pywikipathways

Source: https://github.com/wikipathways/pywikipathways/blob/main/README.md

Install the development version of pywikipathways directly from GitHub using pip.

```bash
pip install git+https://github.com/kozo2/pywikipathways.git
```

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

### Get Help for list_pathway_urls

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Access the help documentation for the list_pathway_urls function to understand its parameters and output.

```python
help(pwpw.list_pathway_urls)
```

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

### Get Help for list_pathway_ids

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Access the help documentation for the list_pathway_ids function to understand its parameters and output.

```python
help(pwpw.list_pathway_ids)
```

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

### Get Help for list_pathway_names

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Access the help documentation for the list_pathway_names function to understand its parameters and output.

```python
help(pwpw.list_pathway_names)
```

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

### Install WikiPathways App in Cytoscape

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Install the WikiPathways app within Cytoscape using py4cytoscape. This app is required for accessing WikiPathways data directly from Cytoscape. Requires Cytoscape 3.7.0 or above.

```python
p4c.install_app('WikiPathways') #only available in Cytoscape 3.7.0 and above
```

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

### Remote Notebook Setup for Py4cytoscape

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Execute this code in remote notebook environments like Google Colab to initialize the py4cytoscape bridge. Ensure Cytoscape is running locally.

```python
_PY4CYTOSCAPE = 'git+https://github.com/cytoscape/py4cytoscape@0.0.10'
import requests
exec(requests.get("https://raw.githubusercontent.com/cytoscape/jupyter-bridge/master/client/p4c_init.py").text)
IPython.display.Javascript(_PY4CYTOSCAPE_BROWSER_CLIENT_JS) # Start browser client
```

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

### Get Xrefs for Molecules (Chemspider)

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Fetches Chemspider IDs for small molecules associated with a pathway. Use 'Cs' as the system code.

```python
pwpw.get_xref_list('WP554', 'Cs')
```

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

### Get Xrefs for Metabolites (ChEBI)

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Retrieves ChEBI IDs for chemical entities within a pathway. Use 'Ce' as the system code.

```python
pwpw.get_xref_list('WP554', 'Ce')
```

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

### Get Pathway Information

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Retrieves basic information about a specified pathway using its WPID. Requires the pathway ID as input.

```python
pwpw.get_pathway_info('WP554')
```

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

### Get Pathways by Community

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve a DataFrame of all pathways belonging to a specific WikiPathways community. Displays the 'id', 'name', and 'species' for the first 5 pathways if the DataFrame is not None.

```python
import pywikipathways as pwpw

df = pwpw.get_pathways_by_community("AOP")
if df is not None:
    print(df[['id', 'name', 'species']].head())
```

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

### Get Xrefs for Metabolites (HMDB)

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Fetches Human Metabolome Database (HMDB) IDs for metabolites in a pathway. Use 'Ch' as the system code.

```python
pwpw.get_xref_list('WP554', 'Ch')
```

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

### Get Ontology Terms

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieves ontology term annotations for pathways. Use `get_ontology_terms` for a flattened DataFrame, and `get_ontology_term_names` and `get_ontology_term_ids` for names and IDs only.

```python
import pywikipathways as pwpw

# Ontology terms for a single pathway
terms = pwpw.get_ontology_terms('WP554')
print(terms[['id', 'terms_id', 'terms_name', 'terms_parent']].head())
```

```python
# All names and IDs for a pathway
names = pwpw.get_ontology_term_names('WP554')
ids   = pwpw.get_ontology_term_ids('WP554')
print(names)  # ['cardiovascular system development', 'hypertension', ...]
print(ids)    # ['PW:0000010', 'DOID:10763', ...]
```

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

### Get Pathway History

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Opens a browser tab displaying the commit history for a specific pathway ID.

```python
import pywikipathways as pwpw

# Opens browser tab for commit history of WP554
pwpw.get_pathway_history('WP554')
```

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

### Get Xrefs for Genes (Entrez)

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Fetches a list of Entrez Gene IDs associated with a pathway. Use 'L' as the system code for Entrez.

```python
pwpw.get_xref_list('WP554','L')
```

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

### Get Xrefs for Genes (Ensembl)

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Retrieves Ensembl IDs for genes linked to a pathway. Use 'En' as the system code for Ensembl.

```python
pwpw.get_xref_list('WP554', 'En')
```

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

### Get Full System Name from Code

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-bridgedbpy.ipynb

Use this function to resolve a short system code (e.g., 'Ce') to its full name (e.g., 'ChEBI'). Useful for understanding unknown system codes.

```python
brdgdbp.get_full_name('Ce')
```

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

### Get Counts

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieves a DataFrame of overall WikiPathways statistics, including total pathways, authors, and organisms.

```python
import pywikipipathways as pwpw

stats = pwpw.get_counts()
print(stats)
#    pathways  authors  organisms  ...
# 0      7800     2400         31  ...
```

