Erkundung des Arbeitsmarktes für Software-Ingenieure

import json
import logging
import os
from threading import Lock

from dotenv import load_dotenv

# linkedin_jobs_scraper loads env statically
# So dotenv should be loaded before imports
load_dotenv()

from linkedin_jobs_scraper import LinkedinScraper
from linkedin_jobs_scraper.events import EventData, Events
from linkedin_jobs_scraper.filters import ExperienceLevelFilters, TypeFilters
from linkedin_jobs_scraper.query import Query, QueryFilters, QueryOptions

CHROMEDRIVER_PATH = os.environ["CHROMEDRIVER_PATH"]

RESULT_FILE_PATH = "result.json"
KEYWORDS = ("Python", "PHP", "Java", "Rust")
LOCATIONS = ("South Korea",)
TYPE_FILTERS = (TypeFilters.FULL_TIME,)
EXPERIENCE = (ExperienceLevelFilters.MID_SENIOR,)
LIMIT = 500

logging.basicConfig(level=logging.INFO)
log = logging.getLogger(__name__)


def main():
    result_lock = Lock()
    result = []

    def on_data(data: EventData):
        with result_lock:
            result.append(data._asdict())

        log.info(
            "[JOB]",
            data.title,
            data.company,
            len(data.description),
        )

    def on_error(error):
        log.error("[ERROR]", error)

    def on_end():
        log.info("Scraping finished")

        if not result:
            return

        with open(RESULT_FILE_PATH, "w") as f:
            json.dump(result, f)

    queries = [
        Query(
            query=keyword,
            options=QueryOptions(
                limit=LIMIT,
                locations=[*LOCATIONS],
                filters=QueryFilters(
                    type=[*TYPE_FILTERS],
                    experience=[*EXPERIENCE],
                ),
            ),
        )
        for keyword in KEYWORDS
    ]

    scraper = LinkedinScraper(
        chrome_executable_path=CHROMEDRIVER_PATH,
        headless=True,
        max_workers=len(queries),
        slow_mo=0.5,
        page_load_timeout=40,
    )

    scraper.on(Events.DATA, on_data)
    scraper.on(Events.ERROR, on_error)
    scraper.on(Events.END, on_end)

    scraper.run(queries)


if __name__ == "__main__":
    main()

#!/usr/bin/env bash
stable_version=$(curl 'https://googlechromelabs.github.io/chrome-for-testing/LATEST_RELEASE_STABLE')
driver_url=$(curl 'https://googlechromelabs.github.io/chrome-for-testing/known-good-versions-with-downloads.json' \
    | jq -r ".versions[] | select(.version == \"${stable_version}\") | .downloads.chromedriver[0] | select(.platform == \"linux64\") | .url")
wget "$driver_url"
driver_zip_name=$(echo "$driver_url" | awk -F'/' '{print $NF}')
unzip "$driver_zip_name"
rm "$driver_zip_name"

CHROMEDRIVER_PATH="chromedriver-linux64/chromedriver"
LI_AT_COOKIE=

class EventData(NamedTuple):
    query: str = ''
    location: str = ''
    job_id: str = ''
    job_index: int = -1  # Only for debug
    link: str = ''
    apply_link: str = ''
    title: str = ''
    company: str = ''
    company_link: str = ''
    company_img_link: str = ''
    place: str = ''
    description: str = ''
    description_html: str = ''
    date: str = ''
    insights: List[str] = []
    skills: List[str] = []

# Replaces description of a job with elipsis
def hide-description [] {
    update description { |row| '...' } 
    | update description_html { |row| '...' } 
}

cat result.json 
| from  json 
| first 
| hide-description
| to md --pretty 

import json
import logging
import os

from dotenv import load_dotenv
from linkedin_jobs_scraper.events import EventData
from openai import OpenAI
from tqdm import tqdm

load_dotenv()

client = OpenAI(
    api_key=os.environ["OPENAI_API_KEY"],
)

with open("result.json", "rb") as f:
    jobs = json.load(f)

parsed_descriptions = []

for job in tqdm(jobs):
    job = EventData(**job)
    chat_completion = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {
                "role": "user",
                "content": """
                    Process given IT job description. 
                    Output only raw JSON with the following fields:
                        - Experience (amount of years or null)
                        - Degree requirement (str if found else null)
                        - Tech stack (array of strings)
                        - Position (middle, senior, lead, manager, other (describe it))
                        - Core responsibilites (array of strings)

                    Output will be passed directrly to the
                    Python's `json.loads` function. So DO NOT APPLY MARKDOWN FORMATTING
                    Example:
                    ```


                    {
                        "experience": 5, 
                        "degree": "bachelor", 
                        "stack": ["Python", "FastAPI", "Docker"], 
                        "position": "middle",
                        "responsibilities": ["Deliver features", "break production"]
                    }


                    ```

                    Here is a job description:
                """
                + "\n\n"
                + job.description_html,
            }
        ],
    )

    content = chat_completion.choices[0].message.content
    try:
        if not content:
            print("Empty result from ChatGPT")
            continue
        result = json.loads(content)
    except json.decoder.JSONDecodeError as e:
        logging.error(e, chat_completion)
        continue

    result["job_id"] = job.job_id
    parsed_descriptions.append(result)

with open("job_descriptions_analysis.json", "w") as f:
    json.dump(parsed_descriptions, f)

cat job_descriptions_analysis.json 
| from json 
| merge (cat result.json | from json)
| to json
| save full.json

cat full.json | from json | columns
╭────┬──────────────────╮
│  0 │ experience       │
│  1 │ degree           │
│  2 │ stack            │
│  3 │ position         │
│  4 │ responsibilities │
│  5 │ job_id           │
│  6 │ query            │
│  7 │ location         │
│  8 │ job_index        │
│  9 │ link             │
│ 10 │ apply_link       │
│ 11 │ title            │
│ 12 │ company          │
│ 13 │ company_link     │
│ 14 │ company_img_link │
│ 15 │ place            │
│ 16 │ description      │
│ 17 │ description_html │
│ 18 │ date             │
│ 19 │ insights         │
│ 20 │ skills           │
╰────┴──────────────────╯

let df = cat full.json | from json

$df
| get 'stack' 
| flatten 
| uniq --count 
| sort-by count --reverse 
| first 20 
| to md --pretty

