PubChem View API

The PubChem View module provides access to experimental property data from PubChem's PUG View service. This includes extraction of experimental values, units, and comprehensive reference information.

provesid.pubchemview

Classes

PropertyData dataclass

Data structure for holding extracted property information

Source code in src/provesid/pubchemview.py

@dataclass
class PropertyData:
    """Data structure for holding extracted property information"""
    value: str
    unit: Optional[str] = None
    conditions: Optional[str] = None
    reference: Optional[str] = None
    reference_number: Optional[int] = None
    description: Optional[str] = None
    name: Optional[str] = None

PubChemViewError

Bases: Exception

Base exception class for PubChem View API errors

Source code in src/provesid/pubchemview.py

class PubChemViewError(Exception):
    """Base exception class for PubChem View API errors"""
    pass

PubChemViewNotFoundError

Bases: PubChemViewError

Exception raised when compound or property is not found

Source code in src/provesid/pubchemview.py

class PubChemViewNotFoundError(PubChemViewError):
    """Exception raised when compound or property is not found"""
    pass

PubChemView

A class that uses PUG View for extracting properties reported for each substance in PubChem but are not included in the standard API response for substance, compound, assay, etc. The response to these queries is a large JSON object that requires some post-processing to extract the relevant information.

Source code in src/provesid/pubchemview.py

class PubChemView:
    """
    A class that uses PUG View for extracting properties reported for each substance in PubChem but are not
    included in the standard API response for substance, compound, assay, etc.
    The response to these queries is a large JSON object that requires some post-processing to extract the
    relevant information.
    """

    def __init__(self, base_url: str = "https://pubchem.ncbi.nlm.nih.gov/rest/pug_view",
                 timeout: int = 30, max_retries: int = 3, backoff_factor: float = 1.0, use_cache: bool = True):
        """
        Initialize PubChemView API client

        Args:
            base_url: Base URL for PubChem PUG View API
            timeout: Request timeout in seconds
            max_retries: Maximum number of retry attempts
            backoff_factor: Backoff factor for retries
            use_cache: Whether to use cache for lookups (default: True). 
                      When False, skips cache lookup but still stores results.
        """
        self.base_url = base_url.rstrip('/')
        self.timeout = timeout
        self.max_retries = max_retries
        self.backoff_factor = backoff_factor
        self.logger = logging.getLogger(__name__)
        self.use_cache = use_cache

        # Rate limiting
        self.last_request_time = 0
        self.min_request_interval = 0.2  # 5 requests per second max

        # Standard experimental property headings
        self.experimental_properties = {
            "Accelerating Rate Calorimetry (ARC)": "Accelerating+Rate+Calorimetry+(ARC)",
            "Acid Value": "Acid+Value",
            "Autoignition Temperature": "Autoignition+Temperature", 
            "Boiling Point": "Boiling+Point",
            "Caco2 Permeability": "Caco2+Permeability",
            "Collision Cross Section": "Collision+Cross+Section",
            "Color/Form": "Color/Form",
            "Corrosivity": "Corrosivity",
            "Decomposition": "Decomposition",
            "Density": "Density",
            "Dielectric Constant": "Dielectric+Constant",
            "Differential Scanning Calorimetry (DSC)": "Differential+Scanning+Calorimetry+(DSC)",
            "Dispersion": "Dispersion",
            "Dissociation Constants": "Dissociation+Constants",
            "Enthalpy of Sublimation": "Enthalpy+of+Sublimation",
            "Flash Point": "Flash+Point",
            "Heat of Combustion": "Heat+of+Combustion",
            "Heat of Vaporization": "Heat+of+Vaporization",
            "Henry's Law Constant": "Henry's+Law+Constant",
            "Hydrophobicity": "Hydrophobicity",
            "Ionization Efficiency": "Ionization+Efficiency",
            "Ionization Potential": "Ionization+Potential",
            "Isoelectric Point": "Isoelectric+Point",
            "Kovats Retention Index": "Kovats+Retention+Index",
            "LogP": "LogP",
            "LogS": "LogS",
            "Melting Point": "Melting+Point",
            "Odor": "Odor",
            "Odor Threshold": "Odor+Threshold",
            "Optical Rotation": "Optical+Rotation",
            "Other Experimental Properties": "Other+Experimental+Properties",
            "pH": "pH",
            "Physical Description": "Physical+Description",
            "Polymerization": "Polymerization",
            "Refractive Index": "Refractive+Index",
            "Relative Evaporation Rate": "Relative+Evaporation+Rate",
            "Self-Accelerating Decomposition Temperature (SADT)": "Self-Accelerating+Decomposition+Temperature+(SADT)",
            "Solubility": "Solubility",
            "Stability/Shelf Life": "Stability/Shelf+Life",
            "Surface Tension": "Surface+Tension",
            "Taste": "Taste",
            "Vapor Density": "Vapor+Density",
            "Vapor Pressure": "Vapor+Pressure",
            "Viscosity": "Viscosity"
        }

    def clear_cache(self):
        """Clear all cached results for PubChem View"""
        from .cache import clear_pubchemview_cache
        clear_pubchemview_cache()

    def get_cache_info(self):
        """Get cache statistics for PubChem View cached methods"""
        from .cache import get_pubchemview_cache_info
        return get_pubchemview_cache_info()

    def _rate_limit(self):
        """Implement rate limiting to respect PubChem's usage policy"""
        current_time = time.time()
        time_since_last = current_time - self.last_request_time
        if time_since_last < self.min_request_interval:
            time.sleep(self.min_request_interval - time_since_last)
        self.last_request_time = time.time()

    def _make_request(self, url: str) -> Dict[str, Any]:
        """
        Make HTTP request with retries and error handling

        Args:
            url: Request URL

        Returns:
            JSON response as dictionary

        Raises:
            PubChemViewError: For API errors
            PubChemViewNotFoundError: When resource not found
        """
        self._rate_limit()

        for attempt in range(self.max_retries + 1):
            try:
                self.logger.debug(f"Making request to: {url}")
                response = requests.get(url, timeout=self.timeout)

                if response.status_code == 200:
                    return response.json()
                elif response.status_code == 404:
                    raise PubChemViewNotFoundError(f"Resource not found: {url}")
                else:
                    response.raise_for_status()

            except requests.exceptions.RequestException as e:
                if attempt == self.max_retries:
                    raise PubChemViewError(f"Request failed after {self.max_retries + 1} attempts: {e}")

                wait_time = self.backoff_factor * (2 ** attempt)
                self.logger.warning(f"Request failed, retrying in {wait_time:.1f}s: {e}")
                time.sleep(wait_time)

        # This should never be reached due to exceptions above
        raise PubChemViewError("Unexpected error in request handling")

    @cached(service='pubchemview')
    def get_experimental_properties(self, cid: Union[int, str]) -> Dict[str, Any]:
        """
        Get all experimental properties for a compound

        Args:
            cid: PubChem Compound ID

        Returns:
            Raw JSON response containing all experimental properties
        """
        url = f"{self.base_url}/data/compound/{cid}/JSON?heading=Experimental+Properties"
        return self._make_request(url)

    @cached(service='pubchemview')
    def get_property(self, cid: Union[int, str], property_name: str) -> Dict[str, Any]:
        """
        Get a specific property for a compound

        Args:
            cid: PubChem Compound ID
            property_name: Name of the property (can be with spaces or plus signs)

        Returns:
            Raw JSON response for the specific property
        """
        # Convert property name to URL-safe format
        if property_name in self.experimental_properties:
            url_property = self.experimental_properties[property_name]
        else:
            url_property = property_name.replace(' ', '+')

        url = f"{self.base_url}/data/compound/{cid}/JSON?heading={url_property}"
        return self._make_request(url)


    def _extract_value_info(self, info_item: Dict[str, Any]) -> PropertyData:
        """
        Extract structured information from an Information item

        Args:
            info_item: Single Information dictionary from PUG View response

        Returns:
            PropertyData object with extracted information
        """
        # Extract value
        value_str = ""
        if "Value" in info_item and "StringWithMarkup" in info_item["Value"]:
            value_str = info_item["Value"]["StringWithMarkup"][0]["String"]

