# PubChemQuery
    [](https://colab.research.google.com/drive/1hKrOe6K1L_fpd6_izhpVXaA1Zmq6Z8Fo?usp=sharing)
**PubChemQuery:** A Python Package for Accessing Chemical Information from [PubChem](https://pubchem.ncbi.nlm.nih.gov/).
PubChemQuery is a Python package that provides a simple and intuitive API for retrieving chemical information from the PubChem database. With this package, you can easily fetch chemical data, including:
* CID (Compound ID) by name
* All CIDs by name
* 2D images by CID or name
* SDF (Structure Data File) by CID or name
* Compound properties, including:
- Molecular formula and weight
- SMILES and InChI representations
- IUPAC name and title
- Physicochemical properties (e.g., XLogP, exact mass, TPSA)
- Structural features (e.g., bond and atom counts, stereochemistry)
- 3D properties (e.g., volume, steric quadrupole moments, feature counts)
- Fingerprint and conformer information
The package offers a straightforward interface, allowing users to access PubChem data with minimal code. Whether you're a chemist, researcher, or developer, PubChemQuery simplifies the process of integrating chemical information into your projects.
**Key Features:**
Retrieve chemical data by name or CID
Access 2D images and SDF files
Get compound properties, including physicochemical, structural, and 3D features
Easy-to-use API with minimal code required
**Simple and Concise API:**
There are functions that perform all of the above-mentioned tasks, making it easy to integrate PubChem data into your projects:
* `get_cid_by_inchi(inchi)`: Get a CID by InChI
* `get_cids_by_formula(formula)`: Get CIDs by formula
* `get_cid_by_name(name)`: Get CID by name
* `get_cids_by_name(name)`: Get all CIDs by name
* `get_image_by_cid(cid)`: Get 2D image by CID
* `get_image_by_name(name)`: Get 2D image by name
* `get_image_by_inchi(inchi)`: Get 2D image by InChI
* `get_structure_by_cid(cid)`: Get SDF by CID
* `get_structure_by_name(name)`: Get SDF by name
* `get_similar_structures_cids_by_compound_id(cid/SMILES/InChI)`: Get similar structures CIDs by cid, SMILES, InChI
**Compound Object:**
The package also includes a `Compound` object that encapsulates the retrieved data, providing a convenient way
to access and manipulate the data.
* `compound(cid_or_name)`: Create a compound object with properties and methods
**Getting Started:**
To use PubChemQuery, simply install the package and import it into your Python script. Refer to the example code snippets above for a quick start.
## Installation
Install PubChemQuery with pip
```python
pip install PubChemQuery
```
## Examples
Import package as:
```python
import pubchemquery as pcq
```
Use the functions to retrieve data:
```python
# get a cid by formula
cid = pcq.get_cids_by_formula('C6H6')
print(type(cid), len(cid))
```
```python
# get a cid by inchi
cid = pcq.get_cid_by_inchi(
'InChI=1S/C6H5NO3/c8-6-3-1-5(2-4-6)7(9)10/h1-4,8H')
print(cid)
```
```python
# get a cid by name
cid = pcq.get_cid_by_name('benzene')
print(cid)
```
```python
# get all cids by name
cids = pcq.get_cids_by_name('benzene')
print(type(cids), len(cids))
```
```python
# get 2d image
# by cid
image = pcq.get_image_by_cid('241')
image
# by name
image = pcq.get_image_by_name('benzene')
image
# by inchi
image = pcq.get_image_by_inchi(
'InChI=1S/C6H5NO3/c8-6-3-1-5(2-4-6)7(9)10/h1-4,8H')
print(image)
```
```python
# get sdf by cid
sdf = pcq.get_structure_by_cid('241')
print(sdf)
```