$df
| filter-by-intersection 'stack' ['python']
| get 'stack' 
| flatten 
| where $it != 'Python' # Exclude python itself
| uniq --count 
| sort-by count --reverse 
| first 10
| to md --pretty

$df
| filter-by-intersection 'stack' ['python'] --invert
| get 'stack' 
| flatten 
| uniq --count 
| sort-by count --reverse 
| first 10
| to md --pretty

# Filters rows by intersecting given `column` with `requirements`
# Case insensitive and works only if ALL requirements exist in a `column` value
# If `--invert` then works as symmetric difference
def filter-by-intersection [
    column: string
    requirements: list<string>
   --invert (-i)
] {
    let required_stack = $requirements | par-each { |el| str downcase }
    let required_len = if $invert { 0 } else { ($requirements | length )}
    $in
    | filter { |row| 
        $required_len == (
            $row 
            | get $column 
            | par-each { |el| str downcase } 
            | where ($it in $requirements) 
            | length
        )
    }
}

$df
| filter-by-intersection 'stack' ['python'] 
| group-by 'position' --to-table
| insert 'group_size' { |group| $group.items | length } 
| where 'group_size' >= 10
| insert 'experience' { |group| 
    $group.items 
    | get 'experience'
    | uniq --count  
    | sort-by 'count' --reverse 
    | update 'value' { |row| if $row.value == null { 0 } else { $row.value }}
    | rename --column { 'value': 'years' }
    | first 3 
} 
| insert 'degree_requirement' { |group| 
    $group.items 
    | each { |row| $row.degree != null } 
    | uniq --count 
    | sort-by 'value'
    | rename --column { 'value': 'required' }
}
| sort-by 'group_size' --reverse 
| select 'group' 'group_size' 'experience' 'degree_requirement'

╭───┬────────┬────────────┬───────────────────────┬──────────────────────────╮
│ # │ group  │ group_size │      experience       │    degree_requirement    │
├───┼────────┼────────────┼───────────────────────┼──────────────────────────┤
│ 0 │ senior │         83 │ ╭───┬───────┬───────╮ │ ╭───┬──────────┬───────╮ │
│   │        │            │ │ # │ years │ count │ │ │ # │ required │ count │ │
│   │        │            │ ├───┼───────┼───────┤ │ ├───┼──────────┼───────┤ │
│   │        │            │ │ 0 │     5 │    30 │ │ │ 0 │ false    │    26 │ │
│   │        │            │ │ 1 │     0 │    11 │ │ │ 1 │ true     │    57 │ │
│   │        │            │ │ 2 │     7 │    11 │ │ ╰───┴──────────┴───────╯ │
│   │        │            │ ╰───┴───────┴───────╯ │                          │
│ 1 │ other  │         14 │ ╭───┬───────┬───────╮ │ ╭───┬──────────┬───────╮ │
│   │        │            │ │ # │ years │ count │ │ │ # │ required │ count │ │
│   │        │            │ ├───┼───────┼───────┤ │ ├───┼──────────┼───────┤ │
│   │        │            │ │ 0 │     0 │     8 │ │ │ 0 │ false    │    12 │ │
│   │        │            │ │ 1 │     5 │     1 │ │ │ 1 │ true     │     2 │ │
│   │        │            │ │ 2 │     3 │     1 │ │ ╰───┴──────────┴───────╯ │
│   │        │            │ ╰───┴───────┴───────╯ │                          │
│ 2 │ lead   │         12 │ ╭───┬───────┬───────╮ │ ╭───┬──────────┬───────╮ │
│   │        │            │ │ # │ years │ count │ │ │ # │ required │ count │ │
│   │        │            │ ├───┼───────┼───────┤ │ ├───┼──────────┼───────┤ │
│   │        │            │ │ 0 │     0 │     5 │ │ │ 0 │ false    │     6 │ │
│   │        │            │ │ 1 │    10 │     4 │ │ │ 1 │ true     │     6 │ │
│   │        │            │ │ 2 │     5 │     1 │ │ ╰───┴──────────┴───────╯ │
│   │        │            │ ╰───┴───────┴───────╯ │                          │
│ 3 │ middle │         10 │ ╭───┬───────┬───────╮ │ ╭───┬──────────┬───────╮ │
│   │        │            │ │ # │ years │ count │ │ │ # │ required │ count │ │
│   │        │            │ ├───┼───────┼───────┤ │ ├───┼──────────┼───────┤ │
│   │        │            │ │ 0 │     3 │     4 │ │ │ 0 │ false    │     4 │ │
│   │        │            │ │ 1 │     5 │     3 │ │ │ 1 │ true     │     6 │ │
│   │        │            │ │ 2 │     2 │     2 │ │ ╰───┴──────────┴───────╯ │
│   │        │            │ ╰───┴───────┴───────╯ │                          │
╰───┴────────┴────────────┴───────────────────────┴──────────────────────────╯