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

### Get Network Table Columns

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Retrieves specified columns ('name', 'degree.layout', 'COMMON') from the Cytoscape network's table. This is useful for analyzing node properties.

```python
net_data = p4c.get_table_columns(columns=['name','degree.layout','COMMON'])
```

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

### Find pathway IDs, names, and URLs by ORCID

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Convenience functions to get only pathway IDs, names, or URLs for pathways associated with a given ORCID.

```python
import pywikipathways as pwpw

orcid = '0000-0001-9773-4008'
ids   = pwpw.find_pathway_ids_by_orcid(orcid)
names = pwpw.find_pathway_names_by_orcid(orcid)

for wpid, name in zip(ids, names):
    print(wpid, "->", name)
```

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

### Build Package

Source: https://github.com/wikipathways/pywikipathways/blob/main/AGENTS.md

Build the package for release using the standard Python build tool.

```bash
python -m build
```

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

### Get Pathways by Ontology Term

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieves pathways annotated with a specific ontology term ID. Use `get_pathway_ids_by_ontology_term` to get only the IDs.

```python
import pywikipathways as pwpw

# All pathways annotated with PW:0000010 (cardiovascular system development)
df = pwpw.get_pathways_by_ontology_term('PW:0000010')
print(df[['id', 'pathways_id', 'pathways_name']].head())
```

```python
# IDs only
ids = pwpw.get_pathway_ids_by_ontology_term('PW:0000010')
print(ids[:5])
# ['WP554', 'WP1771', 'WP2406', ...]
```

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

### Get Pathways by Parent Ontology Term

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieves pathways whose ontology terms have a specific parent ontology term ID. Use `get_pathway_ids_by_parent_ontology_term` to get only the IDs.

```python
import pywikipathways as pwpw

# Pathways with terms that have 'PW:0000001' as parent
df = pwpw.get_pathways_by_parent_ontology_term('PW:0000001')
print(df[['id', 'terms_name']].head())
```

```python
ids = pwpw.get_pathway_ids_by_parent_ontology_term('PW:0000001')
print(ids[:5])
```

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

### Import Pywikipathways Library

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Import the pywikipathways library to begin interacting with WikiPathways data.

```python
import pywikipathways as pwpw
```

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

### Publish Package

Source: https://github.com/wikipathways/pywikipathways/blob/main/AGENTS.md

Publish the built package to a repository using twine.

```bash
twine
```

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

### Open Cytoscape Session

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Opens a sample Cytoscape session. This action will overwrite the current session.

```python
p4c.open_session()
```

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

### Import Py4cytoscape Library

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Import the py4cytoscape library to enable communication with Cytoscape.

```python
import py4cytoscape as p4c
```

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

### Download Pathway Archive

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Initiates the download of a pathway archive. If no organism is specified, it prompts the user to provide one by visiting the data archive URL.

```python
pwpw.download_pathway_archive()
```

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

### Download Pathway Archive

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Downloads a monthly bulk archive of pathway content for a specific organism and format (GPML, GMT, or SVG). If no organism is specified, it opens the data browser. Allows specifying a destination path.

```python
import pywikipathways as pwpw

# Download current GPML archive for mouse
filename = pwpw.download_pathway_archive(organism='Mus musculus')
print(f"Downloaded: {filename}")
```

```python
# Download GMT archive for a specific date
filename = pwpw.download_pathway_archive(
    date='20230710',
    organism='Homo sapiens',
    format='gmt'
)
print(f"Downloaded: {filename}")
# Downloaded: wikipathways-20230710-gmt-Homo_sapiens.gmt
```

```python
# Download SVG archive to a specific folder
filename = pwpw.download_pathway_archive(
    date='20230710',
    organism='Rattus norvegicus',
    format='svg',
    destpath='/tmp/'
)
```

```python
# Browse archive without downloading (opens browser)
pwpw.download_pathway_archive(format='gmt')
```

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

### Preview GPML Pathway Data

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Displays the beginning portion of the retrieved GPML data. This is helpful for a quick inspection of the pathway's XML structure.

```python
gpml[:1000]
```

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

### download_pathway_archive

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Download a monthly bulk archive of WikiPathways pathway content for a specific organism and format.

```APIDOC
## download_pathway_archive

### Description
Download a monthly bulk archive of WikiPathways pathway content for a specific organism and format (GPML, GMT, or SVG). Without an organism argument, opens the data browser in the default web browser.

### Method
```python
pwpw.download_pathway_archive(date: str = None, organism: str = None, format: str = 'gpml', destpath: str = None)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
* **date** (str) - Optional - The date of the archive in YYYYMMDD format.
* **organism** (str) - Optional - The organism for which to download the archive (e.g., 'Homo sapiens'). If None, opens the data browser.
* **format** (str) - Optional - The desired format ('gpml', 'gmt', or 'svg'). Defaults to 'gpml'.
* **destpath** (str) - Optional - The destination path to save the downloaded file.

