fix(linkedin): add fallback for date parsing on new job listings (#343)

LinkedIn uses two CSS classes for job posting dates:
- `job-search-card__listdate` for older posts
- `job-search-card__listdate--new` for recent posts (< 24h)

The scraper only checked the first class, causing `date_posted` to be
None for all fresh listings. This adds a fallback to also check for
the `--new` variant.

.github/CODEOWNERS

@@ -0,0 +1 @@
+* @cullenwatson

README.md

@@ -4,7 +4,7 @@
 
 ## Features
 
-- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, **Google**, **ZipRecruiter**, **Bayt** & **Naukri** concurrently
+- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, **Google**, **ZipRecruiter**, & other job boards concurrently
 - Aggregates the job postings in a dataframe
 - Proxies support to bypass blocking
 
@@ -25,7 +25,7 @@ import csv
 from jobspy import scrape_jobs
 
 jobs = scrape_jobs(
-    site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor", "google", "bayt", "naukri"],
+    site_name=["indeed", "linkedin", "zip_recruiter", "google"], # "glassdoor", "bayt", "naukri", "bdjobs"
     search_term="software engineer",
     google_search_term="software engineer jobs near San Francisco, CA since yesterday",
     location="San Francisco, CA",
@@ -59,7 +59,7 @@ zip_recruiter Software Developer                 TEKsystems        Phoenix
 ```plaintext
 Optional
 ├── site_name (list|str): 
-|    linkedin, zip_recruiter, indeed, glassdoor, google, bayt
+|    linkedin, zip_recruiter, indeed, glassdoor, google, bayt, bdjobs
 |    (default is all)
 │
 ├── search_term (str)
@@ -86,6 +86,9 @@ Optional
 │
 ├── easy_apply (bool): 
 |    filters for jobs that are hosted on the job board site (LinkedIn easy apply filter no longer works)
+|
+├── user_agent (str): 
+|    override the default user agent which may be outdated
 │
 ├── description_format (str): 
 |    markdown, html (Format type of the job descriptions. Default is markdown.)

jobspy/__init__.py

@@ -107,6 +107,7 @@ def scrape_jobs(
         scraped_data: JobResponse = scraper.scrape(scraper_input)
         cap_name = site.value.capitalize()
         site_name = "ZipRecruiter" if cap_name == "Zip_recruiter" else cap_name
+        site_name = "LinkedIn" if cap_name == "Linkedin" else cap_name
         create_logger(site_name).info(f"finished scraping")
         return site.value, scraped_data
 

jobspy/bdjobs/__init__.py

@@ -1,4 +1,4 @@
-#__init__.py
+# __init__.py
 from __future__ import annotations
 
 import random
@@ -12,7 +12,12 @@ from bs4.element import Tag
 
 from jobspy.exception import BDJobsException
 from jobspy.bdjobs.constant import headers, search_params
-from jobspy.bdjobs.util import parse_location, parse_date, find_job_listings, is_job_remote
+from jobspy.bdjobs.util import (
+    parse_location,
+    parse_date,
+    find_job_listings,
+    is_job_remote,
+)
 from jobspy.model import (
     JobPost,
     Location,
@@ -39,9 +44,9 @@ class BDJobs(Scraper):
     search_url = "https://jobs.bdjobs.com/jobsearch.asp"
     delay = 2
     band_delay = 3
-    
+
     def __init__(
-        self, proxies: list[str] | str | None = None, ca_cert: str | None = None
+        self, proxies: list[str] | str | None = None, ca_cert: str | None = None, user_agent: str | None = None
     ):
         """
         Initializes BDJobsScraper with the BDJobs job search url
@@ -58,7 +63,7 @@ class BDJobs(Scraper):
         self.session.headers.update(headers)
         self.scraper_input = None
         self.country = "bangladesh"
-    
+
     def scrape(self, scraper_input: ScraperInput) -> JobResponse:
         """
         Scrapes BDJobs for jobs with scraper_input criteria
@@ -70,72 +75,64 @@ class BDJobs(Scraper):
         seen_ids = set()
         page = 1
         request_count = 0
-        
+
         # Set up search parameters
         params = search_params.copy()
         params["txtsearch"] = scraper_input.search_term
-        
+
         continue_search = lambda: len(job_list) < scraper_input.results_wanted
-        
+
         while continue_search():
             request_count += 1
             log.info(f"search page: {request_count}")
-            
+
             try:
                 # Add page parameter if needed
                 if page > 1:
                     params["pg"] = page
-                
+
                 response = self.session.get(
                     self.search_url,
                     params=params,
-                    timeout=getattr(scraper_input, 'request_timeout', 60)
+                    timeout=getattr(scraper_input, "request_timeout", 60),