        # Extract reference
        reference = None
        reference_number = info_item.get("ReferenceNumber")
        if "Reference" in info_item and info_item["Reference"]:
            reference = info_item["Reference"][0]

        # Extract name/description if available
        name = info_item.get("Name", "")
        description = info_item.get("Description", "")

        # Attempt to parse units and conditions from value string
        unit, conditions = self._parse_value_string(value_str)

        return PropertyData(
            value=value_str,
            unit=unit,
            conditions=conditions,
            reference=reference,
            reference_number=reference_number,
            description=description if description else None,
            name=name if name else None
        )

    def _parse_value_string(self, value_str: str) -> tuple[Optional[str], Optional[str]]:
        """
        Attempt to parse units and conditions from a value string

        Args:
            value_str: Value string from PUG View

        Returns:
            Tuple of (unit, conditions)
        """
        import re

        # Common temperature patterns
        temp_pattern = r'at\s+(-?\d+(?:\.\d+)?)\s*°?C'
        temp_match = re.search(temp_pattern, value_str)
        conditions = None
        if temp_match:
            conditions = f"at {temp_match.group(1)}°C"

        # Common unit patterns
        unit_patterns = [
            r'(\d+(?:\.\d+)?)\s*(cP|mPa·s|Pa·s)', # viscosity
            r'(\d+(?:\.\d+)?)\s*(°C|K)', # temperature  
            r'(\d+(?:\.\d+)?)\s*(g/cm³|g/mL|kg/m³)', # density
            r'(\d+(?:\.\d+)?)\s*(mmHg|kPa|Pa|atm|bar)', # pressure
            r'(\d+(?:\.\d+)?)\s*(mN/m|N/m|dyn/cm)', # surface tension
            r'(\d+(?:\.\d+)?)\s*(g/L|mg/L|%|ppm)', # solubility/concentration
        ]

        unit = None
        for pattern in unit_patterns:
            match = re.search(pattern, value_str)
            if match:
                unit = match.group(2)
                break

        return unit, conditions

    @cached(service='pubchemview')
    def extract_property_data(self, cid: Union[int, str], property_name: str) -> List[PropertyData]:
        """
        Extract structured property data for a specific property

        Args:
            cid: PubChem Compound ID
            property_name: Name of the property to extract

        Returns:
            List of PropertyData objects with extracted information
        """
        try:
            response = self.get_property(cid, property_name)
            return self._parse_property_response(response)
        except (PubChemViewNotFoundError, PubChemViewError):
            self.logger.warning(f"Property '{property_name}' not found for CID {cid}")
            return []

    def _parse_property_response(self, response: Dict[str, Any]) -> List[PropertyData]:
        """
        Parse a property response and extract structured data

        Args:
            response: Raw JSON response from PUG View

        Returns:
            List of PropertyData objects
        """
        property_data = []

        try:
            # Navigate to the Information section
            record = response.get("Record", {})
            sections = record.get("Section", [])

            # Find the experimental properties section
            for section in sections:
                if section.get("TOCHeading") == "Chemical and Physical Properties":
                    exp_sections = section.get("Section", [])
                    for exp_section in exp_sections:
                        if exp_section.get("TOCHeading") == "Experimental Properties":
                            prop_sections = exp_section.get("Section", [])

                            # Find the specific property section
                            for prop_section in prop_sections:
                                information_items = prop_section.get("Information", [])
                                for info_item in information_items:
                                    property_data.append(self._extract_value_info(info_item))

        except Exception as e:
            self.logger.error(f"Error parsing property response: {e}")

        return property_data

    @cached(service='pubchemview')
    def extract_all_experimental_properties(self, cid: Union[int, str]) -> Dict[str, List[PropertyData]]:
        """
        Extract all experimental properties for a compound in structured format

        Args:
            cid: PubChem Compound ID

        Returns:
            Dictionary mapping property names to lists of PropertyData objects
        """
        try:
            response = self.get_experimental_properties(cid)
            return self._parse_all_properties_response(response)
        except PubChemViewNotFoundError:
            self.logger.warning(f"No experimental properties found for CID {cid}")
            return {}

    def _parse_all_properties_response(self, response: Dict[str, Any]) -> Dict[str, List[PropertyData]]:
        """
        Parse a full experimental properties response

        Args:
            response: Raw JSON response from PUG View

        Returns:
            Dictionary mapping property names to PropertyData lists
        """
        all_properties = {}

        try:
            # Navigate to the experimental properties section
            record = response.get("Record", {})
            sections = record.get("Section", [])

            for section in sections:
                if section.get("TOCHeading") == "Chemical and Physical Properties":
                    exp_sections = section.get("Section", [])
                    for exp_section in exp_sections:
                        if exp_section.get("TOCHeading") == "Experimental Properties":
                            prop_sections = exp_section.get("Section", [])

                            # Extract each property
                            for prop_section in prop_sections:
                                prop_name = prop_section.get("TOCHeading", "Unknown")
                                property_data = []

                                information_items = prop_section.get("Information", [])
                                for info_item in information_items:
                                    property_data.append(self._extract_value_info(info_item))

                                if property_data:
                                    all_properties[prop_name] = property_data

        except Exception as e:
            self.logger.error(f"Error parsing all properties response: {e}")

        return all_properties

    @cached(service='pubchemview')
    def get_available_properties(self, cid: Union[int, str]) -> List[str]:
        """
        Get list of available experimental properties for a compound

        Args:
            cid: PubChem Compound ID

        Returns:
            List of available property names
        """
        try:
            response = self.get_experimental_properties(cid)
            return list(self._parse_all_properties_response(response).keys())
        except PubChemViewNotFoundError:
            return []

    @cached(service='pubchemview')
    def get_property_summary(self, cid: Union[int, str], property_name: str) -> Dict[str, Any]:
        """
        Get a summary of a property including all values, units, and references

        Args:
            cid: PubChem Compound ID
            property_name: Name of the property

        Returns:
            Dictionary with property summary
        """
        property_data = self.extract_property_data(cid, property_name)

        if not property_data:
            return {"property": property_name, "values": [], "references": [], "units": set()}

        summary = {
            "property": property_name,
            "values": [data.value for data in property_data],
            "references": [data.reference for data in property_data if data.reference],
            "units": list(set([data.unit for data in property_data if data.unit])),
            "conditions": list(set([data.conditions for data in property_data if data.conditions])),
            "count": len(property_data)
        }

        return summary

    # Convenience methods for common properties
    @cached(service='pubchemview')
    def get_melting_point(self, cid: Union[int, str]) -> List[PropertyData]:
        """Get melting point data for a compound"""
        return self.extract_property_data(cid, "Melting Point")

    @cached(service='pubchemview')
    def get_boiling_point(self, cid: Union[int, str]) -> List[PropertyData]:
        """Get boiling point data for a compound"""
        return self.extract_property_data(cid, "Boiling Point")

    @cached(service='pubchemview')
    def get_density(self, cid: Union[int, str]) -> List[PropertyData]:
        """Get density data for a compound"""
        return self.extract_property_data(cid, "Density")

    @cached(service='pubchemview')
    def get_solubility(self, cid: Union[int, str]) -> List[PropertyData]:
        """Get solubility data for a compound"""
        return self.extract_property_data(cid, "Solubility")

    @cached(service='pubchemview')
    def get_flash_point(self, cid: Union[int, str]) -> List[PropertyData]:
        """Get flash point data for a compound"""
        return self.extract_property_data(cid, "Flash Point")

    @cached(service='pubchemview')
    def get_vapor_pressure(self, cid: Union[int, str]) -> List[PropertyData]:
        """Get vapor pressure data for a compound"""
        return self.extract_property_data(cid, "Vapor Pressure")

    @cached(service='pubchemview')
    def get_viscosity(self, cid: Union[int, str]) -> List[PropertyData]:
        """Get viscosity data for a compound"""
        return self.extract_property_data(cid, "Viscosity")

    @cached(service='pubchemview')
    def get_logp(self, cid: Union[int, str]) -> List[PropertyData]:
        """Get LogP data for a compound"""
        return self.extract_property_data(cid, "LogP")