### Request Example
```python
import pywikipathways as pwpw

# Download current GPML archive for mouse
filename = pwpw.download_pathway_archive(organism='Mus musculus')
print(f"Downloaded: {filename}")

# Download GMT archive for a specific date
filename = pwpw.download_pathway_archive(
    date='20230710',
    organism='Homo sapiens',
    format='gmt'
)
print(f"Downloaded: {filename}")

# Download SVG archive to a specific folder
filename = pwpw.download_pathway_archive(
    date='20230710',
    organism='Rattus norvegicus',
    format='svg',
    destpath='/tmp/'
)

# Browse archive without downloading (opens browser)
pwpw.download_pathway_archive(format='gmt')
```

### Response
#### Success Response (200)
- The filename of the downloaded archive.

#### Response Example
```
Downloaded: wikipathways-20230710-gmt-Homo_sapiens.gmt
```
```

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

### Get System Code for Ensembl

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-bridgedbpy.ipynb

Retrieve the system code for the Ensembl identifier system using bridgedbpy. This code is used in various database queries.

```python
brdgdbp.get_system_code("Ensembl")
```

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

### Download Pathway Archive for Specific Organism and Format

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Downloads the latest pathway archive for a specified organism and format (e.g., GMT). The file is saved to the current working directory or a specified destination path.

```python
pwpw.download_pathway_archive(organism="Mus musculus", format="gmt")
```

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

### Retrieve full GPML XML content

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Fetches the complete GPML (GenMAPP Pathway Markup Language) XML content for a given WikiPathways ID. Includes basic error handling for non-existent pathways.

```python
import pywikipathways as pwpw

gpml_str = pwpw.get_pathway('WP554')
print(gpml_str[:500])
# <?xml version='1.0' encoding='utf-8'?>
# <Pathway xmlns="http://pathvisio.org/GPML/2013a" Name="ACE inhibitor pathway" ...>

# Error handling
try:
    gpml = pwpw.get_pathway('WP99999')
except RuntimeError as e:
    print(f"Error: {e}")
    # Error: Failed to retrieve GPML (404).
```

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

### Import pywikipathways and bridgedbpy

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-bridgedbpy.ipynb

Import the core libraries for pathway data access and identifier mapping. These imports are necessary to use the functions provided by the packages.

```python
import pywikipathways as pwpw
import bridgedbpy as brdgdbp
```

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

### List Supported Organisms with pywikipathways

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-bridgedbpy.ipynb

Retrieve a list of all organism names supported by WikiPathways. This is useful for verifying available species and avoiding typos in subsequent queries.

```python
org_names = pwpw.list_organisms()
```

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

### Get Organism Code with bridgedbpy

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-bridgedbpy.ipynb

Convert a full organism name to its corresponding short code used by WikiPathways and BridgeDb. This is necessary for functions that require organism codes.

```python
brdgdbp.get_organism_code(org_names[14])
```

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

### Get Recent Changes

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieves pathways revised after a given timestamp. Returns a DataFrame excluding verbose author and description fields. Use `get_recent_changes_ids` and `get_recent_changes_names` for IDs and names only.

```python
import pywikipathways as pwpw

# Pathways changed since January 1, 2024
recent = pwpw.get_recent_changes(20240101)
print(recent[['id', 'name', 'species', 'revision']].head())
```

```python
# IDs and names only
ids   = pwpw.get_recent_changes_ids(20240101)
names = pwpw.get_recent_changes_names(20240101)
for wpid, name in zip(ids[:5], names[:5]):
    print(wpid, "->", name)
```

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

### list_pathways

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve a DataFrame of all pathways for a given species or all species.

```APIDOC
## list_pathways

### Description
Retrieve a DataFrame of all pathways for a given species (or all species if no organism is specified), including WPID, name, species, URL, and revision number.

### Method
`list_pathways(organism: str = None)`

### Parameters
- **organism** (str, optional) - The name of the organism to filter pathways by. If None, all pathways are returned.

### Response
- **DataFrame** - A pandas DataFrame containing pathway information (id, url, name, species, revision).
```

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

### Basic Search with find_pathways_by_literature

Source: https://github.com/wikipathways/pywikipathways/blob/main/LITERATURE_API_UPDATE.md

Use this function to search for pathways related to a given query. It supports searching by keywords, PMID, author name, and journal. Ensure proper error handling for network issues or no results.