                 )
 
-                # DEBUG: Save the received HTML content
-                try:
-                    with open("scraper_received_bdjobs.html", "w", encoding="utf-8") as f:
-                        f.write(response.text)
-                    log.info(f"Saved scraper response to scraper_received_bdjobs.html")
-                except Exception as e_write:
-                    log.error(f"Error writing debug HTML file: {e_write}")
-                
                 if response.status_code != 200:
                     log.error(f"BDJobs response status code {response.status_code}")
                     break
-                
+
                 soup = BeautifulSoup(response.text, "html.parser")
                 job_cards = find_job_listings(soup)
-                
+
                 if not job_cards or len(job_cards) == 0:
                     log.info("No more job listings found")
                     break
-                
+
                 log.info(f"Found {len(job_cards)} job cards on page {page}")
-                
+
                 for job_card in job_cards:
                     try:
                         job_post = self._process_job(job_card)
                         if job_post and job_post.id not in seen_ids:
                             seen_ids.add(job_post.id)
                             job_list.append(job_post)
-                            
+
                             if not continue_search():
                                 break
                     except Exception as e:
                         log.error(f"Error processing job card: {str(e)}")
-                
+
                 page += 1
                 # Add delay between requests
                 time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
-                
+
             except Exception as e:
                 log.error(f"Error during scraping: {str(e)}")
                 break
-        
-        job_list = job_list[:scraper_input.results_wanted]
+
+        job_list = job_list[: scraper_input.results_wanted]
         return JobResponse(jobs=job_list)
-    
+
     def _process_job(self, job_card: Tag) -> Optional[JobPost]:
         """
         Processes a job card element into a JobPost object
@@ -147,48 +144,88 @@ class BDJobs(Scraper):
             job_link = job_card.find("a", href=lambda h: h and "jobdetail" in h.lower())
             if not job_link:
                 return None
-            
+
             job_url = job_link.get("href")
             if not job_url.startswith("http"):
                 job_url = urljoin(self.base_url, job_url)
-            
+
             # Extract job ID from URL
-            job_id = job_url.split("jobid=")[-1].split("&")[0] if "jobid=" in job_url else f"bdjobs-{hash(job_url)}"
-            
+            job_id = (
+                job_url.split("jobid=")[-1].split("&")[0]
+                if "jobid=" in job_url
+                else f"bdjobs-{hash(job_url)}"
+            )
+
             # Extract title
             title = job_link.get_text(strip=True)
             if not title:
-                title_elem = job_card.find(["h2", "h3", "h4", "strong", "div"], class_=lambda c: c and "job-title-text" in c)
+                title_elem = job_card.find(
+                    ["h2", "h3", "h4", "strong", "div"],
+                    class_=lambda c: c and "job-title-text" in c,
+                )
                 title = title_elem.get_text(strip=True) if title_elem else "N/A"
-            
+
             # Extract company name - IMPROVED
-            company_elem = job_card.find(["span", "div"], class_=lambda c: c and "comp-name-text" in (c or "").lower())
+            company_elem = job_card.find(
+                ["span", "div"],
+                class_=lambda c: c and "comp-name-text" in (c or "").lower(),
+            )
             if company_elem:
                 company_name = company_elem.get_text(strip=True)
             else:
                 # Try alternative selectors
-                company_elem = job_card.find(["span", "div"], class_=lambda c: c and any(term in (c or "").lower() for term in ["company", "org", "comp-name"]))
-                company_name = company_elem.get_text(strip=True) if company_elem else "N/A"
-            
+                company_elem = job_card.find(
+                    ["span", "div"],
+                    class_=lambda c: c
+                    and any(
+                        term in (c or "").lower()
+                        for term in ["company", "org", "comp-name"]
+                    ),
+                )
+                company_name = (
