bdshare

bdshare is a Python library for fetching live and historical market data from the Dhaka Stock Exchange (DSE). It handles scraping, retries, caching, and rate limiting so you can focus on your analysis.

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Table of Contents

• Installation
• Quick Start
• Core Concepts
• Usage Guide
  • Live Trading Data
  • Historical Data
  • Market & Index Data
  • News & Announcements
  • Saving to CSV
• OOP Client (BDShare)
• Error Handling
• API Reference
• Examples
• Using bdshare with AI Agents (MCP Server)
• Contributing
• Roadmap
• Disclaimer

---

Installation

Requirements: Python 3.7+

pip install bdshare

Install from source (latest development version):

pip install -U git+https://github.com/rochi88/bdshare.git

Dependencies installed automatically: pandas, requests, beautifulsoup4, lxml

---

Quick Start

from bdshare import get_current_trade_data, get_historical_data

# Live prices for all instruments
df = get_current_trade_data()
print(df.head())

# Historical data for a specific symbol
df = get_historical_data('2024-01-01', '2024-01-31', 'GP')
print(df.head())

Or use the object-oriented client:

from bdshare import BDShare

with BDShare() as bd:
    print(bd.get_market_summary())
    print(bd.get_current_trades('ACI'))

---

Core Concepts

Concept	Details
Retries	All network calls retry up to 3 times with exponential back-off
Fallback URL	Every request has a primary and an alternate DSE endpoint
Caching	The BDShare client caches responses automatically (configurable TTL)
Rate limiting	Built-in sliding-window limiter (5 calls/second) prevents being blocked
Errors	All failures raise BDShareError — never silent

---

Usage Guide

Live Trading Data

from bdshare import get_current_trade_data, get_dsex_data, get_current_trading_code

# All instruments — returns columns: symbol, ltp, high, low, close, ycp, change, trade, value, volume
df = get_current_trade_data()

# Single instrument (case-insensitive)
df = get_current_trade_data('GP')

# DSEX index entries
df = get_dsex_data()

# Just the list of tradeable symbols
codes = get_current_trading_code()
print(codes['symbol'].tolist())

Historical Data

from bdshare import get_historical_data, get_basic_historical_data, get_close_price_data
import datetime as dt

start = '2024-01-01'
end   = '2024-03-31'

# Full historical data (ltp, open, high, low, close, volume, trade, value…)
# Indexed by date, sorted newest-first
df = get_historical_data(start, end, 'ACI')

# Simplified OHLCV — sorted oldest-first, ready for TA libraries
df = get_basic_historical_data(start, end, 'ACI')

# Set date as index explicitly
df = get_basic_historical_data(start, end, 'ACI', index='date')

# Rolling 2-year window
end   = dt.date.today()
start = end - dt.timedelta(days=2 * 365)
df    = get_basic_historical_data(str(start), str(end), 'GP')

# Close prices only
df = get_close_price_data(start, end, 'ACI')

Column order note: get_basic_historical_data intentionally returns OHLCV in standard order (open, high, low, close, volume) to be compatible with libraries like ta, pandas-ta, and backtrader.

Deprecated aliases: get_hist_data() and get_basic_hist_data() still work but emit a DeprecationWarning — migrate to get_historical_data() / get_basic_historical_data().

Market & Index Data

from bdshare import (
    get_market_status,
    get_market_info,
    get_market_info_more_data,
    get_market_depth_data,
    get_latest_pe,
    get_top_ten_gainers_losers,
    get_top_twenty_shares,
    get_company_info,
)

# Current market status: Open, Closed, Holiday, etc.
status = get_market_status()

# Last 30 days of market summary (DSEX, DSES, DS30, DGEN, volumes, market cap)
df = get_market_info()

# Historical market summary between two dates
df = get_market_info_more_data('2024-01-01', '2024-03-31')

# Order book (buy/sell depth) for a symbol
df = get_market_depth_data('ACI')

# P/E ratios for all listed companies
df = get_latest_pe()

# Top 10 gainers and losers (adjust limit as needed)
df = get_top_ten_gainers_losers(limit=10)

# Top 20 shares by traded volume (adjust limit as needed)
df = get_top_twenty_shares(limit=20)

# Detailed company profile
tables = get_company_info('GP')

News & Announcements

from bdshare import get_news, get_agm_news, get_all_news

# Unified dispatcher — news_type: 'all' | 'agm' | 'corporate' | 'psn'
df = get_news(news_type='all')
df = get_news(news_type='agm')
df = get_news(news_type='corporate', code='GP')
df = get_news(news_type='psn', code='ACI')   # price-sensitive news

