# National Stock Exchange (India) Web-Scraping For getting Required Data
## WebSite-Url : [https://www.nseindia.com/](https://www.nseindia.com/)
## gereral.py
That uses NSE private search api for getting id of a stock
example tata moors (Common name) :- TATAMOTORSEQN (ID assigned by NSE)
```python
from general import getId
id = getId('tata motors')
```
## today_all_stock.py
Gives all data of all companies including NIFTY, and you save it as CSV file.
getTodayData() returns tuple in the form of (nifty_data, Company_data)
```python
from today_all_stocks import getTodayData
nifty_data, companies_data = getTodayData()
```
## intra_day.py
if you call the function intraDay(company_id) or nifty_intraDay(nifty_type) to get live data i.e., from 09:00:00 AM to till now
For Companies use like this,
```python
from intra_day import Intra_Day
ID = Intra_Day('TATA MOTORS')
timeStamp, dataPoints = ID.intraDay()
```
and for NIFTY use,
```python
from intra_day import Intra_Day
ID = Intra_Day('NIFTY 50')
timeStamp, dataPoints = ID.nifty_intraDay()
```
call nifty_intraday() or intraDay() as many times you need
## individual_company_stock.py
This will give you the historical data of that stock. max 3 years
```python
from individual_company_stock import getHistoryData
getHistoryData('SHREECEM',from_date='30-04-2020',to_date='30-04-2021')
# Default params : from_date = today's date in last year DD-MM-(YYYY-1), to_date=today's date DD-MM-YYYY
# for example today is 30-04-2021; from_date = 30-04-2020 to_date = 30-04-2021
```
```python
from individual_company_stock import niftyHistoryData
niftyHistoryData('NIFTY 50')
# Default params : from_date = today's date in last year DD-MM-(YYYY-1), to_date=today's date DD-MM-YYYY
# for example today is 30-04-2021; from_date = 30-04-2020 to_date = 30-04-2021
```
Raw data
{
"_id": null,
"home_page": "https://github.com/pkjmesra/PKNSETools",
"name": "PKNSETools",
"maintainer": null,
"docs_url": null,
"requires_python": null,
"maintainer_email": null,
"keywords": "NSE, Stocks, Data Download",
"author": "pkjmesra",
"author_email": "pkjmesra@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/12/d2/f76dbef7a60842ccfbbda2c663d5f0de62a31c15631c987aca0a225c47a0/pknsetools-0.1.20250224.139.tar.gz",
"platform": null,
"description": "# National Stock Exchange (India) Web-Scraping For getting Required Data\n\n## WebSite-Url : [https://www.nseindia.com/](https://www.nseindia.com/)\n\n## gereral.py\nThat uses NSE private search api for getting id of a stock\n\nexample tata moors (Common name) :- TATAMOTORSEQN (ID assigned by NSE)\n```python\nfrom general import getId\nid = getId('tata motors')\n```\n\n\n## today_all_stock.py\nGives all data of all companies including NIFTY, and you save it as CSV file.\ngetTodayData() returns tuple in the form of (nifty_data, Company_data)\n\n```python\nfrom today_all_stocks import getTodayData\nnifty_data, companies_data = getTodayData() \n```\n\n## intra_day.py\nif you call the function intraDay(company_id) or nifty_intraDay(nifty_type) to get live data i.e., from 09:00:00 AM to till now\n\nFor Companies use like this,\n```python\nfrom intra_day import Intra_Day\nID = Intra_Day('TATA MOTORS')\ntimeStamp, dataPoints = ID.intraDay()\n```\n\nand for NIFTY use,\n\n```python\nfrom intra_day import Intra_Day\nID = Intra_Day('NIFTY 50')\ntimeStamp, dataPoints = ID.nifty_intraDay()\n```\n\ncall nifty_intraday() or intraDay() as many times you need\n\n\n## individual_company_stock.py\nThis will give you the historical data of that stock. max 3 years \n\n```python\nfrom individual_company_stock import getHistoryData\ngetHistoryData('SHREECEM',from_date='30-04-2020',to_date='30-04-2021') \n# Default params : from_date = today's date in last year DD-MM-(YYYY-1), to_date=today's date DD-MM-YYYY\n# for example today is 30-04-2021; from_date = 30-04-2020 to_date = 30-04-2021\n```\n\n```python\nfrom individual_company_stock import niftyHistoryData\nniftyHistoryData('NIFTY 50') \n# Default params : from_date = today's date in last year DD-MM-(YYYY-1), to_date=today's date DD-MM-YYYY\n# for example today is 30-04-2021; from_date = 30-04-2020 to_date = 30-04-2021\n```\n",
"bugtrack_url": null,
"license": "OSI Approved (MIT)",
"summary": "A Python-based data downloader for NSE, India",
"version": "0.1.20250224.139",
"project_urls": {
"Download": "https://github.com/pkjmesra/PKNSETools/archive/v0.1.20250224.139.zip",