+                    company_elem.get_text(strip=True) if company_elem else "N/A"
+                )
+
             # Extract location
-            location_elem = job_card.find(["span", "div"], class_=lambda c: c and "locon-text-d" in (c or "").lower())
+            location_elem = job_card.find(
+                ["span", "div"],
+                class_=lambda c: c and "locon-text-d" in (c or "").lower(),
+            )
             if not location_elem:
-                location_elem = job_card.find(["span", "div"], class_=lambda c: c and any(term in (c or "").lower() for term in ["location", "area", "locon"]))
-            location_text = location_elem.get_text(strip=True) if location_elem else "Dhaka, Bangladesh"
-            
+                location_elem = job_card.find(
+                    ["span", "div"],
+                    class_=lambda c: c
+                    and any(
+                        term in (c or "").lower()
+                        for term in ["location", "area", "locon"]
+                    ),
+                )
+            location_text = (
+                location_elem.get_text(strip=True)
+                if location_elem
+                else "Dhaka, Bangladesh"
+            )
+
             # Create Location object
             location = parse_location(location_text, self.country)
-            
+
             # Extract date posted
-            date_elem = job_card.find(["span", "div"], class_=lambda c: c and any(term in (c or "").lower() for term in ["date", "deadline", "published"]))
+            date_elem = job_card.find(
+                ["span", "div"],
+                class_=lambda c: c
+                and any(
+                    term in (c or "").lower()
+                    for term in ["date", "deadline", "published"]
+                ),
+            )
             date_posted = None
             if date_elem:
                 date_text = date_elem.get_text(strip=True)
                 date_posted = parse_date(date_text)
-            
+
             # Check if job is remote
             is_remote = is_job_remote(title, location=location)
-            
+
             # Create job post object
             job_post = JobPost(
                 id=job_id,
@@ -200,17 +237,17 @@ class BDJobs(Scraper):
                 is_remote=is_remote,
                 site=self.site,
             )
-            
+
             # Always fetch description for BDJobs
             job_details = self._get_job_details(job_url)
             job_post.description = job_details.get("description", "")
             job_post.job_type = job_details.get("job_type", "")
-            
+
             return job_post
         except Exception as e:
             log.error(f"Error in _process_job: {str(e)}")
             return None
-    
+
     def _get_job_details(self, job_url: str) -> Dict[str, Any]:
         """
         Gets detailed job information from the job page
@@ -221,59 +258,96 @@ class BDJobs(Scraper):
             response = self.session.get(job_url, timeout=60)
             if response.status_code != 200:
                 return {}
-            
+
             soup = BeautifulSoup(response.text, "html.parser")
-            
+
             # Find job description - IMPROVED based on correct.py
             description = ""
-            
+
             # Try to find the job content div first (as in correct.py)
-            job_content_div = soup.find('div', class_='jobcontent')
+            job_content_div = soup.find("div", class_="jobcontent")
             if job_content_div:
                 # Look for responsibilities section
-                responsibilities_heading = job_content_div.find('h4', id='job_resp') or job_content_div.find(['h4', 'h5'], string=lambda s: s and 'responsibilities' in s.lower())
+                responsibilities_heading = job_content_div.find(
+                    "h4", id="job_resp"
+                ) or job_content_div.find(
+                    ["h4", "h5"], string=lambda s: s and "responsibilities" in s.lower()
+                )
                 if responsibilities_heading:
                     responsibilities_elements = []
                     # Find all following elements until the next heading or hr
                     for sibling in responsibilities_heading.find_next_siblings():
-                        if sibling.name in ['hr', 'h4', 'h5']:
+                        if sibling.name in ["hr", "h4", "h5"]:
                             break
-                        if sibling.name == 'ul':
-                            responsibilities_elements.extend(li.get_text(separator=' ', strip=True) for li in sibling.find_all('li'))