# Direct function calls
df = get_agm_news()                          # AGM / dividend declarations
df = get_all_news(code='BEXIMCO')            # All news for one symbol
df = get_all_news('2024-01-01', '2024-03-31', 'GP')  # Filtered by date + symbol

Saving to CSV

from bdshare import get_basic_historical_data, Store
import datetime as dt

end   = dt.date.today()
start = end - dt.timedelta(days=365)

df = get_basic_historical_data(str(start), str(end), 'GP')
Store(df).save()   # saves to current directory as a CSV

---

OOP Client (BDShare)

The BDShare class wraps all functions with automatic caching and rate limiting.

from bdshare import BDShare

bd = BDShare(cache_enabled=True)   # cache_enabled=True is the default

Context manager (auto-cleans cache and session)

with BDShare() as bd:
    data = bd.get_current_trades('GP')

Market methods

bd.get_market_summary()                    # DSEX/DSES/DS30 indices + stats  (1-min TTL)
bd.get_company_profile('ACI')             # Company profile                  (1-hr TTL)
bd.get_latest_pe_ratios()                 # All P/E ratios                   (1-hr TTL)
bd.get_top_movers(limit=10)               # Top gainers/losers               (5-min TTL)

get_market_status() and get_top_twenty_shares() don't have BDShare wrapper methods yet — call the module-level functions directly (see API Reference).

Trading methods

bd.get_current_trades()                   # All live prices                  (30-sec TTL)
bd.get_current_trades('GP')               # Single symbol
bd.get_dsex_index()                       # DSEX index entries               (1-min TTL)
bd.get_trading_codes()                    # All tradeable symbols            (24-hr TTL)
bd.get_historical_data('GP', '2024-01-01', '2024-03-31')    # OHLCV history

News methods

bd.get_news(news_type='all')              # All news                         (5-min TTL)
bd.get_news(news_type='corporate', code='GP')
bd.get_news(news_type='psn')             # Price-sensitive news

Utility methods

bd.clear_cache()                          # Flush all cached data
bd.configure(proxy_url='http://proxy:8080')
print(bd.version)                         # Package version string

---

Error Handling

All failures raise BDShareError. Never catch bare Exception — you'll miss bugs.

from bdshare import BDShare, BDShareError

bd = BDShare()

try:
    df = bd.get_historical_data('INVALID', '2024-01-01', '2024-01-31')
except BDShareError as e:
    print(f"DSE error: {e}")
    # safe fallback logic here

Common causes of BDShareError:

• Symbol not found in the response table
• DSE site returned a non-200 status after all retries
• Table structure changed on the DSE page (report as a bug)
• Network timeout

---

API Reference

Trading Functions

Function	Parameters	Returns	Description
get_current_trade_data(symbol?)	symbol: str	DataFrame	Live prices (all or one symbol)
get_dsex_data(symbol?)	symbol: str	DataFrame	DSEX index entries
get_current_trading_code()	—	DataFrame	All tradeable symbols
get_historical_data(start, end, code?)	str, str, str	DataFrame	Full historical OHLCV
get_basic_historical_data(start, end, code?, index?)	str, str, str, str	DataFrame	Simplified OHLCV (TA-ready)
get_close_price_data(start, end, code?)	str, str, str	DataFrame	Close + prior close
get_last_trade_price_data()	—	DataFrame	Last trade from DSE text file

Deprecated aliases (removed in 2.0.0): get_hist_data() → get_historical_data(), get_basic_hist_data() → get_basic_historical_data().

Market Functions

Function	Parameters	Returns	Description
get_market_status()	—	str	Current market status (Open, Closed, Holiday, etc.)
get_market_info()	—	DataFrame	30-day market summary
get_market_info_more_data(start, end)	str, str	DataFrame	Historical market summary
get_market_depth_data(symbol)	str	DataFrame	Order book (buy/sell depth)
get_latest_pe()	—	DataFrame	P/E ratios for all companies
get_company_info(symbol)	str	list[DataFrame]	Detailed company tables
get_top_ten_gainers_losers(limit?)	int (default 10)	DataFrame	Top movers by price change
get_top_twenty_shares(limit?)	int (default 20)	DataFrame	Top shares by traded volume