```python
# get sdf by name
sdf = pcq.get_structure_by_name('benzene')
print(sdf)
```
```python
# get similar structure cids by cid
# cids = pcq.get_similar_structures_cids_by_compound_id('241')
# cids = pcq.get_similar_structures_cids_by_compound_id(
# 'C1=CC=CC=C1', compound_id='SMILES')
cids = pcq.get_similar_structures_cids_by_compound_id(
'InChI=1S/C6H6/c1-2-4-6-5-3-1/h1-6H', compound_id='InChI')
print(type(cids), len(cids))
```
Make a compound and then get its properties:
```python
# make a compound
cid = 2244
# compound = pcq.compound(cid)
# name
name = '2-acetyloxybenzoic acid'
compound = pcq.compound(name)
print(compound)
# properties
# InChI
print(compound.InChI)
# InChIKey
print(compound.InChIKey)
# IUPACName
print(compound.IUPACName)
# similar structure cids
print(len(compound.similar_structure_cids))
# image
compound.image
# dataframe
compound.prop_df()
```
## FAQ
For any question, contact me on [LinkedIn](https://www.linkedin.com/in/sina-gilassi/)
## Authors
- [@sinagilassi](https://www.github.com/sinagilassi)
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"description": "\r\n# PubChemQuery\r\n\r\n\r\n\r\n    [](https://colab.research.google.com/drive/1hKrOe6K1L_fpd6_izhpVXaA1Zmq6Z8Fo?usp=sharing)\r\n\r\n\r\n\r\n**PubChemQuery:** A Python Package for Accessing Chemical Information from [PubChem](https://pubchem.ncbi.nlm.nih.gov/).\r\n\r\n\r\n\r\nPubChemQuery is a Python package that provides a simple and intuitive API for retrieving chemical information from the PubChem database. With this package, you can easily fetch chemical data, including:\r\n\r\n\r\n\r\n* CID (Compound ID) by name\r\n\r\n* All CIDs by name\r\n\r\n* 2D images by CID or name\r\n\r\n* SDF (Structure Data File) by CID or name\r\n\r\n* Compound properties, including:\r\n\r\n - Molecular formula and weight\r\n\r\n - SMILES and InChI representations\r\n\r\n - IUPAC name and title\r\n\r\n - Physicochemical properties (e.g., XLogP, exact mass, TPSA)\r\n\r\n - Structural features (e.g., bond and atom counts, stereochemistry)\r\n\r\n - 3D properties (e.g., volume, steric quadrupole moments, feature counts)\r\n\r\n - Fingerprint and conformer information\r\n\r\n\r\n\r\nThe package offers a straightforward interface, allowing users to access PubChem data with minimal code. Whether you're a chemist, researcher, or developer, PubChemQuery simplifies the process of integrating chemical information into your projects.\r\n\r\n\r\n\r\n**Key Features:**\r\n\r\n\r\n\r\nRetrieve chemical data by name or CID\r\n\r\nAccess 2D images and SDF files\r\n\r\nGet compound properties, including physicochemical, structural, and 3D features\r\n\r\nEasy-to-use API with minimal code required\r\n\r\n\r\n\r\n**Simple and Concise API:**\r\n\r\n\r\n\r\nThere are functions that perform all of the above-mentioned tasks, making it easy to integrate PubChem data into your projects:\r\n\r\n\r\n\r\n* `get_cid_by_inchi(inchi)`: Get a CID by InChI\r\n\r\n* `get_cids_by_formula(formula)`: Get CIDs by formula\r\n\r\n* `get_cid_by_name(name)`: Get CID by name\r\n\r\n* `get_cids_by_name(name)`: Get all CIDs by name\r\n\r\n* `get_image_by_cid(cid)`: Get 2D image by CID\r\n\r\n* `get_image_by_name(name)`: Get 2D image by name\r\n\r\n* `get_image_by_inchi(inchi)`: Get 2D image by InChI\r\n\r\n* `get_structure_by_cid(cid)`: Get SDF by CID\r\n\r\n* `get_structure_by_name(name)`: Get SDF by name\r\n\r\n* `get_similar_structures_cids_by_compound_id(cid/SMILES/InChI)`: Get similar structures CIDs by cid, SMILES, InChI\r\n\r\n\r\n\r\n**Compound Object:**\r\n\r\nThe package also includes a `Compound` object that encapsulates the retrieved data, providing a convenient way\r\n\r\nto access and manipulate the data.