    @cached(service='pubchemview')
    def get_refractive_index(self, cid: Union[int, str]) -> List[PropertyData]:
        """Get refractive index data for a compound"""
        return self.extract_property_data(cid, "Refractive Index")

    def batch_extract_properties(self, cid: Union[int, str], 
                                property_names: List[str]) -> Dict[str, List[PropertyData]]:
        """
        Extract multiple properties for a compound

        Args:
            cid: PubChem Compound ID
            property_names: List of property names to extract

        Returns:
            Dictionary mapping property names to PropertyData lists
        """
        results = {}
        for prop_name in property_names:
            try:
                results[prop_name] = self.extract_property_data(cid, prop_name)
            except Exception as e:
                self.logger.warning(f"Failed to extract {prop_name} for CID {cid}: {e}")
                results[prop_name] = []

        return results

    def export_properties_to_dict(self, property_data_list: List[PropertyData]) -> List[Dict[str, Any]]:
        """
        Convert PropertyData objects to dictionaries for easy serialization

        Args:
            property_data_list: List of PropertyData objects

        Returns:
            List of dictionaries
        """
        return [
            {
                "value": data.value,
                "unit": data.unit,
                "conditions": data.conditions,
                "reference": data.reference,
                "reference_number": data.reference_number,
                "description": data.description,
                "name": data.name
            }
            for data in property_data_list
        ]


    @cached(service='pubchemview')
    def get_property_table(self, cid: Union[int, str], property_name: str) -> pd.DataFrame:
        """
        Get a comprehensive table of property data with full reference information

        Args:
            cid: PubChem Compound ID
            property_name: Name of the experimental property

        Returns:
            pandas DataFrame with columns: CID, StringWithMarkup, ExperimentalValue, Unit, Temperature, Conditions, FullReference
        """
        try:
            # Get the raw response to extract full reference information
            response = self.get_property(cid, property_name)

            # Extract reference mapping from the response
            reference_map = self._extract_reference_map(response)

            # Get structured property data
            property_data = self._parse_property_response(response)

            # Build table data
            table_data = []
            for data in property_data:
                # Get full reference string
                full_reference = ""
                if data.reference_number and data.reference_number in reference_map:
                    full_reference = reference_map[data.reference_number]
                elif data.reference:
                    full_reference = data.reference

                # Parse experimental value, unit, temperature, and conditions from the StringWithMarkup
                exp_value, unit, temperature, conditions = self._extract_experimental_value_and_unit(data.value, property_name)

                table_data.append({
                    "CID": cid,
                    "StringWithMarkup": data.value,
                    "ExperimentalValue": exp_value,
                    "Unit": unit,  # Use only the parsed unit from improved extraction
                    "Temperature": temperature,
                    "Conditions": conditions,
                    "FullReference": full_reference
                })

            return pd.DataFrame(table_data)

        except Exception as e:
            self.logger.error(f"Error creating property table for CID {cid}, property {property_name}: {e}")
            # Return empty DataFrame with expected columns
            return pd.DataFrame(columns=["CID", "StringWithMarkup", "ExperimentalValue", "Unit", "Temperature", "Conditions", "FullReference"])

    def _extract_reference_map(self, response: Dict[str, Any]) -> Dict[int, str]:
        """
        Extract mapping of reference numbers to full reference strings

        Args:
            response: Raw JSON response from PUG View

        Returns:
            Dictionary mapping reference numbers to full reference strings
        """
        reference_map = {}

        try:
            record = response.get("Record", {})
            references = record.get("Reference", [])

            for ref in references:
                ref_num = ref.get("ReferenceNumber")
                if ref_num:
                    # Build full reference string from available fields
                    ref_parts = []

                    # Add source name
                    if "SourceName" in ref:
                        ref_parts.append(ref["SourceName"])

                    # Add name/title
                    if "Name" in ref:
                        ref_parts.append(ref["Name"])

                    # Add description
                    if "Description" in ref:
                        description = ref["Description"]
                        # Truncate very long descriptions
                        if len(description) > 200:
                            description = description[:200] + "..."
                        ref_parts.append(description)

                    # Add URL if available
                    if "URL" in ref:
                        ref_parts.append(f"URL: {ref['URL']}")

                    # Combine parts with proper separation
                    full_ref = " | ".join(ref_parts) if ref_parts else f"Reference #{ref_num}"
                    reference_map[ref_num] = full_ref

        except Exception as e:
            self.logger.warning(f"Error extracting reference map: {e}")

        return reference_map

    def _extract_experimental_value_and_unit(self, value_str: str, property_name: str = None) -> tuple[Optional[str], Optional[str], Optional[str], Optional[str]]:
        """
        Extract numerical experimental value, unit, temperature, and conditions from StringWithMarkup

        Args:
            value_str: Full StringWithMarkup value
            property_name: Name of the property being extracted (for property-specific patterns)

        Returns:
            Tuple of (experimental_value, unit, temperature, conditions)
        """
        if not value_str:
            return None, None, None, None

        # Helper function to extract temperature and conditions
        def extract_temperature_and_conditions(text: str) -> tuple[Optional[str], Optional[str]]:
            """Extract temperature and conditions from text"""
            # Pattern for "at 25°C", "@ 25°C", "at 20 °C", etc.
            temp_match = re.search(r'(?:at|@)\s+(-?\d+(?:\.\d+)?)\s*[°]?\s*([CF]|K)\b', text, re.IGNORECASE)
            if temp_match:
                temp_value = temp_match.group(1)
                temp_unit = temp_match.group(2)
                temperature = f"{temp_value}°{temp_unit}"

                # Extract any additional conditions
                conditions_parts = []
                # Look for pressure conditions
                pressure_cond = re.search(r'(\d+(?:\.\d+)?)\s*(mmHg|kPa|Pa|atm|bar)', text, re.IGNORECASE)
                if pressure_cond:
                    conditions_parts.append(f"{pressure_cond.group(1)} {pressure_cond.group(2)}")

                # Look for other descriptive conditions
                descriptors = re.findall(r'/([^/]+)/', text)
                conditions_parts.extend(descriptors)

                conditions = "; ".join(conditions_parts) if conditions_parts else None
                return temperature, conditions

            return None, None

        # Property-specific patterns (highest priority)
        if property_name:
            prop_name_lower = property_name.lower()

            # Vapor Pressure specific patterns
            if 'vapor pressure' in prop_name_lower:
                # Pattern: "Vapor pressure at 20°C: negligible" - return None for both value and unit
                negligible_match = re.search(r'negligible', value_str, re.IGNORECASE)
                if negligible_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return None, None, temperature, conditions

                # Pattern: "8.5X10-5 mm Hg at 25 °C" (X represents multiplication)
                scientific_x_match = re.search(r'^(\d+(?:\.\d+)?)X10([+-]?\d+)\s*(mmHg|mm\s+Hg|kPa|Pa|atm|bar|torr)', value_str, re.IGNORECASE)
                if scientific_x_match:
                    # Convert XNotation to E notation
                    mantissa = scientific_x_match.group(1)
                    exponent = scientific_x_match.group(2)
                    unit = scientific_x_match.group(3)
                    scientific_value = f"{mantissa}e{exponent}"
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return scientific_value, unit, temperature, conditions

                # Pattern: "2.7X10+0 at 25 °C /Estimated/" (X notation without unit)
                scientific_x_no_unit_match = re.search(r'^(\d+(?:\.\d+)?)X10([+-]?\d+)\s', value_str, re.IGNORECASE)
                if scientific_x_no_unit_match:
                    # Convert XNotation to E notation
                    mantissa = scientific_x_no_unit_match.group(1)
                    exponent = scientific_x_no_unit_match.group(2)
                    scientific_value = f"{mantissa}e{exponent}"
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return scientific_value, None, temperature, conditions

                # Pattern: "0.05 [mmHg]" (brackets around unit)
                bracketed_unit_match = re.search(r'^(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)\s*\[(mmHg|mm\s+Hg|kPa|Pa|atm|bar|torr)\]', value_str, re.IGNORECASE)
                if bracketed_unit_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return bracketed_unit_match.group(1), bracketed_unit_match.group(2), temperature, conditions