News Functions

Function	Parameters	Returns	Description
get_news(news_type?, code?)	str, str	DataFrame	Unified news dispatcher
get_agm_news()	—	DataFrame	AGM / dividend declarations
get_all_news(start?, end?, code?)	str, str, str	DataFrame	All DSE news
get_corporate_announcements(code?)	str	DataFrame	Corporate actions
get_price_sensitive_news(code?)	str	DataFrame	Price-sensitive news

get_news news_type values

Value	Equivalent direct function
'all'	get_all_news()
'agm'	get_agm_news()
'corporate'	get_corporate_announcements()
'psn'	get_price_sensitive_news()

---

Examples

Stock performance summary

import datetime as dt
from bdshare import BDShare, BDShareError

def summarize(symbol: str, days: int = 30) -> dict:
    end   = dt.date.today()
    start = end - dt.timedelta(days=days)

    with BDShare() as bd:
        try:
            df = bd.get_historical_data(symbol, str(start), str(end))
        except BDShareError as e:
            print(f"Could not fetch data: {e}")
            return {}

    return {
        'symbol':       symbol,
        'current':      df['close'].iloc[0],
        'period_high':  df['high'].max(),
        'period_low':   df['low'].min(),
        'avg_volume':   df['volume'].mean(),
        'change_pct':   (df['close'].iloc[0] - df['close'].iloc[-1])
                        / df['close'].iloc[-1] * 100,
    }

result = summarize('GP', days=30)
print(f"{result['symbol']}: {result['change_pct']:.2f}% over 30 days")

Simple portfolio tracker

from bdshare import BDShare, BDShareError

PORTFOLIO = {
    'GP':      {'qty': 100, 'cost': 450.50},
    'ACI':     {'qty':  50, 'cost': 225.75},
    'BEXIMCO': {'qty': 200, 'cost': 125.25},
}

with BDShare() as bd:
    total_cost = total_value = 0

    for symbol, pos in PORTFOLIO.items():
        try:
            row = bd.get_current_trades(symbol).iloc[0]
            price        = row['ltp']
            market_value = pos['qty'] * price
            cost         = pos['qty'] * pos['cost']
            pnl          = market_value - cost

            print(f"{symbol:10s}  price={price:8.2f}  P&L={pnl:+10.2f}")
            total_cost  += cost
            total_value += market_value

        except BDShareError as e:
            print(f"{symbol}: fetch error — {e}")

    print(f"\nPortfolio P&L: {total_value - total_cost:+.2f} "
          f"({(total_value/total_cost - 1)*100:+.2f}%)")

Fetch and screen top gainers above 5 %

from bdshare import get_top_ten_gainers_losers

df = get_top_ten_gainers_losers(limit=20)
big_movers = df[df['change'] > 5]
print(big_movers[['symbol', 'close', 'change']])

---

Using bdshare with AI Agents (MCP Server)

bdshare ships an MCP server so AI agents running in another program — Claude Desktop, Claude Code, or any other MCP-compatible client — can call live DSE data as tools, without you writing any glue code.

Install

pip install "bdshare[mcp]"

Run

bdshare-mcp
# or
python -m bdshare.mcp_server

By default it speaks MCP over stdio, which is what desktop/CLI agent clients expect.

Connect it to a client

Claude Code:

claude mcp add bdshare -- bdshare-mcp

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "bdshare": {
      "command": "bdshare-mcp"
    }
  }
}

Any other MCP client is configured the same way — point it at the bdshare-mcp command (or python -m bdshare.mcp_server), stdio transport.

What the agent gets

15 tools covering the same data this README documents — market_status, market_summary, market_summary_range, market_depth, latest_pe_ratios, top_ten_gainers_losers, top_twenty_shares, company_info, current_trades, dsex_index, trading_codes, historical_data, basic_historical_data, news, agm_news. Each tool returns JSON — DataFrames are converted to lists of row records — and a BDShareError (bad symbol, DSE outage, parse failure) surfaces as a clean tool error message instead of a raw traceback.

Notes for agent use

• No caching in the MCP server itself. Every tool call scrapes dsebd.org live. If your agent calls the same tool repeatedly in one turn (e.g. checking a price several times), consider fronting it with the BDShare client's caching in a custom wrapper — the bundled server intentionally stays stateless and simple.
• Rate limits are the agent's responsibility. The BDShare OOP client has a built-in 5 calls/second limiter; the MCP tools call the plain module-level functions, which don't. Avoid tight loops of tool calls.
• Source: bdshare/mcp_server.py — a plain FastMCP server, easy to fork if you want a different tool surface.

