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7 Commits

Author SHA1 Message Date
Cullen Watson
286b9e1256 chore: version number 2023-09-21 20:28:57 -05:00
Cullen Watson
162dd40b0f docs: add usejobspy.com 2023-09-21 20:27:04 -05:00
Cullen Watson
558e352939 fix: job type param bug 2023-09-21 17:42:24 -05:00
Zachary Hampton
efad1a1b7d Update README.md 2023-09-21 09:52:18 -07:00
Cullen Watson
eaa481c2f4 docs: add macos catalina to faq 2023-09-19 12:50:14 -05:00
Zachary Hampton
b914aa6449 Update README.md 2023-09-16 13:52:30 -07:00
Zachary Hampton
6adbfb8b29 Update README.md 2023-09-16 13:51:45 -07:00
3 changed files with 21 additions and 3 deletions

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@@ -2,7 +2,11 @@
**JobSpy** is a simple, yet comprehensive, job scraping library.
### Looking to build a data-focused software product? [Book a call](https://calendly.com/zachary-products/15min) to learn more.
**Not technical?** Try out the web scraping tool on our site at [usejobspy.com](https://usejobspy.com).
*Looking to build a data-focused software product?* **[Book a call](https://calendly.com/zachary-products/15min)** *to work with us.*
\
Check out another project we wrote: ***[HomeHarvest](https://github.com/ZacharyHampton/HomeHarvest)** a Python package for real estate scraping*
## Features
@@ -164,4 +168,10 @@ You can specify the following countries when searching on Indeed (use the exact
---
**Q: Experiencing a "Segmentation fault: 11" on macOS Catalina?**
**A:** This is due to `tls_client` dependency not supporting your architecture. Solutions and workarounds include:
- Upgrade to a newer version of MacOS
- Reach out to the maintainers of [tls_client](https://github.com/bogdanfinn/tls-client) for fixes

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@@ -1,6 +1,6 @@
[tool.poetry]
name = "python-jobspy"
version = "1.1.4"
version = "1.1.7"
description = "Job scraper for LinkedIn, Indeed & ZipRecruiter"
authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
homepage = "https://github.com/cullenwatson/JobSpy"

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@@ -32,7 +32,7 @@ def scrape_jobs(
location: str = "",
distance: int = None,
is_remote: bool = False,
job_type: JobType = None,
job_type: str = None,
easy_apply: bool = False, # linkedin
results_wanted: int = 15,
country_indeed: str = "usa",
@@ -44,6 +44,14 @@ def scrape_jobs(
:return: results_wanted: pandas dataframe containing job data
"""
def get_enum_from_value(value_str):
for job_type in JobType:
if value_str in job_type.value:
return job_type
raise Exception(f"Invalid job type: {value_str}")
job_type = get_enum_from_value(job_type) if job_type else None
if type(site_name) == str:
site_type = [_map_str_to_site(site_name)]
else: #: if type(site_name) == list