                # Pattern: "Vapor pressure, kPa at 20°C: 24"
                vp_colon_match = re.search(r'vapor\s+pressure[^:]*:\s*(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)', value_str, re.IGNORECASE)
                if vp_colon_match:
                    # Extract unit from before the colon
                    unit_match = re.search(r'vapor\s+pressure[,\s]*([a-zA-Z]+)', value_str, re.IGNORECASE)
                    unit = unit_match.group(1) if unit_match else None
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return vp_colon_match.group(1), unit, temperature, conditions

                # Pattern: "kPa at 20°C: 24" or similar
                unit_colon_match = re.search(r'(mmHg|mm\s+Hg|kPa|Pa|atm|bar|torr)[^:]*:\s*(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)', value_str, re.IGNORECASE)
                if unit_colon_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return unit_colon_match.group(2), unit_colon_match.group(1), temperature, conditions

                # Standard pressure patterns at start
                pressure_match = re.search(r'^(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)\s*(mmHg|mm\s+Hg|kPa|Pa|atm|bar|torr)\b', value_str, re.IGNORECASE)
                if pressure_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return pressure_match.group(1), pressure_match.group(2), temperature, conditions

                # If no vapor pressure pattern matched, return None (no fallback for property-specific extraction)
                return None, None, None, None

            # LogP specific patterns
            elif 'logp' in prop_name_lower:
                # Pattern: "LogP: -2.3" or "log P = 1.5" or "log Kow = 1.19"
                logp_colon_match = re.search(r'log\s*(?:p|kow|k[ow]{1,2})\s*[=:]\s*(-?\d+(?:\.\d+)?)', value_str, re.IGNORECASE)
                if logp_colon_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return logp_colon_match.group(1), None, temperature, conditions

                # Simple number at start for LogP (usually unitless)
                logp_start_match = re.search(r'^(-?\d+(?:\.\d+)?)\s*$', value_str.strip())
                if logp_start_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return logp_start_match.group(1), None, temperature, conditions

                # If no LogP pattern matched, return None (no fallback for property-specific extraction)
                return None, None, None, None

            # Dissociation Constants specific patterns
            elif 'dissociation' in prop_name_lower:
                # Pattern: "pKa = 14.31 @ 25 °C" or "pKa: 3.6" or "pKb = 10.2"
                pka_colon_match = re.search(r'p[Kk][abAB]\s*[=:@]\s*(-?\d+(?:\.\d+)?)', value_str, re.IGNORECASE)
                if pka_colon_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return pka_colon_match.group(1), None, temperature, conditions

                # Pattern: "Ka: 2.5e-4" or "Kb = 1.0e-10" or "K1=3.3X10-5"
                ka_colon_match = re.search(r'[Kk][abAB\d]*[=:]\s*([^\s;]+)', value_str, re.IGNORECASE)
                if ka_colon_match:
                    # Convert X notation to e notation if present (X10 -> e)
                    value = re.sub(r'([Xx])10', r'e', ka_colon_match.group(1))
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return value, None, temperature, conditions

                # Pattern: "2.91 (at 25 °C)" - just a number with temperature in parentheses
                number_with_temp_match = re.search(r'^([^\s;]+)\s*\(.*?°.*?\)', value_str.strip())
                if number_with_temp_match:
                    # Convert X notation to e notation if present (X10 -> e)
                    value = re.sub(r'([Xx])10', r'e', number_with_temp_match.group(1))
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return value, None, temperature, conditions

                # Simple number at start for dissociation constants (usually unitless pKa/pKb values)
                dc_start_match = re.search(r'^([^\s;]+)\s*$', value_str.strip())
                if dc_start_match:
                    # Convert X notation to e notation if present (X10 -> e)
                    value = re.sub(r'([Xx])10', r'e', dc_start_match.group(1))
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return value, None, temperature, conditions

                # If no dissociation constants pattern matched, return None (no fallback for property-specific extraction)
                return None, None, None, None

            # Melting Point / Boiling Point specific patterns
            elif any(temp_prop in prop_name_lower for temp_prop in ['melting point', 'boiling point', 'temperature']):
                # Range patterns with temperature units
                temp_range_match = re.search(r'^(-?\d+(?:\.\d+)?-\d+(?:\.\d+)?)\s*[°]?\s*([CF]|K)\b', value_str)
                if temp_range_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return temp_range_match.group(1), f"°{temp_range_match.group(2)}", temperature, conditions

                # Single temperature values
                temp_match = re.search(r'^(-?\d+(?:\.\d+)?)\s*[°]?\s*([CF]|K)\b', value_str)
                if temp_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return temp_match.group(1), f"°{temp_match.group(2)}", temperature, conditions

                # If no temperature pattern matched, return None (no fallback for property-specific extraction)
                return None, None, None, None

            # Density specific patterns
            elif 'density' in prop_name_lower:
                density_match = re.search(r'^(-?\d+(?:\.\d+)?)\s*(g/cm³|g/mL|kg/m³|g/L)\b', value_str)
                if density_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return density_match.group(1), density_match.group(2), temperature, conditions

                # If no density pattern matched, return None (no fallback for property-specific extraction)
                return None, None, None, None

            # Viscosity specific patterns
            elif 'viscosity' in prop_name_lower:
                viscosity_match = re.search(r'^(-?\d+(?:\.\d+)?)\s*(cP|mPa·s|Pa·s|cSt)\b', value_str)
                if viscosity_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return viscosity_match.group(1), viscosity_match.group(2), temperature, conditions

                # If no viscosity pattern matched, return None (no fallback for property-specific extraction)
                return None, None, None, None

            # Solubility specific patterns
            elif 'solubility' in prop_name_lower:
                # Pattern: "greater than or equal to 100 mg/mL" - comparison operators
                # Split into two separate searches for clarity
                sol_comparison_match = re.search(r'(?:greater than or equal to|greater than|less than or equal to|less than|≥|≤|>|<|>=|<=)\s*(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)\s*(μg|ug|ng|pg|g|mg|kg)/(mL|L|l|100mL|100ml|dl|dL)', value_str, re.IGNORECASE)
                if not sol_comparison_match:
                    sol_comparison_match = re.search(r'(?:greater than or equal to|greater than|less than or equal to|less than|≥|≤|>|<|>=|<=)\s*(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)\s*(g/L|g/l|mg/L|mg/l|g/100mL|mg/mL|mol/L|M|%|ppm|ppb)', value_str, re.IGNORECASE)

                if sol_comparison_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    value = sol_comparison_match.group(1)
                    unit = sol_comparison_match.group(2)

                    # Handle the compound unit format (e.g., μg/mL) vs simple unit format (e.g., g/L)
                    if '/' in unit:
                        # Simple unit format like g/L, mg/L
                        return value, unit, temperature, conditions
                    else:
                        # Compound unit format - need to get the volume part from the original match
                        if sol_comparison_match.lastindex >= 3:
                            volume_part = sol_comparison_match.group(3) if sol_comparison_match.group(3) else ''
                            if unit.lower() in ['μg', 'ug']:
                                unit = 'μg'
                            final_unit = f"{unit}/{volume_part}" if volume_part else unit
                            return value, final_unit, temperature, conditions
                        else:
                            return value, unit, temperature, conditions

                # Pattern: "1.2 [ug/mL] (additional info)" - bracketed units with microgram notation
                sol_bracketed_unit_match = re.search(r'(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)\s*\[(μg|ug|ng|pg|g|mg|kg)/(?:mL|L|100mL|100ml)\]', value_str, re.IGNORECASE)
                if sol_bracketed_unit_match:
                    value = sol_bracketed_unit_match.group(1)
                    unit_part = sol_bracketed_unit_match.group(2)
                    # Normalize microgram notation
                    if unit_part.lower() in ['μg', 'ug']:
                        unit_part = 'μg'
                    elif unit_part.lower() == 'ng':
                        unit_part = 'ng'
                    elif unit_part.lower() == 'pg':
                        unit_part = 'pg'