-                        elif sibling.name == 'p':
-                            responsibilities_elements.append(sibling.get_text(separator=' ', strip=True))
-                
-                description = "\n".join(responsibilities_elements) if responsibilities_elements else ""
-            
+                        if sibling.name == "ul":
+                            responsibilities_elements.extend(
+                                li.get_text(separator=" ", strip=True)
+                                for li in sibling.find_all("li")
+                            )
+                        elif sibling.name == "p":
+                            responsibilities_elements.append(
+                                sibling.get_text(separator=" ", strip=True)
+                            )
+
+                description = (
+                    "\n".join(responsibilities_elements)
+                    if responsibilities_elements
+                    else ""
+                )
+
             # If no description found yet, try the original approach
             if not description:
-                description_elem = soup.find(["div", "section"], class_=lambda c: c and any(term in (c or "").lower() for term in ["job-description", "details", "requirements"]))
+                description_elem = soup.find(
+                    ["div", "section"],
+                    class_=lambda c: c
+                    and any(
+                        term in (c or "").lower()
+                        for term in ["job-description", "details", "requirements"]
+                    ),
+                )
                 if description_elem:
                     description_elem = remove_attributes(description_elem)
                     description = description_elem.prettify(formatter="html")
-                    if hasattr(self.scraper_input, 'description_format') and self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
+                    if (
+                        hasattr(self.scraper_input, "description_format")
+                        and self.scraper_input.description_format
+                        == DescriptionFormat.MARKDOWN
+                    ):
                         description = markdown_converter(description)
-            
+
             # Extract job type
-            job_type_elem = soup.find(["span", "div"], string=lambda s: s and any(term in (s or "").lower() for term in ["job type", "employment type"]))
+            job_type_elem = soup.find(
+                ["span", "div"],
+                string=lambda s: s
+                and any(
+                    term in (s or "").lower()
+                    for term in ["job type", "employment type"]
+                ),
+            )
             job_type = None
             if job_type_elem:
-                job_type_text = job_type_elem.find_next(["span", "div"]).get_text(strip=True)
+                job_type_text = job_type_elem.find_next(["span", "div"]).get_text(
+                    strip=True
+                )
                 job_type = job_type_text if job_type_text else None
-            
+
             # Extract company industry
-            industry_elem = soup.find(["span", "div"], string=lambda s: s and "industry" in (s or "").lower())
+            industry_elem = soup.find(
+                ["span", "div"], string=lambda s: s and "industry" in (s or "").lower()
+            )
             company_industry = None
             if industry_elem:
-                industry_text = industry_elem.find_next(["span", "div"]).get_text(strip=True)
+                industry_text = industry_elem.find_next(["span", "div"]).get_text(
+                    strip=True
+                )
                 company_industry = industry_text if industry_text else None
-            
+
             return {
                 "description": description,
                 "job_type": job_type,
-                "company_industry": company_industry
+                "company_industry": company_industry,
             }
-            
+
         except Exception as e:
             log.error(f"Error getting job details: {str(e)}")
-            return {}
+            return {}

jobspy/linkedin/__init__.py

@@ -35,6 +35,7 @@ from jobspy.util import (
     extract_emails_from_text,
     currency_parser,
     markdown_converter,
+    plain_converter,
     create_session,
     remove_attributes,
     create_logger,
@@ -164,7 +165,7 @@ class LinkedIn(Scraper):
 
             if continue_search():
                 time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