```python
from pywikipathways.find_pathways_by_literature import find_pathways_by_literature

# Search for pathways related to cancer
results = find_pathways_by_literature('cancer')
if results is not None:
    print(f"Found {len(results)} pathways related to cancer")
    print(results.head())
else:
    print("No pathways found or network error")

# Search by PMID
results = find_pathways_by_literature('15134803')

# Search by author name  
results = find_pathways_by_literature('Schwartz GL')

# Search by journal
results = find_pathways_by_literature('Eur J Pharmacol')
```

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

### Get System Code for Entrez Gene

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-bridgedbpy.ipynb

Retrieve the system code for the Entrez Gene identifier system using bridgedbpy. Note that some codes are not intuitive and require this function for accuracy.

```python
brdgdbp.get_system_code("Entrez Gene")
```

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

### List Pathways for a Species

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve a DataFrame of all pathways for a given species. Displays the head of the DataFrame. If no organism is specified, retrieves all pathways across all species.

```python
import pywikipathways as pwpw

# All pathways for mouse
df = pwpw.list_pathways('Mus musculus')
print(df.head())

# All pathways across all species
all_df = pwpw.list_pathways()
print(f"Total pathways: {len(all_df)}")
```

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

### Get Pathway IDs, Names, and URLs by Community

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Convenience accessors to retrieve pathway IDs, names, or URLs for a specific community. Iterates through and prints WPIDs and names for the 'COVID-19' community.

```python
import pywikipathways as pwpw

ids   = pwpw.get_pathway_ids_by_community("COVID-19")
names = pwpw.get_pathway_names_by_community("COVID-19")
urls  = pwpw.get_pathway_urls_by_community("COVID-19")

for wpid, name in zip(ids, names):
    print(wpid, "->", name)
```

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

### Get Metabolite Identifiers from Pathway

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-bridgedbpy.ipynb

Retrieve a list of metabolite identifiers (e.g., ChEBI) for a given pathway ID. Specify the desired identifier system using BridgeDb system codes.

```python
pwpw.get_xref_list('WP554', brdgdbp.get_system_code('ChEBI'))
```

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

### List Pathway URLs for a Species

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve a pandas Series of pathway URLs for a given species. Displays the first 5 URLs.

```python
import pywikipathways as pwpw

urls = pwpw.list_pathway_urls('Homo sapiens')
print(urls.head())
```

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

### Get Gene Identifiers from Pathway

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-bridgedbpy.ipynb

Retrieve a list of gene identifiers (e.g., Ensembl) for a given pathway ID. Specify the desired identifier system using BridgeDb system codes.

```python
pwpw.get_xref_list('WP554', brdgdbp.get_system_code('Ensembl'))
```

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

### Download Specific Date Pathway Archive

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Downloads a pathway archive for a specific date, organism, and format. This ensures reproducibility by accessing a historical snapshot of the data.

```python
pwpw.download_pathway_archive(date="20171010", organism="Mus musculus", format="gmt")
```

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

### Get Xref List

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieves unique biological entity identifiers (Xrefs) from a pathway's datanode TSV for a specific database system. Supported system codes are listed in the documentation. Includes error handling for unsupported codes.

```python
import pywikipathways as pwpw

# Get Ensembl gene IDs for all datanodes in WP554
ensembl_ids = pwpw.get_xref_list('WP554', 'En')
print(ensembl_ids[:5])
# ['ENSG00000159640', 'ENSG00000162551', ...]
```

```python
# NCBI gene IDs, with prefix kept (compact=True)
ncbi_ids_compact = pwpw.get_xref_list('WP554', 'L', compact=True)
print(ncbi_ids_compact[:3])
# ['ncbigene:4311', 'ncbigene:1636', ...]
```

```python
# ChEBI compound IDs
chebi_ids = pwpw.get_xref_list('WP4846', 'Ce')
print(chebi_ids[:5])
```

```python
# Error handling
try:
    result = pwpw.get_xref_list('WP554', 'XX')
except ValueError as e:
    print(f"Unsupported code: {e}")
```

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

### Display Pathway IDs

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Display the Series of extracted human Glioblastoma pathway IDs. This confirms the IDs that will be used for import.

```python
human_gbm_wpids
```

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

### Display Imported Pathway Image

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Display the visual representation of the pathway that was just imported into Cytoscape. This confirms the successful import and visualization.

```python
p4c.notebook_show_image()
```

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

### find_pathway_ids_by_xref / find_pathway_names_by_xref / find_pathway_urls_by_xref

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Return just IDs, names, or URLs from an Xref-based pathway search.