                    # Extract volume part from the match
                    if '/mL' in sol_bracketed_unit_match.group(0):
                        unit = f"{unit_part}/mL"
                    elif '/L' in sol_bracketed_unit_match.group(0):
                        unit = f"{unit_part}/L"
                    elif '/100mL' in sol_bracketed_unit_match.group(0) or '/100ml' in sol_bracketed_unit_match.group(0):
                        unit = f"{unit_part}/100mL"
                    else:
                        unit = sol_bracketed_unit_match.group(2)

                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return value, unit, temperature, conditions

                # Pattern: "Soluble in water: 5.6 g/L at 20°C"
                sol_colon_match = re.search(r'[sS]olub[a-z]*[^:]*:\s*(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)\s*(μg|ug|ng|pg|g|mg|kg)/(mL|L|100mL|100ml|dl|dL)|[sS]olub[a-z]*[^:]*:\s*(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)\s*(g/L|mg/L|g/100mL|mg/mL|mol/L|M|%|ppm|ppb)\b', value_str, re.IGNORECASE)
                if sol_colon_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    if sol_colon_match.group(1):  # First pattern (microgram notation)
                        unit_part = sol_colon_match.group(2)
                        if unit_part.lower() in ['μg', 'ug']:
                            unit_part = 'μg'
                        volume_part = sol_colon_match.group(3)
                        return sol_colon_match.group(1), f"{unit_part}/{volume_part}", temperature, conditions
                    else:  # Second pattern (standard units)
                        return sol_colon_match.group(4), sol_colon_match.group(5), temperature, conditions

                # Pattern: "5.6 g/L at 20°C" (starts with value and unit) - updated with microgram support
                sol_start_match = re.search(r'^(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)\s*(μg|ug|ng|pg|g|mg|kg)/(mL|L|100mL|100ml|dl|dL)|^(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)\s*(g/L|mg/L|g/100mL|mg/mL|mol/L|M|%|ppm|ppb)\b', value_str, re.IGNORECASE)
                if sol_start_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    if sol_start_match.group(1):  # First pattern (microgram notation)
                        unit_part = sol_start_match.group(2)
                        if unit_part.lower() in ['μg', 'ug']:
                            unit_part = 'μg'
                        volume_part = sol_start_match.group(3)
                        return sol_start_match.group(1), f"{unit_part}/{volume_part}", temperature, conditions
                    else:  # Second pattern (standard units)
                        return sol_start_match.group(4), sol_start_match.group(5), temperature, conditions

                # Pattern: "2.5X10-3 g/L" (X notation)
                sol_scientific_x_match = re.search(r'^(-?\d+(?:\.\d+)?)X10([+-]?\d+)\s*(g/L|mg/L|g/100mL|mg/mL|mol/L|M|%|ppm|ppb)\b', value_str, re.IGNORECASE)
                if sol_scientific_x_match:
                    # Convert XNotation to E notation
                    mantissa = sol_scientific_x_match.group(1)
                    exponent = sol_scientific_x_match.group(2)
                    unit = sol_scientific_x_match.group(3)
                    scientific_value = f"{mantissa}e{exponent}"
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return scientific_value, unit, temperature, conditions

                # Pattern: "[2.5] g/L" (brackets around value)
                sol_bracketed_val_match = re.search(r'^\[(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)\]\s*(g/L|mg/L|g/100mL|mg/mL|mol/L|M|%|ppm|ppb)\b', value_str, re.IGNORECASE)
                if sol_bracketed_val_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return sol_bracketed_val_match.group(1), sol_bracketed_val_match.group(2), temperature, conditions

                # Pattern: "1.35X10+5 mg/l" appearing anywhere in text (X notation anywhere)
                sol_scientific_x_anywhere_match = re.search(r'(-?\d+(?:\.\d+)?)X10([+-]?\d+)\s*(mg/l|g/L|mg/L|g/100mL|mg/mL|mol/L|M|%|ppm|ppb)\b', value_str, re.IGNORECASE)
                if sol_scientific_x_anywhere_match:
                    # Convert XNotation to E notation
                    mantissa = sol_scientific_x_anywhere_match.group(1)
                    exponent = sol_scientific_x_anywhere_match.group(2)
                    unit = sol_scientific_x_anywhere_match.group(3)
                    scientific_value = f"{mantissa}e{exponent}"
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return scientific_value, unit, temperature, conditions

                # Pattern: "0.9%" or "0.86% wt" (standalone percentage values)
                sol_percentage_match = re.search(r'^(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)%(?:\s+wt|w/w|v/v)?$', value_str, re.IGNORECASE)
                if sol_percentage_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return sol_percentage_match.group(1), "%", temperature, conditions

                # Pattern: "Solubility in water: 0.86% wt" (colon-based percentage)
                sol_colon_percentage_match = re.search(r'[sS]olub[a-z]*[^:]*:\s*(-?\d+(?:\.\d+)?(?:[Ee][+-]?\d+)?)%(?:\s+wt|w/w|v/v)?$', value_str, re.IGNORECASE)
                if sol_colon_percentage_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return sol_colon_percentage_match.group(1), "%", temperature, conditions

                # Pattern: "Insoluble" or "slightly soluble" - return None for both value and unit
                insoluble_match = re.search(r'(insoluble|practically insoluble|very slightly soluble)', value_str, re.IGNORECASE)
                if insoluble_match:
                    temperature, conditions = extract_temperature_and_conditions(value_str)
                    return None, None, temperature, conditions

                # If no solubility pattern matched, return None (no fallback for property-specific extraction)
                return None, None, None, None

            # For other property types, return None to avoid fallback to generic patterns
            return None, None, None, None

        # General patterns (fallback only when no property name is specified)

        # 1. Range patterns at start (e.g., "138-140", "135-140 °C")
        range_match = re.search(r'^(-?\d+(?:\.\d+)?-\d+(?:\.\d+)?)\s*([°]?[CF]|K)?\b', value_str)
        if range_match:
            temperature, conditions = extract_temperature_and_conditions(value_str)
            return range_match.group(1), range_match.group(2), temperature, conditions

        # 2. Temperature patterns at start (main value, not conditions)
        temp_match = re.search(r'^(-?\d+(?:\.\d+)?)\s*[°]?([CF]|K)\b', value_str)
        if temp_match:
            temperature, conditions = extract_temperature_and_conditions(value_str)
            return temp_match.group(1), temp_match.group(2), temperature, conditions

        # 3. Density patterns
        density_match = re.search(r'^(-?\d+(?:\.\d+)?)\s*(g/cm³|g/mL|kg/m³|g/L)\b', value_str)
        if density_match:
            temperature, conditions = extract_temperature_and_conditions(value_str)
            return density_match.group(1), density_match.group(2), temperature, conditions

        # 4. Pressure patterns (not conditions)
        pressure_match = re.search(r'^(-?\d+(?:\.\d+)?)\s*(mmHg|mm Hg|kPa|Pa|atm|bar|torr)\b', value_str)
        if pressure_match:
            temperature, conditions = extract_temperature_and_conditions(value_str)
            return pressure_match.group(1), pressure_match.group(2), temperature, conditions

        # 5. Viscosity patterns
        viscosity_match = re.search(r'^(\d+(?:\.\d+)?)\s*(cP|mPa·s|Pa·s|cSt)\b', value_str)
        if viscosity_match:
            temperature, conditions = extract_temperature_and_conditions(value_str)
            return viscosity_match.group(1), viscosity_match.group(2), temperature, conditions

        # 6. General numeric value at the start with various units
        general_match = re.search(r'^(-?\d+(?:\.\d+)?)\s*([a-zA-Z/²³·°%]+)?', value_str)
        if general_match:
            value = general_match.group(1)
            unit = general_match.group(2) if general_match.group(2) else None

            # Clean up unit
            if unit:
                unit = unit.strip()
                # Filter out common non-unit words that might be captured
                if unit.lower() in ['at', 'in', 'on', 'to', 'from', 'with', 'and', 'or']:
                    unit = None
                elif not unit or unit in ['', ' ']:
                    unit = None

            temperature, conditions = extract_temperature_and_conditions(value_str)
            return value, unit, temperature, conditions