-                start += len(job_list)
+                start += len(job_cards)
 
         job_list = job_list[: scraper_input.results_wanted]
         return JobResponse(jobs=job_list)
@@ -208,6 +209,10 @@ class LinkedIn(Scraper):
             if metadata_card
             else None
         )
+        if not datetime_tag and metadata_card:
+            datetime_tag = metadata_card.find(
+                "time", class_="job-search-card__listdate--new"
+            )
         date_posted = None
         if datetime_tag and "datetime" in datetime_tag.attrs:
             datetime_str = datetime_tag["datetime"]
@@ -267,7 +272,8 @@ class LinkedIn(Scraper):
             description = div_content.prettify(formatter="html")
             if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
                 description = markdown_converter(description)
-
+            elif self.scraper_input.description_format == DescriptionFormat.PLAIN:
+                description = plain_converter(description)
         h3_tag = soup.find(
             "h3", text=lambda text: text and "Job function" in text.strip()
         )

jobspy/model.py

@@ -234,7 +234,7 @@ class Compensation(BaseModel):
 class DescriptionFormat(Enum):
     MARKDOWN = "markdown"
     HTML = "html"
-
+    PLAIN = "plain"
 
 class JobPost(BaseModel):
     id: str | None = None

jobspy/naukri/__init__.py

@@ -164,12 +164,15 @@ class Naukri(Scraper):
         date_posted = self._parse_date(job.get("footerPlaceholderLabel"), job.get("createdDate"))
 
         job_url = f"https://www.naukri.com{job.get('jdURL', f'/job/{job_id}')}"
-        description = job.get("jobDescription") if full_descr else None
+        raw_description = job.get("jobDescription") if full_descr else None
+
+        job_type = parse_job_type(raw_description) if raw_description else None
+        company_industry = parse_company_industry(raw_description) if raw_description else None
+
+        description = raw_description
         if description and self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
             description = markdown_converter(description)
 
-        job_type = parse_job_type(description) if description else None
-        company_industry = parse_company_industry(description) if description else None
         is_remote = is_job_remote(title, description or "", location)
         company_logo = job.get("logoPathV3") or job.get("logoPath")
 

jobspy/naukri/util.py

@@ -5,10 +5,12 @@ from jobspy.model import JobType, Location
 from jobspy.util import get_enum_from_job_type
 
 
-def parse_job_type(soup: BeautifulSoup) -> list[JobType] | None:
+def parse_job_type(soup: BeautifulSoup |str) -> list[JobType] | None:
     """
     Gets the job type from the job page
     """
+    if isinstance(soup, str):
+        soup = BeautifulSoup(soup, "html.parser")
     job_type_tag = soup.find("span", class_="job-type")
     if job_type_tag:
         job_type_str = job_type_tag.get_text(strip=True).lower().replace("-", "")
@@ -16,10 +18,12 @@ def parse_job_type(soup: BeautifulSoup) -> list[JobType] | None:
     return None
 
 
-def parse_company_industry(soup: BeautifulSoup) -> str | None:
+def parse_company_industry(soup: BeautifulSoup | str) -> str | None:
     """
     Gets the company industry from the job page
     """
+    if isinstance(soup, str):
+        soup = BeautifulSoup(soup, "html.parser")
     industry_tag = soup.find("span", class_="industry")
     return industry_tag.get_text(strip=True) if industry_tag else None
 

jobspy/util.py

@@ -157,6 +157,15 @@ def markdown_converter(description_html: str):
     markdown = md(description_html)
     return markdown.strip()
 
+def plain_converter(decription_html:str):
+    from bs4 import BeautifulSoup
+    if decription_html is None:
+        return None
+    soup = BeautifulSoup(decription_html, "html.parser")
+    text = soup.get_text(separator=" ")
+    text = re.sub(r'\s+',' ',text)
+    return text.strip()
+
 
 def extract_emails_from_text(text: str) -> list[str] | None:
     if not text:

poetry.lock

@@ -749,17 +749,6 @@ files = [
 [package.extras]
 all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2)"]
 
-[[package]]
-name = "iniconfig"
-version = "2.0.0"
-description = "brain-dead simple config-ini parsing"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"},
-    {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
-]
-
 [[package]]
 name = "ipykernel"
 version = "6.29.5"
@@ -1229,13 +1218,13 @@ files = [
 
 [[package]]
 name = "markdownify"
-version = "0.13.1"
+version = "1.1.0"
 description = "Convert HTML to markdown."