```APIDOC
## find_pathway_ids_by_xref / find_pathway_names_by_xref / find_pathway_urls_by_xref

### Description
Return just IDs, names, or URLs from an Xref-based pathway search.

### Method
```python
find_pathway_ids_by_xref(identifier: str, system_code: str)
find_pathway_names_by_xref(identifier: str, system_code: str)
find_pathway_urls_by_xref(identifier: str, system_code: str)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
* **identifier** (str) - Required - The database identifier of the biological entity.
* **system_code** (str) - Required - The BridgeDb system code for the database (e.g., 'En', 'L', 'U').

### Request Example
```python
import pywikipathways as pwpw

# Ensembl identifier for TNF
ids = pwpw.find_pathway_ids_by_xref('ENSG00000232810', 'En')
print(list(ids[:5]))

names = pwpw.find_pathway_names_by_xref('ENSG00000232810', 'En')
print(list(names[:3]))
```

### Response
#### Success Response (List of strings)
- Returns a list of pathway IDs, names, or URLs matching the Xref query.

#### Response Example
```
['WP2813', 'WP4341', 'WP4673', 'WP1584', 'WP2571']
```
```

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

### Retrieve Specific Pathway Data with Helper Functions

Source: https://github.com/wikipathways/pywikipathways/blob/main/LITERATURE_API_UPDATE.md

Utilize helper functions to extract specific types of pathway information such as IDs, names, or URLs based on a literature query. These functions are useful when only a particular data point is needed.

```python
from pywikipathways.find_pathways_by_literature import (
    find_pathway_ids_by_literature,
    find_pathway_names_by_literature, 
    find_pathway_urls_by_literature
)

# Get just the pathway IDs
pathway_ids = find_pathway_ids_by_literature('diabetes')
if pathway_ids is not None:
    print("Pathway IDs:", list(pathway_ids))

# Get just the pathway names
pathway_names = find_pathway_names_by_literature('diabetes')
if pathway_names is not None:
    print("Pathway names:", list(pathway_names))

# Get just the pathway URLs
pathway_urls = find_pathway_urls_by_literature('diabetes')
if pathway_urls is not None:
    print("Pathway URLs:", list(pathway_urls))
```

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

### List Pathways for a Specific Organism

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Retrieve a DataFrame containing information about all pathways for a given organism. This includes pathway ID, URL, name, species, and revision number. Ensure the organism name is spelled correctly as listed by `pwpw.list_organisms()`.

```python
hs_pathways = pwpw.list_pathways('Homo sapiens')
```

```python
hs_pathways
```

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

### Find Pathway URLs by Xref

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Retrieves a list of pathway URLs associated with a given identifier and system code. Be aware that a pathway may be listed multiple times if the Xref appears more than once.

```python
>>> find_pathway_urls_by_xref('ENSG00000232810','En')
0     https://www.wikipathways.org/index.php/Pathway...
1     https://www.wikipathways.org/index.php/Pathway...
2     https://www.wikipathways.org/index.php/Pathway...
3     https://www.wikipathways.org/index.php/Pathway...
4     https://www.wikipathways.org/index.php/Pathway...
                                    ...
82    https://www.wikipathways.org/index.php/Pathway...
83    https://www.wikipathways.org/index.php/Pathway...
84    https://www.wikipathways.org/index.php/Pathway...
85    https://www.wikipathways.org/index.php/Pathway...
86    https://www.wikipathways.org/index.php/Pathway...
Name: url, Length: 87, dtype: object
```

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

### Open pathway revision history in browser

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Opens the GitHub revision history page for a specific WikiPathways pathway directly in the default web browser.

```python
import pywikipathways as pwpw


```

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

### List Pathway IDs for a Species

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve a pandas Series of pathway WPIDs for a given species. Displays the first 5 IDs.

```python
import pywikipathways as pwpw

ids = pwpw.list_pathway_ids('Homo sapiens')
print(ids.head())
```

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

### get_pathway_info

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve metadata for a specific pathway (or all pathways) as a DataFrame, including WPID, URL, name, species, revision, authors, description, and citedIn.

```APIDOC
## get_pathway_info

### Description
Retrieve metadata for a specific pathway (or all pathways) as a DataFrame, including WPID, URL, name, species, revision, authors, description, and citedIn.

### Method
```python
get_pathway_info(pathway_id: str = None)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
* **pathway_id** (str) - Optional - The WikiPathways ID of the pathway. If not provided, metadata for all pathways is returned.

### Request Example
```python
import pywikipathways as pwpw

# Single pathway info
info = pwpw.get_pathway_info('WP554')
print(info[['id', 'name', 'species', 'revision']].iloc[0])

# All pathway info
all_info = pwpw.get_pathway_info()
print(f"Total pathways: {len(all_info)}")
print(all_info.columns.tolist())
```

### Response
#### Success Response (Pandas DataFrame)
- Returns a Pandas DataFrame containing pathway metadata.

#### Response Example
```
id           WP554
name         ACE inhibitor pathway
species      Homo sapiens
revision     12345
```
```

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

### Find Pathway IDs by Xref

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Retrieve a list of pathway WPIDs that contain a specific cross-reference identifier and system code. Note that the same pathway may appear multiple times if the Xref is present more than once.