        # 7. Scientific notation
        sci_match = re.search(r'^(-?\d+(?:\.\d+)?[Ee][+-]?\d+)\s*([a-zA-Z/²³·°%]+)?', value_str)
        if sci_match:
            temperature, conditions = extract_temperature_and_conditions(value_str)
            return sci_match.group(1), sci_match.group(2), temperature, conditions

        # 8. Fallback: any number in the string
        number_match = re.search(r'(-?\d+(?:\.\d+)?)', value_str)
        if number_match:
            temperature, conditions = extract_temperature_and_conditions(value_str)
            return number_match.group(1), None, temperature, conditions

        return None, None, None, None

Functions

__init__(base_url='https://pubchem.ncbi.nlm.nih.gov/rest/pug_view', timeout=30, max_retries=3, backoff_factor=1.0, use_cache=True)

Initialize PubChemView API client

Parameters:

Name	Type	Description	Default
base_url	str	Base URL for PubChem PUG View API	'https://pubchem.ncbi.nlm.nih.gov/rest/pug_view'
timeout	int	Request timeout in seconds	30
max_retries	int	Maximum number of retry attempts	3
backoff_factor	float	Backoff factor for retries	1.0
use_cache	bool	Whether to use cache for lookups (default: True). When False, skips cache lookup but still stores results.	True

Source code in src/provesid/pubchemview.py

def __init__(self, base_url: str = "https://pubchem.ncbi.nlm.nih.gov/rest/pug_view",
             timeout: int = 30, max_retries: int = 3, backoff_factor: float = 1.0, use_cache: bool = True):
    """
    Initialize PubChemView API client

    Args:
        base_url: Base URL for PubChem PUG View API
        timeout: Request timeout in seconds
        max_retries: Maximum number of retry attempts
        backoff_factor: Backoff factor for retries
        use_cache: Whether to use cache for lookups (default: True). 
                  When False, skips cache lookup but still stores results.
    """
    self.base_url = base_url.rstrip('/')
    self.timeout = timeout
    self.max_retries = max_retries
    self.backoff_factor = backoff_factor
    self.logger = logging.getLogger(__name__)
    self.use_cache = use_cache

    # Rate limiting
    self.last_request_time = 0
    self.min_request_interval = 0.2  # 5 requests per second max

    # Standard experimental property headings
    self.experimental_properties = {
        "Accelerating Rate Calorimetry (ARC)": "Accelerating+Rate+Calorimetry+(ARC)",
        "Acid Value": "Acid+Value",
        "Autoignition Temperature": "Autoignition+Temperature", 
        "Boiling Point": "Boiling+Point",
        "Caco2 Permeability": "Caco2+Permeability",
        "Collision Cross Section": "Collision+Cross+Section",
        "Color/Form": "Color/Form",
        "Corrosivity": "Corrosivity",
        "Decomposition": "Decomposition",
        "Density": "Density",
        "Dielectric Constant": "Dielectric+Constant",
        "Differential Scanning Calorimetry (DSC)": "Differential+Scanning+Calorimetry+(DSC)",
        "Dispersion": "Dispersion",
        "Dissociation Constants": "Dissociation+Constants",
        "Enthalpy of Sublimation": "Enthalpy+of+Sublimation",
        "Flash Point": "Flash+Point",
        "Heat of Combustion": "Heat+of+Combustion",
        "Heat of Vaporization": "Heat+of+Vaporization",
        "Henry's Law Constant": "Henry's+Law+Constant",
        "Hydrophobicity": "Hydrophobicity",
        "Ionization Efficiency": "Ionization+Efficiency",
        "Ionization Potential": "Ionization+Potential",
        "Isoelectric Point": "Isoelectric+Point",
        "Kovats Retention Index": "Kovats+Retention+Index",
        "LogP": "LogP",
        "LogS": "LogS",
        "Melting Point": "Melting+Point",
        "Odor": "Odor",
        "Odor Threshold": "Odor+Threshold",
        "Optical Rotation": "Optical+Rotation",
        "Other Experimental Properties": "Other+Experimental+Properties",
        "pH": "pH",
        "Physical Description": "Physical+Description",
        "Polymerization": "Polymerization",
        "Refractive Index": "Refractive+Index",
        "Relative Evaporation Rate": "Relative+Evaporation+Rate",
        "Self-Accelerating Decomposition Temperature (SADT)": "Self-Accelerating+Decomposition+Temperature+(SADT)",
        "Solubility": "Solubility",
        "Stability/Shelf Life": "Stability/Shelf+Life",
        "Surface Tension": "Surface+Tension",
        "Taste": "Taste",
        "Vapor Density": "Vapor+Density",
        "Vapor Pressure": "Vapor+Pressure",
        "Viscosity": "Viscosity"
    }

clear_cache()

Clear all cached results for PubChem View

Source code in src/provesid/pubchemview.py

def clear_cache(self):
    """Clear all cached results for PubChem View"""
    from .cache import clear_pubchemview_cache
    clear_pubchemview_cache()

get_cache_info()

Get cache statistics for PubChem View cached methods

Source code in src/provesid/pubchemview.py

def get_cache_info(self):
    """Get cache statistics for PubChem View cached methods"""
    from .cache import get_pubchemview_cache_info
    return get_pubchemview_cache_info()

get_experimental_properties(cid)

Get all experimental properties for a compound

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required

Returns:

Type	Description
Dict[str, Any]	Raw JSON response containing all experimental properties

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_experimental_properties(self, cid: Union[int, str]) -> Dict[str, Any]:
    """
    Get all experimental properties for a compound

    Args:
        cid: PubChem Compound ID

    Returns:
        Raw JSON response containing all experimental properties
    """
    url = f"{self.base_url}/data/compound/{cid}/JSON?heading=Experimental+Properties"
    return self._make_request(url)

get_property(cid, property_name)

Get a specific property for a compound

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required
property_name	str	Name of the property (can be with spaces or plus signs)	required

Returns:

Type	Description
Dict[str, Any]	Raw JSON response for the specific property

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_property(self, cid: Union[int, str], property_name: str) -> Dict[str, Any]:
    """
    Get a specific property for a compound

    Args:
        cid: PubChem Compound ID
        property_name: Name of the property (can be with spaces or plus signs)

    Returns:
        Raw JSON response for the specific property
    """
    # Convert property name to URL-safe format
    if property_name in self.experimental_properties:
        url_property = self.experimental_properties[property_name]
    else:
        url_property = property_name.replace(' ', '+')

    url = f"{self.base_url}/data/compound/{cid}/JSON?heading={url_property}"
    return self._make_request(url)

extract_property_data(cid, property_name)

Extract structured property data for a specific property

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required
property_name	str	Name of the property to extract	required

Returns:

Type	Description
List[PropertyData]	List of PropertyData objects with extracted information

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def extract_property_data(self, cid: Union[int, str], property_name: str) -> List[PropertyData]:
    """
    Extract structured property data for a specific property

    Args:
        cid: PubChem Compound ID
        property_name: Name of the property to extract

    Returns:
        List of PropertyData objects with extracted information
    """
    try:
        response = self.get_property(cid, property_name)
        return self._parse_property_response(response)
    except (PubChemViewNotFoundError, PubChemViewError):
        self.logger.warning(f"Property '{property_name}' not found for CID {cid}")
        return []

extract_all_experimental_properties(cid)

Extract all experimental properties for a compound in structured format

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required

Returns:

Type	Description
Dict[str, List[PropertyData]]	Dictionary mapping property names to lists of PropertyData objects

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def extract_all_experimental_properties(self, cid: Union[int, str]) -> Dict[str, List[PropertyData]]:
    """
    Extract all experimental properties for a compound in structured format

    Args:
        cid: PubChem Compound ID

    Returns:
        Dictionary mapping property names to lists of PropertyData objects
    """
    try:
        response = self.get_experimental_properties(cid)
        return self._parse_all_properties_response(response)
    except PubChemViewNotFoundError:
        self.logger.warning(f"No experimental properties found for CID {cid}")
        return {}

get_available_properties(cid)

Get list of available experimental properties for a compound

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required

Returns:

Type	Description
List[str]	List of available property names

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_available_properties(self, cid: Union[int, str]) -> List[str]:
    """
    Get list of available experimental properties for a compound

    Args:
        cid: PubChem Compound ID

    Returns:
        List of available property names
    """
    try:
        response = self.get_experimental_properties(cid)
        return list(self._parse_all_properties_response(response).keys())
    except PubChemViewNotFoundError:
        return []

get_property_summary(cid, property_name)

Get a summary of a property including all values, units, and references

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required
property_name	str	Name of the property	required

Returns:

Type	Description
Dict[str, Any]	Dictionary with property summary

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_property_summary(self, cid: Union[int, str], property_name: str) -> Dict[str, Any]:
    """
    Get a summary of a property including all values, units, and references

    Args:
        cid: PubChem Compound ID
        property_name: Name of the property

    Returns:
        Dictionary with property summary
    """
    property_data = self.extract_property_data(cid, property_name)

    if not property_data:
        return {"property": property_name, "values": [], "references": [], "units": set()}

    summary = {
        "property": property_name,
        "values": [data.value for data in property_data],
        "references": [data.reference for data in property_data if data.reference],
        "units": list(set([data.unit for data in property_data if data.unit])),
        "conditions": list(set([data.conditions for data in property_data if data.conditions])),
        "count": len(property_data)
    }

    return summary

get_melting_point(cid)

Get melting point data for a compound

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_melting_point(self, cid: Union[int, str]) -> List[PropertyData]:
    """Get melting point data for a compound"""
    return self.extract_property_data(cid, "Melting Point")

get_boiling_point(cid)

Get boiling point data for a compound

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_boiling_point(self, cid: Union[int, str]) -> List[PropertyData]:
    """Get boiling point data for a compound"""
    return self.extract_property_data(cid, "Boiling Point")

get_density(cid)

Get density data for a compound

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_density(self, cid: Union[int, str]) -> List[PropertyData]:
    """Get density data for a compound"""
    return self.extract_property_data(cid, "Density")

get_solubility(cid)

Get solubility data for a compound

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_solubility(self, cid: Union[int, str]) -> List[PropertyData]:
    """Get solubility data for a compound"""
    return self.extract_property_data(cid, "Solubility")

get_flash_point(cid)

Get flash point data for a compound

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_flash_point(self, cid: Union[int, str]) -> List[PropertyData]:
    """Get flash point data for a compound"""
    return self.extract_property_data(cid, "Flash Point")

get_vapor_pressure(cid)

Get vapor pressure data for a compound

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_vapor_pressure(self, cid: Union[int, str]) -> List[PropertyData]:
    """Get vapor pressure data for a compound"""
    return self.extract_property_data(cid, "Vapor Pressure")

get_viscosity(cid)

Get viscosity data for a compound

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_viscosity(self, cid: Union[int, str]) -> List[PropertyData]:
    """Get viscosity data for a compound"""
    return self.extract_property_data(cid, "Viscosity")

get_logp(cid)

Get LogP data for a compound

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_logp(self, cid: Union[int, str]) -> List[PropertyData]:
    """Get LogP data for a compound"""
    return self.extract_property_data(cid, "LogP")

get_refractive_index(cid)

Get refractive index data for a compound

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_refractive_index(self, cid: Union[int, str]) -> List[PropertyData]:
    """Get refractive index data for a compound"""
    return self.extract_property_data(cid, "Refractive Index")

batch_extract_properties(cid, property_names)

Extract multiple properties for a compound

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required
property_names	List[str]	List of property names to extract	required

Returns:

Type	Description
Dict[str, List[PropertyData]]	Dictionary mapping property names to PropertyData lists

Source code in src/provesid/pubchemview.py

def batch_extract_properties(self, cid: Union[int, str], 
                            property_names: List[str]) -> Dict[str, List[PropertyData]]:
    """
    Extract multiple properties for a compound

    Args:
        cid: PubChem Compound ID
        property_names: List of property names to extract

    Returns:
        Dictionary mapping property names to PropertyData lists
    """
    results = {}
    for prop_name in property_names:
        try:
            results[prop_name] = self.extract_property_data(cid, prop_name)
        except Exception as e:
            self.logger.warning(f"Failed to extract {prop_name} for CID {cid}: {e}")
            results[prop_name] = []

    return results

export_properties_to_dict(property_data_list)

Convert PropertyData objects to dictionaries for easy serialization

Parameters:

Name	Type	Description	Default
property_data_list	List[PropertyData]	List of PropertyData objects	required

Returns:

Type	Description
List[Dict[str, Any]]	List of dictionaries

Source code in src/provesid/pubchemview.py

def export_properties_to_dict(self, property_data_list: List[PropertyData]) -> List[Dict[str, Any]]:
    """
    Convert PropertyData objects to dictionaries for easy serialization

    Args:
        property_data_list: List of PropertyData objects

    Returns:
        List of dictionaries
    """
    return [
        {
            "value": data.value,
            "unit": data.unit,
            "conditions": data.conditions,
            "reference": data.reference,
            "reference_number": data.reference_number,
            "description": data.description,
            "name": data.name
        }
        for data in property_data_list
    ]

get_property_table(cid, property_name)

Get a comprehensive table of property data with full reference information

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required
property_name	str	Name of the experimental property	required

Returns:

Type	Description
DataFrame	pandas DataFrame with columns: CID, StringWithMarkup, ExperimentalValue, Unit, Temperature, Conditions, FullReference

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_property_table(self, cid: Union[int, str], property_name: str) -> pd.DataFrame:
    """
    Get a comprehensive table of property data with full reference information

    Args:
        cid: PubChem Compound ID
        property_name: Name of the experimental property

    Returns:
        pandas DataFrame with columns: CID, StringWithMarkup, ExperimentalValue, Unit, Temperature, Conditions, FullReference
    """
    try:
        # Get the raw response to extract full reference information
        response = self.get_property(cid, property_name)

        # Extract reference mapping from the response
        reference_map = self._extract_reference_map(response)

        # Get structured property data
        property_data = self._parse_property_response(response)

        # Build table data
        table_data = []
        for data in property_data:
            # Get full reference string
            full_reference = ""
            if data.reference_number and data.reference_number in reference_map:
                full_reference = reference_map[data.reference_number]
            elif data.reference:
                full_reference = data.reference

            # Parse experimental value, unit, temperature, and conditions from the StringWithMarkup
            exp_value, unit, temperature, conditions = self._extract_experimental_value_and_unit(data.value, property_name)

            table_data.append({
                "CID": cid,
                "StringWithMarkup": data.value,
                "ExperimentalValue": exp_value,
                "Unit": unit,  # Use only the parsed unit from improved extraction
                "Temperature": temperature,
                "Conditions": conditions,
                "FullReference": full_reference
            })

        return pd.DataFrame(table_data)

    except Exception as e:
        self.logger.error(f"Error creating property table for CID {cid}, property {property_name}: {e}")
        # Return empty DataFrame with expected columns
        return pd.DataFrame(columns=["CID", "StringWithMarkup", "ExperimentalValue", "Unit", "Temperature", "Conditions", "FullReference"])

Functions

get_experimental_property(cid, property_name)

Convenience function to get experimental property data

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required
property_name	str	Name of the property	required

Returns:

Type	Description
List[PropertyData]	List of PropertyData objects

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_experimental_property(cid: Union[int, str], property_name: str) -> List[PropertyData]:
    """
    Convenience function to get experimental property data

    Args:
        cid: PubChem Compound ID
        property_name: Name of the property

    Returns:
        List of PropertyData objects
    """
    pugview = PubChemView()
    return pugview.extract_property_data(cid, property_name)

get_all_experimental_properties(cid)

Convenience function to get all experimental properties

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required

Returns:

Type	Description
Dict[str, List[PropertyData]]	Dictionary mapping property names to PropertyData lists

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_all_experimental_properties(cid: Union[int, str]) -> Dict[str, List[PropertyData]]:
    """
    Convenience function to get all experimental properties

    Args:
        cid: PubChem Compound ID

    Returns:
        Dictionary mapping property names to PropertyData lists
    """
    pugview = PubChemView()
    return pugview.extract_all_experimental_properties(cid)

get_property_values_only(cid, property_name)