 optional = false
 python-versions = "*"
 files = [
-    {file = "markdownify-0.13.1-py3-none-any.whl", hash = "sha256:1d181d43d20902bcc69d7be85b5316ed174d0dda72ff56e14ae4c95a4a407d22"},
-    {file = "markdownify-0.13.1.tar.gz", hash = "sha256:ab257f9e6bd4075118828a28c9d02f8a4bfeb7421f558834aa79b2dfeb32a098"},
+    {file = "markdownify-1.1.0-py3-none-any.whl", hash = "sha256:32a5a08e9af02c8a6528942224c91b933b4bd2c7d078f9012943776fc313eeef"},
+    {file = "markdownify-1.1.0.tar.gz", hash = "sha256:449c0bbbf1401c5112379619524f33b63490a8fa479456d41de9dc9e37560ebd"},
 ]
 
 [package.dependencies]
@@ -1710,21 +1699,6 @@ docs = ["furo (>=2024.8.6)", "proselint (>=0.14)", "sphinx (>=8.0.2)", "sphinx-a
 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=8.3.2)", "pytest-cov (>=5)", "pytest-mock (>=3.14)"]
 type = ["mypy (>=1.11.2)"]
 
-[[package]]
-name = "pluggy"
-version = "1.5.0"
-description = "plugin and hook calling mechanisms for python"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "pluggy-1.5.0-py3-none-any.whl", hash = "sha256:44e1ad92c8ca002de6377e165f3e0f1be63266ab4d554740532335b9d75ea669"},
-    {file = "pluggy-1.5.0.tar.gz", hash = "sha256:2cffa88e94fdc978c4c574f15f9e59b7f4201d439195c3715ca9e2486f1d0cf1"},
-]
-
-[package.extras]
-dev = ["pre-commit", "tox"]
-testing = ["pytest", "pytest-benchmark"]
-
 [[package]]
 name = "pre-commit"
 version = "4.0.1"
@@ -1975,28 +1949,6 @@ files = [
 [package.extras]
 windows-terminal = ["colorama (>=0.4.6)"]
 
-[[package]]
-name = "pytest"
-version = "7.4.4"
-description = "pytest: simple powerful testing with Python"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "pytest-7.4.4-py3-none-any.whl", hash = "sha256:b090cdf5ed60bf4c45261be03239c2c1c22df034fbffe691abe93cd80cea01d8"},
-    {file = "pytest-7.4.4.tar.gz", hash = "sha256:2cf0005922c6ace4a3e2ec8b4080eb0d9753fdc93107415332f50ce9e7994280"},
-]
-
-[package.dependencies]
-colorama = {version = "*", markers = "sys_platform == \"win32\""}
-exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
-iniconfig = "*"
-packaging = "*"
-pluggy = ">=0.12,<2.0"
-tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
-
-[package.extras]
-testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
-
 [[package]]
 name = "python-dateutil"
 version = "2.9.0.post0"
@@ -2869,4 +2821,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "57169347d2ce0ff19c4d3024ce000651bb3a816e36f454618f480741094fb4a7"
+content-hash = "6260adc8f96f6cf1ba4e2c23f05504c19e67140b9d346aed3d12eea6957b2104"

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.80"
+version = "1.1.82"
 description = "Job scraper for LinkedIn, Indeed, Glassdoor, ZipRecruiter & Bayt"
 authors = ["Cullen Watson <cullen@cullenwatson.com>", "Zachary Hampton <zachary@zacharysproducts.com>"]
 homepage = "https://github.com/cullenwatson/JobSpy"
@@ -21,10 +21,10 @@ python = "^3.10"
 requests = "^2.31.0"
 beautifulsoup4 = "^4.12.2"
 pandas = "^2.1.0"
-NUMPY = "1.26.3"
+numpy = ">=1.26.0"
 pydantic = "^2.3.0"
 tls-client = "^1.0.1"
-markdownify = "^0.13.1"
+markdownify = "^1.1.0"
 regex = "^2024.4.28"
 
 [tool.poetry.group.dev.dependencies]