```python
help(pwpw.find_pathway_ids_by_xref)
```

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

### get_pathway

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve the full GPML (GenMAPP Pathway Markup Language) XML content for a specific WikiPathways pathway.

```APIDOC
## get_pathway

### Description
Retrieve the full GPML (GenMAPP Pathway Markup Language) XML content for a specific WikiPathways pathway.

### Method
```python
get_pathway(pathway_id: str)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
* **pathway_id** (str) - Required - The WikiPathways ID of the pathway (e.g., 'WP554').

### Request Example
```python
import pywikipathways as pwpw

gpml_str = pwpw.get_pathway('WP554')
print(gpml_str[:500])

# Error handling
try:
    gpml = pwpw.get_pathway('WP99999')
except RuntimeError as e:
    print(f"Error: {e}")
```

### Response
#### Success Response (String)
- Returns the GPML XML content as a string.

#### Response Example
```xml
<?xml version='1.0' encoding='utf-8'?>
<Pathway xmlns="http://pathvisio.org/GPML/2013a" Name="ACE inhibitor pathway" ...>
```

#### Error Response
- **404**: If the pathway ID is not found.
- **RuntimeError**: For other retrieval errors.
```

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

### Display Found Pathways

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Print the resulting DataFrame containing pathways found via a cross-reference search.

```python
tnf_pathways
```

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

### find_pathway_ids_by_literature / find_pathway_names_by_literature / find_pathway_urls_by_literature

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Return just IDs, names, or URLs from a literature-based pathway search.

```APIDOC
## find_pathway_ids_by_literature / find_pathway_names_by_literature / find_pathway_urls_by_literature

### Description
Return just IDs, names, or URLs from a literature-based pathway search.

### Method
```python
find_pathway_ids_by_literature(query: str)
find_pathway_names_by_literature(query: str)
find_pathway_urls_by_literature(query: str)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
* **query** (str) - Required - The literature citation (PMID, title keyword, journal abbreviation, year, or author name).

### Request Example
```python
import pywikipathways as pwpw

ids = pwpw.find_pathway_ids_by_literature('15134803')
print(list(ids))
```

### Response
#### Success Response (List of strings)
- Returns a list of pathway IDs, names, or URLs matching the literature query.

#### Response Example
```
['WP197', 'WP1234', ...]
```
```

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

### Find pathways by multiple text terms

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Performs a search for pathways where any of the provided terms are present in the pathway information.

```python
# Multi-term search (any term matches)
multi = pwpw.find_pathways_by_text(['TNF', 'NF-kB'])
print(len(multi))
```

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

### List Organisms

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve the list of all organism names supported by WikiPathways. Displays the first 5 organisms.

```python
import pywikipathways as pwpw

organisms = pwpw.list_organisms()
print(organisms[:5])
```

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

### Import WikiPathway into Cytoscape

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Imports a pathway from WikiPathways into Cytoscape using its ID. The 'id' parameter is dynamically set from the 'mcm1_pathways' variable.

```python
p4c.commands_run('wikipathways import-as-pathway id=' + mcm1_pathways[0])
```

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

### Import Pathway into Cytoscape

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Import a specific pathway into Cytoscape using its WPID. This command is executed via the py4cytoscape interface.

```python
p4c.commands_run('wikipathways import-as-pathway id=' + human_gbm_wpids[0])
```

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

### Find Pathway Names by Xref

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Retrieve a list of pathway names that contain a specific cross-reference identifier and system code. Similar to finding IDs, pathways may be listed multiple times if the Xref appears more than once.

```python
help(pwpw.find_pathway_names_by_xref)
```

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

### Retrieve Pathway in GPML Format

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Fetches a pathway in its native GPML (XML) format using its WikiPathways ID. This is useful for programmatic access to pathway data structures.

```python
gpml = pwpw.get_pathway('WP554')
```

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

### Display Search Results

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Display the DataFrame containing the search results for pathways. This shows the score, ID, URL, name, species, and revision of each pathway found.

```python
gbm_pathways
```

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

### Retrieve pathway metadata

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Fetches metadata for a single pathway or all pathways, returning a DataFrame with details like ID, name, species, revision, authors, and description.

```python
import pywikipathways as pwpw

# Single pathway info
info = pwpw.get_pathway_info('WP554')
print(info[['id', 'name', 'species', 'revision']].iloc[0])
# id           WP554
# name         ACE inhibitor pathway
# species      Homo sapiens
# revision     12345

# All pathway info
all_info = pwpw.get_pathway_info()
print(f"Total pathways: {len(all_info)}")
print(all_info.columns.tolist())
# ['id', 'url', 'name', 'species', 'revision', 'authors', 'description', 'citedIn']
```

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

### get_pathways_by_ontology_term

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve all pathways annotated with a given ontology term.