\r\n\r\n\r\n\r\n* `compound(cid_or_name)`: Create a compound object with properties and methods\r\n\r\n\r\n\r\n**Getting Started:**\r\n\r\n\r\n\r\nTo use PubChemQuery, simply install the package and import it into your Python script. Refer to the example code snippets above for a quick start.\r\n\r\n\r\n\r\n## Installation\r\n\r\n\r\n\r\nInstall PubChemQuery with pip\r\n\r\n\r\n\r\n```python\r\n\r\n pip install PubChemQuery\r\n\r\n```\r\n\r\n\r\n\r\n## Examples\r\n\r\n\r\n\r\nImport package as:\r\n\r\n\r\n\r\n```python\r\n\r\nimport pubchemquery as pcq\r\n\r\n```\r\n\r\n\r\n\r\nUse the functions to retrieve data:\r\n\r\n\r\n\r\n```python\r\n\r\n# get a cid by formula\r\n\r\ncid = pcq.get_cids_by_formula('C6H6')\r\n\r\nprint(type(cid), len(cid))\r\n\r\n```\r\n\r\n\r\n\r\n```python\r\n\r\n# get a cid by inchi\r\n\r\ncid = pcq.get_cid_by_inchi(\r\n\r\n 'InChI=1S/C6H5NO3/c8-6-3-1-5(2-4-6)7(9)10/h1-4,8H')\r\n\r\nprint(cid)\r\n\r\n```\r\n\r\n\r\n\r\n```python\r\n\r\n# get a cid by name\r\n\r\ncid = pcq.get_cid_by_name('benzene')\r\n\r\nprint(cid)\r\n\r\n```\r\n\r\n\r\n\r\n```python\r\n\r\n# get all cids by name\r\n\r\ncids = pcq.get_cids_by_name('benzene')\r\n\r\nprint(type(cids), len(cids))\r\n\r\n```\r\n\r\n\r\n\r\n```python\r\n\r\n# get 2d image\r\n\r\n# by cid\r\n\r\nimage = pcq.get_image_by_cid('241')\r\n\r\nimage\r\n\r\n\r\n\r\n# by name\r\n\r\nimage = pcq.get_image_by_name('benzene')\r\n\r\nimage\r\n\r\n\r\n\r\n# by inchi\r\n\r\nimage = pcq.get_image_by_inchi(\r\n\r\n 'InChI=1S/C6H5NO3/c8-6-3-1-5(2-4-6)7(9)10/h1-4,8H')\r\n\r\nprint(image)\r\n\r\n```\r\n\r\n\r\n\r\n```python\r\n\r\n# get sdf by cid\r\n\r\nsdf = pcq.get_structure_by_cid('241')\r\n\r\nprint(sdf)\r\n\r\n```\r\n\r\n\r\n\r\n```python\r\n\r\n# get sdf by name\r\n\r\nsdf = pcq.get_structure_by_name('benzene')\r\n\r\nprint(sdf)\r\n\r\n```\r\n\r\n\r\n\r\n```python\r\n\r\n# get similar structure cids by cid\r\n\r\n# cids = pcq.get_similar_structures_cids_by_compound_id('241')\r\n\r\n# cids = pcq.get_similar_structures_cids_by_compound_id(\r\n\r\n# 'C1=CC=CC=C1', compound_id='SMILES')\r\n\r\ncids = pcq.get_similar_structures_cids_by_compound_id(\r\n\r\n 'InChI=1S/C6H6/c1-2-4-6-5-3-1/h1-6H', compound_id='InChI')\r\n\r\nprint(type(cids), len(cids))\r\n\r\n```\r\n\r\n\r\n\r\nMake a compound and then get its properties:\r\n\r\n\r\n\r\n```python\r\n\r\n# make a compound\r\n\r\ncid = 2244\r\n\r\n# compound = pcq.compound(cid)\r\n\r\n# name\r\n\r\nname = '2-acetyloxybenzoic acid'\r\n\r\ncompound = pcq.compound(name)\r\n\r\nprint(compound)\r\n\r\n# properties\r\n\r\n# InChI\r\n\r\nprint(compound.InChI)\r\n\r\n# InChIKey\r\n\r\nprint(compound.InChIKey)\r\n\r\n# IUPACName\r\n\r\nprint(compound.IUPACName)\r\n\r\n# similar structure cids\r\n\r\nprint(len(compound.similar_structure_cids))\r\n\r\n# image\r\n\r\ncompound.image\r\n\r\n# dataframe\r\n\r\ncompound.prop_df()\r\n\r\n```\r\n\r\n\r\n\r\n## FAQ\r\n\r\n\r\n\r\nFor any question, contact me on [LinkedIn](https://www.linkedin.com/in/sina-gilassi/) \r\n\r\n\r\n\r\n\r\n\r\n## Authors\r\n\r\n\r\n\r\n- [@sinagilassi](https://www.github.com/sinagilassi)\r\n\r\n",
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