"Homepage": "https://github.com/pkjmesra/PKNSETools"
},
"split_keywords": [
"nse",
" stocks",
" data download"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "0436296c885ea22a29f12e9da7998eb311d2553eddb10a47f8d4b7836ce13b51",
"md5": "8398120ef098d4bb279ff1a7fe16957a",
"sha256": "f56c17335f8b04b27cc542eb52f2e89c9de0fc584de648969e00df37a5e7c776"
},
"downloads": -1,
"filename": "PKNSETools-0.1.20250224.139-cp310-cp310-macosx_10_9_x86_64.whl",
"has_sig": false,
"md5_digest": "8398120ef098d4bb279ff1a7fe16957a",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": null,
"size": 85756,
"upload_time": "2025-02-24T10:08:05",
"upload_time_iso_8601": "2025-02-24T10:08:05.072062Z",
"url": "https://files.pythonhosted.org/packages/04/36/296c885ea22a29f12e9da7998eb311d2553eddb10a47f8d4b7836ce13b51/PKNSETools-0.1.20250224.139-cp310-cp310-macosx_10_9_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "72a5e37d0b418881d769a9d9952905e9476e35d86962b737d995383a49deddfc",
"md5": "913b269dd1689d439cdcb1de7ba5eb84",
"sha256": "48eaa5272b12b28c80a86c6b7da8515de82526d833b1311c0147f4676d5d605c"
},
"downloads": -1,
"filename": "PKNSETools-0.1.20250224.139-cp310-cp310-macosx_13_0_arm64.whl",
"has_sig": false,
"md5_digest": "913b269dd1689d439cdcb1de7ba5eb84",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": null,
"size": 85757,
"upload_time": "2025-02-24T10:06:38",
"upload_time_iso_8601": "2025-02-24T10:06:38.945551Z",
"url": "https://files.pythonhosted.org/packages/72/a5/e37d0b418881d769a9d9952905e9476e35d86962b737d995383a49deddfc/PKNSETools-0.1.20250224.139-cp310-cp310-macosx_13_0_arm64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "d174e33f91f4bd8d6fbf6f4d61356b363c3d9545516ab540391b73a4bd062210",
"md5": "f25f96d6ccc92e49204708d5d5673adb",
"sha256": "89e50830a635d3011f6a1ca198a616a8b4302c55a1fe223047ee9de39bcd7a3c"
},
"downloads": -1,
"filename": "PKNSETools-0.1.20250224.139-cp312-cp312-manylinux2014_x86_64.whl",
"has_sig": false,
"md5_digest": "f25f96d6ccc92e49204708d5d5673adb",
"packagetype": "bdist_wheel",
"python_version": "cp312",
"requires_python": null,
"size": 85821,
"upload_time": "2025-02-24T10:06:34",
"upload_time_iso_8601": "2025-02-24T10:06:34.300500Z",
"url": "https://files.pythonhosted.org/packages/d1/74/e33f91f4bd8d6fbf6f4d61356b363c3d9545516ab540391b73a4bd062210/PKNSETools-0.1.20250224.139-cp312-cp312-manylinux2014_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "efcf0feeb9daae5f8a65d52eeee62317e8fe7a13c86568ebf6834271b90d3984",
"md5": "7077b7628972707ba85e79d676627f1a",
"sha256": "a6d0b4ee03444e044e7605ae3196a10a14243a5f40ab4a0024dad1db5fac6f6e"
},
"downloads": -1,
"filename": "PKNSETools-0.1.20250224.139-cp312-cp312-win_amd64.whl",
"has_sig": false,
"md5_digest": "7077b7628972707ba85e79d676627f1a",
"packagetype": "bdist_wheel",
"python_version": "cp312",
"requires_python": null,
"size": 86207,
"upload_time": "2025-02-24T10:08:39",
"upload_time_iso_8601": "2025-02-24T10:08:39.433329Z",
"url": "https://files.pythonhosted.org/packages/ef/cf/0feeb9daae5f8a65d52eeee62317e8fe7a13c86568ebf6834271b90d3984/PKNSETools-0.1.20250224.139-cp312-cp312-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "12d2f76dbef7a60842ccfbbda2c663d5f0de62a31c15631c987aca0a225c47a0",
"md5": "4ff9369d73974678141d92802ed48f29",
"sha256": "54913f94a3af2f3d2476529b2d552f4781870a5a46757fdb455c504806a9b66a"
},
"downloads": -1,
"filename": "pknsetools-0.1.20250224.139.tar.gz",
"has_sig": false,
"md5_digest": "4ff9369d73974678141d92802ed48f29",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 69118,
"upload_time": "2025-02-24T10:06:37",
"upload_time_iso_8601": "2025-02-24T10:06:37.895323Z",
"url": "https://files.pythonhosted.org/packages/12/d2/f76dbef7a60842ccfbbda2c663d5f0de62a31c15631c987aca0a225c47a0/pknsetools-0.1.20250224.139.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-02-24 10:06:37",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "pkjmesra",
"github_project": "PKNSETools",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [
{
"name": "brotli",
"specs": []
},
{
"name": "bs4",
"specs": []
},
{
"name": "mthrottle",
"specs": []
},
{
"name": "numpy",
"specs": []
},
{
"name": "pandas",
"specs": []
},
{
"name": "PKDevTools",
"specs": []
},
{
"name": "pytz",
"specs": []
},
{
"name": "requests",
"specs": []
},
{
"name": "urllib3",
"specs": []
},
{
"name": "xmltodict",
"specs": []
},
{
"name": "yfinance",
"specs": []
}
],
"lcname": "pknsetools"
}
JSON