```APIDOC
## get_pathways_by_ontology_term

### Description
Retrieve all pathways annotated with a given ontology term (by exact term ID).

### Method
```python
pwpw.get_pathways_by_ontology_term(term_id: str)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
* **term_id** (str) - Required - The ontology term ID.

### Request Example
```python
import pywikipathways as pwpw

df = pwpw.get_pathways_by_ontology_term('PW:0000010')
print(df[['id', 'pathways_id', 'pathways_name']].head())
```

### Response
#### Success Response (200)
- DataFrame with pathway information.

#### Response Example
```
   id pathways_id             pathways_name
0  WP554      WP554  MAPK signaling pathway
1  WP2406     WP2406  Insulin signaling pathway
...
```
```

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

### Find Pathways by Xref

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Search for pathways associated with a specific molecule identifier (e.g., gene symbol 'TNF') and its corresponding system code (e.g., 'H' for HGNC).

```python
tnf_pathways = pwpw.find_pathways_by_xref('TNF','H')
```

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

### list_organisms

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve the list of all organism names supported by WikiPathways.

```APIDOC
## list_organisms

### Description
Retrieve the list of all organism names supported by WikiPathways.

### Method
`list_organisms()`

### Parameters
None

### Response
- **organisms** (list) - A list of organism names.
```

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

### Find pathway IDs, names, and URLs by text

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Convenience functions to retrieve only pathway IDs, names, or URLs based on a text search. Useful for targeted data extraction.

```python
import pywikipathways as pwpw

ids   = pwpw.find_pathway_ids_by_text('insulin')
names = pwpw.find_pathway_names_by_text('insulin')
urls  = pwpw.find_pathway_urls_by_text('insulin')

for wpid, name in zip(ids, names):
    print(wpid, "->", name)
# WP481 -> Insulin Signaling
```

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

### List Pathway Names for a Species

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve a pandas Series of pathway names for a given species. Displays the first 5 names.

```python
import pywikipathways as pwpw

names = pwpw.list_pathway_names('Homo sapiens')
print(names.head())
```

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

### get_ontology_terms

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve ontology term annotations for a specific pathway or all pathways.

```APIDOC
## get_ontology_terms

### Description
Retrieve ontology term annotations for a specific pathway (or all pathways), returning a flattened DataFrame with term IDs, names, and parent terms.

### Method
```python
pwpw.get_ontology_terms(pathway_id: str = None)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
* **pathway_id** (str) - Optional - The ID of the pathway to retrieve terms for. If None, retrieves terms for all pathways.

### Request Example
```python
import pywikipathways as pwpw

# Ontology terms for a single pathway
terms = pwpw.get_ontology_terms('WP554')
print(terms[['id', 'terms_id', 'terms_name', 'terms_parent']].head())
```

### Response
#### Success Response (200)
- DataFrame with ontology term information (id, terms_id, terms_name, terms_parent).

#### Response Example
```
   id      terms_id                  terms_name terms_parent
0  WP554  PW:0000010  cardiovascular system development  PW:0000001
1  WP554  DOID:10763                     hypertension  DOID:4852
...
```
```

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

### find_pathways_by_literature

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Search WikiPathways by literature citation — accepts PMID, title keyword, journal abbreviation, year, or author name.

```APIDOC
## find_pathways_by_literature

### Description
Search WikiPathways by literature citation — accepts PMID, title keyword, journal abbreviation, year, or author name.

### Method
```python
find_pathways_by_literature(query: str)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
* **query** (str) - Required - The literature citation (PMID, title keyword, journal abbreviation, year, or author name).

### Request Example
```python
import pywikipathways as pwpw

# Search by PMID
df_pmid = pwpw.find_pathways_by_literature('15134803')
print(df_pmid[['id', 'name']].head())

# Search by author name
df_author = pwpw.find_pathways_by_literature('Schwartz GL')
print(df_author[['id', 'name']].head())

# Search by year
df_year = pwpw.find_pathways_by_literature('2021')
print(f"Pathways citing 2021 publications: {len(df_year)}")
```

### Response
#### Success Response (Pandas DataFrame)
- Returns a Pandas DataFrame containing pathway information (id, name, species, etc.) matching the literature query.

#### Response Example
```
         id                                name
0    WP197  Insulin signaling pathway
1   WP1234  MAPK signaling pathway
```
```

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

### Find pathways by text field

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Searches for pathways using a specific text query and allows filtering by a particular field like 'name'.

```python
import pywikipathways as pwpw

name_results = pwpw.find_pathways_by_text('apoptosis', field='name')
print(name_results[['id', 'name']].head())
```

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

### Find Pathway URLs by Xref

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways_Overview.ipynb

Retrieve a list of pathway URLs that contain a specific cross-reference identifier and system code. The function notes that multiple listings of the same pathway may occur if the Xref is present multiple times.

```python
help(pwpw.find_pathway_urls_by_xref)
```

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

### get_pathway_history

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Open the GitHub revision history page for a pathway in the default web browser.

```APIDOC
## get_pathway_history

### Description
Open the GitHub revision history page for a pathway in the default web browser.

### Method
```python
get_pathway_history(pathway_id: str)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
* **pathway_id** (str) - Required - The WikiPathways ID of the pathway.