---

Contributing

Contributions are welcome! To get started:

git clone https://github.com/rochi88/bdshare.git
cd bdshare
pip install -e ".[dev]"
pytest

Please open an issue before submitting a pull request for significant changes. See CONTRIBUTING.md for the full guide.

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Roadmap

• Chittagong Stock Exchange (CSE) support
• WebSocket streaming for real-time ticks
• Built-in technical indicators (ta integration)
• Portfolio management helpers
• Docker demo examples
• Shared session with exponential back-off
• lxml-based fast parsing
• BDShareError for clean error handling
• Unified get_news() dispatcher
• Rate limiter and response caching
• MCP server for AI agent integration

---

Support

• Docs: bdshare.readthedocs.io
• Bugs / Features: GitHub Issues
• Discussion: GitHub Discussions

---

License

MIT — see LICENSE for details.

Disclaimer

bdshare is intended for educational and research use. Always respect DSE's terms of service. The authors are not responsible for financial decisions made using this library.

Change log

All notable changes to bdshare are documented here.

Format follows Keep a Changelog. Versioning follows Semantic Versioning.

---

[1.2.2] - 2026-07-22

Added

• Optional as_polars=True parameter across all data-fetching functions to return polars.DataFrame instead of pandas.DataFrame (requires pip install bdshare[polars])
• get_market_status() — current market status (Open, Closed, Holiday, etc.)
• get_top_twenty_shares() — top twenty shares by traded volume
• MCP (Model Context Protocol) server (bdshare/mcp_server.py) exposing 15 tools so AI agents (Claude Desktop, Claude Code, etc.) can call live DSE data directly; install with pip install bdshare[mcp], run with bdshare-mcp

Changed

• Renamed get_top_gainers_losers() → get_top_ten_gainers_losers(); returned columns changed from symbol, ltp, change to symbol, close, high, low, ycp, change

Removed

• get_sector_performance() (module function and BDShare.get_sector_performance()) — no aliased replacement; use get_top_twenty_shares() instead

Fixed

• Bundled the missing Sectigo DV R36 intermediate certificate so requests to dsebd.org verify correctly instead of relying on an incomplete chain
• Corrected DSE_ALT_URL fallback domain to dse.com.bd
• get_corporate_announcements() and get_price_sensitive_news() always raised BDShareError — the row parser assumed each news item was one <tr> with 4 <td>s, but DSE renders each field (Trading Code:, News Title:, News:, Post Date:) as its own <th>/<td> row pair
• as_polars=True could crash with unexpected value while building Series of type String; found value of type Float64: NaN on tables mixing strings and missing values (e.g. get_company_info()); NaN now converts to a proper polars null instead
• Corrected usage.rst/README documentation that had get_historical_data()/get_basic_historical_data() mislabeled as the deprecated aliases — get_hist_data()/get_basic_hist_data() are the deprecated ones

[1.2.1] - 2026-02-22

Added

• Added code filter on market index

[1.2.0] - 2026-02-21

Changed

• Updated

[1.1.6] - 2026-02-20

Changed

• Updated readthedocs structure

[1.1.5] - 2026-02-20

Changed

• Renamed get_hist_data() → get_historical_data() (improved readability)
• Renamed get_basic_hist_data() → get_basic_historical_data() (improved readability)
• Renamed get_market_inf() → get_market_info() (improved readability)
• Renamed get_market_inf_more_data() → get_market_info_more_data() (improved readability)
• Renamed get_company_inf() → get_company_info() (improved readability)

Deprecated

• get_hist_data() — still callable but emits DeprecationWarning; will be removed in 2.0.0
• get_basic_hist_data() — still callable but emits DeprecationWarning; will be removed in 2.0.0
• get_market_inf() — still callable but emits DeprecationWarning; will be removed in 2.0.0
• get_market_inf_more_data() — still callable but emits DeprecationWarning; will be removed in 2.0.0
• get_company_inf() — still callable but emits DeprecationWarning; will be removed in 2.0.0