Convenience function to get just the property values as strings

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required
property_name	str	Name of the property	required

Returns:

Type	Description
List[str]	List of property value strings

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_property_values_only(cid: Union[int, str], property_name: str) -> List[str]:
    """
    Convenience function to get just the property values as strings

    Args:
        cid: PubChem Compound ID
        property_name: Name of the property

    Returns:
        List of property value strings
    """
    pugview = PubChemView()
    property_data = pugview.extract_property_data(cid, property_name)
    return [data.value for data in property_data if data.value]

get_property_table(cid, property_name)

Convenience function to get a comprehensive property table with full references

Parameters:

Name	Type	Description	Default
cid	Union[int, str]	PubChem Compound ID	required
property_name	str	Name of the experimental property	required

Returns:

Type	Description
DataFrame	pandas DataFrame with columns: CID, StringWithMarkup, ExperimentalValue, Unit, FullReference

Source code in src/provesid/pubchemview.py

@cached(service='pubchemview')
def get_property_table(cid: Union[int, str], property_name: str) -> pd.DataFrame:
    """
    Convenience function to get a comprehensive property table with full references

    Args:
        cid: PubChem Compound ID
        property_name: Name of the experimental property

    Returns:
        pandas DataFrame with columns: CID, StringWithMarkup, ExperimentalValue, Unit, FullReference
    """
    pugview = PubChemView()
    return pugview.get_property_table(cid, property_name)

Quick Start

from provesid import PubChemView
from provesid.pubchemview import get_experimental_properties_table

# Initialize the view client
view = PubChemView()

# Get experimental melting points for aspirin (CID 2244)
properties = view.get_experimental_properties(2244, 'Melting Point')
for prop in properties:
    print(f"Value: {prop.value} {prop.unit}")
    print(f"Reference: {prop.reference_title}")

# Get a structured DataFrame
df = view.experimental_properties_to_dataframe(2244, 'Melting Point')
print(df.head())

# Use the convenience function for a complete table
table = get_experimental_properties_table(2244, 'Boiling Point')
print(table)

Available Property Types

The PubChem View service provides access to various experimental properties:

Physical Properties

• Melting Point - Melting point temperatures
• Boiling Point - Boiling point temperatures
• Density - Density measurements
• Vapor Pressure - Vapor pressure data
• Solubility - Solubility in various solvents
• LogP - Partition coefficient data
• Viscosity - Viscosity measurements
• Refractive Index - Refractive index values

Spectroscopic Properties

• UV/Vis Spectrum - UV-Visible spectroscopy data
• IR Spectrum - Infrared spectroscopy data
• NMR Spectrum - Nuclear magnetic resonance data
• Mass Spectrum - Mass spectrometry data

Safety and Toxicity

• Flash Point - Flash point temperatures
• Auto-Ignition Temperature - Auto-ignition data
• LD50 - Lethal dose data
• LC50 - Lethal concentration data

Data Structures

PropertyData Class

The PropertyData dataclass represents a single experimental property measurement:

@dataclass
class PropertyData:
    cid: int
    heading: str
    string_with_markup: str
    value: Optional[str]
    unit: Optional[str] 
    reference_number: Optional[str]
    reference_title: Optional[str]
    reference_authors: Optional[str]
    reference_journal: Optional[str]
    reference_year: Optional[str]
    reference_doi: Optional[str]
    reference_pmid: Optional[str]
    full_reference: Optional[str]

Fields: - cid: PubChem Compound ID - heading: Property type (e.g., "Melting Point") - string_with_markup: Original text with markup - value: Extracted numeric/text value - unit: Unit of measurement - reference_*: Citation information - full_reference: Complete formatted reference

Advanced Usage

Custom Value Parsing

The module includes sophisticated value parsing that handles:

# Complex value strings
examples = [
    "139-140 °C",           # Range values
    "25.5 ± 0.2 °C",       # Values with uncertainty
    "< 100 °C",            # Comparison operators
    "decomp. at 180 °C",   # Qualitative descriptions
    "760 mmHg at 20 °C"    # Conditional values
]

# The parser extracts the main numeric value
for example in examples:
    # Internal parsing would extract the primary value
    pass

Reference Information Extraction

Complete bibliographic information is extracted and structured:

# Get properties with full reference details
properties = view.get_experimental_properties(2244, 'Melting Point')
for prop in properties:
    if prop.reference_doi:
        print(f"DOI: {prop.reference_doi}")
    if prop.reference_pmid:
        print(f"PubMed ID: {prop.reference_pmid}")
    if prop.full_reference:
        print(f"Full citation: {prop.full_reference}")

DataFrame Operations

Convert to pandas DataFrame for data analysis:

import pandas as pd

# Get DataFrame with all experimental data
df = view.experimental_properties_to_dataframe(2244, 'Solubility')

# Filter by specific units
water_solubility = df[df['Unit'].str.contains('g/L', na=False)]

# Group by reference source
by_source = df.groupby('Reference').agg({
    'Value': ['count', 'mean'],
    'Unit': lambda x: list(x.unique())
})

# Export to CSV
df.to_csv('solubility_data.csv', index=False)

Error Handling

The module provides specific exception classes:

from provesid.pubchemview import PubChemViewError, PubChemViewNotFoundError

try:
    properties = view.get_experimental_properties(999999, 'Melting Point')
except PubChemViewNotFoundError:
    print("Compound or property not found")
except PubChemViewError as e:
    print(f"API error: {e}")

Batch Processing

Process multiple compounds efficiently:

def batch_extract_properties(cids, property_type):
    """Extract properties for multiple compounds"""
    results = {}
    view = PubChemView()

    for cid in cids:
        try:
            df = view.experimental_properties_to_dataframe(cid, property_type)
            if not df.empty:
                results[cid] = {
                    'count': len(df),
                    'mean_value': df['Value'].mean() if df['Value'].notna().any() else None,
                    'units': df['Unit'].unique().tolist()
                }
        except Exception as e:
            results[cid] = {'error': str(e)}

    return results

# Process multiple compounds
cids = [2244, 2519, 3672]  # Aspirin, Caffeine, Ibuprofen
melting_data = batch_extract_properties(cids, 'Melting Point')

Integration with Other APIs

Combine with PubChem compound data:

from provesid import PubChemAPI, PubChemView

def comprehensive_compound_analysis(cid):
    """Get both computed and experimental data"""
    api = PubChemAPI()
    view = PubChemView()

    # Get computed properties
    computed = api.get_compound_properties(
        [cid], 
        ['MolecularWeight', 'MolecularFormula', 'ConnectivitySMILES']
    )

    # Get experimental properties
    experimental = {}
    for prop_type in ['Melting Point', 'Boiling Point', 'Density']:
        try:
            df = view.experimental_properties_to_dataframe(cid, prop_type)
            if not df.empty:
                experimental[prop_type] = df
        except:
            pass

    return {
        'computed': computed,
        'experimental': experimental
    }

# Analyze aspirin
analysis = comprehensive_compound_analysis(2244)

Performance Considerations

Rate Limiting

The PubChemView client includes automatic rate limiting:

# Adjust request frequency for large batch jobs
view = PubChemView(pause_time=1.0)  # 1 second between requests

# For development/testing with faster requests
view_fast = PubChemView(pause_time=0.1)  # 100ms between requests

Caching

Consider implementing caching for frequently accessed data:

import pickle
from pathlib import Path

def cached_property_extraction(cid, property_type, cache_dir='cache'):
    """Extract properties with file-based caching"""
    cache_path = Path(cache_dir) / f"{cid}_{property_type}.pkl"

    if cache_path.exists():
        with open(cache_path, 'rb') as f:
            return pickle.load(f)

    # Extract fresh data
    view = PubChemView()
    df = view.experimental_properties_to_dataframe(cid, property_type)

    # Cache the results
    cache_path.parent.mkdir(exist_ok=True)
    with open(cache_path, 'wb') as f:
        pickle.dump(df, f)

    return df

See Also

• PubChem API - For computed compound properties
• PubChem Tutorial - Complete tutorial with detailed examples