### Request Example
```python
import pywikipathways as pwpw

pwpw.get_pathway_history('WP554')
```

### Response
#### Success Response
- Opens the pathway's revision history page in the default web browser. No data is returned directly to the script.
```

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

### Find pathway IDs, names, and URLs by cross-reference (Xref)

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Convenience functions to retrieve only pathway IDs, names, or URLs when searching pathways using a cross-reference identifier.

```python
import pywikipathways as pwpw

# Ensembl identifier for TNF
ids = pwpw.find_pathway_ids_by_xref('ENSG00000232810', 'En')
print(list(ids[:5]))
# ['WP2813', 'WP4341', 'WP4673', 'WP1584', 'WP2571']

names = pwpw.find_pathway_names_by_xref('ENSG00000232810', 'En')
print(list(names[:3]))
# ['Mammary gland development pathway - Embryonic development',
#  'Non-genomic actions of 1,25 dihydroxyvitamin D3',
#  'Male infertility']
```

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

### Find Pathways by Text Search

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Search all WikiPathways pathway metadata for a query string. Optionally restrict the search to a single field. Displays the 'id', 'name', and 'species' for the first 5 results of a 'cancer' search.

```python
import pywikipathways as pwpw

# Search across all fields
results = pwpw.find_pathways_by_text('cancer')
print(results[['id', 'name', 'species']].head())
```

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

### find_pathway_ids_by_orcid / find_pathway_names_by_orcid / find_pathway_urls_by_orcid

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Convenience accessors for ORCID-based search results.

```APIDOC
## find_pathway_ids_by_orcid / find_pathway_names_by_orcid / find_pathway_urls_by_orcid

### Description
Convenience accessors for ORCID-based search results.

### Method
```python
find_pathway_ids_by_orcid(orcid_id: str)
find_pathway_names_by_orcid(orcid_id: str)
find_pathway_urls_by_orcid(orcid_id: str)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
* **orcid_id** (str) - Required - The ORCID identifier of the researcher.

### Request Example
```python
import pywikipathways as pwpw

orcid = '0000-0001-9773-4008'
ids   = pwpw.find_pathway_ids_by_orcid(orcid)
names = pwpw.find_pathway_names_by_orcid(orcid)

for wpid, name in zip(ids, names):
    print(wpid, "->", name)
```

### Response
#### Success Response (List of strings)
- Returns a list of pathway IDs, names, or URLs contributed by the specified researcher.

#### Response Example
```
WP554 -> ACE inhibitor pathway
```
```

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

### find_pathway_ids_by_text / find_pathway_names_by_text / find_pathway_urls_by_text

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Convenience wrappers that return just IDs, names, or URLs from a text search result.

```APIDOC
## find_pathway_ids_by_text / find_pathway_names_by_text / find_pathway_urls_by_text

### Description
Convenience wrappers that return just IDs, names, or URLs from a text search result.

### Method
```python
find_pathway_ids_by_text(query: str)
find_pathway_names_by_text(query: str)
find_pathway_urls_by_text(query: str)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
* **query** (str) - Required - The text to search for.

### Request Example
```python
import pywikipathways as pwpw

ids   = pwpw.find_pathway_ids_by_text('insulin')
names = pwpw.find_pathway_names_by_text('insulin')
urls  = pwpw.find_pathway_urls_by_text('insulin')

for wpid, name in zip(ids, names):
    print(wpid, "->", name)
```

### Response
#### Success Response (List of strings)
- Returns a list of pathway IDs, names, or URLs corresponding to the search query.

#### Response Example
```
WP481 -> Insulin Signaling
```
```

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

### list_pathway_urls

Source: https://context7.com/wikipathways/pywikipathways/llms.txt

Retrieve a pandas Series of pathway URLs for a given species.

```APIDOC
## list_pathway_urls

### Description
Retrieve a pandas Series of pathway URLs for a given species.

### Method
`list_pathway_urls(organism: str)`

### Parameters
- **organism** (str) - The name of the organism to filter pathway URLs by.

### Response
- **Series** - A pandas Series containing pathway URLs.
```

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

### Check Cytoscape Connection

Source: https://github.com/wikipathways/pywikipathways/blob/main/docs/pywikipathways-and-py4cytoscape.ipynb

Verify that py4cytoscape is successfully connected to a running Cytoscape instance. This is essential before proceeding with network operations.

```python
p4c.cytoscape_ping()
```
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