Added

• BDShareError custom exception — all network and scraping failures now raise this instead of silently printing and returning None
• Shared requests.Session (_session) across all modules — reuses TCP connections for significantly faster repeated calls
• Exponential back-off retry logic in safe_get() — pauses 0.2 s → 0.4 s → 0.8 s between attempts before raising BDShareError
• Fallback URL support in safe_get() — primary and alternate DSE endpoints tried within the same retry attempt
• lxml-based HTML parsing in _fetch_table() with html.parser fallback — replaces html5lib (~10× faster)
• _safe_num() helper — all scraped values now returned as typed numerics (float/int) instead of raw strings
• _parse_trade_rows() and _filter_symbol() internal helpers in trading.py — eliminate duplicated parsing logic between get_current_trade_data() and get_dsex_data()
• get_news() unified dispatcher — accepts news_type of 'all', 'agm', 'corporate', or 'psn'
• get_corporate_announcements() and get_price_sensitive_news() — previously missing functions now fully implemented
• Column count guards (len(cols) < N) across all table parsers — malformed rows are skipped rather than raising IndexError
• Backward-compatibility aliases for all renamed functions with DeprecationWarning
• Type hints throughout all public functions
• Comprehensive docstrings with parameter and return documentation

Fixed

• get_agm_news(): corrected field name typo agmData → agmDate
• get_agm_news(): corrected field name typo vanue → venue
• get_market_depth_data(): no longer creates a new requests.Session on every retry iteration
• get_basic_hist_data(): redundant double sort_index() call removed
• get_hist_data() and get_close_price_data(): no longer silently return None on empty results
• RateLimiter in __init__.py: switched from time.time() to time.monotonic() for reliable elapsed-time measurement

Removed

• html5lib as the default parser — replaced by lxml with html.parser fallback
• Silent print(e) error handling — all error paths now raise BDShareError
• Dead timeout parameter from BDShare.configure() — it had no effect

[1.1.4] - 2025-09-16

Added

• Enhanced error handling and robustness across all functions
• Improved parameter handling for news functions
• Better file path resolution for utility functions
• Comprehensive fallback mechanisms for network issues

Changed

• Fixed get_all_news() function to support date range parameters as documented
• Enhanced market info functions with better error handling
• Improved Store utility with proper file saving mechanism
• Fixed Tickers utility with correct file path resolution

Fixed

• All major function issues identified in testing (18/18 functions now working)
• Parameter signature mismatches in news functions
• HTML parsing errors in market data functions
• File saving issues in Store utility
• Missing tickers.json file dependency

[1.1.2] - 2024-12-31

Added

• n/a

Changed

• update tests

Fixed

• n/a

[1.1.1] - 2024-12-31

Added

• n/a

Changed

• update runner

Fixed

• n/a

[1.1.0] - 2024-12-31

Added

• new function for getting company info

Changed

• n/a

Fixed

• n/a

[1.0.4] - 2024-12-30

Added

• n/a

Changed

• changed lint

Fixed

• fixed typo

[1.0.3] - 2024-07-29

Added

• n/a

Changed

• n/a

Fixed

• check fix for latest P/E url [#6]

[1.0.2] - 2024-07-29

Added

• n/a

Changed

• n/a

Fixed

• fixed latest P/E url [#6]

[1.0.0] - 2024-03-04

Added

• Updated docs

Changed

• n/a

[0.7.2] - 2024-03-04

Added

• Updated docs

Changed

• n/a

[0.7.1] - 2024-03-04

Added

• n/a

Changed

• fixed market depth data api

[0.7.0] - 2024-03-04

Added

• n/a

Changed

• n/a

[0.6.0] - 2024-03-03

Added

• n/a

Changed

• n/a

[0.5.1] - 2024-02-29

Added

• n/a

Changed

• n/a

[0.5.0] - 2024-02-29

Added

• fixed store datafrave to csv file method

Changed

• n/a

[0.4.0] - 2023-03-12

Added

• n/a

Changed

• changed package manager

[0.3.2] - 2022-10-10

Added

• n/a

Changed

• n/a

[0.3.1] - 2022-06-15

Added

• n/a

Changed

• n/a

[0.2.1] - 2021-08-01

Added

Changed

• get_current_trading_code()

[0.2.0] - 2021-06-01

Added

• added get_market_depth_data
• added get_dsex_data
• added 'dse.com.bd' as redundant

Changed

• Changed documentation
• changed get_agm_news
• changed get_all_news

[0.1.4] - 2020-08-22

Added

• added get_market_inf_more_data

Changed

• Changed documentation

[0.1.3] - 2020-08-20

Added

• html5lib
• added get params

Changed

• post request to get

[0.1.2] - 2020-05-21

Added

• modified index declaration

[0.1.1] - 2020-05-20

Added

• modified index declaration

[0.1.0] - 2020-04-08

Added

• added git tag
• VERSION.txt

Changed

• setup.py
• HISTORY.md to CHANGELOG.md

[0.0.1] - 2020-04-06

Added

• get_hist_data(), get_current_trade_data()
• HISTORY.md